| | *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, 09 Dec 2010 19:58:40 +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/09/t12919246007ftftu67h2p1ey7.htm/, Retrieved Thu, 09 Dec 2010 20:56:52 +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/09/t12919246007ftftu67h2p1ey7.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 « | 235.1
280.7
264.6
240.7
201.4
240.8
241.1
223.8
206.1
174.7
203.3
220.5
299.5
347.4
338.3
327.7
351.6
396.6
438.8
395.6
363.5
378.8
357
369
464.8
479.1
431.3
366.5
326.3
355.1
331.6
261.3
249
205.5
235.6
240.9
264.9
253.8
232.3
193.8
177
213.2
207.2
180.6
188.6
175.4
199
179.6
225.8
234
200.2
183.6
178.2
203.2
208.5
191.8
172.8
148
159.4
154.5
213.2
196.4
182.8
176.4
153.6
173.2
171
151.2
161.9
157.2
201.7
236.4
356.1
398.3
403.7
384.6
365.8
368.1
367.9
347
343.3
292.9
311.5
300.9
366.9
356.9
329.7
316.2
269
289.3
266.2
253.6
233.8
228.4
253.6
260.1
306.6
309.2
309.5
271
279.9
317.9
298.4
246.7
227.3
209.1
259.9
266
320.6
308.5
282.2
262.7
263.5
313.1
284.3
252.6
250.3
246.5
312.7
333.2
446.4
511.6
515.5
506.4
483.2
522.3
509.8
460.7
405.8
375
378.5
406.8
467.8
469.8
429.8
355.8
332.7
378
360.5
334.7
319.5
323.1
363.6
352.1
411.9
388.6
416.4
360.7
338
417.2
388. 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!
Multiple Linear Regression - Estimated Regression Equation | unemployment[t] = + 176.343118279570 + 72.2415821012546M1[t] + 81.1193268369179M2[t] + 57.8325554435488M3[t] + 17.8909453405018M4[t] -3.66679379480305M5[t] + 68.0399831989246M6[t] + 44.2499859991041M7[t] + 12.0857952508962M8[t] -6.03968581989235M9[t] -22.5006507616486M10[t] -1.44871247759849M11[t] + 1.01902945788530t + 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) | 176.343118279570 | 21.582495 | 8.1707 | 0 | 0 | M1 | 72.2415821012546 | 27.125671 | 2.6632 | 0.008088 | 0.004044 | M2 | 81.1193268369179 | 27.124642 | 2.9906 | 0.002976 | 0.001488 | M3 | 57.8325554435488 | 27.12371 | 2.1322 | 0.033671 | 0.016835 | M4 | 17.8909453405018 | 27.122876 | 0.6596 | 0.509917 | 0.254959 | M5 | -3.66679379480305 | 27.122141 | -0.1352 | 0.892533 | 0.446267 | M6 | 68.0399831989246 | 27.121503 | 2.5087 | 0.012557 | 0.006279 | M7 | 44.2499859991041 | 27.120964 | 1.6316 | 0.103645 | 0.051823 | M8 | 12.0857952508962 | 27.120522 | 0.4456 | 0.656131 | 0.328066 | M9 | -6.03968581989235 | 27.120179 | -0.2227 | 0.823895 | 0.411948 | M10 | -22.5006507616486 | 27.119934 | -0.8297 | 0.407276 | 0.203638 | M11 | -1.44871247759849 | 27.119787 | -0.0534 | 0.957428 | 0.478714 | t | 1.01902945788530 | 0.051577 | 19.7576 | 0 | 0 |
Multiple Linear Regression - Regression Statistics | Multiple R | 0.735625547908382 | R-squared | 0.541144946735507 | Adjusted R-squared | 0.525807173367334 | F-TEST (value) | 35.2818452682604 | F-TEST (DF numerator) | 12 | F-TEST (DF denominator) | 359 | p-value | 0 | Multiple Linear Regression - Residual Statistics | Residual Standard Deviation | 106.770513988965 | Sum Squared Residuals | 4092579.41403091 |
Multiple Linear Regression - Actuals, Interpolation, and Residuals | Time or Index | Actuals | Interpolation Forecast | Residuals Prediction Error | 1 | 235.1 | 249.603729838712 | -14.5037298387122 | 2 | 280.7 | 259.500504032259 | 21.1994959677414 | 3 | 264.6 | 237.232762096775 | 27.3672379032247 | 4 | 240.7 | 198.310181451615 | 42.3898185483852 | 5 | 201.4 | 177.771471774194 | 23.6285282258064 | 6 | 240.8 | 250.497278225805 | -9.69727822580526 | 7 | 241.1 | 227.726310483869 | 13.3736895161307 | 8 | 223.8 | 196.581149193548 | 27.2188508064515 | 9 | 206.1 | 179.474697580645 | 26.6253024193548 | 10 | 174.7 | 164.032762096774 | 10.6672379032258 | 11 | 203.3 | 186.10372983871 | 17.1962701612899 | 12 | 220.5 | 188.571471774194 | 31.9285282258064 | 13 | 299.5 | 261.832083333332 | 37.6679166666677 | 14 | 347.4 | 271.728857526882 | 75.6711424731183 | 15 | 338.3 | 249.461115591398 | 88.8388844086021 | 16 | 327.7 | 210.538534946236 | 117.161465053763 | 17 | 351.6 | 189.999825268817 | 161.600174731183 | 18 | 396.6 | 262.72563172043 | 133.87436827957 | 19 | 438.8 | 239.954663978495 | 198.845336021505 | 20 | 395.6 | 208.809502688172 | 186.790497311828 | 21 | 363.5 | 191.703051075269 | 171.796948924731 | 22 | 378.8 | 176.261115591398 | 202.538884408602 | 23 | 357 | 198.332083333333 | 158.667916666667 | 24 | 369 | 200.799825268817 | 168.200174731183 | 25 | 464.8 | 274.060436827957 | 190.739563172043 | 26 | 479.1 | 283.957211021505 | 195.142788978495 | 27 | 431.3 | 261.689469086022 | 169.610530913978 | 28 | 366.5 | 222.76688844086 | 143.733111559140 | 29 | 326.3 | 202.228178763441 | 124.071821236559 | 30 | 355.1 | 274.953985215054 | 80.1460147849462 | 31 | 331.6 | 252.183017473118 | 79.4169825268817 | 32 | 261.3 | 221.037856182796 | 40.2621438172043 | 33 | 249 | 203.931404569892 | 45.0685954301075 | 34 | 205.5 | 188.489469086021 | 17.0105309139785 | 35 | 235.6 | 210.560436827957 | 25.0395631720430 | 36 | 240.9 | 213.028178763441 | 27.8718212365592 | 37 | 264.9 | 286.288790322581 | -21.3887903225806 | 38 | 253.8 | 296.185564516129 | -42.3855645161291 | 39 | 232.3 | 273.917822580645 | -41.6178225806451 | 40 | 193.8 | 234.995241935484 | -41.1952419354838 | 41 | 177 | 214.456532258064 | -37.4565322580645 | 42 | 213.2 | 287.182338709677 | -73.9823387096774 | 43 | 207.2 | 264.411370967742 | -57.2113709677419 | 44 | 180.6 | 233.266209677419 | -52.6662096774194 | 45 | 188.6 | 216.159758064516 | -27.5597580645161 | 46 | 175.4 | 200.717822580645 | -25.3178225806451 | 47 | 199 | 222.788790322581 | -23.7887903225806 | 48 | 179.6 | 225.256532258064 | -45.6565322580645 | 49 | 225.8 | 298.517143817204 | -72.7171438172043 | 50 | 234 | 308.413918010753 | -74.4139180107527 | 51 | 200.2 | 286.146176075269 | -85.9461760752688 | 52 | 183.6 | 247.223595430107 | -63.6235954301074 | 53 | 178.2 | 226.684885752688 | -48.4848857526882 | 54 | 203.2 | 299.410692204301 | -96.2106922043011 | 55 | 208.5 | 276.639724462366 | -68.1397244623656 | 56 | 191.8 | 245.494563172043 | -53.694563172043 | 57 | 172.8 | 228.38811155914 | -55.5881115591398 | 58 | 148 | 212.946176075269 | -64.9461760752688 | 59 | 159.4 | 235.017143817204 | -75.6171438172043 | 60 | 154.5 | 237.484885752688 | -82.9848857526881 | 61 | 213.2 | 310.745497311828 | -97.545497311828 | 62 | 196.4 | 320.642271505376 | -124.242271505376 | 63 | 182.8 | 298.374529569892 | -115.574529569892 | 64 | 176.4 | 259.451948924731 | -83.051948924731 | 65 | 153.6 | 238.913239247312 | -85.3132392473119 | 66 | 173.2 | 311.639045698925 | -138.439045698925 | 67 | 171 | 288.868077956989 | -117.868077956989 | 68 | 151.2 | 257.722916666667 | -106.522916666667 | 69 | 161.9 | 240.616465053763 | -78.7164650537634 | 70 | 157.2 | 225.174529569892 | -67.9745295698925 | 71 | 201.7 | 247.245497311828 | -45.5454973118279 | 72 | 236.4 | 249.713239247312 | -13.3132392473118 | 73 | 356.1 | 322.973850806452 | 33.1261491935485 | 74 | 398.3 | 332.870625 | 65.429375 | 75 | 403.7 | 310.602883064516 | 93.0971169354839 | 76 | 384.6 | 271.680302419355 | 112.919697580645 | 77 | 365.8 | 251.141592741936 | 114.658407258064 | 78 | 368.1 | 323.867399193548 | 44.2326008064516 | 79 | 367.9 | 301.096431451613 | 66.803568548387 | 80 | 347 | 269.951270161290 | 77.0487298387096 | 81 | 343.3 | 252.844818548387 | 90.4551814516129 | 82 | 292.9 | 237.402883064516 | 55.4971169354838 | 83 | 311.5 | 259.473850806452 | 52.0261491935484 | 84 | 300.9 | 261.941592741935 | 38.9584072580645 | 85 | 366.9 | 335.202204301075 | 31.6977956989248 | 86 | 356.9 | 345.098978494624 | 11.8010215053763 | 87 | 329.7 | 322.83123655914 | 6.86876344086021 | 88 | 316.2 | 283.908655913978 | 32.2913440860215 | 89 | 269 | 263.369946236559 | 5.63005376344086 | 90 | 289.3 | 336.095752688172 | -46.7957526881721 | 91 | 266.2 | 313.324784946237 | -47.1247849462366 | 92 | 253.6 | 282.179623655914 | -28.579623655914 | 93 | 233.8 | 265.073172043011 | -31.2731720430107 | 94 | 228.4 | 249.63123655914 | -21.2312365591397 | 95 | 253.6 | 271.702204301075 | -18.1022043010753 | 96 | 260.1 | 274.169946236559 | -14.0699462365591 | 97 | 306.6 | 347.430557795699 | -40.8305577956988 | 98 | 309.2 | 357.327331989247 | -48.1273319892474 | 99 | 309.5 | 335.059590053763 | -25.5595900537634 | 100 | 271 | 296.137009408602 | -25.1370094086021 | 101 | 279.9 | 275.598299731183 | 4.30170026881719 | 102 | 317.9 | 348.324106182796 | -30.4241061827957 | 103 | 298.4 | 325.55313844086 | -27.1531384408603 | 104 | 246.7 | 294.407977150538 | -47.7079771505377 | 105 | 227.3 | 277.301525537634 | -50.0015255376344 | 106 | 209.1 | 261.859590053763 | -52.7595900537634 | 107 | 259.9 | 283.930557795699 | -24.0305577956989 | 108 | 266 | 286.398299731183 | -20.3982997311827 | 109 | 320.6 | 359.658911290323 | -39.0589112903225 | 110 | 308.5 | 369.555685483871 | -61.055685483871 | 111 | 282.2 | 347.287943548387 | -65.0879435483871 | 112 | 262.7 | 308.365362903226 | -45.6653629032258 | 113 | 263.5 | 287.826653225806 | -24.3266532258065 | 114 | 313.1 | 360.552459677419 | -47.4524596774194 | 115 | 284.3 | 337.781491935484 | -53.4814919354839 | 116 | 252.6 | 306.636330645161 | -54.0363306451613 | 117 | 250.3 | 289.529879032258 | -39.2298790322581 | 118 | 246.5 | 274.087943548387 | -27.5879435483871 | 119 | 312.7 | 296.158911290323 | 16.5410887096774 | 120 | 333.2 | 298.626653225806 | 34.5733467741936 | 121 | 446.4 | 371.887264784946 | 74.5127352150538 | 122 | 511.6 | 381.784038978495 | 129.815961021505 | 123 | 515.5 | 359.516297043011 | 155.983702956989 | 124 | 506.4 | 320.593716397849 | 185.806283602151 | 125 | 483.2 | 300.05500672043 | 183.14499327957 | 126 | 522.3 | 372.780813172043 | 149.519186827957 | 127 | 509.8 | 350.009845430108 | 159.790154569892 | 128 | 460.7 | 318.864684139785 | 141.835315860215 | 129 | 405.8 | 301.758232526882 | 104.041767473118 | 130 | 375 | 286.316297043011 | 88.6837029569892 | 131 | 378.5 | 308.387264784946 | 70.1127352150537 | 132 | 406.8 | 310.85500672043 | 95.94499327957 | 133 | 467.8 | 384.11561827957 | 83.6843817204302 | 134 | 469.8 | 394.012392473118 | 75.7876075268817 | 135 | 429.8 | 371.744650537634 | 58.0553494623656 | 136 | 355.8 | 332.822069892473 | 22.9779301075269 | 137 | 332.7 | 312.283360215054 | 20.4166397849462 | 138 | 378 | 385.009166666667 | -7.00916666666671 | 139 | 360.5 | 362.238198924731 | -1.73819892473126 | 140 | 334.7 | 331.093037634409 | 3.60696236559136 | 141 | 319.5 | 313.986586021505 | 5.5134139784946 | 142 | 323.1 | 298.544650537634 | 24.5553494623656 | 143 | 363.6 | 320.61561827957 | 42.9843817204301 | 144 | 352.1 | 323.083360215054 | 29.0166397849463 | 145 | 411.9 | 396.343971774194 | 15.5560282258065 | 146 | 388.6 | 406.240745967742 | -17.6407459677419 | 147 | 416.4 | 383.973004032258 | 32.4269959677419 | 148 | 360.7 | 345.050423387097 | 15.6495766129033 | 149 | 338 | 324.511713709677 | 13.4882862903226 | 150 | 417.2 | 397.237520161290 | 19.9624798387096 | 151 | 388.4 | 374.466552419355 | 13.9334475806451 | 152 | 371.1 | 343.321391129032 | 27.7786088709677 | 153 | 331.5 | 326.214939516129 | 5.28506048387095 | 154 | 353.7 | 310.773004032258 | 42.9269959677419 | 155 | 396.7 | 332.843971774194 | 63.8560282258065 | 156 | 447 | 335.311713709677 | 111.688286290323 | 157 | 533.5 | 408.572325268817 | 124.927674731183 | 158 | 565.4 | 418.469099462366 | 146.930900537634 | 159 | 542.3 | 396.201357526882 | 146.098642473118 | 160 | 488.7 | 357.278776881720 | 131.421223118280 | 161 | 467.1 | 336.740067204301 | 130.359932795699 | 162 | 531.3 | 409.465873655914 | 121.834126344086 | 163 | 496.1 | 386.694905913979 | 109.405094086021 | 164 | 444 | 355.549744623656 | 88.450255376344 | 165 | 403.4 | 338.443293010753 | 64.9567069892473 | 166 | 386.3 | 323.001357526882 | 63.2986424731183 | 167 | 394.1 | 345.072325268817 | 49.0276747311828 | 168 | 404.1 | 347.540067204301 | 56.559932795699 | 169 | 462.1 | 420.800678763441 | 41.2993212365592 | 170 | 448.1 | 430.697452956989 | 17.4025470430107 | 171 | 432.3 | 408.429711021505 | 23.8702889784946 | 172 | 386.3 | 369.507130376344 | 16.7928696236560 | 173 | 395.2 | 348.968420698925 | 46.2315793010753 | 174 | 421.9 | 421.694227150538 | 0.205772849462304 | 175 | 382.9 | 398.923259408602 | -16.0232594086022 | 176 | 384.2 | 367.77809811828 | 16.4219018817204 | 177 | 345.5 | 350.671646505376 | -5.17164650537636 | 178 | 323.4 | 335.229711021505 | -11.8297110215054 | 179 | 372.6 | 357.300678763441 | 15.2993212365592 | 180 | 376 | 359.768420698925 | 16.2315793010753 | 181 | 462.7 | 433.029032258064 | 29.6709677419355 | 182 | 487 | 442.925806451613 | 44.0741935483871 | 183 | 444.2 | 420.658064516129 | 23.5419354838710 | 184 | 399.3 | 381.735483870968 | 17.5645161290323 | 185 | 394.9 | 361.196774193548 | 33.7032258064516 | 186 | 455.4 | 433.922580645161 | 21.4774193548386 | 187 | 414 | 411.151612903226 | 2.84838709677412 | 188 | 375.5 | 380.006451612903 | -4.50645161290325 | 189 | 347 | 362.9 | -15.9000000000000 | 190 | 339.4 | 347.458064516129 | -8.05806451612904 | 191 | 385.8 | 369.529032258064 | 16.2709677419355 | 192 | 378.8 | 371.996774193548 | 6.80322580645166 | 193 | 451.8 | 445.257385752688 | 6.5426142473119 | 194 | 446.1 | 455.154159946237 | -9.05415994623656 | 195 | 422.5 | 432.886418010753 | -10.3864180107527 | 196 | 383.1 | 393.963837365591 | -10.8638373655913 | 197 | 352.8 | 373.425127688172 | -20.6251276881720 | 198 | 445.3 | 446.150934139785 | -0.850934139784974 | 199 | 367.5 | 423.37996639785 | -55.8799663978495 | 200 | 355.1 | 392.234805107527 | -37.1348051075269 | 201 | 326.2 | 375.128353494624 | -48.9283534946237 | 202 | 319.8 | 359.686418010753 | -39.8864180107527 | 203 | 331.8 | 381.757385752688 | -49.9573857526882 | 204 | 340.9 | 384.225127688172 | -43.325127688172 | 205 | 394.1 | 457.485739247312 | -63.3857392473117 | 206 | 417.2 | 467.38251344086 | -50.1825134408602 | 207 | 369.9 | 445.114771505376 | -75.2147715053764 | 208 | 349.2 | 406.192190860215 | -56.992190860215 | 209 | 321.4 | 385.653481182796 | -64.2534811827957 | 210 | 405.7 | 458.379287634409 | -52.6792876344086 | 211 | 342.9 | 435.608319892473 | -92.7083198924732 | 212 | 316.5 | 404.463158602151 | -87.9631586021506 | 213 | 284.2 | 387.356706989247 | -103.156706989247 | 214 | 270.9 | 371.914771505376 | -101.014771505376 | 215 | 288.8 | 393.985739247312 | -105.185739247312 | 216 | 278.8 | 396.453481182796 | -117.653481182796 | 217 | 324.4 | 469.714092741935 | -145.314092741935 | 218 | 310.9 | 479.610866935484 | -168.710866935484 | 219 | 299 | 457.343125 | -158.343125 | 220 | 273 | 418.420544354839 | -145.420544354839 | 221 | 279.3 | 397.881834677419 | -118.581834677419 | 222 | 359.2 | 470.607641129032 | -111.407641129032 | 223 | 305 | 447.836673387097 | -142.836673387097 | 224 | 282.1 | 416.691512096774 | -134.591512096774 | 225 | 250.3 | 399.585060483871 | -149.285060483871 | 226 | 246.5 | 384.143125 | -137.643125 | 227 | 257.9 | 406.214092741936 | -148.314092741936 | 228 | 266.5 | 408.681834677419 | -142.181834677419 | 229 | 315.9 | 481.942446236559 | -166.042446236559 | 230 | 318.4 | 491.839220430108 | -173.439220430108 | 231 | 295.4 | 469.571478494624 | -174.171478494624 | 232 | 266.4 | 430.648897849462 | -164.248897849462 | 233 | 245.8 | 410.110188172043 | -164.310188172043 | 234 | 362.8 | 482.835994623656 | -120.035994623656 | 235 | 324.9 | 460.065026881721 | -135.165026881721 | 236 | 294.2 | 428.919865591398 | -134.719865591398 | 237 | 289.5 | 411.813413978495 | -122.313413978495 | 238 | 295.2 | 396.371478494624 | -101.171478494624 | 239 | 290.3 | 418.442446236559 | -128.142446236559 | 240 | 272 | 420.910188172043 | -148.910188172043 | 241 | 307.4 | 494.170799731183 | -186.770799731183 | 242 | 328.7 | 504.067573924731 | -175.367573924731 | 243 | 292.9 | 481.799831989247 | -188.899831989247 | 244 | 249.1 | 442.877251344086 | -193.777251344086 | 245 | 230.4 | 422.338541666667 | -191.938541666667 | 246 | 361.5 | 495.06434811828 | -133.564348118280 | 247 | 321.7 | 472.293380376344 | -150.593380376344 | 248 | 277.2 | 441.148219086022 | -163.948219086022 | 249 | 260.7 | 424.041767473118 | -163.341767473118 | 250 | 251 | 408.599831989247 | -157.599831989247 | 251 | 257.6 | 430.670799731183 | -173.070799731183 | 252 | 241.8 | 433.138541666667 | -191.338541666667 | 253 | 287.5 | 506.399153225806 | -218.899153225806 | 254 | 292.3 | 516.295927419355 | -223.995927419355 | 255 | 274.7 | 494.028185483871 | -219.328185483871 | 256 | 254.2 | 455.105604838710 | -200.905604838710 | 257 | 230 | 434.56689516129 | -204.566895161290 | 258 | 339 | 507.292701612903 | -168.292701612903 | 259 | 318.2 | 484.521733870968 | -166.321733870968 | 260 | 287 | 453.376572580645 | -166.376572580645 | 261 | 295.8 | 436.270120967742 | -140.470120967742 | 262 | 284 | 420.828185483871 | -136.828185483871 | 263 | 271 | 442.899153225806 | -171.899153225806 | 264 | 262.7 | 445.36689516129 | -182.666895161290 | 265 | 340.6 | 518.62750672043 | -178.02750672043 | 266 | 379.4 | 528.524280913978 | -149.124280913979 | 267 | 373.3 | 506.256538978495 | -132.956538978495 | 268 | 355.2 | 467.333958333333 | -112.133958333333 | 269 | 338.4 | 446.795248655914 | -108.395248655914 | 270 | 466.9 | 519.521055107527 | -52.6210551075269 | 271 | 451 | 496.750087365591 | -45.7500873655915 | 272 | 422 | 465.604926075269 | -43.6049260752688 | 273 | 429.2 | 448.498474462366 | -19.2984744623656 | 274 | 425.9 | 433.056538978495 | -7.15653897849466 | 275 | 460.7 | 455.12750672043 | 5.57249327956991 | 276 | 463.6 | 457.595248655914 | 6.00475134408608 | 277 | 541.4 | 530.855860215054 | 10.5441397849463 | 278 | 544.2 | 540.752634408602 | 3.44736559139789 | 279 | 517.5 | 518.484892473118 | -0.98489247311826 | 280 | 469.4 | 479.562311827957 | -10.1623118279570 | 281 | 439.4 | 459.023602150538 | -19.6236021505376 | 282 | 549 | 531.749408602151 | 17.2505913978494 | 283 | 533 | 508.978440860215 | 24.0215591397850 | 284 | 506.1 | 477.833279569893 | 28.2667204301075 | 285 | 484 | 460.726827956989 | 23.2731720430108 | 286 | 457 | 445.284892473118 | 11.7151075268817 | 287 | 481.5 | 467.355860215054 | 14.1441397849463 | 288 | 469.5 | 469.823602150538 | -0.323602150537566 | 289 | 544.7 | 543.084213709677 | 1.6157862903227 | 290 | 541.2 | 552.980987903226 | -11.7809879032258 | 291 | 521.5 | 530.713245967742 | -9.21324596774191 | 292 | 469.7 | 491.790665322581 | -22.0906653225806 | 293 | 434.4 | 471.251955645161 | -36.8519556451613 | 294 | 542.6 | 543.977762096774 | -1.37776209677415 | 295 | 517.3 | 521.206794354839 | -3.90679435483874 | 296 | 485.7 | 490.061633064516 | -4.36163306451613 | 297 | 465.8 | 472.955181451613 | -7.15518145161284 | 298 | 447 | 457.513245967742 | -10.5132459677419 | 299 | 426.6 | 479.584213709677 | -52.9842137096773 | 300 | 411.6 | 482.051955645161 | -70.4519556451612 | 301 | 467.5 | 555.312567204301 | -87.812567204301 | 302 | 484.5 | 565.209341397849 | -80.7093413978495 | 303 | 451.2 | 542.941599462366 | -91.7415994623656 | 304 | 417.4 | 504.019018817204 | -86.6190188172043 | 305 | 379.9 | 483.480309139785 | -103.580309139785 | 306 | 484.7 | 556.206115591398 | -71.5061155913979 | 307 | 455 | 533.435147849462 | -78.4351478494624 | 308 | 420.8 | 502.28998655914 | -81.4899865591398 | 309 | 416.5 | 485.183534946236 | -68.6835349462365 | 310 | 376.3 | 469.741599462366 | -93.4415994623656 | 311 | 405.6 | 491.812567204301 | -86.212567204301 | 312 | 405.8 | 494.280309139785 | -88.4803091397849 | 313 | 500.8 | 567.540920698925 | -66.7409206989247 | 314 | 514 | 577.437694892473 | -63.4376948924731 | 315 | 475.5 | 555.169952956989 | -79.6699529569892 | 316 | 430.1 | 516.247372311828 | -86.1473723118279 | 317 | 414.4 | 495.708662634409 | -81.3086626344086 | 318 | 538 | 568.434469086022 | -30.4344690860215 | 319 | 526 | 545.663501344086 | -19.663501344086 | 320 | 488.5 | 514.518340053763 | -26.0183400537635 | 321 | 520.2 | 497.41188844086 | 22.7881115591399 | 322 | 504.4 | 481.969952956989 | 22.4300470430108 | 323 | 568.5 | 504.040920698925 | 64.4590793010754 | 324 | 610.6 | 506.508662634408 | 104.091337365592 | 325 | 818 | 579.769274193548 | 238.230725806452 | 326 | 830.9 | 589.666048387097 | 241.233951612903 | 327 | 835.9 | 567.398306451613 | 268.501693548387 | 328 | 782 | 528.475725806452 | 253.524274193548 | 329 | 762.3 | 507.937016129032 | 254.362983870968 | 330 | 856.9 | 580.662822580645 | 276.237177419355 | 331 | 820.9 | 557.89185483871 | 263.00814516129 | 332 | 769.6 | 526.746693548387 | 242.853306451613 | 333 | 752.2 | 509.640241935484 | 242.559758064516 | 334 | 724.4 | 494.198306451613 | 230.201693548387 | 335 | 723.1 | 516.269274193548 | 206.830725806452 | 336 | 719.5 | 518.737016129032 | 200.762983870968 | 337 | 817.4 | 591.997627688172 | 225.402372311828 | 338 | 803.3 | 601.89440188172 | 201.405598118280 | 339 | 752.5 | 579.626659946237 | 172.873340053763 | 340 | 689 | 540.704079301075 | 148.295920698925 | 341 | 630.4 | 520.165369623656 | 110.234630376344 | 342 | 765.5 | 592.891176075269 | 172.608823924731 | 343 | 757.7 | 570.120208333333 | 187.579791666667 | 344 | 732.2 | 538.975047043011 | 193.224952956989 | 345 | 702.6 | 521.868595430107 | 180.731404569893 | 346 | 683.3 | 506.426659946237 | 176.873340053763 | 347 | 709.5 | 528.497627688172 | 181.002372311828 | 348 | 702.2 | 530.965369623656 | 171.234630376344 | 349 | 784.8 | 604.225981182796 | 180.574018817204 | 350 | 810.9 | 614.122755376344 | 196.777244623656 | 351 | 755.6 | 591.85501344086 | 163.744986559140 | 352 | 656.8 | 552.932432795699 | 103.867567204301 | 353 | 615.1 | 532.39372311828 | 82.7062768817205 | 354 | 745.3 | 605.119529569893 | 140.180470430107 | 355 | 694.1 | 582.348561827957 | 111.751438172043 | 356 | 675.7 | 551.203400537634 | 124.496599462366 | 357 | 643.7 | 534.096948924731 | 109.603051075269 | 358 | 622.1 | 518.65501344086 | 103.444986559140 | 359 | 634.6 | 540.725981182796 | 93.8740188172043 | 360 | 588 | 543.193723118279 | 44.8062768817206 | 361 | 689.7 | 616.45433467742 | 73.2456653225807 | 362 | 673.9 | 626.351108870968 | 47.5488911290322 | 363 | 647.9 | 604.083366935484 | 43.8166330645161 | 364 | 568.8 | 565.160786290322 | 3.6392137096775 | 365 | 545.7 | 544.622076612903 | 1.07792338709684 | 366 | 632.6 | 617.347883064516 | 15.2521169354839 | 367 | 643.8 | 594.576915322581 | 49.2230846774193 | 368 | 593.1 | 563.431754032258 | 29.6682459677420 | 369 | 579.7 | 546.325302419355 | 33.3746975806452 | 370 | 546 | 530.883366935484 | 15.1166330645162 | 371 | 562.9 | 552.954334677419 | 9.94566532258072 | 372 | 572.5 | 555.422076612903 | 17.0779233870969 |
Goldfeld-Quandt test for Heteroskedasticity | p-values | Alternative Hypothesis | breakpoint index | greater | 2-sided | less | 16 | 0.000399178512635825 | 0.00079835702527165 | 0.999600821487364 | 17 | 0.00545991681860451 | 0.0109198336372090 | 0.994540083181396 | 18 | 0.00411753782965193 | 0.00823507565930386 | 0.995882462170348 | 19 | 0.00637570237606125 | 0.0127514047521225 | 0.993624297623939 | 20 | 0.0033812817551152 | 0.0067625635102304 | 0.996618718244885 | 21 | 0.00135724937088816 | 0.00271449874177632 | 0.998642750629112 | 22 | 0.00114644940941755 | 0.00229289881883510 | 0.998853550590582 | 23 | 0.000420720753556692 | 0.000841441507113384 | 0.999579279246443 | 24 | 0.000145665302782798 | 0.000291330605565597 | 0.999854334697217 | 25 | 4.85615086243534e-05 | 9.71230172487067e-05 | 0.999951438491376 | 26 | 2.18707346218092e-05 | 4.37414692436184e-05 | 0.999978129265378 | 27 | 1.93823739557943e-05 | 3.87647479115885e-05 | 0.999980617626044 | 28 | 5.35346640481e-05 | 0.0001070693280962 | 0.999946465335952 | 29 | 0.000189443590562915 | 0.00037888718112583 | 0.999810556409437 | 30 | 0.000444766373404705 | 0.00088953274680941 | 0.999555233626595 | 31 | 0.00168061051882611 | 0.00336122103765221 | 0.998319389481174 | 32 | 0.0067628537177279 | 0.0135257074354558 | 0.993237146282272 | 33 | 0.0122129188737802 | 0.0244258377475605 | 0.98778708112622 | 34 | 0.0254733374816815 | 0.0509466749633629 | 0.974526662518319 | 35 | 0.0314085519118060 | 0.0628171038236119 | 0.968591448088194 | 36 | 0.0377129535930309 | 0.0754259071860618 | 0.962287046406969 | 37 | 0.0580057042769299 | 0.116011408553860 | 0.94199429572307 | 38 | 0.102490982662226 | 0.204981965324452 | 0.897509017337774 | 39 | 0.138726256395225 | 0.277452512790451 | 0.861273743604775 | 40 | 0.169503466453696 | 0.339006932907391 | 0.830496533546304 | 41 | 0.188670521824274 | 0.377341043648547 | 0.811329478175726 | 42 | 0.200514187195145 | 0.401028374390289 | 0.799485812804855 | 43 | 0.213531737636849 | 0.427063475273697 | 0.786468262363151 | 44 | 0.208208345144114 | 0.416416690288227 | 0.791791654855886 | 45 | 0.185744988547286 | 0.371489977094573 | 0.814255011452714 | 46 | 0.161520532640513 | 0.323041065281027 | 0.838479467359487 | 47 | 0.136163681642835 | 0.27232736328567 | 0.863836318357165 | 48 | 0.120646139894827 | 0.241292279789653 | 0.879353860105173 | 49 | 0.103316653160991 | 0.206633306321982 | 0.89668334683901 | 50 | 0.09043245520783 | 0.18086491041566 | 0.90956754479217 | 51 | 0.0801768997009601 | 0.16035379940192 | 0.91982310029904 | 52 | 0.066773071645181 | 0.133546143290362 | 0.933226928354819 | 53 | 0.053576113671498 | 0.107152227342996 | 0.946423886328502 | 54 | 0.0438596203765383 | 0.0877192407530766 | 0.956140379623462 | 55 | 0.0350823770058382 | 0.0701647540116765 | 0.964917622994162 | 56 | 0.0268112819413435 | 0.053622563882687 | 0.973188718058656 | 57 | 0.0203822206239281 | 0.0407644412478563 | 0.979617779376072 | 58 | 0.015484143468679 | 0.030968286937358 | 0.98451585653132 | 59 | 0.0117379677617544 | 0.0234759355235089 | 0.988262032238246 | 60 | 0.0089714926106093 | 0.0179429852212186 | 0.99102850738939 | 61 | 0.00659815355483022 | 0.0131963071096604 | 0.99340184644517 | 62 | 0.00522584826193136 | 0.0104516965238627 | 0.994774151738069 | 63 | 0.00395384948428146 | 0.00790769896856293 | 0.996046150515719 | 64 | 0.00281760532317324 | 0.00563521064634649 | 0.997182394676827 | 65 | 0.00200205640836714 | 0.00400411281673429 | 0.997997943591633 | 66 | 0.00150501656383118 | 0.00301003312766236 | 0.998494983436169 | 67 | 0.00111407115071734 | 0.00222814230143468 | 0.998885928849283 | 68 | 0.000789616676108056 | 0.00157923335221611 | 0.999210383323892 | 69 | 0.000540613908012835 | 0.00108122781602567 | 0.999459386091987 | 70 | 0.00037121434223006 | 0.00074242868446012 | 0.99962878565777 | 71 | 0.00027273823352226 | 0.00054547646704452 | 0.999727261766478 | 72 | 0.000233191255085327 | 0.000466382510170654 | 0.999766808744915 | 73 | 0.000411839639189725 | 0.00082367927837945 | 0.99958816036081 | 74 | 0.000876514219583321 | 0.00175302843916664 | 0.999123485780417 | 75 | 0.00219429504498293 | 0.00438859008996587 | 0.997805704955017 | 76 | 0.00489972790920429 | 0.00979945581840857 | 0.995100272090796 | 77 | 0.00905097351948609 | 0.0181019470389722 | 0.990949026480514 | 78 | 0.0113739350083114 | 0.0227478700166228 | 0.988626064991689 | 79 | 0.0135848810265822 | 0.0271697620531643 | 0.986415118973418 | 80 | 0.0167288160530484 | 0.0334576321060969 | 0.983271183946952 | 81 | 0.0207380419401111 | 0.0414760838802221 | 0.979261958059889 | 82 | 0.0208297002607997 | 0.0416594005215995 | 0.9791702997392 | 83 | 0.0205092756098908 | 0.0410185512197815 | 0.97949072439011 | 84 | 0.0186632917560113 | 0.0373265835120226 | 0.981336708243989 | 85 | 0.0171875456028787 | 0.0343750912057574 | 0.982812454397121 | 86 | 0.0144051541998519 | 0.0288103083997038 | 0.985594845800148 | 87 | 0.0117799816612343 | 0.0235599633224687 | 0.988220018338766 | 88 | 0.00992838629422759 | 0.0198567725884552 | 0.990071613705772 | 89 | 0.00780953149835774 | 0.0156190629967155 | 0.992190468501642 | 90 | 0.00602265307712571 | 0.0120453061542514 | 0.993977346922874 | 91 | 0.00458036925997208 | 0.00916073851994415 | 0.995419630740028 | 92 | 0.00345810655390801 | 0.00691621310781602 | 0.996541893446092 | 93 | 0.00258524802411095 | 0.0051704960482219 | 0.997414751975889 | 94 | 0.00193142982184565 | 0.0038628596436913 | 0.998068570178154 | 95 | 0.00144047551774178 | 0.00288095103548355 | 0.998559524482258 | 96 | 0.00106919529229014 | 0.00213839058458028 | 0.99893080470771 | 97 | 0.000779111619079718 | 0.00155822323815944 | 0.99922088838092 | 98 | 0.000563192753627762 | 0.00112638550725552 | 0.999436807246372 | 99 | 0.00040671096925529 | 0.00081342193851058 | 0.999593289030745 | 100 | 0.000289553578172521 | 0.000579107156345042 | 0.999710446421827 | 101 | 0.000212665140181034 | 0.000425330280362069 | 0.99978733485982 | 102 | 0.000157140211354742 | 0.000314280422709484 | 0.999842859788645 | 103 | 0.000111253353698923 | 0.000222506707397846 | 0.999888746646301 | 104 | 7.72868560652615e-05 | 0.000154573712130523 | 0.999922713143935 | 105 | 5.3496906692715e-05 | 0.00010699381338543 | 0.999946503093307 | 106 | 3.67874561006927e-05 | 7.35749122013853e-05 | 0.9999632125439 | 107 | 2.53937331283655e-05 | 5.07874662567309e-05 | 0.999974606266872 | 108 | 1.74397854759989e-05 | 3.48795709519979e-05 | 0.999982560214524 | 109 | 1.18413435256532e-05 | 2.36826870513064e-05 | 0.999988158656474 | 110 | 7.96619132592526e-06 | 1.59323826518505e-05 | 0.999992033808674 | 111 | 5.36755535482594e-06 | 1.07351107096519e-05 | 0.999994632444645 | 112 | 3.5412713241476e-06 | 7.0825426482952e-06 | 0.999996458728676 | 113 | 2.32189338924435e-06 | 4.64378677848871e-06 | 0.99999767810661 | 114 | 1.57196323725913e-06 | 3.14392647451826e-06 | 0.999998428036763 | 115 | 1.02104880155917e-06 | 2.04209760311834e-06 | 0.999998978951198 | 116 | 6.59109172687584e-07 | 1.31821834537517e-06 | 0.999999340890827 | 117 | 4.22704330627277e-07 | 8.45408661254553e-07 | 0.99999957729567 | 118 | 2.75955080694566e-07 | 5.51910161389133e-07 | 0.99999972404492 | 119 | 2.15330693461612e-07 | 4.30661386923224e-07 | 0.999999784669307 | 120 | 1.8604866596728e-07 | 3.7209733193456e-07 | 0.999999813951334 | 121 | 2.70602516879263e-07 | 5.41205033758526e-07 | 0.999999729397483 | 122 | 8.0811693741337e-07 | 1.61623387482674e-06 | 0.999999191883063 | 123 | 3.0624279935591e-06 | 6.1248559871182e-06 | 0.999996937572006 | 124 | 1.34320135237388e-05 | 2.68640270474776e-05 | 0.999986567986476 | 125 | 4.46655500078963e-05 | 8.93311000157926e-05 | 0.999955334449992 | 126 | 0.000119776013438795 | 0.00023955202687759 | 0.99988022398656 | 127 | 0.000280073040597697 | 0.000560146081195394 | 0.999719926959402 | 128 | 0.000496399156266922 | 0.000992798312533844 | 0.999503600843733 | 129 | 0.000593611424177291 | 0.00118722284835458 | 0.999406388575823 | 130 | 0.000638865613468797 | 0.00127773122693759 | 0.999361134386531 | 131 | 0.000604898065746728 | 0.00120979613149346 | 0.999395101934253 | 132 | 0.000653166831694775 | 0.00130633366338955 | 0.999346833168305 | 133 | 0.000665242169948891 | 0.00133048433989778 | 0.999334757830051 | 134 | 0.000637668245364504 | 0.00127533649072901 | 0.999362331754636 | 135 | 0.000559176977242997 | 0.00111835395448599 | 0.999440823022757 | 136 | 0.000444537181460655 | 0.00088907436292131 | 0.99955546281854 | 137 | 0.000352930584074137 | 0.000705861168148273 | 0.999647069415926 | 138 | 0.000265171841993376 | 0.000530343683986752 | 0.999734828158007 | 139 | 0.000200335141496026 | 0.000400670282992051 | 0.999799664858504 | 140 | 0.000151478184273942 | 0.000302956368547884 | 0.999848521815726 | 141 | 0.000114522140648833 | 0.000229044281297666 | 0.99988547785935 | 142 | 8.97027561842686e-05 | 0.000179405512368537 | 0.999910297243816 | 143 | 7.43557326688881e-05 | 0.000148711465337776 | 0.999925644267331 | 144 | 5.87440787828728e-05 | 0.000117488157565746 | 0.999941255921217 | 145 | 4.4763985718145e-05 | 8.952797143629e-05 | 0.999955236014282 | 146 | 3.31680421771903e-05 | 6.63360843543806e-05 | 0.999966831957823 | 147 | 2.63672292067048e-05 | 5.27344584134096e-05 | 0.999973632770793 | 148 | 2.03512226304026e-05 | 4.07024452608053e-05 | 0.99997964877737 | 149 | 1.57496546633976e-05 | 3.14993093267951e-05 | 0.999984250345337 | 150 | 1.21265046191535e-05 | 2.42530092383069e-05 | 0.99998787349538 | 151 | 9.12600146918587e-06 | 1.82520029383717e-05 | 0.99999087399853 | 152 | 7.14785279332256e-06 | 1.42957055866451e-05 | 0.999992852147207 | 153 | 5.2776279607864e-06 | 1.05552559215728e-05 | 0.99999472237204 | 154 | 4.40640381640768e-06 | 8.81280763281536e-06 | 0.999995593596184 | 155 | 4.12499719819859e-06 | 8.24999439639718e-06 | 0.999995875002802 | 156 | 5.64132172378465e-06 | 1.12826434475693e-05 | 0.999994358678276 | 157 | 8.98498626418482e-06 | 1.79699725283696e-05 | 0.999991015013736 | 158 | 1.81013353041292e-05 | 3.62026706082584e-05 | 0.999981898664696 | 159 | 3.49835891964552e-05 | 6.99671783929103e-05 | 0.999965016410804 | 160 | 5.71391145673299e-05 | 0.000114278229134660 | 0.999942860885433 | 161 | 9.31857227369458e-05 | 0.000186371445473892 | 0.999906814277263 | 162 | 0.000147882685577353 | 0.000295765371154706 | 0.999852117314423 | 163 | 0.000206317950247559 | 0.000412635900495119 | 0.999793682049752 | 164 | 0.000248051796000572 | 0.000496103592001144 | 0.999751948204 | 165 | 0.000261204888026086 | 0.000522409776052172 | 0.999738795111974 | 166 | 0.000276452802643881 | 0.000552905605287761 | 0.999723547197356 | 167 | 0.000278944901246526 | 0.000557889802493052 | 0.999721055098753 | 168 | 0.000300405955349146 | 0.000600811910698292 | 0.99969959404465 | 169 | 0.000299031015405547 | 0.000598062030811094 | 0.999700968984594 | 170 | 0.000281945633847421 | 0.000563891267694843 | 0.999718054366153 | 171 | 0.000279431367254462 | 0.000558862734508924 | 0.999720568632745 | 172 | 0.000283483824319828 | 0.000566967648639655 | 0.99971651617568 | 173 | 0.000325331993960903 | 0.000650663987921806 | 0.999674668006039 | 174 | 0.000288990208923437 | 0.000577980417846874 | 0.999711009791077 | 175 | 0.000263239906199481 | 0.000526479812398962 | 0.9997367600938 | 176 | 0.000256181154457830 | 0.000512362308915659 | 0.999743818845542 | 177 | 0.000237333528098568 | 0.000474667056197137 | 0.999762666471901 | 178 | 0.000219835097317482 | 0.000439670194634965 | 0.999780164902683 | 179 | 0.000223473778684304 | 0.000446947557368608 | 0.999776526221316 | 180 | 0.000239189373614314 | 0.000478378747228629 | 0.999760810626386 | 181 | 0.000261580343590371 | 0.000523160687180742 | 0.99973841965641 | 182 | 0.000315729952195946 | 0.000631459904391892 | 0.999684270047804 | 183 | 0.000363302019054011 | 0.000726604038108022 | 0.999636697980946 | 184 | 0.000430960561101024 | 0.000861921122202048 | 0.999569039438899 | 185 | 0.000576347802828128 | 0.00115269560565626 | 0.999423652197172 | 186 | 0.00062409250853556 | 0.00124818501707112 | 0.999375907491464 | 187 | 0.000665446337721024 | 0.00133089267544205 | 0.999334553662279 | 188 | 0.000706180638295575 | 0.00141236127659115 | 0.999293819361704 | 189 | 0.000725754802037806 | 0.00145150960407561 | 0.999274245197962 | 190 | 0.000773941032118385 | 0.00154788206423677 | 0.999226058967882 | 191 | 0.000956254607848208 | 0.00191250921569642 | 0.999043745392152 | 192 | 0.00120845655382294 | 0.00241691310764588 | 0.998791543446177 | 193 | 0.00146112931766521 | 0.00292225863533042 | 0.998538870682335 | 194 | 0.00172264739729650 | 0.00344529479459301 | 0.998277352602704 | 195 | 0.00212431969366968 | 0.00424863938733936 | 0.99787568030633 | 196 | 0.00276951147228650 | 0.00553902294457299 | 0.997230488527713 | 197 | 0.0037071691584039 | 0.0074143383168078 | 0.996292830841596 | 198 | 0.00432954144740540 | 0.00865908289481081 | 0.995670458552595 | 199 | 0.00463396023859803 | 0.00926792047719607 | 0.995366039761402 | 200 | 0.00517057126418452 | 0.0103411425283690 | 0.994829428735815 | 201 | 0.0055790331086752 | 0.0111580662173504 | 0.994420966891325 | 202 | 0.0062322045174414 | 0.0124644090348828 | 0.993767795482559 | 203 | 0.00721061674845659 | 0.0144212334969132 | 0.992789383251543 | 204 | 0.00894380121375928 | 0.0178876024275186 | 0.99105619878624 | 205 | 0.0100695245229974 | 0.0201390490459948 | 0.989930475477003 | 206 | 0.0117756671414754 | 0.0235513342829508 | 0.988224332858525 | 207 | 0.0137853968664847 | 0.0275707937329694 | 0.986214603133515 | 208 | 0.0172873820699430 | 0.0345747641398860 | 0.982712617930057 | 209 | 0.0222500200030461 | 0.0445000400060921 | 0.977749979996954 | 210 | 0.0240041583433847 | 0.0480083166867694 | 0.975995841656615 | 211 | 0.0253865577882857 | 0.0507731155765715 | 0.974613442211714 | 212 | 0.0271801175633047 | 0.0543602351266094 | 0.972819882436695 | 213 | 0.0284061997974066 | 0.0568123995948131 | 0.971593800202593 | 214 | 0.0299222064788705 | 0.059844412957741 | 0.97007779352113 | 215 | 0.0326196021891931 | 0.0652392043783862 | 0.967380397810807 | 216 | 0.0368895673129198 | 0.0737791346258396 | 0.96311043268708 | 217 | 0.0404708321095527 | 0.0809416642191054 | 0.959529167890447 | 218 | 0.0467481795794756 | 0.0934963591589511 | 0.953251820420524 | 219 | 0.052428551588272 | 0.104857103176544 | 0.947571448411728 | 220 | 0.0585230935468378 | 0.117046187093676 | 0.941476906453162 | 221 | 0.0653349833104167 | 0.130669966620833 | 0.934665016689583 | 222 | 0.0635039852786895 | 0.127007970557379 | 0.93649601472131 | 223 | 0.0631700870206419 | 0.126340174041284 | 0.936829912979358 | 224 | 0.062505300125056 | 0.125010600250112 | 0.937494699874944 | 225 | 0.0616310777819835 | 0.123262155563967 | 0.938368922218016 | 226 | 0.0600898675707749 | 0.120179735141550 | 0.939910132429225 | 227 | 0.0601941651361356 | 0.120388330272271 | 0.939805834863864 | 228 | 0.0610581330914621 | 0.122116266182924 | 0.938941866908538 | 229 | 0.0612230581107886 | 0.122446116221577 | 0.938776941889211 | 230 | 0.0620711609799164 | 0.124142321959833 | 0.937928839020084 | 231 | 0.0631327994341906 | 0.126265598868381 | 0.93686720056581 | 232 | 0.063911843039016 | 0.127823686078032 | 0.936088156960984 | 233 | 0.0655464123299779 | 0.131092824659956 | 0.934453587670022 | 234 | 0.0595751018929033 | 0.119150203785807 | 0.940424898107097 | 235 | 0.0542965190097588 | 0.108593038019518 | 0.945703480990241 | 236 | 0.0495856821982509 | 0.0991713643965018 | 0.95041431780175 | 237 | 0.0444019736824011 | 0.0888039473648022 | 0.9555980263176 | 238 | 0.0404114905293515 | 0.080822981058703 | 0.959588509470649 | 239 | 0.0368375290563434 | 0.0736750581126869 | 0.963162470943657 | 240 | 0.0343992095479981 | 0.0687984190959961 | 0.965600790452002 | 241 | 0.0337687411910621 | 0.0675374823821242 | 0.966231258808938 | 242 | 0.0319162692949045 | 0.0638325385898091 | 0.968083730705095 | 243 | 0.0312990055133308 | 0.0625980110266615 | 0.96870099448667 | 244 | 0.0311869563064593 | 0.0623739126129187 | 0.96881304369354 | 245 | 0.0309292481787948 | 0.0618584963575895 | 0.969070751821205 | 246 | 0.0264985287385806 | 0.0529970574771613 | 0.97350147126142 | 247 | 0.0230773998660325 | 0.046154799732065 | 0.976922600133967 | 248 | 0.0205754137223807 | 0.0411508274447614 | 0.97942458627762 | 249 | 0.0182531827190186 | 0.0365063654380373 | 0.981746817280981 | 250 | 0.0159150264684465 | 0.0318300529368931 | 0.984084973531553 | 251 | 0.0143682056852634 | 0.0287364113705267 | 0.985631794314737 | 252 | 0.0137102762021063 | 0.0274205524042127 | 0.986289723797894 | 253 | 0.0157963197645172 | 0.0315926395290344 | 0.984203680235483 | 254 | 0.0187167349744869 | 0.0374334699489738 | 0.981283265025513 | 255 | 0.0213409266298473 | 0.0426818532596946 | 0.978659073370153 | 256 | 0.0216251634687032 | 0.0432503269374063 | 0.978374836531297 | 257 | 0.0219617601315230 | 0.0439235202630461 | 0.978038239868477 | 258 | 0.0206439234435908 | 0.0412878468871815 | 0.97935607655641 | 259 | 0.0194365967843918 | 0.0388731935687836 | 0.980563403215608 | 260 | 0.0182824442827772 | 0.0365648885655543 | 0.981717555717223 | 261 | 0.0160985670608248 | 0.0321971341216496 | 0.983901432939175 | 262 | 0.0138779305961314 | 0.0277558611922629 | 0.986122069403869 | 263 | 0.0134152844319906 | 0.0268305688639812 | 0.98658471556801 | 264 | 0.0135177432046220 | 0.0270354864092440 | 0.986482256795378 | 265 | 0.0154295260989067 | 0.0308590521978134 | 0.984570473901093 | 266 | 0.0152893895227095 | 0.030578779045419 | 0.98471061047729 | 267 | 0.0140668481585513 | 0.0281336963171026 | 0.985933151841449 | 268 | 0.0118003669706390 | 0.0236007339412781 | 0.98819963302936 | 269 | 0.00964898435981788 | 0.0192979687196358 | 0.990351015640182 | 270 | 0.0080427673418423 | 0.0160855346836846 | 0.991957232658158 | 271 | 0.00671603186112961 | 0.0134320637222592 | 0.99328396813887 | 272 | 0.00557038127130607 | 0.0111407625426121 | 0.994429618728694 | 273 | 0.00480045163599543 | 0.00960090327199086 | 0.995199548364005 | 274 | 0.00426137975265501 | 0.00852275950531001 | 0.995738620247345 | 275 | 0.00396353627124117 | 0.00792707254248234 | 0.996036463728759 | 276 | 0.00371475092917316 | 0.00742950185834631 | 0.996285249070827 | 277 | 0.00340100260503555 | 0.0068020052100711 | 0.996598997394964 | 278 | 0.00302306340714812 | 0.00604612681429625 | 0.996976936592852 | 279 | 0.00263643702503081 | 0.00527287405006163 | 0.99736356297497 | 280 | 0.00224671490371316 | 0.00449342980742632 | 0.997753285096287 | 281 | 0.00187199750037595 | 0.00374399500075189 | 0.998128002499624 | 282 | 0.00171729559536451 | 0.00343459119072903 | 0.998282704404636 | 283 | 0.00161366652414033 | 0.00322733304828067 | 0.99838633347586 | 284 | 0.00155037757509183 | 0.00310075515018366 | 0.998449622424908 | 285 | 0.00144042819539400 | 0.00288085639078801 | 0.998559571804606 | 286 | 0.00128311454875391 | 0.00256622909750783 | 0.998716885451246 | 287 | 0.00116033620881015 | 0.0023206724176203 | 0.99883966379119 | 288 | 0.000993099807246658 | 0.00198619961449332 | 0.999006900192753 | 289 | 0.00082046252810922 | 0.00164092505621844 | 0.99917953747189 | 290 | 0.000654297407065074 | 0.00130859481413015 | 0.999345702592935 | 291 | 0.000517331408454555 | 0.00103466281690911 | 0.999482668591545 | 292 | 0.000395139032103646 | 0.000790278064207293 | 0.999604860967896 | 293 | 0.000292153407147838 | 0.000584306814295676 | 0.999707846592852 | 294 | 0.000230175351631545 | 0.00046035070326309 | 0.999769824648368 | 295 | 0.000178845314320242 | 0.000357690628640485 | 0.99982115468568 | 296 | 0.000137602852308379 | 0.000275205704616758 | 0.999862397147692 | 297 | 0.000104448564304350 | 0.000208897128608699 | 0.999895551435696 | 298 | 7.78610969688502e-05 | 0.000155722193937700 | 0.999922138903031 | 299 | 5.57735806067862e-05 | 0.000111547161213572 | 0.999944226419393 | 300 | 4.04688735184171e-05 | 8.09377470368343e-05 | 0.999959531126482 | 301 | 4.35977872951015e-05 | 8.7195574590203e-05 | 0.999956402212705 | 302 | 4.50237122153241e-05 | 9.00474244306482e-05 | 0.999954976287785 | 303 | 4.81828882952675e-05 | 9.6365776590535e-05 | 0.999951817111705 | 304 | 4.33447121867859e-05 | 8.66894243735718e-05 | 0.999956655287813 | 305 | 4.15129184511982e-05 | 8.30258369023965e-05 | 0.999958487081549 | 306 | 4.39375684244566e-05 | 8.78751368489133e-05 | 0.999956062431576 | 307 | 5.26607579116613e-05 | 0.000105321515823323 | 0.999947339242088 | 308 | 6.59061952608613e-05 | 0.000131812390521723 | 0.99993409380474 | 309 | 8.35980276708226e-05 | 0.000167196055341645 | 0.99991640197233 | 310 | 0.000132385195584362 | 0.000264770391168723 | 0.999867614804416 | 311 | 0.000221332527878352 | 0.000442665055756704 | 0.999778667472122 | 312 | 0.000411582676251128 | 0.000823165352502256 | 0.999588417323749 | 313 | 0.00144847269929645 | 0.0028969453985929 | 0.998551527300704 | 314 | 0.00497333064488382 | 0.00994666128976764 | 0.995026669355116 | 315 | 0.0199996200380530 | 0.0399992400761059 | 0.980000379961947 | 316 | 0.0611328835084542 | 0.122265767016908 | 0.938867116491546 | 317 | 0.155852075782472 | 0.311704151564944 | 0.844147924217528 | 318 | 0.349611472694731 | 0.699222945389462 | 0.650388527305269 | 319 | 0.64766232816231 | 0.704675343675379 | 0.352337671837690 | 320 | 0.926656661048378 | 0.146686677903245 | 0.0733433389516223 | 321 | 0.99269176286407 | 0.0146164742718619 | 0.00730823713593094 | 322 | 0.999940292166853 | 0.000119415666293056 | 5.97078331465281e-05 | 323 | 0.999999965107944 | 6.978411129635e-08 | 3.4892055648175e-08 | 324 | 0.999999999999326 | 1.34862878006138e-12 | 6.74314390030692e-13 | 325 | 0.999999999999904 | 1.91466545653566e-13 | 9.57332728267828e-14 | 326 | 0.999999999999973 | 5.48582628733222e-14 | 2.74291314366611e-14 | 327 | 0.99999999999995 | 9.92858004591825e-14 | 4.96429002295912e-14 | 328 | 0.999999999999925 | 1.50080651178752e-13 | 7.50403255893762e-14 | 329 | 0.999999999999962 | 7.53232717590489e-14 | 3.76616358795244e-14 | 330 | 0.999999999999946 | 1.07453032733339e-13 | 5.37265163666694e-14 | 331 | 0.999999999999863 | 2.73200258438187e-13 | 1.36600129219094e-13 | 332 | 0.999999999999649 | 7.02822907031687e-13 | 3.51411453515843e-13 | 333 | 0.999999999998965 | 2.07006233604904e-12 | 1.03503116802452e-12 | 334 | 0.999999999996897 | 6.2054389326539e-12 | 3.10271946632695e-12 | 335 | 0.999999999994636 | 1.07286996605331e-11 | 5.36434983026654e-12 | 336 | 0.99999999998684 | 2.63181667673297e-11 | 1.31590833836649e-11 | 337 | 0.999999999958063 | 8.3873421355345e-11 | 4.19367106776725e-11 | 338 | 0.999999999920814 | 1.58371383511822e-10 | 7.9185691755911e-11 | 339 | 0.999999999920103 | 1.59794716703227e-10 | 7.98973583516137e-11 | 340 | 0.999999999762847 | 4.7430645441025e-10 | 2.37153227205125e-10 | 341 | 0.999999999862214 | 2.75571849905803e-10 | 1.37785924952901e-10 | 342 | 0.999999999699195 | 6.01610027867943e-10 | 3.00805013933971e-10 | 343 | 0.99999999900485 | 1.99030041685643e-09 | 9.95150208428216e-10 | 344 | 0.99999999591185 | 8.17630029480756e-09 | 4.08815014740378e-09 | 345 | 0.999999987135937 | 2.57281253578105e-08 | 1.28640626789052e-08 | 346 | 0.999999950882892 | 9.82342156129844e-08 | 4.91171078064922e-08 | 347 | 0.99999977252841 | 4.54943180670553e-07 | 2.27471590335276e-07 | 348 | 0.999998890682427 | 2.21863514665183e-06 | 1.10931757332591e-06 | 349 | 0.99999527523036 | 9.4495392823276e-06 | 4.7247696411638e-06 | 350 | 0.999996482226451 | 7.03554709786324e-06 | 3.51777354893162e-06 | 351 | 0.999991199273105 | 1.76014537902644e-05 | 8.80072689513222e-06 | 352 | 0.999958810084454 | 8.23798310922406e-05 | 4.11899155461203e-05 | 353 | 0.999765195737345 | 0.000469608525310464 | 0.000234804262655232 | 354 | 0.99970129491697 | 0.00059741016606149 | 0.000298705083030745 | 355 | 0.998184692405011 | 0.00363061518997738 | 0.00181530759498869 | 356 | 0.991833845944853 | 0.0163323081102941 | 0.00816615405514705 |
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity | Description | # significant tests | % significant tests | OK/NOK | 1% type I error level | 213 | 0.624633431085044 | NOK | 5% type I error level | 277 | 0.812316715542522 | NOK | 10% type I error level | 302 | 0.885630498533724 | NOK |
| | Charts produced by software: | | http://www.freestatistics.org/blog/date/2010/Dec/09/t12919246007ftftu67h2p1ey7/10m4mn1291924695.png (open in new window) | http://www.freestatistics.org/blog/date/2010/Dec/09/t12919246007ftftu67h2p1ey7/10m4mn1291924695.ps (open in new window) |
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| | 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)
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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