Multiple regression

*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: Thu, 11 Dec 2008 07:51:05 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/Dec/11/t1229007221m16ppvwsvp1i6bs.htm/, Retrieved Thu, 11 Dec 2008 14:53:41 +0000

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/2008/Dec/11/t1229007221m16ppvwsvp1i6bs.htm/}, year = {2008}, } @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 = {2008}, note = {{ISBN} 3-900051-07-0}, url = {http://www.R-project.org}, }

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

Feedback Forum:

Post a new message

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

Dataseries X:

» Textbox « » Textfile « » CSV «

2560 0 2491 0 2380 0 2291 0 2079 0 1929 0 1851 0 1607 0 1661 0 2259 0 1668 0 2011 0 1944 0 1958 0 1844 0 1868 0 1701 0 2338 0 2018 0 1302 0 2168 0 2139 0 1560 0 2093 0 1973 0 2090 0 2811 0 1984 0 1849 0 2433 0 2071 0 1855 0 1756 0 1898 0 1770 0 1969 0 1769 0 2139 0 3013 0 2061 0 2132 0 2973 0 2081 0 2257 0 2075 0 2084 0 1747 0 2092 0 1919 0 2551 0 2643 0 2153 0 2496 0 2645 0 2035 0 2294 0 2205 0 2044 0 1762 0 1897 0 1821 0 1905 0 2111 0 1643 0 1956 0 1977 0 1685 0 1393 0 1574 0 1793 0 1562 0 1510 0 1675 0 1965 0 2173 0 2395 0 2197 0 2257 0 2885 0 1594 0 1950 0 1772 0 1280 0 1724 0 1473 0 1461 0 1576 0 1900 0 1618 0 2303 0 1994 0 1575 0 1893 0 1788 0 1817 0 3233 0 727 1 1121 1 1665 1 1401 1 1415 1 2058 1 1544 1 1379 1 1402 1 1313 1 1296 1 1398 1 1288 1 1563 1 1972 1 1496 1 1481 1 1819 1 1479 1 1635 1 1511 1 1547 1 1388 1 1958 1 1390 1 1597 1 1842 1 1396 1 1671 1 1385 1 1632 1 1313 1 1300 1 1431 1 1398 1 1198 1 1292 1 1434 1 1660 1 1837 1 1455 1 1315 1 1642 1 1069 1 1209 1 1586 1 1122 1 1063 1 1125 1 1414 1 1347 1 1403 1 1299 1 1547 1 1515 1 1247 1 1639 1 1296 1 1063 1 1282 1 1365 1 1268 1 1532 1 1455 1 1393 1 1515 1 1510 1 1225 1 1577 1 1417 1 1224 1 1693 1 1633 1 1639 1 1914 1 1586 1 1552 1 2081 1 1500 1 1437 1 1470 1 1849 1 1387 1 1592 1 1589 1 1798 1 1935 1 1887 1 2027 1 2080 1 1556 1 1682 1 1785 1 1869 1 1781 1 2082 1 2570 1 1862 1 1936 1 1504 1 1765 1 1607 1 1577 1 1493 1 1615 1 1700 1 1335 1 1523 1 1623 1 1540 1 1637 1 1524 1 1419 1 1821 1 1593 1 1357 1 1263 1 1750 1 1405 1 1393 1 1639 1 1679 1 1551 1 1744 1 1429 1 1784 1

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 Input view raw input (R code) Raw Output view raw output of R engine Computing time 7 seconds R Server 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 Multiple Linear Regression - Estimated Regression Equation y[t] = + 1975.73335444405 -576.108850300459x[t] -92.2789154827092M1[t] + 17.3171429368757M2[t] + 230.439517145934M3[t] + 18.2461018813088M4[t] -13.9473133833168M5[t] + 244.754008194163M6[t] + 30.0401757383326M7[t] -218.334526076001M8[t] -89.3203390014449M9[t] -7.91726303800026M10[t] -284.958631519M11[t] + 0.930257369888725t + 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) 1975.73335444405 76.087183 25.9667 0 0 x -576.108850300459 74.62835 -7.7197 0 0 M1 -92.2789154827092 92.958221 -0.9927 0.322013 0.161007 M2 17.3171429368757 92.9328 0.1863 0.852359 0.42618 M3 230.439517145934 92.910954 2.4802 0.013924 0.006962 M4 18.2461018813088 92.892688 0.1964 0.844472 0.422236 M5 -13.9473133833168 92.878001 -0.1502 0.880778 0.440389 M6 244.754008194163 92.866897 2.6355 0.009033 0.004517 M7 30.0401757383326 94.14107 0.3191 0.749973 0.374986 M8 -218.334526076001 94.125156 -2.3196 0.021332 0.010666 M9 -89.3203390014449 94.112777 -0.9491 0.343682 0.171841 M10 -7.91726303800026 94.103934 -0.0841 0.933031 0.466516 M11 -284.958631519 94.098628 -3.0283 0.002771 0.001385 t 0.930257369888725 0.576962 1.6123 0.108405 0.054202 Multiple Linear Regression - Regression Statistics Multiple R 0.710974440699702 R-squared 0.505484655328254 Adjusted R-squared 0.47457744628627 F-TEST (value) 16.3549110707993 F-TEST (DF numerator) 13 F-TEST (DF denominator) 208 p-value 0 Multiple Linear Regression - Residual Statistics Residual Standard Deviation 282.290577689333 Sum Squared Residuals 16575097.8124528 Multiple Linear Regression - Actuals, Interpolation, and Residuals Time or Index Actuals Interpolation Forecast Residuals Prediction Error 1 2560 1884.38469633123 675.61530366877 2 2491 1994.91101212070 496.088987879296 3 2380 2208.96364369965 171.036356300348 4 2291 1997.70048580492 293.299514195085 5 2079 1966.43732791018 112.562672089821 6 1929 2226.06890685755 -297.068906857547 7 1851 2012.28533177161 -161.285331771605 8 1607 1764.84088732716 -157.840887327161 9 1661 1894.78533177161 -233.785331771605 10 2259 1977.11866510494 281.881334895061 11 1668 1701.00755399383 -33.0075539938275 12 2011 1986.89644288272 24.1035571172837 13 1944 1895.54778476990 48.4522152301041 14 1958 2006.07410055937 -48.0741005593695 15 1844 2220.12673213832 -376.126732138317 16 1868 2008.86357424358 -140.86357424358 17 1701 1977.60041634884 -276.600416348843 18 2338 2237.23199529621 100.768004703788 19 2018 2023.44842021027 -5.44842021027002 20 1302 1776.00397576583 -474.003975765825 21 2168 1905.94842021027 262.05157978973 22 2139 1988.28175354360 150.718246456397 23 1560 1712.17064243249 -152.170642432492 24 2093 1998.05953132138 94.940468678619 25 1973 1906.71087320856 66.2891267914395 26 2090 2017.23718899803 72.7628110019658 27 2811 2231.28982057698 579.710179423019 28 1984 2020.02666268224 -36.0266626822447 29 1849 1988.76350478751 -139.763504787508 30 2433 2248.39508373488 184.604916265124 31 2071 2034.61150864893 36.3884913510653 32 1855 1787.16706420449 67.8329357955097 33 1756 1917.11150864893 -161.111508648935 34 1898 1999.44484198227 -101.444841982268 35 1770 1723.33373087116 46.6662691288429 36 1969 2009.22261976005 -40.2226197600457 37 1769 1917.87396164723 -148.873961647225 38 2139 2028.4002774367 110.599722563301 39 3013 2242.45290901565 770.547090984354 40 2061 2031.18975112091 29.8102488790906 41 2132 1999.92659322617 132.073406773827 42 2973 2259.55817217354 713.44182782646 43 2081 2045.7745970876 35.2254029124006 44 2257 1798.33015264316 458.669847356845 45 2075 1928.2745970876 146.725402912401 46 2084 2010.60793042093 73.3920695790672 47 1747 1734.49681930982 12.5031806901782 48 2092 2020.38570819871 71.6142918012896 49 1919 1929.03705008589 -10.0370500858900 50 2551 2039.56336587536 511.436634124636 51 2643 2253.61599745431 389.384002545689 52 2153 2042.35283955957 110.647160440426 53 2496 2011.08968166484 484.910318335163 54 2645 2270.72126061221 374.278739387794 55 2035 2056.93768552626 -21.9376855262641 56 2294 1809.49324108182 484.50675891818 57 2205 1939.43768552626 265.562314473736 58 2044 2021.77101885960 22.2289811404025 59 1762 1745.65990774849 16.3400922515135 60 1897 2031.54879663738 -134.548796637375 61 1821 1940.20013852455 -119.200138524555 62 1905 2050.72645431403 -145.726454314028 63 2111 2264.77908589298 -153.779085892976 64 1643 2053.51592799824 -410.515927998239 65 1956 2022.2527701035 -66.2527701035019 66 1977 2281.88434905087 -304.884349050870 67 1685 2068.10077396493 -383.100773964929 68 1393 1820.65632952048 -427.656329520484 69 1574 1950.60077396493 -376.600773964929 70 1793 2032.93410729826 -239.934107298262 71 1562 1756.82299618715 -194.822996187151 72 1510 2042.71188507604 -532.71188507604 73 1675 1951.36322696322 -276.363226963219 74 1965 2061.88954275269 -96.889542752693 75 2173 2275.94217433164 -102.942174331640 76 2395 2064.67901643690 330.320983563096 77 2197 2033.41585854217 163.584141457833 78 2257 2293.04743748954 -36.0474374895350 79 2885 2079.26386240359 805.736137596407 80 1594 1831.81941795915 -237.819417959149 81 1950 1961.76386240359 -11.7638624035936 82 1772 2044.09719573693 -272.097195736927 83 1280 1767.98608462582 -487.986084625815 84 1724 2053.87497351470 -329.874973514705 85 1473 1962.52631540188 -489.526315401884 86 1461 2073.05263119136 -612.052631191357 87 1576 2287.10526277030 -711.105262770305 88 1900 2075.84210487557 -175.842104875568 89 1618 2044.57894698083 -426.578946980831 90 2303 2304.2105259282 -1.21052592819982 91 1994 2090.42695084226 -96.4269508422582 92 1575 1842.98250639781 -267.982506397814 93 1893 1972.92695084226 -79.9269508422582 94 1788 2055.26028417559 -267.260284175592 95 1817 1779.14917306448 37.8508269355195 96 3233 2065.03806195337 1167.96193804663 97 727 1397.58055354009 -670.580553540089 98 1121 1508.10686932956 -387.106869329563 99 1665 1722.15950090851 -57.1595009085103 100 1401 1510.89634301377 -109.896343013773 101 1415 1479.63318511904 -64.6331851190365 102 2058 1739.26476406640 318.735235933595 103 1544 1525.48118898046 18.5188110195365 104 1379 1278.03674453602 100.963255463981 105 1402 1407.98118898046 -5.98118898046343 106 1313 1490.31452231380 -177.314522313797 107 1296 1214.20341120269 81.7965887973144 108 1398 1500.09230009157 -102.092300091574 109 1288 1408.74364197875 -120.743641978754 110 1563 1519.26995776823 43.7300422317724 111 1972 1733.32258934717 238.677410652825 112 1496 1522.05943145244 -26.0594314524382 113 1481 1490.7962735577 -9.79627355770128 114 1819 1750.42785250507 68.5721474949302 115 1479 1536.64427741913 -57.6442774191281 116 1635 1289.19983297468 345.800167025316 117 1511 1419.14427741913 91.8557225808718 118 1547 1501.47761075246 45.5223892475385 119 1388 1225.36649964135 162.633500358650 120 1958 1511.25538853024 446.744611469761 121 1390 1419.90673041742 -29.9067304174187 122 1597 1530.43304620689 66.5669537931076 123 1842 1744.48567778584 97.5143222141603 124 1396 1533.22251989110 -137.222519891103 125 1671 1501.95936199637 169.040638003634 126 1385 1761.59094094373 -376.590940943734 127 1632 1547.80736585779 84.1926341422071 128 1313 1300.36292141335 12.6370785866516 129 1300 1430.30736585779 -130.307365857793 130 1431 1512.64069919113 -81.6406991911262 131 1398 1236.52958808002 161.470411919985 132 1198 1522.41847696890 -324.418476968904 133 1292 1431.06981885608 -139.069818856083 134 1434 1541.59613464556 -107.596134645557 135 1660 1755.64876622450 -95.6487662245044 136 1837 1544.38560832977 292.614391670232 137 1455 1513.12245043503 -58.1224504350307 138 1315 1772.7540293824 -457.754029382399 139 1642 1558.97045429646 83.0295457035424 140 1069 1311.52600985201 -242.526009852013 141 1209 1441.47045429646 -232.470454296458 142 1586 1523.80378762979 62.1962123702091 143 1122 1247.69267651868 -125.692676518680 144 1063 1533.58156540757 -470.581565407569 145 1125 1442.23290729475 -317.232907294748 146 1414 1552.75922308422 -138.759223084222 147 1347 1766.81185466317 -419.811854663169 148 1403 1555.54869676843 -152.548696768432 149 1299 1524.28553887370 -225.285538873695 150 1547 1783.91711782106 -236.917117821064 151 1515 1570.13354273512 -55.1335427351222 152 1247 1322.68909829068 -75.6890982906778 153 1639 1452.63354273512 186.366457264878 154 1296 1534.96687606846 -238.966876068455 155 1063 1258.85576495734 -195.855764957344 156 1282 1544.74465384623 -262.744653846233 157 1365 1453.39599573341 -88.3959957334128 158 1268 1563.92231152289 -295.922311522886 159 1532 1777.97494310183 -245.974943101834 160 1455 1566.71178520710 -111.711785207097 161 1393 1535.44862731236 -142.44862731236 162 1515 1795.08020625973 -280.080206259728 163 1510 1581.29663117379 -71.296631173787 164 1225 1333.85218672934 -108.852186729343 165 1577 1463.79663117379 113.203368826213 166 1417 1546.12996450712 -129.129964507120 167 1224 1270.01885339601 -46.0188533960091 168 1693 1555.90774228490 137.092257715102 169 1633 1464.55908417208 168.440915827922 170 1639 1575.08539996155 63.9146000384488 171 1914 1789.1380315405 124.861968459502 172 1586 1577.87487364576 8.12512635423834 173 1552 1546.61171575102 5.3882842489752 174 2081 1806.24329469839 274.756705301607 175 1500 1592.45971961245 -92.4597196124516 176 1437 1345.01527516801 91.9847248319928 177 1470 1474.95971961245 -4.95971961245168 178 1849 1557.29305294578 291.706947054215 179 1387 1281.18194183467 105.818058165326 180 1592 1567.07083072356 24.9291692764373 181 1589 1475.72217261074 113.277827389258 182 1798 1586.24848840022 211.751511599784 183 1935 1800.30111997916 134.698880020837 184 1887 1589.03796208443 297.962037915574 185 2027 1557.77480418969 469.225195810310 186 2080 1817.40638313706 262.593616862942 187 1556 1603.62280805112 -47.6228080511164 188 1682 1356.17836360667 325.821636393328 189 1785 1486.12280805112 298.877191948884 190 1869 1568.45614138445 300.543858615550 191 1781 1292.34503027334 488.654969726661 192 2082 1578.23391916223 503.766080837773 193 2570 1486.88526104941 1083.11473895059 194 1862 1597.41157683888 264.588423161119 195 1936 1811.46420841783 124.535791582172 196 1504 1600.20105052309 -96.201050523091 197 1765 1568.93789262835 196.062107371646 198 1607 1828.56947157572 -221.569471575723 199 1577 1614.78589648978 -37.7858964897811 200 1493 1367.34145204534 125.658547954663 201 1615 1497.28589648978 117.714103510219 202 1700 1579.61922982311 120.380770176886 203 1335 1303.50811871200 31.4918812879967 204 1523 1589.39700760089 -66.3970076008921 205 1623 1498.04834948807 124.951650511928 206 1540 1608.57466527755 -68.5746652775453 207 1637 1822.62729685649 -185.627296856493 208 1524 1611.36413896176 -87.3641389617558 209 1419 1580.10098106702 -161.100981067019 210 1821 1839.73256001439 -18.7325600143874 211 1593 1625.94898492845 -32.9489849284458 212 1357 1378.50454048400 -21.5045404840013 213 1263 1508.44898492845 -245.448984928446 214 1750 1590.78231826178 159.217681738221 215 1405 1314.67120715067 90.328792849332 216 1393 1600.56009603956 -207.560096039557 217 1639 1509.21143792674 129.788562073264 218 1679 1619.73775371621 59.26224628379 219 1551 1833.79038529516 -282.790385295157 220 1744 1622.52722740042 121.472772599580 221 1429 1591.26406950568 -162.264069505684 222 1784 1850.89564845305 -66.895648453052

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/11/t1229007221m16ppvwsvp1i6bs/11zh41229007052.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/11/t1229007221m16ppvwsvp1i6bs/11zh41229007052.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/11/t1229007221m16ppvwsvp1i6bs/2gkgs1229007052.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/11/t1229007221m16ppvwsvp1i6bs/2gkgs1229007052.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/11/t1229007221m16ppvwsvp1i6bs/3jj8p1229007052.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/11/t1229007221m16ppvwsvp1i6bs/3jj8p1229007052.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/11/t1229007221m16ppvwsvp1i6bs/4eond1229007052.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/11/t1229007221m16ppvwsvp1i6bs/4eond1229007052.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/11/t1229007221m16ppvwsvp1i6bs/5s6i91229007052.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/11/t1229007221m16ppvwsvp1i6bs/5s6i91229007052.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/11/t1229007221m16ppvwsvp1i6bs/6soy71229007052.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/11/t1229007221m16ppvwsvp1i6bs/6soy71229007052.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/11/t1229007221m16ppvwsvp1i6bs/7ixja1229007052.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/11/t1229007221m16ppvwsvp1i6bs/7ixja1229007052.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/11/t1229007221m16ppvwsvp1i6bs/8uzrk1229007053.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/11/t1229007221m16ppvwsvp1i6bs/8uzrk1229007053.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/11/t1229007221m16ppvwsvp1i6bs/9h3ct1229007053.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/11/t1229007221m16ppvwsvp1i6bs/9h3ct1229007053.ps (open in new window)

Parameters (Session):

par1 = 1 ; par2 = Include Monthly Dummies ; par3 = Linear Trend ;

Parameters (R input):

par1 = 1 ; par2 = Include Monthly Dummies ; par3 = Linear Trend ;

R code (references can be found in the software module):

library(lattice) 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)) 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$resid, main='Residual Normal Q-Q Plot') grid() dev.off() (myerror <- as.ts(mysum$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() 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')

Copyright

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