Enter (or paste) a matrix (table) containing all data (time) series. Every column represents a different variable and must be delimited by a space or Tab. Every row represents a period in time (or category) and must be delimited by hard returns. The easiest way to enter data is to copy and paste a block of spreadsheet cells. Please, do not use commas or spaces to seperate groups of digits!
Multiple Linear Regression - Estimated Regression Equation | Amerika[t] = + 21.3306619568714 + 2.58093783647922Japan[t] + 0.975790218631132M1[t] -0.87383793484388M2[t] -1.02335061465325M3[t] + 1.22657961626806M4[t] + 0.93810072930787M5[t] -0.327050703946156M6[t] -2.67486024012326M7[t] -3.16863872749503M8[t] -2.30195608196747M9[t] -3.16648593853321M10[t] -2.22805248447522M11[t] + e[t] |
Multiple Linear Regression - Ordinary Least Squares | Variable | Parameter | S.D. | T-STAT H0: parameter = 0 | 2-tail p-value | 1-tail p-value | (Intercept) | 21.3306619568714 | 7.223483 | 2.953 | 0.003342 | 0.001671 | Japan | 2.58093783647922 | 0.060275 | 42.8197 | 0 | 0 | M1 | 0.975790218631132 | 4.371571 | 0.2232 | 0.823489 | 0.411745 | M2 | -0.87383793484388 | 4.371612 | -0.1999 | 0.841674 | 0.420837 | M3 | -1.02335061465325 | 4.371604 | -0.2341 | 0.81504 | 0.40752 | M4 | 1.22657961626806 | 4.371619 | 0.2806 | 0.779186 | 0.389593 | M5 | 0.93810072930787 | 4.371615 | 0.2146 | 0.830202 | 0.415101 | M6 | -0.327050703946156 | 4.371601 | -0.0748 | 0.940403 | 0.470201 | M7 | -2.67486024012326 | 4.371662 | -0.6119 | 0.540992 | 0.270496 | M8 | -3.16863872749503 | 4.371643 | -0.7248 | 0.469008 | 0.234504 | M9 | -2.30195608196747 | 4.371572 | -0.5266 | 0.598795 | 0.299398 | M10 | -3.16648593853321 | 4.37157 | -0.7243 | 0.469303 | 0.234651 | M11 | -2.22805248447522 | 4.37162 | -0.5097 | 0.610582 | 0.305291 |
Multiple Linear Regression - Regression Statistics | Multiple R | 0.909820004925928 | R-squared | 0.827772441363416 | Adjusted R-squared | 0.822362151563314 | F-TEST (value) | 152.999649177350 | F-TEST (DF numerator) | 12 | F-TEST (DF denominator) | 382 | p-value | 0 | Multiple Linear Regression - Residual Statistics | Residual Standard Deviation | 17.6202766756169 | Sum Squared Residuals | 118601.12534786 |
Multiple Linear Regression - Actuals, Interpolation, and Residuals | Time or Index | Actuals | Interpolation Forecast | Residuals Prediction Error | 1 | 358.59 | 338.110005847094 | 20.4799941529060 | 2 | 362.96 | 338.76388739501 | 24.1961126049899 | 3 | 362.42 | 337.865902742622 | 24.5540972573785 | 4 | 364.97 | 343.961430349897 | 21.0085696501032 | 5 | 364.04 | 345.221514164824 | 18.8184858351759 | 6 | 361.06 | 345.814637973835 | 15.2453620261648 | 7 | 358.48 | 345.144438031370 | 13.3355619686304 | 8 | 352.96 | 344.728087679092 | 8.23191232090777 | 9 | 359.59 | 346.988476756319 | 12.6015232436814 | 10 | 360.39 | 339.619983551825 | 20.7700164481748 | 11 | 357.4 | 341.461745248651 | 15.9382547513491 | 12 | 362.93 | 342.192853787968 | 20.7371462120319 | 13 | 364.55 | 339.34885600861 | 25.2011439913899 | 14 | 365.73 | 338.71226863828 | 27.0177313617198 | 15 | 364.7 | 338.562755958471 | 26.1372440415291 | 16 | 364.65 | 344.8389492143 | 19.8110507857002 | 17 | 359.43 | 343.956854624949 | 15.4731453750506 | 18 | 362.14 | 342.923987596978 | 19.2160124030215 | 19 | 356.97 | 341.014937493003 | 15.9550625069972 | 20 | 354.82 | 338.301552466259 | 16.5184475337410 | 21 | 353.17 | 337.206722356062 | 15.9632776439377 | 22 | 357.06 | 337.839136444654 | 19.2208635553455 | 23 | 356.18 | 334.72549749544 | 21.4545025045599 | 24 | 355.01 | 341.599238085578 | 13.4107619144221 | 25 | 355.65 | 343.736450330625 | 11.9135496693753 | 26 | 357.31 | 344.751663175642 | 12.5583368243584 | 27 | 357.07 | 344.731197387656 | 12.3388026123438 | 28 | 357.91 | 346.542368186376 | 11.3676318136240 | 29 | 358.48 | 346.460364326334 | 12.0196356736658 | 30 | 358.97 | 345.040356622891 | 13.9296433771086 | 31 | 351.77 | 342.331215789607 | 9.43878421039276 | 32 | 352.16 | 347.489691164125 | 4.67030883587507 | 33 | 359.08 | 340.820035327133 | 18.2599646728668 | 34 | 360.35 | 339.258652254718 | 21.091347745282 | 35 | 359.53 | 345.410580138464 | 14.1194198615359 | 36 | 359.3 | 347.509585731115 | 11.7904142688847 | 37 | 358.41 | 346.936813247859 | 11.4731867521411 | 38 | 359.68 | 342.299772230986 | 17.3802277690136 | 39 | 355.31 | 343.105206550674 | 12.2047934493257 | 40 | 357.08 | 345.819705592162 | 11.2602944078381 | 41 | 349.71 | 348.963874027719 | 0.746125972280924 | 42 | 354.13 | 349.118238404529 | 5.01176159547140 | 43 | 345.49 | 343.389400302564 | 2.10059969743631 | 44 | 341.69 | 337.424033601856 | 4.265966398144 | 45 | 344.25 | 340.071563354554 | 4.17843664544577 | 46 | 340.17 | 337.426186390818 | 2.74381360918220 | 47 | 342.47 | 340.222895087141 | 2.24710491285917 | 48 | 344.43 | 333.753187062681 | 10.6768129373189 | 49 | 333.23 | 334.651549146218 | -1.42154914621781 | 50 | 339.72 | 338.505793611362 | 1.2142063886381 | 51 | 342.61 | 333.426689663877 | 9.18331033612281 | 52 | 346.36 | 334.618435381842 | 11.7415646181580 | 53 | 339.09 | 333.839578305951 | 5.25042169404917 | 54 | 339.73 | 339.259055869178 | 0.470944130822044 | 55 | 341.12 | 327.284348202933 | 13.8356517970667 | 56 | 335.94 | 326.661522823738 | 9.27847717626238 | 57 | 333.46 | 330.263999575933 | 3.1960004240668 | 58 | 335.66 | 324.340831559868 | 11.3191684401319 | 59 | 341.12 | 324.866314960089 | 16.2536850399105 | 60 | 342.21 | 309.905321453613 | 32.3046785463869 | 61 | 342.62 | 318.365831398034 | 24.2541686019661 | 62 | 346.06 | 323.304069754499 | 22.7559302455007 | 63 | 344.43 | 319.102484671418 | 25.3275153285825 | 64 | 346.65 | 328.088662655550 | 18.5613373444504 | 65 | 343.74 | 326.406477336891 | 17.3335226631094 | 66 | 335.67 | 327.696454361751 | 7.97354563824898 | 67 | 342.75 | 328.419960850984 | 14.3300391490158 | 68 | 341.77 | 318.092809206627 | 23.6771907933734 | 69 | 345.84 | 321.204907769891 | 24.6350922301089 | 70 | 346.52 | 328.392903963140 | 18.1270960368595 | 71 | 350.79 | 328.376390417701 | 22.4136095822988 | 72 | 345.44 | 328.25578947098 | 17.1842105290197 | 73 | 345.87 | 326.934545015145 | 18.9354549848550 | 74 | 338.48 | 324.259016753997 | 14.2209832460034 | 75 | 337.21 | 328.858429693309 | 8.35157030669099 | 76 | 340.81 | 322.281552523471 | 18.5284474765287 | 77 | 339.86 | 321.580123582675 | 18.2798764173255 | 78 | 342.86 | 320.36659090615 | 22.49340909385 | 79 | 343.33 | 315.360415398399 | 27.9695846016007 | 80 | 341.73 | 318.738043665746 | 22.9919563342536 | 81 | 351.38 | 319.837010716557 | 31.5429892834429 | 82 | 351.13 | 309.939198432314 | 41.190801567686 | 83 | 345.99 | 322.207948988516 | 23.7820510114842 | 84 | 347.55 | 328.049314444062 | 19.500685555938 | 85 | 346.02 | 324.43103531376 | 21.5889646862399 | 86 | 345.29 | 323.820257321795 | 21.4697426782049 | 87 | 347.03 | 328.239004612554 | 18.7909953874460 | 88 | 348.01 | 328.966181519953 | 19.0438184800474 | 89 | 345.48 | 335.981756710229 | 9.49824328977146 | 90 | 349.4 | 337.452399383643 | 11.9476006163575 | 91 | 351.05 | 332.317176984068 | 18.7328230159322 | 92 | 349.7 | 336.417467845629 | 13.2825321543709 | 93 | 350.86 | 339.245663246881 | 11.6143367531192 | 94 | 354.45 | 337.142283228805 | 17.3077167711949 | 95 | 355.3 | 336.480535224246 | 18.8194647757540 | 96 | 357.48 | 339.353822167841 | 18.1261778321590 | 97 | 355.24 | 339.865043575906 | 15.3749564240941 | 98 | 351.79 | 337.808940395512 | 13.9810596044875 | 99 | 355.22 | 337.272287040231 | 17.9477129597687 | 100 | 351.02 | 339.522217271153 | 11.4977827288474 | 101 | 350.28 | 338.743360195261 | 11.5366398047386 | 102 | 350.17 | 332.832520656345 | 17.3374793436553 | 103 | 348.16 | 326.845588770732 | 21.3144112292681 | 104 | 340.3 | 331.900826631790 | 8.39917336820956 | 105 | 343.75 | 332.844937412412 | 10.9050625875876 | 106 | 344.71 | 324.005309641126 | 20.7046903588741 | 107 | 344.13 | 325.640596311033 | 18.4894036889668 | 108 | 342.14 | 328.100933200792 | 14.0390667992084 | 109 | 345.04 | 325.824741745459 | 19.2152582545411 | 110 | 346.02 | 329.911270615886 | 16.1087293841139 | 111 | 346.43 | 334.742967960482 | 11.6870320395184 | 112 | 347.07 | 337.018707569768 | 10.0512924302323 | 113 | 339.33 | 337.452891277022 | 1.87710872297826 | 114 | 339.1 | 336.187739843768 | 2.91226015623232 | 115 | 337.19 | 331.878417551866 | 5.31158244813362 | 116 | 339.58 | 326.99704474248 | 12.5829552575201 | 117 | 327.85 | 326.986208523605 | 0.863791476395487 | 118 | 326.81 | 328.805854016977 | -1.99585401697719 | 119 | 321.73 | 321.227192610654 | 0.502807389346251 | 120 | 320.45 | 324.53923898645 | -4.08923898645026 | 121 | 327.69 | 320.662866072500 | 7.02713392749958 | 122 | 323.95 | 314.322406083552 | 9.62759391644841 | 123 | 320.47 | 322.070563183369 | -1.60056318336861 | 124 | 322.13 | 326.462671818568 | -4.3326718185677 | 125 | 316.34 | 326.174192931607 | -9.83419293160753 | 126 | 314.78 | 318.611553177344 | -3.8315531773442 | 127 | 308.9 | 318.767253342552 | -9.86725334255194 | 128 | 308.62 | 315.537680748512 | -6.91768074851216 | 129 | 314.41 | 317.514166663726 | -3.10416666372579 | 130 | 306.88 | 315.255930375461 | -8.37593037546127 | 131 | 310.6 | 325.382502527385 | -14.7825025273853 | 132 | 321.6 | 325.984564174879 | -4.3845641748786 | 133 | 321.5 | 322.985710125332 | -1.48571012533174 | 134 | 325.68 | 329.601558075509 | -3.92155807550859 | 135 | 324.35 | 329.890804827901 | -5.54080482790067 | 136 | 320.01 | 333.224728950143 | -13.2147289501433 | 137 | 326.88 | 331.439306118025 | -4.55930611802515 | 138 | 332.39 | 329.245017063639 | 3.14498293636139 | 139 | 331.48 | 331.104136200923 | 0.375863799077405 | 140 | 332.62 | 332.365395442357 | 0.254604557643310 | 141 | 324.79 | 331.554468494173 | -6.76446849417277 | 142 | 327.12 | 335.542101770188 | -8.42210177018796 | 143 | 328.91 | 330.105618768142 | -1.19561876814227 | 144 | 328.37 | 323.764957635507 | 4.60504236449351 | 145 | 324.83 | 319.191731505707 | 5.6382684942927 | 146 | 325.9 | 313.031937165312 | 12.8680628346880 | 147 | 326.18 | 310.895102351414 | 15.2848976485864 | 148 | 328.94 | 310.718951016044 | 18.2210489839556 | 149 | 333.78 | 311.282181615122 | 22.4978183848776 | 150 | 328.06 | 317.475940529293 | 10.5840594707067 | 151 | 325.87 | 314.611943425820 | 11.2580565741796 | 152 | 325.41 | 312.621220993291 | 12.7887790067094 | 153 | 318.86 | 315.242941367624 | 3.61705863237594 | 154 | 319.13 | 320.262949778231 | -1.13294977823095 | 155 | 310.16 | 321.640142664490 | -11.4801426644904 | 156 | 311.73 | 313.441206289590 | -1.71120628958957 | 157 | 306.54 | 308.661505132872 | -2.12150513287203 | 158 | 311.16 | 309.883193004807 | 1.27680699519271 | 159 | 311.98 | 311.230624270156 | 0.749375729844128 | 160 | 306.72 | 306.486212964219 | 0.233787035781517 | 161 | 308.05 | 306.920396671473 | 1.12960332852750 | 162 | 300.76 | 306.816667264634 | -6.05666726463411 | 163 | 301.9 | 303.384863837136 | -1.48486383713574 | 164 | 293.09 | 291.457530734161 | 1.63246926583898 | 165 | 292.76 | 300.273501916045 | -7.51350191604458 | 166 | 294.58 | 300.363919058976 | -5.78391905897616 | 167 | 289.9 | 294.153154705987 | -4.2531547059867 | 168 | 296.69 | 278.108167308189 | 18.5818326918110 | 169 | 297.21 | 285.071733307452 | 12.1382666925480 | 170 | 293.31 | 289.622830988445 | 3.68716901155459 | 171 | 296.25 | 303.513620139083 | -7.26362013908302 | 172 | 298.6 | 293.710570673646 | 4.88942932635368 | 173 | 296.87 | 300.932620890841 | -4.06262089084069 | 174 | 301.02 | 300.080419511423 | 0.939580488576657 | 175 | 304.73 | 302.197632432355 | 2.53236756764473 | 176 | 301.92 | 299.355200513787 | 2.56479948621258 | 177 | 295.72 | 306.028993291393 | -10.3089932913932 | 178 | 293.18 | 303.848185138223 | -10.6681851382231 | 179 | 298.35 | 292.940113922841 | 5.40988607715858 | 180 | 297.99 | 294.084172515995 | 3.9058274840046 | 181 | 299.85 | 291.033699709719 | 8.81630029028108 | 182 | 299.85 | 290.706824879767 | 9.14317512023336 | 183 | 304.45 | 289.499127687001 | 14.9508723129992 | 184 | 299.45 | 289.735926405468 | 9.71407359453167 | 185 | 298.14 | 300.39062394518 | -2.25062394518008 | 186 | 298.78 | 299.228710025385 | -0.448710025385213 | 187 | 297.02 | 295.590431570968 | 1.42956842903151 | 188 | 301.33 | 298.555109784479 | 2.77489021552112 | 189 | 294.96 | 290.104606840316 | 4.85539315968354 | 190 | 296.69 | 297.679743709038 | -0.989743709037738 | 191 | 300.73 | 295.804954921333 | 4.92504507866664 | 192 | 301.96 | 303.349739348956 | -1.38973934895582 | 193 | 297.38 | 304.919145269977 | -7.53914526997717 | 194 | 293.87 | 308.695961600027 | -14.8259616000269 | 195 | 285.96 | 308.856161460595 | -22.8961614605950 | 196 | 285.41 | 310.977044799692 | -25.5670447996923 | 197 | 283.7 | 297.603211081782 | -13.9032110817825 | 198 | 284.76 | 295.53796891922 | -10.7779689192199 | 199 | 277.11 | 291.615787302790 | -14.5057873027905 | 200 | 274.73 | 299.510056783976 | -24.7800567839762 | 201 | 274.73 | 300.376739429504 | -25.6467394295037 | 202 | 274.73 | 299.512209572938 | -24.782209572938 | 203 | 274.73 | 300.450643026996 | -25.720643026996 | 204 | 274.69 | 299.271857567319 | -24.5818575673186 | 205 | 275.42 | 293.795303194752 | -18.3753031947517 | 206 | 264.15 | 292.694147013856 | -28.5441470138557 | 207 | 276.24 | 284.130776987124 | -7.89077698712402 | 208 | 268.88 | 282.044731652760 | -13.1647316527603 | 209 | 277.97 | 293.267235516497 | -15.2972355164974 | 210 | 280.49 | 293.137696731294 | -12.6476967312942 | 211 | 281.09 | 297.113184894491 | -16.0231848944912 | 212 | 276.16 | 298.555109784479 | -22.3951097844788 | 213 | 272.58 | 294.414773027237 | -21.8347730272368 | 214 | 270.94 | 299.744493978221 | -28.8044939782211 | 215 | 284.31 | 290.694698005105 | -6.38469800510454 | 216 | 283.94 | 301.130132809584 | -17.1901328095837 | 217 | 284.18 | 303.112488784442 | -18.9324887844417 | 218 | 282.83 | 305.366551790969 | -22.5365517909687 | 219 | 283.84 | 304.778279678958 | -20.9382796789579 | 220 | 282.71 | 308.680010125226 | -25.9700101252259 | 221 | 279.29 | 302.506992971093 | -23.216992971093 | 222 | 280.7 | 298.970616241737 | -18.2706162417373 | 223 | 274.47 | 293.835393842163 | -19.3653938421626 | 224 | 273.44 | 301.652235188254 | -28.2122351882539 | 225 | 275.49 | 295.602004432017 | -20.1120044320172 | 226 | 279.46 | 294.995568359099 | -15.5355683590994 | 227 | 280.19 | 299.650552297687 | -19.4605522976875 | 228 | 288.21 | 304.846683294114 | -16.6366832941138 | 229 | 284.8 | 304.686860864694 | -19.886860864694 | 230 | 281.41 | 310.450999328833 | -29.0409993288327 | 231 | 283.39 | 306.868839326506 | -23.478839326506 | 232 | 287.97 | 308.189631936295 | -20.2196319362948 | 233 | 290.77 | 304.132983808075 | -13.3629838080749 | 234 | 290.6 | 314.146530720235 | -23.5465307202351 | 235 | 289.67 | 312.573002535002 | -22.9030025350018 | 236 | 289.84 | 312.595411614926 | -22.7554116149259 | 237 | 298.55 | 308.945453046615 | -10.3954530466148 | 238 | 296.07 | 312.184614350051 | -16.114614350051 | 239 | 297.14 | 314.387707343984 | -17.2477073439838 | 240 | 295.34 | 317.028709882296 | -21.6887098822957 | 241 | 296.25 | 320.017631613381 | -23.7676316133806 | 242 | 294.3 | 312.438321462922 | -18.1383214629217 | 243 | 296.15 | 312.701758836949 | -16.5517588369491 | 244 | 296.49 | 313.067604447241 | -16.5776044472405 | 245 | 298.05 | 314.06959447852 | -16.0195944785199 | 246 | 301.03 | 313.836818179858 | -12.8068181798576 | 247 | 300.52 | 316.470218668085 | -15.9502186680854 | 248 | 301.5 | 319.150993719583 | -17.6509937195831 | 249 | 296.93 | 321.101670256432 | -24.1716702564319 | 250 | 289.84 | 321.217896777728 | -31.3778967777283 | 251 | 291.44 | 317.510642126124 | -26.0706421261237 | 252 | 286.88 | 318.551463205818 | -31.6714632058184 | 253 | 286.74 | 320.895150477784 | -34.1551504777836 | 254 | 288.93 | 311.715658868708 | -22.7856588687076 | 255 | 292.19 | 314.663271592673 | -22.4732715926733 | 256 | 295.39 | 311.622279258812 | -16.2322792588122 | 257 | 295.86 | 315.824632207326 | -19.9646322073258 | 258 | 293.36 | 321.063444121999 | -27.7034441219994 | 259 | 292.86 | 324.832457258278 | -31.9724572582781 | 260 | 292.73 | 318.815471800841 | -26.0854718008408 | 261 | 296.73 | 324.172986281842 | -27.4429862818422 | 262 | 285.02 | 319.695143454205 | -34.6751434542055 | 263 | 285.24 | 325.769643202857 | -40.5296432028572 | 264 | 288.62 | 316.486712936635 | -27.8667129366351 | 265 | 283.36 | 311.423108617905 | -28.0631086179048 | 266 | 285.84 | 312.722224624934 | -26.8822246249345 | 267 | 291.48 | 303.565238895813 | -12.0852388958126 | 268 | 291.41 | 307.312113071892 | -15.9021130718918 | 269 | 287.77 | 313.553406911224 | -25.7834069112241 | 270 | 284.97 | 312.752824288536 | -27.7828242885363 | 271 | 286.05 | 312.366527508083 | -26.3165275080834 | 272 | 278.19 | 304.388029294922 | -26.1980292949219 | 273 | 281.21 | 302.828630374159 | -21.618630374159 | 274 | 277.92 | 298.686309465265 | -20.7663094652646 | 275 | 280.08 | 300.011883594795 | -19.9318835947946 | 276 | 269.24 | 301.284989079772 | -32.0449890797724 | 277 | 268.48 | 301.228404163812 | -32.7484041638118 | 278 | 268.83 | 299.043254091595 | -30.2132540915946 | 279 | 269.54 | 299.332500843987 | -29.7925008439867 | 280 | 262.37 | 301.582431074908 | -39.212431074908 | 281 | 265.12 | 297.938733000525 | -32.8187330005248 | 282 | 265.34 | 293.499028028401 | -28.1590280284013 | 283 | 263.32 | 291.228646627319 | -27.9086466273186 | 284 | 267.18 | 293.083521571143 | -25.9035215711429 | 285 | 260.75 | 287.084909571636 | -26.3349095716357 | 286 | 261.78 | 288.130273714065 | -26.3502737140646 | 287 | 257.27 | 289.404229086865 | -32.1342290868649 | 288 | 255.63 | 292.638847327567 | -37.0088473275670 | 289 | 251.39 | 292.685499925066 | -41.2954999250657 | 290 | 259.49 | 288.487218340395 | -28.9972183403945 | 291 | 261.18 | 288.286086903856 | -27.1060869038556 | 292 | 261.65 | 288.961645054525 | -27.3116450545246 | 293 | 262.01 | 284.595284385927 | -22.5852843859272 | 294 | 265.23 | 284.594792492548 | -19.3647924925480 | 295 | 268.1 | 287.925046196625 | -19.8250461966252 | 296 | 262.27 | 288.954021032776 | -26.6840210327762 | 297 | 263.59 | 297.202185890634 | -33.6121858906343 | 298 | 257.85 | 287.846370552052 | -29.9963705520519 | 299 | 265.69 | 284.42301906246 | -18.7330190624600 | 300 | 271.15 | 286.805927817124 | -15.655927817124 | 301 | 266.69 | 292.040265465946 | -25.3502654659459 | 302 | 265.77 | 290.758443636496 | -24.9884436364963 | 303 | 262.32 | 285.059914608257 | -22.7399146082566 | 304 | 270.48 | 280.470359572508 | -9.99035957250792 | 305 | 273.03 | 284.001668683537 | -10.971668683537 | 306 | 269.13 | 281.807379629150 | -12.6773796291504 | 307 | 280.65 | 276.388254067563 | 4.26174593243693 | 308 | 282.75 | 279.120647875790 | 3.6293521242097 | 309 | 281.44 | 279.419524197292 | 2.02047580270755 | 310 | 281.99 | 279.071181908023 | 2.91881809197746 | 311 | 282.86 | 272.834608176668 | 10.0253918233317 | 312 | 287.21 | 274.469044958753 | 12.7409550412467 | 313 | 283.11 | 279.238813797009 | 3.87118620299114 | 314 | 280.66 | 277.569851292087 | 3.09014870791259 | 315 | 282.39 | 271.6132284802 | 10.7767715198002 | 316 | 280.83 | 275.902099601940 | 4.92790039806031 | 317 | 284.71 | 275.149051904413 | 9.56094809558673 | 318 | 279.99 | 274.322659903361 | 5.66734009663932 | 319 | 283.5 | 269.264865638880 | 14.2351343611196 | 320 | 284.88 | 269.132418448616 | 15.7475815513843 | 321 | 288.6 | 268.605394662444 | 19.9946053375555 | 322 | 284.8 | 267.58600853569 | 17.2139914643100 | 323 | 287.2 | 278.874002714030 | 8.32599728597029 | 324 | 286.22 | 271.036397636236 | 15.1836023637641 | 325 | 286.54 | 274.567316312981 | 11.9726836870185 | 326 | 279.58 | 273.182256970073 | 6.39774302992724 | 327 | 283.08 | 274.116738181585 | 8.96326181841533 | 328 | 288.88 | 264.752448148349 | 24.1275518516506 | 329 | 280.18 | 274.684483093847 | 5.49551690615304 | 330 | 284.16 | 269.289831122226 | 14.8701688777738 | 331 | 290.57 | 266.400024640388 | 24.1699753596116 | 332 | 286.82 | 263.815686505469 | 23.0043134945315 | 333 | 273 | 266.669691285085 | 6.33030871491492 | 334 | 278.69 | 256.204072676817 | 22.4859273231834 | 335 | 264.54 | 255.981084104459 | 8.55891589554106 | 336 | 271.92 | 261.280452614344 | 10.6395473856556 | 337 | 283.6 | 253.971432377877 | 29.6285676221227 | 338 | 269.25 | 260.174330274217 | 9.07566972578257 | 339 | 263.58 | 268.670959346613 | -5.0909593466135 | 340 | 264.16 | 269.785276929484 | -5.62527692948391 | 341 | 268.85 | 264.799491180132 | 4.05050881986848 | 342 | 269.67 | 263.353674098324 | 6.31632590167603 | 343 | 249.41 | 260.231583211203 | -10.8215832112031 | 344 | 268.99 | 260.666942344964 | 8.32305765503618 | 345 | 268.65 | 247.932082592246 | 20.7179174077541 | 346 | 260.16 | 246.757840195303 | 13.4021598046974 | 347 | 256.55 | 240.082507031747 | 16.4674929682531 | 348 | 251.47 | 243.936550353204 | 7.53344964679595 | 349 | 234.93 | 242.537877762274 | -7.6078777622743 | 350 | 232.96 | 235.526373935841 | -2.56637393584084 | 351 | 215.49 | 221.052656263572 | -5.56265626357178 | 352 | 213.68 | 225.677049304054 | -11.9970493040540 | 353 | 236.07 | 208.225333804507 | 27.8446661954931 | 354 | 235.41 | 229.414341548622 | 5.99565845137784 | 355 | 214.77 | 228.769950984521 | -13.9999509845213 | 356 | 225.85 | 231.476535414384 | -5.62653541438384 | 357 | 224.64 | 214.792840771853 | 9.84715922814734 | 358 | 238.26 | 213.541170239815 | 24.7188297601850 | 359 | 232.44 | 221.060995176895 | 11.3790048231049 | 360 | 222.5 | 221.121059878728 | 1.37894012127230 | 361 | 225.28 | 220.625715530566 | 4.6542844694343 | 362 | 220.49 | 212.091458380609 | 8.39854161939052 | 363 | 216.86 | 213.748602186336 | 3.11139781366442 | 364 | 234.7 | 200.07414596618 | 34.6258540338199 | 365 | 230.06 | 211.219221694823 | 18.8407783051772 | 366 | 238.27 | 210.083117153393 | 28.1868828466072 | 367 | 238.56 | 221.698181312568 | 16.8618186874317 | 368 | 242.7 | 213.358351802300 | 29.3416481977003 | 369 | 249.14 | 212.573234232481 | 36.5667657675195 | 370 | 234.89 | 234.627432363850 | 0.262567636149691 | 371 | 227.78 | 224.596880012872 | 3.1831199871284 | 372 | 234.04 | 228.141210793951 | 5.8987892060488 | 373 | 230.7 | 228.162054013085 | 2.53794598691494 | 374 | 230.17 | 222.286162834702 | 7.88383716529755 | 375 | 218.23 | 221.749509479421 | -3.51950947942117 | 376 | 232.2 | 226.580377546822 | 5.61962245317828 | 377 | 220.76 | 211.503124856836 | 9.25687514316444 | 378 | 215.6 | 215.012708421068 | 0.5872915789319 | 379 | 217.69 | 207.735307617216 | 9.9546923827843 | 380 | 204.35 | 208.428760534624 | -4.07876053462436 | 381 | 191.44 | 208.90830250468 | -17.46830250468 | 382 | 203.84 | 200.378387273771 | 3.46161272622905 | 383 | 211.86 | 202.994430321541 | 8.86556967845952 | 384 | 210.57 | 212.887868180359 | -2.31786818035899 | 385 | 219.57 | 211.540814346159 | 8.02918565384119 | 386 | 219.98 | 208.891095463375 | 11.0889045366247 | 387 | 226.01 | 211.838708187341 | 14.1712918126591 | 388 | 207.04 | 216.953479416754 | -9.91347941675418 | 389 | 212.52 | 207.399433696834 | 5.1205663031664 | 390 | 217.92 | 206.67627920924 | 11.2437207907598 | 391 | 210.45 | 206.909407509542 | 3.54059249045767 | 392 | 218.53 | 205.202588239025 | 13.3274117609747 | 393 | 223.32 | 204.701373831219 | 18.6186261687811 | 394 | 218.76 | 209.927857268744 | 8.83214273125589 | 395 | 217.63 | 210.866290722802 | 6.76370927719789 |
Goldfeld-Quandt test for Heteroskedasticity | p-values | Alternative Hypothesis | breakpoint index | greater | 2-sided | less | 16 | 0.00185420745353597 | 0.00370841490707195 | 0.998145792546464 | 17 | 0.000172565944697840 | 0.000345131889395679 | 0.999827434055302 | 18 | 0.000165468836506716 | 0.000330937673013431 | 0.999834531163493 | 19 | 2.26489824161312e-05 | 4.52979648322625e-05 | 0.999977351017584 | 20 | 5.19290062297979e-06 | 1.03858012459596e-05 | 0.999994807099377 | 21 | 1.21726415170108e-06 | 2.43452830340216e-06 | 0.999998782735848 | 22 | 2.11541060870751e-07 | 4.23082121741503e-07 | 0.99999978845894 | 23 | 2.9962443864673e-08 | 5.9924887729346e-08 | 0.999999970037556 | 24 | 4.54585278155623e-08 | 9.09170556311247e-08 | 0.999999954541472 | 25 | 6.11985544903147e-08 | 1.22397108980629e-07 | 0.999999938801446 | 26 | 6.11071506376289e-08 | 1.22214301275258e-07 | 0.99999993889285 | 27 | 2.88606932791186e-08 | 5.77213865582371e-08 | 0.999999971139307 | 28 | 1.62782273018288e-08 | 3.25564546036576e-08 | 0.999999983721773 | 29 | 4.03450554550198e-09 | 8.06901109100397e-09 | 0.999999995965494 | 30 | 9.51999784803648e-10 | 1.90399956960730e-09 | 0.999999999048 | 31 | 4.92845870175416e-10 | 9.85691740350832e-10 | 0.999999999507154 | 32 | 9.89297357249243e-11 | 1.97859471449849e-10 | 0.99999999990107 | 33 | 2.33347480908778e-11 | 4.66694961817556e-11 | 0.999999999976665 | 34 | 5.16933960201992e-12 | 1.03386792040398e-11 | 0.99999999999483 | 35 | 1.68487623088036e-12 | 3.36975246176073e-12 | 0.999999999998315 | 36 | 3.40369901546132e-13 | 6.80739803092263e-13 | 0.99999999999966 | 37 | 6.50273959429726e-14 | 1.30054791885945e-13 | 0.999999999999935 | 38 | 1.45719507150819e-14 | 2.91439014301639e-14 | 0.999999999999985 | 39 | 8.07457916685841e-15 | 1.61491583337168e-14 | 0.999999999999992 | 40 | 3.89358601887026e-15 | 7.78717203774051e-15 | 0.999999999999996 | 41 | 1.41573742955586e-14 | 2.83147485911172e-14 | 0.999999999999986 | 42 | 5.94851607804214e-15 | 1.18970321560843e-14 | 0.999999999999994 | 43 | 1.48255711338460e-14 | 2.96511422676921e-14 | 0.999999999999985 | 44 | 1.20526465165684e-13 | 2.41052930331369e-13 | 0.99999999999988 | 45 | 5.68040825090465e-13 | 1.13608165018093e-12 | 0.999999999999432 | 46 | 1.87791293550296e-11 | 3.75582587100592e-11 | 0.99999999998122 | 47 | 6.44466603992532e-11 | 1.28893320798506e-10 | 0.999999999935553 | 48 | 1.31253490789673e-10 | 2.62506981579345e-10 | 0.999999999868747 | 49 | 3.68706569039908e-09 | 7.37413138079816e-09 | 0.999999996312934 | 50 | 1.93284560764517e-08 | 3.86569121529034e-08 | 0.999999980671544 | 51 | 1.95520758194988e-08 | 3.91041516389976e-08 | 0.999999980447924 | 52 | 1.09735852971201e-08 | 2.19471705942402e-08 | 0.999999989026415 | 53 | 6.71078784105171e-09 | 1.34215756821034e-08 | 0.999999993289212 | 54 | 7.23670542319618e-09 | 1.44734108463924e-08 | 0.999999992763295 | 55 | 3.50944574710868e-09 | 7.01889149421737e-09 | 0.999999996490554 | 56 | 1.53243208701345e-09 | 3.06486417402689e-09 | 0.999999998467568 | 57 | 1.08424335336246e-09 | 2.16848670672493e-09 | 0.999999998915757 | 58 | 5.19129060639301e-10 | 1.03825812127860e-09 | 0.99999999948087 | 59 | 2.53840172736788e-10 | 5.07680345473577e-10 | 0.99999999974616 | 60 | 5.742921654381e-10 | 1.1485843308762e-09 | 0.999999999425708 | 61 | 3.71032446907294e-10 | 7.42064893814587e-10 | 0.999999999628968 | 62 | 1.93697259572442e-10 | 3.87394519144884e-10 | 0.999999999806303 | 63 | 1.08726326605933e-10 | 2.17452653211866e-10 | 0.999999999891274 | 64 | 5.22056140476174e-11 | 1.04411228095235e-10 | 0.999999999947794 | 65 | 2.54849119011467e-11 | 5.09698238022933e-11 | 0.999999999974515 | 66 | 1.47092467951504e-11 | 2.94184935903008e-11 | 0.99999999998529 | 67 | 6.70322119264e-12 | 1.340644238528e-11 | 0.999999999993297 | 68 | 6.22082672409523e-12 | 1.24416534481905e-11 | 0.99999999999378 | 69 | 5.19827649507548e-12 | 1.03965529901510e-11 | 0.999999999994802 | 70 | 2.5365334470296e-12 | 5.0730668940592e-12 | 0.999999999997463 | 71 | 1.60847358410317e-12 | 3.21694716820634e-12 | 0.999999999998392 | 72 | 8.12188563000704e-13 | 1.62437712600141e-12 | 0.999999999999188 | 73 | 4.02358606505863e-13 | 8.04717213011726e-13 | 0.999999999999598 | 74 | 2.70166622505117e-13 | 5.40333245010234e-13 | 0.99999999999973 | 75 | 3.16957395048769e-13 | 6.33914790097538e-13 | 0.999999999999683 | 76 | 1.62721538317656e-13 | 3.25443076635311e-13 | 0.999999999999837 | 77 | 8.10449163087087e-14 | 1.62089832617417e-13 | 0.99999999999992 | 78 | 5.52413509520862e-14 | 1.10482701904172e-13 | 0.999999999999945 | 79 | 6.08643060682267e-14 | 1.21728612136453e-13 | 0.99999999999994 | 80 | 4.37818238848486e-14 | 8.75636477696972e-14 | 0.999999999999956 | 81 | 8.87692636758636e-14 | 1.77538527351727e-13 | 0.999999999999911 | 82 | 4.38472615422749e-13 | 8.76945230845498e-13 | 0.999999999999561 | 83 | 2.84138162937284e-13 | 5.68276325874567e-13 | 0.999999999999716 | 84 | 1.64887038583886e-13 | 3.29774077167772e-13 | 0.999999999999835 | 85 | 1.01017292482336e-13 | 2.02034584964672e-13 | 0.999999999999899 | 86 | 6.22675668287382e-14 | 1.24535133657476e-13 | 0.999999999999938 | 87 | 3.7043587383879e-14 | 7.4087174767758e-14 | 0.999999999999963 | 88 | 2.22222216161965e-14 | 4.4444443232393e-14 | 0.999999999999978 | 89 | 1.23778432481031e-14 | 2.47556864962063e-14 | 0.999999999999988 | 90 | 6.4932050755743e-15 | 1.29864101511486e-14 | 0.999999999999994 | 91 | 4.38385760540924e-15 | 8.76771521081848e-15 | 0.999999999999996 | 92 | 2.45077572558679e-15 | 4.90155145117357e-15 | 0.999999999999998 | 93 | 1.37040897439675e-15 | 2.74081794879349e-15 | 0.999999999999999 | 94 | 8.7746259802468e-16 | 1.75492519604936e-15 | 1 | 95 | 6.30112043862649e-16 | 1.26022408772530e-15 | 1 | 96 | 4.46427445339231e-16 | 8.92854890678462e-16 | 1 | 97 | 2.87208974694046e-16 | 5.74417949388091e-16 | 1 | 98 | 1.86070074029661e-16 | 3.72140148059321e-16 | 1 | 99 | 1.36578848327520e-16 | 2.73157696655041e-16 | 1 | 100 | 9.19578613913585e-17 | 1.83915722782717e-16 | 1 | 101 | 5.37226758506081e-17 | 1.07445351701216e-16 | 1 | 102 | 3.90850822390839e-17 | 7.81701644781678e-17 | 1 | 103 | 3.45452901131305e-17 | 6.9090580226261e-17 | 1 | 104 | 2.33892323281547e-17 | 4.67784646563094e-17 | 1 | 105 | 1.74408418456501e-17 | 3.48816836913003e-17 | 1 | 106 | 1.5156755538715e-17 | 3.031351107743e-17 | 1 | 107 | 1.24332835684482e-17 | 2.48665671368964e-17 | 1 | 108 | 1.19996994371957e-17 | 2.39993988743914e-17 | 1 | 109 | 1.04534449812965e-17 | 2.09068899625931e-17 | 1 | 110 | 9.35537302790848e-18 | 1.87107460558170e-17 | 1 | 111 | 8.95637201215318e-18 | 1.79127440243064e-17 | 1 | 112 | 8.59637098337867e-18 | 1.71927419667573e-17 | 1 | 113 | 1.16466280724069e-17 | 2.32932561448139e-17 | 1 | 114 | 1.59519485312256e-17 | 3.19038970624513e-17 | 1 | 115 | 2.43594569355149e-17 | 4.87189138710298e-17 | 1 | 116 | 1.91295487675207e-17 | 3.82590975350413e-17 | 1 | 117 | 9.3678275367999e-17 | 1.87356550735998e-16 | 1 | 118 | 1.63690763936155e-15 | 3.27381527872311e-15 | 0.999999999999998 | 119 | 1.60438127565520e-14 | 3.20876255131040e-14 | 0.999999999999984 | 120 | 2.90937769608763e-13 | 5.81875539217527e-13 | 0.99999999999971 | 121 | 6.04624832258804e-13 | 1.20924966451761e-12 | 0.999999999999395 | 122 | 1.21431677406494e-12 | 2.42863354812989e-12 | 0.999999999998786 | 123 | 7.63511669959964e-12 | 1.52702333991993e-11 | 0.999999999992365 | 124 | 4.40295099735112e-11 | 8.80590199470223e-11 | 0.99999999995597 | 125 | 2.49651738503705e-10 | 4.9930347700741e-10 | 0.999999999750348 | 126 | 6.29497951983631e-10 | 1.25899590396726e-09 | 0.999999999370502 | 127 | 4.45528190513313e-09 | 8.91056381026625e-09 | 0.999999995544718 | 128 | 1.23056233172599e-08 | 2.46112466345197e-08 | 0.999999987694377 | 129 | 2.22873275169126e-08 | 4.45746550338252e-08 | 0.999999977712672 | 130 | 1.06091380494867e-07 | 2.12182760989733e-07 | 0.99999989390862 | 131 | 7.1748674518679e-07 | 1.43497349037358e-06 | 0.999999282513255 | 132 | 1.29898050310926e-06 | 2.59796100621852e-06 | 0.999998701019497 | 133 | 1.9763995401906e-06 | 3.9527990803812e-06 | 0.99999802360046 | 134 | 3.70840512961016e-06 | 7.41681025922032e-06 | 0.99999629159487 | 135 | 6.61924294039617e-06 | 1.32384858807923e-05 | 0.99999338075706 | 136 | 1.80368878701685e-05 | 3.6073775740337e-05 | 0.99998196311213 | 137 | 1.93096500539708e-05 | 3.86193001079415e-05 | 0.999980690349946 | 138 | 1.84552712945638e-05 | 3.69105425891276e-05 | 0.999981544728705 | 139 | 2.01855124746052e-05 | 4.03710249492105e-05 | 0.999979814487525 | 140 | 2.09772005345737e-05 | 4.19544010691474e-05 | 0.999979022799465 | 141 | 2.95673746764305e-05 | 5.9134749352861e-05 | 0.999970432625324 | 142 | 5.6554390703956e-05 | 0.000113108781407912 | 0.999943445609296 | 143 | 6.66588971949256e-05 | 0.000133317794389851 | 0.999933341102805 | 144 | 7.20166895003778e-05 | 0.000144033379000756 | 0.9999279833105 | 145 | 7.94912745470819e-05 | 0.000158982549094164 | 0.999920508725453 | 146 | 9.48829430685597e-05 | 0.000189765886137119 | 0.999905117056931 | 147 | 0.000120480591820684 | 0.000240961183641368 | 0.99987951940818 | 148 | 0.000178332512633598 | 0.000356665025267196 | 0.999821667487366 | 149 | 0.0003699287731869 | 0.0007398575463738 | 0.999630071226813 | 150 | 0.000417792180843591 | 0.000835584361687182 | 0.999582207819156 | 151 | 0.000491002891199505 | 0.00098200578239901 | 0.9995089971088 | 152 | 0.00059629258664358 | 0.00119258517328716 | 0.999403707413356 | 153 | 0.000624778005872654 | 0.00124955601174531 | 0.999375221994127 | 154 | 0.0007705540298505 | 0.001541108059701 | 0.99922944597015 | 155 | 0.00122805872731333 | 0.00245611745462666 | 0.998771941272687 | 156 | 0.00141338437767957 | 0.00282676875535914 | 0.99858661562232 | 157 | 0.00165532483934545 | 0.0033106496786909 | 0.998344675160655 | 158 | 0.00193759583582752 | 0.00387519167165505 | 0.998062404164172 | 159 | 0.00219158825152050 | 0.00438317650304100 | 0.99780841174848 | 160 | 0.00223599598280155 | 0.00447199196560311 | 0.997764004017198 | 161 | 0.00211941674484534 | 0.00423883348969069 | 0.997880583255155 | 162 | 0.00212924540664771 | 0.00425849081329542 | 0.997870754593352 | 163 | 0.00207058266102541 | 0.00414116532205082 | 0.997929417338975 | 164 | 0.00180773555846554 | 0.00361547111693107 | 0.998192264441534 | 165 | 0.00177564930615818 | 0.00355129861231635 | 0.998224350693842 | 166 | 0.00179153862970067 | 0.00358307725940134 | 0.9982084613703 | 167 | 0.00156770001785260 | 0.00313540003570519 | 0.998432299982147 | 168 | 0.0023662910308510 | 0.0047325820617020 | 0.997633708969149 | 169 | 0.00264552773945159 | 0.00529105547890317 | 0.997354472260548 | 170 | 0.00255674046760571 | 0.00511348093521141 | 0.997443259532394 | 171 | 0.00284646962165486 | 0.00569293924330972 | 0.997153530378345 | 172 | 0.00276752250698864 | 0.00553504501397727 | 0.997232477493011 | 173 | 0.00249390671838519 | 0.00498781343677038 | 0.997506093281615 | 174 | 0.00227536113567966 | 0.00455072227135932 | 0.99772463886432 | 175 | 0.00226170991604698 | 0.00452341983209396 | 0.997738290083953 | 176 | 0.00216330623271497 | 0.00432661246542993 | 0.997836693767285 | 177 | 0.00224753112552285 | 0.0044950622510457 | 0.997752468874477 | 178 | 0.00249621688344141 | 0.00499243376688282 | 0.997503783116559 | 179 | 0.00247086844892289 | 0.00494173689784578 | 0.997529131551077 | 180 | 0.00243933925258960 | 0.00487867850517919 | 0.99756066074741 | 181 | 0.00276552790028012 | 0.00553105580056024 | 0.99723447209972 | 182 | 0.00327384480202112 | 0.00654768960404224 | 0.996726155197979 | 183 | 0.00508698659162201 | 0.0101739731832440 | 0.994913013408378 | 184 | 0.0060271104249597 | 0.0120542208499194 | 0.99397288957504 | 185 | 0.00557296731944119 | 0.0111459346388824 | 0.99442703268056 | 186 | 0.0052183319379548 | 0.0104366638759096 | 0.994781668062045 | 187 | 0.00511481148158956 | 0.0102296229631791 | 0.99488518851841 | 188 | 0.00520644911130803 | 0.0104128982226161 | 0.994793550888692 | 189 | 0.00519934515844495 | 0.0103986903168899 | 0.994800654841555 | 190 | 0.00506683887275937 | 0.0101336777455187 | 0.99493316112724 | 191 | 0.00545191034844053 | 0.0109038206968811 | 0.99454808965156 | 192 | 0.00598875265269327 | 0.0119775053053865 | 0.994011247347307 | 193 | 0.0071343937123961 | 0.0142687874247922 | 0.992865606287604 | 194 | 0.0106643867357388 | 0.0213287734714776 | 0.989335613264261 | 195 | 0.0195456661782081 | 0.0390913323564163 | 0.980454333821792 | 196 | 0.0358670659828772 | 0.0717341319657543 | 0.964132934017123 | 197 | 0.0350056013877028 | 0.0700112027754057 | 0.964994398612297 | 198 | 0.0325136370962175 | 0.0650272741924351 | 0.967486362903782 | 199 | 0.0326724869359434 | 0.0653449738718867 | 0.967327513064057 | 200 | 0.0464539886938119 | 0.0929079773876239 | 0.953546011306188 | 201 | 0.062668532439199 | 0.125337064878398 | 0.937331467560801 | 202 | 0.0813982456947391 | 0.162796491389478 | 0.91860175430526 | 203 | 0.105582541197311 | 0.211165082394623 | 0.894417458802689 | 204 | 0.135592905445132 | 0.271185810890265 | 0.864407094554868 | 205 | 0.143789739837518 | 0.287579479675036 | 0.856210260162482 | 206 | 0.188879479463176 | 0.377758958926353 | 0.811120520536823 | 207 | 0.17301588208925 | 0.3460317641785 | 0.82698411791075 | 208 | 0.158064061061653 | 0.316128122123306 | 0.841935938938347 | 209 | 0.146823882057710 | 0.293647764115419 | 0.85317611794229 | 210 | 0.134038724710732 | 0.268077449421464 | 0.865961275289268 | 211 | 0.129936256234403 | 0.259872512468805 | 0.870063743765597 | 212 | 0.138621466619253 | 0.277242933238505 | 0.861378533380747 | 213 | 0.140793589403801 | 0.281587178807602 | 0.859206410596199 | 214 | 0.172394573884328 | 0.344789147768656 | 0.827605426115672 | 215 | 0.157809573894926 | 0.315619147789852 | 0.842190426105074 | 216 | 0.158889069107774 | 0.317778138215549 | 0.841110930892226 | 217 | 0.166678784877285 | 0.333357569754569 | 0.833321215122715 | 218 | 0.183787161341629 | 0.367574322683257 | 0.816212838658371 | 219 | 0.193473616343859 | 0.386947232687717 | 0.806526383656141 | 220 | 0.219085313514925 | 0.438170627029849 | 0.780914686485075 | 221 | 0.222891716670388 | 0.445783433340775 | 0.777108283329612 | 222 | 0.212627630349696 | 0.425255260699393 | 0.787372369650304 | 223 | 0.204867020339520 | 0.409734040679041 | 0.79513297966048 | 224 | 0.23149798433144 | 0.46299596866288 | 0.76850201566856 | 225 | 0.222459201872112 | 0.444918403744224 | 0.777540798127888 | 226 | 0.205610482724814 | 0.411220965449627 | 0.794389517275186 | 227 | 0.199378562480186 | 0.398757124960372 | 0.800621437519814 | 228 | 0.195880490144429 | 0.391760980288858 | 0.804119509855571 | 229 | 0.199239946837814 | 0.398479893675627 | 0.800760053162186 | 230 | 0.236117244942885 | 0.47223448988577 | 0.763882755057115 | 231 | 0.245890072087203 | 0.491780144174406 | 0.754109927912797 | 232 | 0.243428660245141 | 0.486857320490281 | 0.75657133975486 | 233 | 0.224819558609785 | 0.449639117219570 | 0.775180441390215 | 234 | 0.233371823356547 | 0.466743646713095 | 0.766628176643453 | 235 | 0.243264420707188 | 0.486528841414376 | 0.756735579292812 | 236 | 0.248673383028195 | 0.497346766056391 | 0.751326616971805 | 237 | 0.233156855155753 | 0.466313710311506 | 0.766843144844247 | 238 | 0.225622300478359 | 0.451244600956717 | 0.774377699521641 | 239 | 0.223969000003926 | 0.447938000007851 | 0.776030999996074 | 240 | 0.237952920066636 | 0.475905840133272 | 0.762047079933364 | 241 | 0.263568210079716 | 0.527136420159432 | 0.736431789920284 | 242 | 0.262422724358191 | 0.524845448716381 | 0.737577275641809 | 243 | 0.260078395593069 | 0.520156791186138 | 0.739921604406931 | 244 | 0.252815216377291 | 0.505630432754583 | 0.747184783622709 | 245 | 0.241146399288340 | 0.482292798576681 | 0.75885360071166 | 246 | 0.229892826574708 | 0.459785653149416 | 0.770107173425292 | 247 | 0.227212542846892 | 0.454425085693784 | 0.772787457153108 | 248 | 0.223723913324522 | 0.447447826649045 | 0.776276086675478 | 249 | 0.233212708355394 | 0.466425416710787 | 0.766787291644606 | 250 | 0.269502164619667 | 0.539004329239335 | 0.730497835380333 | 251 | 0.283131387346737 | 0.566262774693473 | 0.716868612653263 | 252 | 0.323539697461846 | 0.647079394923692 | 0.676460302538154 | 253 | 0.379751177776123 | 0.759502355552246 | 0.620248822223877 | 254 | 0.377821071247439 | 0.755642142494879 | 0.622178928752561 | 255 | 0.378422396741721 | 0.756844793483442 | 0.621577603258279 | 256 | 0.364059422700828 | 0.728118845401655 | 0.635940577299172 | 257 | 0.35189673246926 | 0.70379346493852 | 0.64810326753074 | 258 | 0.364661501855558 | 0.729323003711117 | 0.635338498144442 | 259 | 0.403003401294119 | 0.806006802588239 | 0.596996598705881 | 260 | 0.407922694535834 | 0.815845389071668 | 0.592077305464166 | 261 | 0.420616405103667 | 0.841232810207333 | 0.579383594896334 | 262 | 0.462024966614415 | 0.924049933228831 | 0.537975033385585 | 263 | 0.544164731672152 | 0.911670536655696 | 0.455835268327848 | 264 | 0.552561823069179 | 0.894876353861642 | 0.447438176930821 | 265 | 0.556285444871882 | 0.887429110256235 | 0.443714555128118 | 266 | 0.555934414118768 | 0.888131171762464 | 0.444065585881232 | 267 | 0.5356419615958 | 0.9287160768084 | 0.4643580384042 | 268 | 0.51229979303307 | 0.97540041393386 | 0.48770020696693 | 269 | 0.504091959932499 | 0.991816080135003 | 0.495908040067501 | 270 | 0.502170293239859 | 0.995659413520282 | 0.497829706760141 | 271 | 0.496152601284309 | 0.992305202568618 | 0.503847398715691 | 272 | 0.489639901753642 | 0.979279803507283 | 0.510360098246359 | 273 | 0.468379188134016 | 0.936758376268032 | 0.531620811865984 | 274 | 0.445522354924328 | 0.891044709848656 | 0.554477645075672 | 275 | 0.419982956372995 | 0.839965912745989 | 0.580017043627005 | 276 | 0.436234068066211 | 0.872468136132423 | 0.563765931933789 | 277 | 0.453460424893686 | 0.906920849787373 | 0.546539575106314 | 278 | 0.457239628246448 | 0.914479256492897 | 0.542760371753552 | 279 | 0.455151315306400 | 0.910302630612799 | 0.5448486846936 | 280 | 0.510707941673781 | 0.978584116652438 | 0.489292058326219 | 281 | 0.54120867580136 | 0.917582648397279 | 0.458791324198640 | 282 | 0.550819342214657 | 0.898361315570687 | 0.449180657785343 | 283 | 0.557217661027893 | 0.885564677944214 | 0.442782338972107 | 284 | 0.56522568438745 | 0.869548631225099 | 0.434774315612550 | 285 | 0.58133565588949 | 0.83732868822102 | 0.41866434411051 | 286 | 0.598402440800875 | 0.80319511839825 | 0.401597559199125 | 287 | 0.644258910737955 | 0.711482178524089 | 0.355741089262045 | 288 | 0.721122684562106 | 0.557754630875787 | 0.278877315437894 | 289 | 0.81629422939915 | 0.367411541201701 | 0.183705770600851 | 290 | 0.834314497119528 | 0.331371005760944 | 0.165685502880472 | 291 | 0.839426730259873 | 0.321146539480254 | 0.160573269740127 | 292 | 0.85576294846278 | 0.288474103074440 | 0.144237051537220 | 293 | 0.871840826764959 | 0.256318346470083 | 0.128159173235041 | 294 | 0.877930667141233 | 0.244138665717535 | 0.122069332858767 | 295 | 0.88049789932948 | 0.239004201341038 | 0.119502100670519 | 296 | 0.914521540531123 | 0.170956918937753 | 0.0854784594688766 | 297 | 0.961841006985434 | 0.0763179860291313 | 0.0381589930145656 | 298 | 0.983988313645764 | 0.0320233727084714 | 0.0160116863542357 | 299 | 0.987928477974268 | 0.0241430440514647 | 0.0120715220257323 | 300 | 0.989316953595434 | 0.0213660928091324 | 0.0106830464045662 | 301 | 0.994546929943158 | 0.0109061401136849 | 0.00545307005684247 | 302 | 0.997281656395193 | 0.0054366872096133 | 0.00271834360480665 | 303 | 0.998302852881294 | 0.00339429423741209 | 0.00169714711870605 | 304 | 0.998359697293054 | 0.00328060541389139 | 0.00164030270694570 | 305 | 0.99887635909589 | 0.00224728180822171 | 0.00112364090411085 | 306 | 0.99931531439133 | 0.00136937121733951 | 0.000684685608669757 | 307 | 0.999226133894438 | 0.00154773221112391 | 0.000773866105561954 | 308 | 0.99918191573405 | 0.00163616853189857 | 0.000818084265949286 | 309 | 0.999220141567917 | 0.00155971686416531 | 0.000779858432082655 | 310 | 0.999222600846457 | 0.00155479830708593 | 0.000777399153542967 | 311 | 0.999177438523714 | 0.00164512295257271 | 0.000822561476286353 | 312 | 0.999168887499481 | 0.00166222500103827 | 0.000831112500519134 | 313 | 0.999010277430233 | 0.00197944513953356 | 0.00098972256976678 | 314 | 0.998801592724215 | 0.00239681455157035 | 0.00119840727578518 | 315 | 0.998775298002614 | 0.00244940399477118 | 0.00122470199738559 | 316 | 0.998505988360476 | 0.00298802327904853 | 0.00149401163952427 | 317 | 0.99831323722508 | 0.00337352554984041 | 0.00168676277492020 | 318 | 0.998084612171626 | 0.00383077565674854 | 0.00191538782837427 | 319 | 0.998087694208599 | 0.00382461158280253 | 0.00191230579140127 | 320 | 0.997985892307383 | 0.00402821538523352 | 0.00201410769261676 | 321 | 0.998068320471725 | 0.00386335905655065 | 0.00193167952827532 | 322 | 0.997957360790639 | 0.00408527841872216 | 0.00204263920936108 | 323 | 0.99740582958066 | 0.00518834083867995 | 0.00259417041933998 | 324 | 0.99733108085635 | 0.00533783828729792 | 0.00266891914364896 | 325 | 0.99679328427064 | 0.00641343145871858 | 0.00320671572935929 | 326 | 0.99587166989821 | 0.00825666020358137 | 0.00412833010179069 | 327 | 0.995185893704455 | 0.00962821259108962 | 0.00481410629554481 | 328 | 0.997241640721453 | 0.00551671855709299 | 0.00275835927854650 | 329 | 0.99652556253732 | 0.00694887492536021 | 0.00347443746268010 | 330 | 0.995929994928083 | 0.0081400101438335 | 0.00407000507191675 | 331 | 0.997968520226065 | 0.00406295954786943 | 0.00203147977393471 | 332 | 0.998486168583261 | 0.00302766283347813 | 0.00151383141673907 | 333 | 0.997966197349698 | 0.00406760530060369 | 0.00203380265030184 | 334 | 0.998306703721833 | 0.00338659255633471 | 0.00169329627816735 | 335 | 0.997743055886287 | 0.00451388822742512 | 0.00225694411371256 | 336 | 0.997436631839848 | 0.00512673632030494 | 0.00256336816015247 | 337 | 0.999338098293186 | 0.00132380341362810 | 0.000661901706814051 | 338 | 0.99917344267232 | 0.00165311465535860 | 0.000826557327679298 | 339 | 0.998743974797852 | 0.00251205040429589 | 0.00125602520214794 | 340 | 0.998106438744953 | 0.00378712251009411 | 0.00189356125504706 | 341 | 0.997274389774911 | 0.00545122045017733 | 0.00272561022508866 | 342 | 0.996167439500185 | 0.00766512099962941 | 0.00383256049981471 | 343 | 0.9948261556389 | 0.0103476887222020 | 0.00517384436110099 | 344 | 0.993312928242892 | 0.0133741435142152 | 0.00668707175710758 | 345 | 0.994253601174693 | 0.0114927976506147 | 0.00574639882530735 | 346 | 0.99397799925735 | 0.0120440014852995 | 0.00602200074264973 | 347 | 0.99501900514416 | 0.0099619897116814 | 0.0049809948558407 | 348 | 0.995113842134653 | 0.00977231573069397 | 0.00488615786534698 | 349 | 0.992714105861255 | 0.0145717882774902 | 0.0072858941387451 | 350 | 0.98937137876569 | 0.0212572424686193 | 0.0106286212343097 | 351 | 0.985671046542996 | 0.0286579069140081 | 0.0143289534570041 | 352 | 0.985398224046634 | 0.0292035519067325 | 0.0146017759533662 | 353 | 0.986706769755279 | 0.0265864604894422 | 0.0132932302447211 | 354 | 0.981018438406727 | 0.0379631231865461 | 0.0189815615932731 | 355 | 0.981134763747487 | 0.0377304725050252 | 0.0188652362525126 | 356 | 0.976847324104287 | 0.0463053517914253 | 0.0231526758957126 | 357 | 0.967702826264755 | 0.0645943474704897 | 0.0322971737352449 | 358 | 0.973491096192206 | 0.0530178076155888 | 0.0265089038077944 | 359 | 0.964627655143662 | 0.0707446897126754 | 0.0353723448563377 | 360 | 0.949505625806753 | 0.100988748386494 | 0.0504943741932472 | 361 | 0.929546130611643 | 0.140907738776713 | 0.0704538693883567 | 362 | 0.904405201373958 | 0.191189597252085 | 0.0955947986260425 | 363 | 0.872057342139906 | 0.255885315720187 | 0.127942657860094 | 364 | 0.94157247137043 | 0.116855057259141 | 0.0584275286295703 | 365 | 0.928270881313492 | 0.143458237373016 | 0.071729118686508 | 366 | 0.941366093237305 | 0.11726781352539 | 0.0586339067626949 | 367 | 0.923811623487774 | 0.152376753024453 | 0.0761883765122264 | 368 | 0.948575081840161 | 0.102849836319678 | 0.0514249181598392 | 369 | 0.993743540431849 | 0.0125129191363019 | 0.00625645956815094 | 370 | 0.987797748361534 | 0.0244045032769313 | 0.0122022516384657 | 371 | 0.977014319470333 | 0.0459713610593341 | 0.0229856805296671 | 372 | 0.968239903755135 | 0.0635201924897306 | 0.0317600962448653 | 373 | 0.943080282934493 | 0.113839434131013 | 0.0569197170655066 | 374 | 0.903672698568102 | 0.192654602863796 | 0.0963273014318982 | 375 | 0.86942782810753 | 0.261144343784941 | 0.130572171892471 | 376 | 0.86921472154707 | 0.261570556905858 | 0.130785278452929 | 377 | 0.792572455165422 | 0.414855089669156 | 0.207427544834578 | 378 | 0.665188679121543 | 0.669622641756915 | 0.334811320878457 | 379 | 0.511472148029409 | 0.977055703941181 | 0.488527851970591 |
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity | Description | # significant tests | % significant tests | OK/NOK | 1% type I error level | 210 | 0.576923076923077 | NOK | 5% type I error level | 242 | 0.664835164835165 | NOK | 10% type I error level | 252 | 0.692307692307692 | NOK |
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| | Parameters (Session): | par1 = 1 ; par2 = Include Monthly Dummies ; par3 = No Linear Trend ; | | Parameters (R input): | par1 = 1 ; par2 = Include Monthly Dummies ; par3 = No Linear Trend ; | | R code (references can be found in the software module): | library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
par1 <- as.numeric(par1)
x <- t(y)
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
for (i in 1:n-1) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
k <- length(x[1,])
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
k <- length(x[1,])
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
qqline(mysum$resid)
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
if (rownames(mysum$coefficients)[i] != '(Intercept)') {
myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
}
}
myeq <- paste(myeq, ' + e[t]')
a<-table.row.start(a)
a<-table.element(a, myeq)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',header=TRUE)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'T-STAT<br />H0: parameter = 0',header=TRUE)
a<-table.element(a,'2-tail p-value',header=TRUE)
a<-table.element(a,'1-tail p-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:k){
a<-table.row.start(a)
a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
a<-table.element(a,mysum$coefficients[i,1])
a<-table.element(a, round(mysum$coefficients[i,2],6))
a<-table.element(a, round(mysum$coefficients[i,3],4))
a<-table.element(a, round(mysum$coefficients[i,4],6))
a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, sqrt(mysum$r.squared))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, mysum$r.squared)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, mysum$adj.r.squared)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, mysum$fstatistic[1])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, mysum$fstatistic[2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, mysum$fstatistic[3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
a<-table.element(a, mysum$sigma)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, sum(myerror*myerror))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation<br />Forecast', 1, TRUE)
a<-table.element(a, 'Residuals<br />Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,x[i])
a<-table.element(a,x[i]-mysum$resid[i])
a<-table.element(a,mysum$resid[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable4.tab')
if (n > n25) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-values',header=TRUE)
a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'breakpoint index',header=TRUE)
a<-table.element(a,'greater',header=TRUE)
a<-table.element(a,'2-sided',header=TRUE)
a<-table.element(a,'less',header=TRUE)
a<-table.row.end(a)
for (mypoint in kp3:nmkm3) {
a<-table.row.start(a)
a<-table.element(a,mypoint,header=TRUE)
a<-table.element(a,gqarr[mypoint-kp3+1,1])
a<-table.element(a,gqarr[mypoint-kp3+1,2])
a<-table.element(a,gqarr[mypoint-kp3+1,3])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable5.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description',header=TRUE)
a<-table.element(a,'# significant tests',header=TRUE)
a<-table.element(a,'% significant tests',header=TRUE)
a<-table.element(a,'OK/NOK',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'1% type I error level',header=TRUE)
a<-table.element(a,numsignificant1)
a<-table.element(a,numsignificant1/numgqtests)
if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'5% type I error level',header=TRUE)
a<-table.element(a,numsignificant5)
a<-table.element(a,numsignificant5/numgqtests)
if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'10% type I error level',header=TRUE)
a<-table.element(a,numsignificant10)
a<-table.element(a,numsignificant10/numgqtests)
if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable6.tab')
}
| |
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Software written by Ed van Stee & Patrick Wessa
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