Home » date » 2010 » Dec » 03 »

W4_Mini1

*The author of this computation has been verified*
R Software Module: /rwasp_multipleregression.wasp (opens new window with default values)
Title produced by software: Multiple Regression
Date of computation: Fri, 03 Dec 2010 07:22:55 +0000
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Dec/03/t12913608805lw9xqzu9ppcs9c.htm/, Retrieved Fri, 03 Dec 2010 08:21:20 +0100
 
BibTeX entries for LaTeX users:
@Manual{KEY,
    author = {{YOUR NAME}},
    publisher = {Office for Research Development and Education},
    title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2010/Dec/03/t12913608805lw9xqzu9ppcs9c.htm/},
    year = {2010},
}
@Manual{R,
    title = {R: A Language and Environment for Statistical Computing},
    author = {{R Development Core Team}},
    organization = {R Foundation for Statistical Computing},
    address = {Vienna, Austria},
    year = {2010},
    note = {{ISBN} 3-900051-07-0},
    url = {http://www.R-project.org},
}
 
Original text written by user:
 
IsPrivate?
No (this computation is public)
 
User-defined keywords:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
1 162556 1081 213118 6282929 1 29790 309 81767 4324047 1 87550 458 153198 4108272 0 84738 588 -26007 -1212617 1 54660 299 126942 1485329 1 42634 156 157214 1779876 0 40949 481 129352 1367203 1 42312 323 234817 2519076 1 37704 452 60448 912684 1 16275 109 47818 1443586 0 25830 115 245546 1220017 0 12679 110 48020 984885 1 18014 239 -1710 1457425 0 43556 247 32648 -572920 1 24524 497 95350 929144 0 6532 103 151352 1151176 0 7123 109 288170 790090 1 20813 502 114337 774497 1 37597 248 37884 990576 0 17821 373 122844 454195 1 12988 119 82340 876607 1 22330 84 79801 711969 0 13326 102 165548 702380 0 16189 295 116384 264449 0 7146 105 134028 450033 0 15824 64 63838 541063 1 26088 267 74996 588864 0 11326 129 31080 -37216 0 8568 37 32168 783310 0 14416 361 49857 467359 1 3369 28 87161 688779 1 11819 85 106113 608419 1 6620 44 80570 696348 1 4519 49 102129 597793 0 2220 22 301670 821730 0 18562 155 102313 377934 0 10327 91 88577 651939 1 5336 81 112477 697458 1 2365 79 191778 70 etc...
 
Output produced by software:

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!


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time15 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24
R Framework
error message
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.


Multiple Linear Regression - Estimated Regression Equation
Dividends[t] = + 57146.7295028292 + 3361.87435099314Group[t] -0.560278388449414Costs[t] + 79.195399053517Trades[t] + 0.0312971227269294`Wealth `[t] + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0		2-tail p-value1-tail p-value
(Intercept)57146.72950282922085.08645627.407400
Group3361.874350993143123.4938561.07630.2823940.141197
Costs-0.5602783884494140.21626-2.59080.0099050.004952
Trades79.19539905351719.2389354.11644.6e-052.3e-05
`Wealth `0.03129712272692940.0043267.235200


Multiple Linear Regression - Regression Statistics
Multiple R0.478593618443197
R-squared0.229051851614552
Adjusted R-squared0.221812901864454
F-TEST (value)31.6415860755835
F-TEST (DF numerator)4
F-TEST (DF denominator)426
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation28321.2251469301
Sum Squared Residuals341691104168.644


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast		Residuals
Prediction Error
1213118251679.816515475-38561.8165154749
281767203619.518605462-121852.518605462
3153198176304.816691195-23106.8166911945
4-2600718285.3309961099-44292.3309961099
5126942100049.73546104626892.2645389537
6157214104681.17490373552532.8250962652
7129352115086.39680258214265.6031974181
8234817141222.04930649993594.950693501
960448103744.571026820-43296.5710268202
1047818105202.459787519-57384.4597875186
1124554689965.2313982755155580.768601724
124802089578.5204284778-41558.5204284778
13-1710114956.658428380-116666.658428380
143264834373.7600290329-1725.76002903289
1595350115207.983784077-19857.9837840770
1615135297672.613724285653679.3862757144
1728817086515.708734057201654.291265943
18114337112843.1477405291493.85225947112
193788490086.4548909127-52202.4548909127
2012284490916.888846191831927.1111538082
218234090091.2374942953-7751.23749429528
227980176932.58213101162868.41786898844
2316554879740.863462751785807.1365372483
2411638479715.51820102336668.4817989771
2513402875543.235071757258484.7649282428
266383870283.1049374314-6445.10493743137
277499685466.9816807136-10470.9816807136
283108059852.4692337495-28772.4692337495
293216879791.8432388058-47623.8432388058
304985792286.2872937971-42429.2872937971
318716182395.29803136654765.70196863355
3210611379660.046612683326452.9533873167
338057082077.8472972938-1507.84729729381
3410212980566.481256341121562.5187436589
3530167083362.9949180486218307.005081951
3610231370850.375690405731462.6243095943
378857778971.33079265389605.66920734621
3811247785762.214319269926714.7856807301
3919177887359.4852403814104418.514759619
407980473423.00117955646380.9988204436
41128294128363.578964821-69.5789648207874
429644865986.952624311930461.0473756881
439381188211.67812739555599.32187260451
4411752074562.659601597442957.3403984026
456915971351.3055021593-2192.30550215935
4610179270886.566966258330905.4330337417
4721056881787.8444210385128780.155578961
4813699696874.743164960140121.2568350399
4912192075734.917992595746185.0820074043
507640365113.238457649511289.7615423505
5110809484940.457177885723153.5428221143
5213475986084.976111486448674.0238885136
5318887381840.7483798167107032.251620183
5414621689724.030785767456491.9692142326
5515660880717.967873349575890.0321266505
566134876739.8622926026-15391.8622926026
575035071710.612749023-21360.6127490229
588772073632.134221874814087.8657781252
599948976410.884891926323078.1151080737
608741975998.864180897711420.1358191023
619435576555.089108065517799.9108919345
626032666590.4636515686-6264.46365156855
639467074471.72394155120198.2760584490
648242573622.04852778128802.95147221878
655901773218.8632558262-14201.8632558262
6690829136016.474938148-45187.4749381477
678079169886.525577632210904.4744223678
6810042376332.664934072924090.3350659271
6913111677886.229764153253229.7702358468
7010026976343.834119327423925.1658806726
712733071138.9539543539-43808.9539543539
723903970005.7945834536-30966.7945834536
7310688569260.444270056537624.5557299435
747928567980.233149245111304.7668507549
7511888170899.74987772347981.250122277
767762370012.21205715257610.78794284755
7711476871888.888790811242879.1112091889
787401568524.6183019945490.38169800601
796946577141.7941440408-7676.7941440408
8011786986834.650028581231034.3499714188
816098269255.5150094827-8273.51500948265
829013177222.484438346912908.5155616531
8313897174438.067758070364532.9322419297
843962567426.3229579108-27801.3229579108
8510272571090.567018607731634.4329813923
866423974202.6841726761-9963.68417267614
879026276261.817052727914000.1829472721
8810396070108.27906723733851.720932763
8910661172272.812153766734338.1878462333
9010334570455.656384754432889.3436152456
919555172429.709101762823121.2908982372
928290373782.72061534669120.27938465343
936359377131.5152624856-13538.5152624856
9412691074349.711851755752560.2881482444
953752770876.838353347-33349.8383533470
966024773990.135137404-13743.1351374040
9711299572257.017158479540737.9828415205
987018486816.9098513669-16632.9098513669
9913014071105.218341190759034.7816588093
1007322170905.3346698272315.66533017294
1017611472348.15232898573765.84767101434
1029053467399.500609418923134.4993905811
10310847973385.621045983335093.3789540167
10411376170993.652114205942767.3478857941
1056869670455.6537478103-1759.65374781034
1067156167046.89277255184514.10722744817
1075983168281.0663564456-8450.06635644556
1089789077011.367843510120878.6321564899
10910148168918.453842096832562.5461579032
1107295470555.64490001032398.35509998974
1116793972173.2580629561-4234.25806295609
1124802266351.8913510745-18329.8913510745
1138611165888.870666279220222.1293337208
1147402068683.04399787075336.95600212934
1155753071496.622271322-13966.6222713220
1165636470491.9624979915-14127.9624979915
1178499070363.748364443714626.2516355563
1188859071847.419744326216742.5802556738
1197720067150.983679328110049.0163206719
1206126272732.6107118508-11470.6107118508
12111030971604.305919248238704.6940807518
1226700068765.6280871145-1765.62808711455
1239309976193.840637762916905.1593622371
12410757777071.710954524630505.2890454754
1256292070696.061594281-7776.06159428102
1267583267340.4887250628491.51127493796
1276072067335.8207778084-6615.82077780836
1286079367829.8233104779-7036.82331047791
1295793569206.8763821187-11271.8763821187
1306072067335.8207778084-6615.82077780836
1316063067951.5550928156-7321.55509281556
1325563773063.0175014853-17426.0175014853
1336072067335.8207778084-6615.82077780836
1346088767495.7969244025-6608.79692440253
1356072067335.8207778084-6615.82077780836
1366050568057.8744672561-7552.87446725613
1376094568303.1823436687-7358.18234366873
1386072067335.8207778084-6615.82077780836
1396072067335.8207778084-6615.82077780836
1406072067335.8207778084-6615.82077780836
1415899068123.4840520655-9133.48405206554
1426072067335.8207778084-6615.82077780836
1435675067973.1816228483-11223.1816228483
1446089467566.5382301437-6672.53823014367
1456334668910.2749762582-5564.27497625822
1465653568044.4225728479-11509.4225728479
1476072067335.8207778084-6615.82077780836
1486083567799.5660535971-6964.56605359712
1496072067335.8207778084-6615.82077780836
1506101667418.7522148326-6402.75221483255
1515865067600.4497009888-8950.44970098878
1526043872153.578589454-11715.5785894541
1536072067335.8207778084-6615.82077780836
1545862567241.9522925632-8616.95229256316
1556093867561.5754647454-6623.57546474538
1566072067335.8207778084-6615.82077780836
1576072067335.8207778084-6615.82077780836
1586149067476.1097101742-5986.10971017422
1596084568133.3586072194-7288.35860721944
1606072067335.8207778084-6615.82077780836
1616072067335.8207778084-6615.82077780836
1626072067335.8207778084-6615.82077780836
1636072067335.8207778084-6615.82077780836
1646083069399.6524558846-8569.65245588464
1656326171049.6569466961-7788.6569466961
1666072067335.8207778084-6615.82077780836
1676072067335.8207778084-6615.82077780836
1684568970361.8943627204-24672.8943627204
1696072067335.8207778084-6615.82077780836
1706072067335.8207778084-6615.82077780836
1716072067335.8207778084-6615.82077780836
1726156467602.324519975-6038.32451997494
1736072067335.8207778084-6615.82077780836
1746193868033.9295469882-6095.92954698824
1756072067335.8207778084-6615.82077780836
1766095167902.7783028262-6951.77830282622
1776072067335.8207778084-6615.82077780836
1786074570744.809854466-9999.80985446593
1796072067335.8207778084-6615.82077780836
1806072067335.8207778084-6615.82077780836
1817164271429.6784662338212.321533766244
1827164171948.5614542572-307.561454257182
1835579270214.7132843708-14422.7132843708
1847187370701.45482038511171.54517961488
1856255571205.2543782197-8650.25437821975
1866037071495.7623021968-11125.7623021968
1876487372533.5391310075-7660.53913100746
1886204167738.7962750005-5697.79627500053
1896574567026.2406810836-1281.24068108364
1906072067335.8207778084-6615.82077780836
1915950067679.5796721741-8179.57967217412
1926072067335.8207778084-6615.82077780836
1936163067928.0390961196-6298.03909611958
1946072067335.8207778084-6615.82077780836
1956089067482.4359213797-6592.43592137967
1966072070697.6951288015-9977.69512880149
19711352178065.621633930935455.3783660691
1986072070697.6951288015-9977.69512880149
1996072070697.6951288015-9977.69512880149
2008004571790.37275924448254.62724075562
2016072070697.6951288015-9977.69512880149
2026072070697.6951288015-9977.69512880149
2036072070697.6951288015-9977.69512880149
2045080472291.8050615278-21487.8050615278
2058739072146.817032890715243.1829671093
2066165670877.7429369192-9221.74293691919
2076568871041.6482435062-5353.6482435062
2086072070697.6951288015-9977.69512880149
2094852273574.7586193611-25052.7586193611
2106072070697.6951288015-9977.69512880149
2116072067335.8207778084-6615.82077780836
2126072067335.8207778084-6615.82077780836
2135764069632.2526288377-11992.2526288377
2146197768195.4035778223-6218.40357782234
2156262067551.4090515014-4931.40905150142
2166072067335.8207778084-6615.82077780836
2176083167979.632879555-7148.632879555
2186064669374.6774029101-8728.67740291012
2196072067335.8207778084-6615.82077780836
2205622568570.987099263-12345.9870992630
2216051066621.2134834631-6111.21348346308
2226072067335.8207778084-6615.82077780836
2236069867491.7796098046-6793.7796098046
2246072067335.8207778084-6615.82077780836
2256080567489.3280269372-6684.32802693724
2266140469314.1629643873-7910.16296438731
2276072067335.8207778084-6615.82077780836
2286072067335.8207778084-6615.82077780836
2296527667324.7284765653-2048.72847656528
2306072067335.8207778084-6615.82077780836
2316391567689.9172651763-3774.91726517626
2326072067335.8207778084-6615.82077780836
2336072067335.8207778084-6615.82077780836
2346168668681.5196168392-6995.51961683923
2356072067335.8207778084-6615.82077780836
2366074367411.5796330032-6668.57963300318
2376072067335.8207778084-6615.82077780836
2386034967789.9990176597-7440.99901765972
2396072067335.8207778084-6615.82077780836
2406072067335.8207778084-6615.82077780836
2416072067335.8207778084-6615.82077780836
2426136067715.0020472207-6355.00204722071
2436072067335.8207778084-6615.82077780836
2445981867923.4821726459-8105.48217264588
2457268066797.80713872165882.19286127838
2466072070697.6951288015-9977.69512880149
2476072070697.6951288015-9977.69512880149
2486180867946.4794988486-6138.47949884859
2496072070697.6951288015-9977.69512880149
2506072070697.6951288015-9977.69512880149
2515311067359.9552185257-14249.9552185257
2526072070697.6951288015-9977.69512880149
2536424567163.0060321788-2918.00603217876
2547300772954.121094624852.8789053751984
2558273273881.17446159448850.82553840564
2566072067335.8207778084-6615.82077780836
2575482068034.7887448495-13214.7887448495
2584770569517.2928369765-21812.2928369765
2596072070697.6951288015-9977.69512880149
2606072067335.8207778084-6615.82077780836
2616072070697.6951288015-9977.69512880149
2626072070697.6951288015-9977.69512880149
2637283568883.06953386213951.93046613785
2645885668450.8642860333-9594.86428603333
2656072070697.6951288015-9977.69512880149
2666072067335.8207778084-6615.82077780836
2676072070697.6951288015-9977.69512880149
2687765570055.1416367387599.85836326197
2696072070697.6951288015-9977.69512880149
2706981768082.44989019231734.55010980766
2716072070697.6951288015-9977.69512880149
2726072070697.6951288015-9977.69512880149
2736072070697.6951288015-9977.69512880149
2746079868107.0915923138-7309.09159231376
2756072067335.8207778084-6615.82077780836
2766245269826.3447770681-7374.34477706814
2776417570157.077426344-5982.07742634407
2786072067335.8207778084-6615.82077780836
2796744076594.2477726912-9154.24777269117
2806813669347.8032808273-1211.80328082727
2816072070697.6951288015-9977.69512880149
2826072067335.8207778084-6615.82077780836
2835672672829.2448468339-16103.2448468339
2846072067335.8207778084-6615.82077780836
2857081168247.2663666772563.73363332305
2866072067335.8207778084-6615.82077780836
2876072070697.6951288015-9977.69512880149
2886204567717.0726500908-5672.07265009078
2896072070697.6951288015-9977.69512880149
2905432371669.3305843982-17346.3305843982
2916072070697.6951288015-9977.69512880149
2926284169469.6170916041-6628.61709160413
2938112570211.889001684910913.1109983151
2946072067335.8207778084-6615.82077780836
2955950668235.9672564627-8729.96725646265
2965936573093.8856925-13728.8856925
2976072067335.8207778084-6615.82077780836
2986072070697.6951288015-9977.69512880149
2996072067335.8207778084-6615.82077780836
3006072067335.8207778084-6615.82077780836
3016079870950.3158266762-10152.3158266762
3025879066890.5666013063-8100.56660130626
3036072067335.8207778084-6615.82077780836
3046072070697.6951288015-9977.69512880149
3056180872199.9589852763-10391.9589852763
3066073568048.3977261949-7313.39772619492
3076072070697.6951288015-9977.69512880149
3086401671704.5292554557-7688.52925545571
3095468368880.6868272846-14197.6868272846
3106072070697.6951288015-9977.69512880149
3116072070697.6951288015-9977.69512880149
3128719275075.852016869412116.1479831306
3136072070697.6951288015-9977.69512880149
3146410771505.7650131525-7398.76501315249
3156076167660.6549440252-6899.65494402515
3166599068889.7280617745-2899.72806177449
3175998867378.5280746544-7390.52807465442
3186116768140.2045821543-6973.20458215426
3196071967810.3390023728-7091.33900237283
3206072067335.8207778084-6615.82077780836
3216072067335.8207778084-6615.82077780836
3226072067335.8207778084-6615.82077780836
3236072067335.8207778084-6615.82077780836
3246072070697.6951288015-9977.69512880149
3256072067335.8207778084-6615.82077780836
3266072267390.7795271114-6668.77952711141
3276072070697.6951288015-9977.69512880149
3286072070697.6951288015-9977.69512880149
3296072067335.8207778084-6615.82077780836
3306072067335.8207778084-6615.82077780836
3316072067335.8207778084-6615.82077780836
3326072067335.8207778084-6615.82077780836
3336072067335.8207778084-6615.82077780836
3346037967647.9032157215-7268.90321572149
3356072767493.870377386-6766.87037738603
3366072067335.8207778084-6615.82077780836
3376092567796.1389958782-6871.1389958782
3386072067335.8207778084-6615.82077780836
3396089667406.3327978349-6510.33279783485
3405973468227.2549250168-8493.25492501683
3416296968035.7300407214-5066.73004072143
3426072067335.8207778084-6615.82077780836
3436072067335.8207778084-6615.82077780836
3446072067335.8207778084-6615.82077780836
3456072067335.8207778084-6615.82077780836
3466072067335.8207778084-6615.82077780836
3475911867328.5377684767-8210.53776847672
3486072067335.8207778084-6615.82077780836
3496072067335.8207778084-6615.82077780836
3506072067335.8207778084-6615.82077780836
3515859868113.7646476904-9515.76464769036
3526112468084.3307685003-6960.3307685003
3535959568188.9121577328-8593.91215773276
3546206567338.766330521-5273.76633052105
3556072067335.8207778084-6615.82077780836
3566072067335.8207778084-6615.82077780836
3577878071782.33267478976997.66732521033
3586072067335.8207778084-6615.82077780836
3596072067335.8207778084-6615.82077780836
3606072067335.8207778084-6615.82077780836
3616072267652.0107985112-6930.01079851124
3626072067335.8207778084-6615.82077780836
3636072067335.8207778084-6615.82077780836
3646160070717.3184301522-9117.3184301522
3655963567930.5744961008-8295.5744961008
3666072067335.8207778084-6615.82077780836
3676072067335.8207778084-6615.82077780836
3686072067335.8207778084-6615.82077780836
3696072067335.8207778084-6615.82077780836
3706072067335.8207778084-6615.82077780836
3716072067335.8207778084-6615.82077780836
3725978170032.2689808034-10251.2689808034
3737664468474.1659567158169.83404328498
3746482067056.9478934473-2236.94789344726
3756072067335.8207778084-6615.82077780836
3766072067335.8207778084-6615.82077780836
3775617868807.7043594353-12629.7043594353
3786043667700.6621668055-7264.66216680553
3796072067335.8207778084-6615.82077780836
3806072067335.8207778084-6615.82077780836
3816072067335.8207778084-6615.82077780836
3827343372535.6251816557897.374818344258
3834147772213.4764685658-30736.4764685658
3846072067335.8207778084-6615.82077780836
3856270068674.5753456143-5974.57534561431
3866780466458.51921023211345.48078976793
3875966167788.3606363057-8127.36063630567
3885862067368.2455402986-8748.2455402986
3896039867456.6080601787-7058.60806017866
3905858067681.28149401-9101.28149400997
3916271068205.0767924849-5495.07679248491
3925932567176.1627406084-7851.16274060837
3936095066795.9162761074-5845.91627610744
3946806069359.7608985558-1299.76089855581
3958362068279.090741065815340.9092589342
3965845667210.8140055547-8754.81400555472
3975281165343.5913794875-12532.5913794875
39812117385717.153434419535455.8465655805
3996387067571.0130583341-3701.01305833408
4002100175613.6545371736-54612.6545371736
4017041567816.55256035092598.44743964907
4026423068189.2009411879-3959.20094118786
4035919067198.7214532531-8008.72145325314
4046935171091.8387658145-1740.83876581454
4056427067281.4616348421-3011.46163484215
4067069467950.45307126782743.54692873221
4076800568840.9590151311-835.959015131116
4085893067467.4193890635-8537.41938906351
4095832067198.73216391-8878.73216391002
4106998066378.61461181333601.38538818672
4116986371224.0334309938-1361.03343099382
4126325567812.114649769-4557.11464976898
4135732070806.095919599-13486.0959195990
4147523070897.81170551074332.18829448933
4157942066714.480419365612705.5195806344
4167349066223.86419323777266.13580676227
4173525072235.6737366828-36985.6737366828
4186228570590.8078789302-8305.80787893017
4196920668684.16132506521.838674940056
4206592066128.3510628838-208.351062883817
4216977064911.52172739734858.47827260267
4227268368841.00082034543841.99917965464
423-1454557140.4805318006-71685.4805318006
4245583053729.72450848792100.27549151206
4255517464884.4284727271-9710.42847272712
4266703872811.4604328358-5773.46043283578
4275125257947.6341080591-6695.63410805914
42815727862317.786948491594960.2130515085
4297951061951.447307982617558.5526920174
4307744068830.78350993698609.21649006315
4312728451958.6487994728-24674.6487994728


Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
80.9999994990242071.00195158624281e-065.00975793121405e-07
90.9999996374554047.25089192436563e-073.62544596218281e-07
100.9999999624508577.50982857293423e-083.75491428646711e-08
110.9999999997026955.94609392327649e-102.97304696163824e-10
120.9999999999984863.02892014242363e-121.51446007121182e-12
1312.09433435176829e-151.04716717588415e-15
1411.04634850279565e-155.23174251397826e-16
1512.19043752089915e-171.09521876044958e-17
1613.35225033604623e-171.67612516802312e-17
1713.82740992913123e-271.91370496456561e-27
1814.33489240487099e-282.16744620243549e-28
1915.54959735935686e-312.77479867967843e-31
2012.24200159931932e-301.12100079965966e-30
2117.6710380848333e-313.83551904241665e-31
2213.69112618631154e-311.84556309315577e-31
2317.05290052959428e-313.52645026479714e-31
2411.76601724437378e-308.8300862218689e-31
2513.06363784377873e-301.53181892188936e-30
2617.4605578461973e-323.73027892309865e-32
2719.91413187721468e-334.95706593860734e-33
2814.99215851941777e-342.49607925970889e-34
2911.69599578139970e-408.47997890699851e-41
3014.50427439893732e-432.25213719946866e-43
3112.25558938368670e-431.12779469184335e-43
3211.03124906949786e-435.15624534748928e-44
3315.06654179452642e-452.53327089726321e-45
3415.75555814593983e-452.87777907296992e-45
3511.08587637770715e-625.42938188853575e-63
3612.66421951574173e-621.33210975787087e-62
3712.55672547611442e-641.27836273805721e-64
3817.80685105561663e-653.90342552780831e-65
3916.30166185399429e-693.15083092699715e-69
4017.77139548073245e-693.88569774036622e-69
4118.442345948377e-694.2211729741885e-69
4212.03351351828701e-681.01675675914350e-68
4313.09525325639802e-681.54762662819901e-68
4419.43241011006875e-684.71620505503438e-68
4514.50774782840439e-682.25387391420220e-68
4617.04667318385506e-683.52333659192753e-68
4712.69895030358693e-761.34947515179347e-76
4811.55952885727057e-767.79764428635286e-77
4913.67957453198968e-761.83978726599484e-76
5012.09915577108341e-761.04957788554170e-76
5118.10536232558138e-764.05268116279069e-76
5215.65112196771794e-762.82556098385897e-76
5311.03931613708804e-815.19658068544021e-82
5415.42967034343081e-832.71483517171541e-83
5517.31725455828713e-893.65862727914357e-89
5611.07845571944937e-895.39227859724683e-90
5714.78726574244234e-932.39363287122117e-93
5811.17780848517402e-925.88904242587008e-93
5911.09372457670818e-925.46862288354088e-93
6012.55530554213172e-921.27765277106586e-92
6117.75716717320577e-923.87858358660289e-92
6218.1499323646613e-924.07496618233065e-92
6313.32990723091110e-911.66495361545555e-91
6411.28853714588164e-906.44268572940821e-91
6515.92641060055672e-912.96320530027836e-91
6611.12125635655891e-925.60628178279457e-93
6718.06500428864148e-934.03250214432074e-93
6812.0894997771483e-921.04474988857415e-92
6911.42736599930807e-937.13682999654034e-94
7015.5810990285906e-932.7905495142953e-93
7114.12778715873806e-952.06389357936903e-95
7211.80545896164606e-989.0272948082303e-99
7319.68165280386025e-1004.84082640193012e-100
7411.71084302039442e-998.55421510197212e-100
7514.73371073652614e-1012.36685536826307e-101
7617.29461063100121e-1013.64730531550060e-101
7711.60781753457034e-1028.0390876728517e-103
7812.06767376287119e-1021.03383688143560e-102
7913.54219355081229e-1021.77109677540614e-102
8018.59942086329307e-1034.29971043164653e-103
8111.16164234044813e-1025.80821170224065e-103
8215.1387997970421e-1022.56939989852105e-102
8315.51519854279638e-1072.75759927139819e-107
8415.48869266875813e-1082.74434633437906e-108
8512.38070702823126e-1081.19035351411563e-108
8611.07139350680557e-1085.35696753402787e-109
8714.63148191940385e-1082.31574095970192e-108
8815.18358321019034e-1092.59179160509517e-109
8913.64228318684222e-1101.82114159342111e-110
9017.03945364778253e-1113.51972682389127e-111
9111.00841184425918e-1105.04205922129589e-111
9214.48830455667173e-1102.24415227833587e-110
9311.02173832727673e-1105.10869163638363e-111
9414.4920248193186e-1132.2460124096593e-113
9515.83440944820092e-1162.91720472410046e-116
9612.20769447618346e-1161.10384723809173e-116
9711.27338598231302e-1176.3669299115651e-118
9812.27170055373319e-1171.13585027686660e-117
9919.75223499828026e-1224.87611749914013e-122
10013.46161487042137e-1211.73080743521069e-121
10119.58657855782815e-1214.79328927891407e-121
10212.22754895113966e-1221.11377447556983e-122
10311.14605620303689e-1235.73028101518443e-124
10413.50201197281844e-1271.75100598640922e-127
10511.08921570628166e-1265.4460785314083e-127
10611.08504612259665e-1265.42523061298326e-127
10712.19971860368144e-1261.09985930184072e-126
10811.14609174586046e-1255.7304587293023e-126
10911.09403305132342e-1265.47016525661712e-127
11011.86565347077856e-1269.32826735389281e-127
11113.42114309290872e-1261.71057154645436e-126
11219.34157561716645e-1264.67078780858322e-126
11312.20145810942015e-1271.10072905471008e-127
11413.40806797273958e-1271.70403398636979e-127
11513.76720979675731e-1271.88360489837866e-127
11612.36883645427757e-1271.18441822713879e-127
11711.69434129814223e-1278.47170649071114e-128
11818.82295055230918e-1274.41147527615459e-127
11915.46579342157891e-1282.73289671078946e-128
12011.27427506386771e-1276.37137531933855e-128
12114.18181949360415e-1272.09090974680208e-127
12211.60785752079601e-1268.03928760398004e-127
12315.80366834710875e-1272.90183417355437e-127
12411.82150277038905e-1279.10751385194524e-128
12517.93104808175509e-1273.96552404087755e-127
12612.07410628744924e-1271.03705314372462e-127
12716.83424357177206e-1273.41712178588603e-127
12812.29468514037209e-1261.14734257018605e-126
12916.13972215946063e-1263.06986107973031e-126
13012.15385342012920e-1251.07692671006460e-125
13117.59570186677184e-1253.79785093338592e-125
13211.84708139731656e-1259.2354069865828e-126
13316.88401593116706e-1253.44200796558353e-125
13412.61671010397793e-1241.30835505198896e-124
13511.00184351704781e-1235.00921758523905e-124
13613.66397500365801e-1231.83198750182901e-123
13711.42556765295642e-1227.12783826478208e-123
13815.6458906181287e-1222.82294530906435e-122
13912.25791403926524e-1211.12895701963262e-121
14019.1118426561536e-1214.5559213280768e-121
14113.29768538873181e-1201.64884269436590e-120
14211.35360745399649e-1196.76803726998244e-120
14313.39613167306029e-1191.69806583653014e-119
14411.41932549687510e-1187.09662748437551e-119
14515.99291356912138e-1182.99645678456069e-118
14611.76656511649054e-1178.83282558245272e-118
14717.51042142408e-1173.75521071204e-117
14813.19853438577330e-1161.59926719288665e-116
14911.37208311695382e-1156.86041558476908e-116
15015.94729060033156e-1152.97364530016578e-115
15112.30449502377876e-1141.15224751188938e-114
15216.44293228438216e-1143.22146614219108e-114
15312.80762345957903e-1131.40381172978952e-113
15411.18223095850995e-1125.91115479254974e-113
15515.19254050652046e-1122.59627025326023e-112
15612.2795402876527e-1111.13977014382635e-111
15711.00253745223480e-1105.01268726117398e-111
15814.48087231774715e-1102.24043615887358e-110
15911.78745460527194e-1098.93727302635968e-110
16017.89345839107567e-1093.94672919553783e-109
16113.48893606836456e-1081.74446803418228e-108
16211.54321017374248e-1077.71605086871238e-108
16316.82937143961749e-1073.41468571980874e-107
16412.75332687642504e-1061.37666343821252e-106
16511.22942316506744e-1056.14711582533718e-106
16615.4426220730449e-1052.72131103652245e-105
16712.40910577010168e-1041.20455288505084e-104
16814.54918639541144e-1062.27459319770572e-106
16912.06219155501163e-1051.03109577750582e-105
17019.34198511228822e-1054.67099255614411e-105
17114.22871184276412e-1042.11435592138206e-104
17211.93842699940476e-1039.69213499702382e-104
17318.75616968257645e-1034.37808484128823e-103
17413.99422426691291e-1021.99711213345646e-102
17511.79958956112004e-1018.99794780560018e-102
17618.06766248961876e-1014.03383124480938e-101
17713.62471380074227e-1001.81235690037113e-100
17811.42305390201926e-997.11526951009632e-100
17916.36868379253291e-993.18434189626645e-99
18012.84549592137110e-981.42274796068555e-98
18111.34170680282306e-976.7085340141153e-98
18215.07928153818666e-972.53964076909333e-97
18311.11253573677304e-965.5626786838652e-97
18411.78393347464190e-968.91966737320951e-97
18517.27984792600813e-963.63992396300406e-96
18612.70963888193436e-951.35481944096718e-95
18711.08176363196123e-945.40881815980615e-95
18814.84302003258976e-942.42151001629488e-94
18911.74562692384294e-938.72813461921472e-94
19017.66810537181597e-933.83405268590798e-93
19113.04114849291892e-921.52057424645946e-92
19211.33059619208158e-916.65298096040789e-92
19315.79677259187376e-912.89838629593688e-91
19412.52419471376343e-901.26209735688172e-90
19511.09744644084384e-895.48723220421921e-90
19614.34389915065562e-892.17194957532781e-89
19718.16403359841434e-924.08201679920717e-92
19813.33428286273028e-911.66714143136514e-91
19911.36701094902928e-906.8350547451464e-91
20015.20708777100306e-912.60354388550153e-91
20112.16013902652972e-901.08006951326486e-90
20218.98569833214785e-904.49284916607392e-90
20313.74649512382946e-891.87324756191473e-89
20417.41846721038726e-893.70923360519363e-89
20515.71001844463684e-902.85500922231842e-90
20612.43373338717997e-891.21686669358999e-89
20719.06510709978725e-894.53255354989362e-89
20813.86512241924994e-881.93256120962497e-88
20918.42141181505153e-894.21070590752577e-89
21013.66830707744634e-881.83415353872317e-88
21111.64430618085989e-878.22153090429944e-88
21217.35034500508705e-873.67517250254352e-87
21312.61169376676588e-861.30584688338294e-86
21411.17370408629364e-855.8685204314682e-86
21515.32466548931905e-852.66233274465952e-85
21612.35551334835855e-841.17775667417928e-84
21711.03228605777644e-835.1614302888822e-84
21814.25664259384067e-832.12832129692034e-83
21911.86665978723008e-829.33329893615041e-83
22014.05995065935774e-822.02997532967887e-82
22111.75867717324037e-818.79338586620184e-82
22217.66681111587806e-813.83340555793903e-81
22313.32374542383241e-801.66187271191620e-80
22411.4395344779053e-797.1976723895265e-80
22516.20888267612856e-793.10444133806428e-79
22612.60334657180726e-781.30167328590363e-78
22711.11635421690262e-775.58177108451309e-78
22814.77068403261225e-772.38534201630613e-77
22911.90120696062575e-769.50603480312875e-77
23018.07322769474602e-764.03661384737301e-76
23113.42042646899397e-751.71021323449698e-75
23211.44236716340197e-747.21183581700986e-75
23316.06059934876929e-743.03029967438464e-74
23412.46948207668964e-731.23474103834482e-73
23511.03019464259029e-725.15097321295147e-73
23614.28109615935187e-722.14054807967594e-72
23711.77282662191777e-718.86413310958884e-72
23817.18452442962864e-713.59226221481432e-71
23912.95314742362659e-701.47657371181330e-70
24011.20927696029109e-696.04638480145544e-70
24114.93296225632522e-692.46648112816261e-69
24211.99074857303379e-689.95374286516894e-69
24318.05808980146765e-684.02904490073382e-68
24413.15244436637134e-671.57622218318567e-67
24511.24331251097364e-666.21656255486819e-67
24614.78413401040549e-662.39206700520275e-66
24711.83859611095326e-659.19298055476631e-66
24817.38522181233186e-653.69261090616593e-65
24912.82268715440292e-641.41134357720146e-64
25011.07710986516288e-635.38554932581441e-64
25112.98846221291047e-631.49423110645524e-63
25211.13633561517625e-625.68167807588127e-63
25314.32492984411389e-622.16246492205695e-62
25411.25384629636145e-616.26923148180723e-62
25519.65748555671255e-624.82874277835627e-62
25613.76314321038005e-611.88157160519003e-61
25718.4088510419447e-614.20442552097235e-61
25819.26540898037836e-614.63270449018918e-61
25913.51604247898836e-601.75802123949418e-60
26011.36163418287259e-596.80817091436297e-60
26115.13427680172383e-592.56713840086191e-59
26211.93138760371427e-589.65693801857134e-59
26315.7245456689049e-582.86227283445245e-58
26411.93180825613821e-579.65904128069105e-58
26517.20520713703663e-573.60260356851832e-57
26612.72802959270116e-561.36401479635058e-56
26711.01044997974207e-555.05224989871035e-56
26813.03125632251813e-551.51562816125906e-55
26911.1164069891769e-545.58203494588451e-55
27013.51857809033637e-541.75928904516818e-54
27111.28787221511459e-536.43936107557296e-54
27214.6995406176586e-532.3497703088293e-53
27311.70951469762211e-528.54757348811056e-53
27416.26978986125972e-523.13489493062986e-52
27512.29088161595781e-511.14544080797890e-51
27618.27316091921657e-514.13658045960828e-51
27713.02879044107585e-501.51439522053792e-50
27811.09176391242423e-495.45881956212114e-50
27913.33898156134419e-491.66949078067209e-49
28011.00309914094782e-485.01549570473908e-49
28113.53366885970794e-481.76683442985397e-48
28211.25339052052203e-476.26695260261017e-48
28313.56053174021685e-471.78026587010843e-47
28411.25353275993829e-466.26766379969146e-47
28513.34675997870856e-461.67337998935428e-46
28611.17052298179073e-455.85261490895366e-46
28714.02780143484692e-452.01390071742346e-45
28811.41093514162994e-447.0546757081497e-45
28914.81309843731366e-442.40654921865683e-44
29011.24189917895540e-436.209495894777e-44
29114.20758829242988e-432.10379414621494e-43
29211.43542399411217e-427.17711997056086e-43
29312.54794090884780e-421.27397045442390e-42
29418.6482971448897e-424.32414857244485e-42
29512.86663395073869e-411.43331697536934e-41
29617.83645520619547e-413.91822760309773e-41
29712.62496352300238e-401.31248176150119e-40
29818.68028743168671e-404.34014371584336e-40
29912.87834485011361e-391.43917242505681e-39
30019.49543123320408e-394.74771561660204e-39
30113.09066222476180e-381.54533111238090e-38
30219.92150956008423e-384.96075478004212e-38
30313.22287510442433e-371.61143755221216e-37
30411.03524137695200e-365.17620688475998e-37
30512.91109325436028e-361.45554662718014e-36
30619.28747515389654e-364.64373757694827e-36
30712.94170099199357e-351.47085049599679e-35
30819.06530972240984e-354.53265486120492e-35
30912.01079132144115e-341.00539566072057e-34
31016.29192399567694e-343.14596199783847e-34
31111.95888971094365e-339.79444855471823e-34
31211.48308550588628e-337.4154275294314e-34
31314.64205751991835e-332.32102875995917e-33
31411.40959485489941e-327.04797427449707e-33
31514.37082756971078e-322.18541378485539e-32
31611.35779121020213e-316.78895605101067e-32
31714.11205019027282e-312.05602509513641e-31
31811.26311030492520e-306.31555152462601e-31
31913.82860548117238e-301.91430274058619e-30
32011.15437012246215e-295.77185061231073e-30
32113.46012717111076e-291.73006358555538e-29
32211.03100802128775e-285.15504010643877e-29
32313.05376190905506e-281.52688095452753e-28
32418.98310693862201e-284.49155346931101e-28
32512.62918618352407e-271.31459309176203e-27
32617.67510143869246e-273.83755071934623e-27
32712.21832077177338e-261.10916038588669e-26
32816.37424933551718e-263.18712466775859e-26
32911.82073655380482e-259.10368276902412e-26
33015.1680633897089e-252.58403169485445e-25
33111.45763349085255e-247.28816745426275e-25
33214.08493653403795e-242.04246826701897e-24
33311.13740459630618e-235.6870229815309e-24
33413.12638928584251e-231.56319464292125e-23
33518.592437658231e-234.2962188291155e-23
33612.34584916212725e-221.17292458106362e-22
33716.37844728456821e-223.18922364228411e-22
33811.71820237595558e-218.5910118797779e-22
33914.60295844100302e-212.30147922050151e-21
34011.20415341261190e-206.02076706305948e-21
34113.20446953441634e-201.60223476720817e-20
34218.40107279829513e-204.20053639914757e-20
34312.18696400850292e-191.09348200425146e-19
34415.6525809374796e-192.8262904687398e-19
34511.45050580612909e-187.25252903064544e-19
34613.69511702787635e-181.84755851393818e-18
34719.31222355442626e-184.65611177721313e-18
34812.33761234301992e-171.16880617150996e-17
34915.82409784052602e-172.91204892026301e-17
35011.44008173356514e-167.20040866782569e-17
35113.39718802252080e-161.69859401126040e-16
35218.3097419660468e-164.1548709830234e-16
35311.86628686150369e-159.33143430751846e-16
3540.9999999999999984.53663360732709e-152.26831680366354e-15
3550.9999999999999951.07976731934383e-145.39883659671917e-15
3560.9999999999999872.54918330735312e-141.27459165367656e-14
3570.999999999999983.98095357023285e-141.99047678511643e-14
3580.9999999999999539.327503091278e-144.663751545639e-14
3590.9999999999998922.16718901295248e-131.08359450647624e-13
3600.999999999999754.99270452463104e-132.49635226231552e-13
3610.999999999999431.14149747428235e-125.70748737141176e-13
3620.9999999999987082.58466488974103e-121.29233244487051e-12
3630.99999999999715.80092083496537e-122.90046041748269e-12
3640.999999999993511.29819419519185e-116.49097097595926e-12
3650.9999999999857922.8416272156446e-111.4208136078223e-11
3660.9999999999689416.21171965631575e-113.10585982815788e-11
3670.9999999999327361.34528620175108e-106.7264310087554e-11
3680.9999999998556932.88614157254647e-101.44307078627324e-10
3690.9999999996933596.1328256659766e-103.0664128329883e-10
3700.9999999993547151.29056953941629e-096.45284769708147e-10
3710.9999999986554242.68915250205368e-091.34457625102684e-09
3720.9999999972304645.53907205475484e-092.76953602737742e-09
3730.999999995263359.47330040516328e-094.73665020258164e-09
3740.999999990248421.95031582484410e-089.75157912422052e-09
3750.9999999803089133.93821733597482e-081.96910866798741e-08
3760.9999999606586377.86827268385578e-083.93413634192789e-08
3770.9999999254738121.49052376618847e-077.45261883094235e-08
3780.9999998555966332.88806734635628e-071.44403367317814e-07
3790.9999997206064145.58787172965523e-072.79393586482761e-07
3800.9999994655463181.06890736397836e-065.34453681989179e-07
3810.9999989894323512.02113529767439e-061.01056764883719e-06
3820.9999982111463223.57770735613864e-061.78885367806932e-06
3830.9999978635482264.27290354767919e-062.13645177383960e-06
3840.9999960367446577.92651068515337e-063.96325534257669e-06
3850.9999926430362251.47139275491815e-057.35696377459074e-06
3860.9999878383640962.43232718076805e-051.21616359038402e-05
3870.9999785238329964.29523340077188e-052.14761670038594e-05
3880.9999640532791767.18934416476179e-053.59467208238090e-05
3890.99993710760540.0001257847891998446.2892394599922e-05
3900.999892246314730.0002155073705380960.000107753685269048
3910.9998163634729540.0003672730540923340.000183636527046167
3920.9996917338773120.0006165322453751360.000308266122687568
3930.9994808277026450.001038344594709670.000519172297354833
3940.9991705390995160.001658921800967710.000829460900483855
3950.9991676123066930.001664775386613390.000832387693306695
3960.9986491373629280.002701725274143370.00135086263707169
3970.9981506115849260.003698776830147370.00184938841507369
3980.999474790341880.001050419316241790.000525209658120897
3990.9990848277602060.001830344479587560.00091517223979378
4000.9987087623143670.002582475371265440.00129123768563272
4010.9977854045743920.004429190851215690.00221459542560784
4020.9964027888564320.007194422287136960.00359721114356848
4030.9943557664245780.01128846715084360.00564423357542182
4040.9924250696158520.01514986076829580.0075749303841479
4050.9878604873852080.02427902522958440.0121395126147922
4060.9807849837425220.03843003251495520.0192150162574776
4070.9703517614498730.05929647710025430.0296482385501271
4080.9583170743205280.0833658513589430.0416829256794715
4090.940606581466210.1187868370675790.0593934185337893
4100.9136490826513910.1727018346972180.086350917348609
4110.877912487140830.2441750257183410.122087512859170
4120.8310950329715620.3378099340568750.168904967028438
4130.7736284656061050.4527430687877890.226371534393895
4140.7461952170542860.5076095658914270.253804782945714
4150.6813758727679270.6372482544641450.318624127232073
4160.6013324490918040.7973351018163920.398667550908196
4170.7916669000048080.4166661999903840.208333099995192
4180.7682953900675080.4634092198649830.231704609932492
4190.6781488126783180.6437023746433650.321851187321682
4200.5627221892446680.8745556215106630.437277810755332
4210.4402060091017080.8804120182034160.559793990898292
4220.309728997307090.619457994614180.69027100269291
4230.8033515544578970.3932968910842060.196648445542103


Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level3950.94951923076923NOK
5% type I error level3990.959134615384615NOK
10% type I error level4010.963942307692308NOK
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/Dec/03/t12913608805lw9xqzu9ppcs9c/10dwj01291360955.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/03/t12913608805lw9xqzu9ppcs9c/10dwj01291360955.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/03/t12913608805lw9xqzu9ppcs9c/17d461291360955.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/03/t12913608805lw9xqzu9ppcs9c/17d461291360955.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/03/t12913608805lw9xqzu9ppcs9c/2zm3r1291360955.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/03/t12913608805lw9xqzu9ppcs9c/2zm3r1291360955.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/03/t12913608805lw9xqzu9ppcs9c/3zm3r1291360955.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/03/t12913608805lw9xqzu9ppcs9c/3zm3r1291360955.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/03/t12913608805lw9xqzu9ppcs9c/4avku1291360955.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/03/t12913608805lw9xqzu9ppcs9c/4avku1291360955.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/03/t12913608805lw9xqzu9ppcs9c/5avku1291360955.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/03/t12913608805lw9xqzu9ppcs9c/5avku1291360955.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/03/t12913608805lw9xqzu9ppcs9c/63m2f1291360955.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/03/t12913608805lw9xqzu9ppcs9c/63m2f1291360955.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/03/t12913608805lw9xqzu9ppcs9c/73m2f1291360955.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/03/t12913608805lw9xqzu9ppcs9c/73m2f1291360955.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/03/t12913608805lw9xqzu9ppcs9c/83m2f1291360955.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/03/t12913608805lw9xqzu9ppcs9c/83m2f1291360955.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/03/t12913608805lw9xqzu9ppcs9c/9dwj01291360955.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/03/t12913608805lw9xqzu9ppcs9c/9dwj01291360955.ps (open in new window)


 
Parameters (Session):
par1 = 4 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
 
Parameters (R input):
par1 = 4 ; par2 = Do not include Seasonal 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')
}
 




Copyright

Creative Commons License

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.

Software written by Ed van Stee & Patrick Wessa


Disclaimer

Information provided on this web site is provided "AS IS" without warranty of any kind, either express or implied, including, without limitation, warranties of merchantability, fitness for a particular purpose, and noninfringement. We use reasonable efforts to include accurate and timely information and periodically update the information, and software without notice. However, we make no warranties or representations as to the accuracy or completeness of such information (or software), and we assume no liability or responsibility for errors or omissions in the content of this web site, or any software bugs in online applications. Your use of this web site is AT YOUR OWN RISK. Under no circumstances and under no legal theory shall we be liable to you or any other person for any direct, indirect, special, incidental, exemplary, or consequential damages arising from your access to, or use of, this web site.


Privacy Policy

We may request personal information to be submitted to our servers in order to be able to:

  • personalize online software applications according to your needs
  • enforce strict security rules with respect to the data that you upload (e.g. statistical data)
  • manage user sessions of online applications
  • alert you about important changes or upgrades in resources or applications

We NEVER allow other companies to directly offer registered users information about their products and services. Banner references and hyperlinks of third parties NEVER contain any personal data of the visitor.

We do NOT sell, nor transmit by any means, personal information, nor statistical data series uploaded by you to third parties.

We carefully protect your data from loss, misuse, alteration, and destruction. However, at any time, and under any circumstance you are solely responsible for managing your passwords, and keeping them secret.

We store a unique ANONYMOUS USER ID in the form of a small 'Cookie' on your computer. This allows us to track your progress when using this website which is necessary to create state-dependent features. The cookie is used for NO OTHER PURPOSE. At any time you may opt to disallow cookies from this website - this will not affect other features of this website.

We examine cookies that are used by third-parties (banner and online ads) very closely: abuse from third-parties automatically results in termination of the advertising contract without refund. We have very good reason to believe that the cookies that are produced by third parties (banner ads) do NOT cause any privacy or security risk.

FreeStatistics.org is safe. There is no need to download any software to use the applications and services contained in this website. Hence, your system's security is not compromised by their use, and your personal data - other than data you submit in the account application form, and the user-agent information that is transmitted by your browser - is never transmitted to our servers.

As a general rule, we do not log on-line behavior of individuals (other than normal logging of webserver 'hits'). However, in cases of abuse, hacking, unauthorized access, Denial of Service attacks, illegal copying, hotlinking, non-compliance with international webstandards (such as robots.txt), or any other harmful behavior, our system engineers are empowered to log, track, identify, publish, and ban misbehaving individuals - even if this leads to ban entire blocks of IP addresses, or disclosing user's identity.

FreeStatistics.org is powered by