| | *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: Wed, 01 Dec 2010 15:23:45 +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/01/t1291216977cah4z8nchqh8wkb.htm/, Retrieved Wed, 01 Dec 2010 16:23:18 +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/01/t1291216977cah4z8nchqh8wkb.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 « | 162556 84738 807 428 213118 -26007 6282154 223193
29790 40949 444 263 81767 129352 4321023 1398893
87550 25830 412 104 153198 245546 4111912 1073089
54660 12679 315 122 126942 48020 1491348 984885
42634 43556 168 190 157214 32648 1629616 227132
45187 6575 267 63 234817 151352 1926517 1071292
37704 7123 228 102 60448 288170 983660 638830
16275 17821 129 277 47818 122844 1443586 444477
18014 13326 393 103 -1710 165548 1405225 702380
24811 16189 280 290 95350 116384 929118 358589
21950 7146 265 83 114337 134028 856956 297978
37597 15824 234 56 37884 63838 992426 585715
12988 11920 73 73 82340 31080 857217 209458
22330 8568 67 34 79801 32168 711969 786690
27664 14416 236 139 74996 49857 657954 439798
3369 2220 26 12 87161 301670 688779 644190
11819 18562 70 211 106113 102313 574339 377934
6984 10327 40 74 80570 88577 741409 640273
4519 4069 42 131 102129 79804 597793 207393
5336 8636 80 203 112477 128294 697458 301607
2365 13718 83 56 191778 96448 550608 345783
3689 4525 25 89 101792 93811 37 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 | W1[t] = + 222775.888361243 -1.65138733483591C0[t] -1.40857166832423C1[t] -0.00170135179447743O0[t] + 0.158745331059232O1[t] -0.286214482864696D0[t] + 1.32534465035903D1[t] + 0.166709574316368W0[t] + e[t] |
Multiple Linear Regression - Ordinary Least Squares | Variable | Parameter | S.D. | T-STAT H0: parameter = 0 | 2-tail p-value | 1-tail p-value | (Intercept) | 222775.888361243 | 15558.373436 | 14.3187 | 0 | 0 | C0 | -1.65138733483591 | 0.206677 | -7.9902 | 0 | 0 | C1 | -1.40857166832423 | 0.192394 | -7.3213 | 0 | 0 | O0 | -0.00170135179447743 | 0.014871 | -0.1144 | 0.908992 | 0.454496 | O1 | 0.158745331059232 | 0.051771 | 3.0663 | 0.002363 | 0.001181 | D0 | -0.286214482864696 | 0.209459 | -1.3664 | 0.172812 | 0.086406 | D1 | 1.32534465035903 | 0.189955 | 6.9772 | 0 | 0 | W0 | 0.166709574316368 | 0.013197 | 12.6327 | 0 | 0 |
Multiple Linear Regression - Regression Statistics | Multiple R | 0.866129992505376 | R-squared | 0.750181163917363 | Adjusted R-squared | 0.744409771664629 | F-TEST (value) | 129.982702797919 | F-TEST (DF numerator) | 7 | F-TEST (DF denominator) | 303 | p-value | 0 | Multiple Linear Regression - Residual Statistics | Residual Standard Deviation | 99152.9549855605 | Sum Squared Residuals | 2978886470157.68 |
Multiple Linear Regression - Actuals, Interpolation, and Residuals | Time or Index | Actuals | Interpolation Forecast | Residuals Prediction Error | 1 | 223193 | 786869.515388798 | -563676.515388798 | 2 | 1398893 | 984331.439566217 | 414561.560433783 | 3 | 1073089 | 1008910.01987855 | 64178.9801214489 | 4 | 984885 | 390603.008925 | 594281.991075 | 5 | 227132 | 360994.287023091 | -133862.287023091 | 6 | 1071292 | 593457.203119255 | 477834.796880745 | 7 | 638830 | 679103.54311647 | -40273.5431164695 | 8 | 444477 | 560625.198404052 | -116148.198404052 | 9 | 702380 | 628434.897509316 | 73945.1024906839 | 10 | 358589 | 440896.737341543 | -82307.7373415434 | 11 | 297978 | 464246.165662878 | -166268.165662878 | 12 | 585715 | 377619.250597342 | 208095.749402658 | 13 | 209458 | 345080.051961288 | -135622.051961288 | 14 | 786690 | 312322.584152953 | 474367.415847047 | 15 | 439798 | 311107.602177554 | 128690.397822446 | 16 | 644190 | 703783.230056218 | -59593.2300562183 | 17 | 377934 | 378122.33030886 | -188.330308859960 | 18 | 640273 | 414642.689691157 | 225630.310308843 | 19 | 207393 | 385797.337174368 | -178404.337174368 | 20 | 301607 | 455945.896276505 | -154338.896276505 | 21 | 345783 | 364285.144732812 | -18502.1447328121 | 22 | 501749 | 368422.137777039 | 133326.862222961 | 23 | 379983 | 362346.330832834 | 17636.6691671657 | 24 | 387475 | 328174.475323189 | 59300.5246768106 | 25 | 469107 | 429778.870007707 | 39328.1299922935 | 26 | 194493 | 361818.468721471 | -167325.468721471 | 27 | 405972 | 316553.524707521 | 89418.4752924788 | 28 | 652925 | 328366.146682301 | 324558.853317699 | 29 | 446211 | 317933.507115142 | 128277.492884858 | 30 | 341340 | 377041.100787314 | -35701.1007873142 | 31 | 146494 | 346641.438517298 | -200147.438517298 | 32 | 355178 | 334077.581330947 | 21100.4186690525 | 33 | 357760 | 349183.127735342 | 8576.87226465816 | 34 | 261216 | 362689.46323192 | -101473.463231920 | 35 | 374943 | 430026.540718406 | -55083.5407184055 | 36 | 378525 | 288145.275540025 | 90379.7244599755 | 37 | 310768 | 378480.949298256 | -67712.949298256 | 38 | 325738 | 348895.172902710 | -23157.1729027095 | 39 | 394510 | 415102.162967147 | -20592.1629671466 | 40 | 368078 | 405243.55913148 | -37165.5591314802 | 41 | 236761 | 354235.101492344 | -117474.101492344 | 42 | 312378 | 326756.349086157 | -14378.3490861575 | 43 | 347385 | 342159.888024213 | 5225.11197578656 | 44 | 352850 | 438414.096146164 | -85564.0961461642 | 45 | 301881 | 303903.319326167 | -2022.31932616679 | 46 | 377516 | 385600.773562287 | -8084.77356228703 | 47 | 458343 | 335797.908470587 | 122545.091529413 | 48 | 354228 | 413566.421838309 | -59338.4218383093 | 49 | 308636 | 378712.141950415 | -70076.1419504151 | 50 | 386212 | 365948.861093272 | 20263.1389067283 | 51 | 393343 | 369721.653379533 | 23621.3466204666 | 52 | 452469 | 348160.494870626 | 104308.505129374 | 53 | 358649 | 279784.846587169 | 78864.153412831 | 54 | 429112 | 418705.993526578 | 10406.0064734220 | 55 | 403560 | 428125.961991523 | -24565.9619915230 | 56 | 235133 | 350458.526619379 | -115325.526619379 | 57 | 299243 | 397021.64855183 | -97778.6485518303 | 58 | 314073 | 406382.252431307 | -92309.2524313066 | 59 | 368186 | 339837.606963803 | 28348.3930361966 | 60 | 269661 | 351111.722896792 | -81450.7228967922 | 61 | 321896 | 386465.899295022 | -64569.8992950215 | 62 | 408881 | 347837.500523008 | 61043.4994769921 | 63 | 292154 | 364880.167261055 | -72726.1672610548 | 64 | 343466 | 322941.915888204 | 20524.0841117964 | 65 | 332743 | 370049.876495589 | -37306.8764955894 | 66 | 442882 | 372234.99979015 | 70647.0002098501 | 67 | 315688 | 324046.720079697 | -8358.72007969676 | 68 | 375195 | 389284.578437303 | -14089.5784373030 | 69 | 334280 | 345541.306817837 | -11261.3068178374 | 70 | 355864 | 379147.265496153 | -23283.2654961534 | 71 | 315380 | 338547.969803793 | -23167.9698037933 | 72 | 314533 | 331645.820754077 | -17112.8207540773 | 73 | 318056 | 334011.667510752 | -15955.6675107517 | 74 | 315380 | 337455.25370409 | -22075.2537040900 | 75 | 314353 | 338282.676441456 | -23929.6764414557 | 76 | 369448 | 335843.360221783 | 33604.6397782167 | 77 | 315380 | 336605.419800971 | -21225.4198009711 | 78 | 312846 | 338612.676560887 | -25766.6765608868 | 79 | 312075 | 337540.843934649 | -25465.8439346487 | 80 | 315009 | 337719.3149137 | -22710.3149137002 | 81 | 318903 | 338586.541937178 | -19683.5419371777 | 82 | 314887 | 338441.853566383 | -23554.8535663830 | 83 | 314913 | 337185.883874231 | -22272.8838742310 | 84 | 315380 | 338448.737679394 | -23068.7376793936 | 85 | 325506 | 335609.227017943 | -10103.2270179428 | 86 | 315380 | 338448.737679394 | -23068.7376793936 | 87 | 298568 | 331777.476804449 | -33209.476804449 | 88 | 315834 | 338629.274049821 | -22795.2740498207 | 89 | 329784 | 341283.530943773 | -11499.5309437732 | 90 | 312878 | 332468.350380108 | -19590.3503801084 | 91 | 315380 | 338448.737679394 | -23068.7376793936 | 92 | 314987 | 330555.562221279 | -15568.5622212789 | 93 | 325249 | 338067.33224794 | -12818.3322479399 | 94 | 315877 | 338467.32506718 | -22590.3250671797 | 95 | 291650 | 334973.928202939 | -43323.9282029392 | 96 | 305959 | 335594.755206960 | -29635.7552069605 | 97 | 315380 | 342472.271343864 | -27092.2713438643 | 98 | 297765 | 335028.126030116 | -37263.1260301164 | 99 | 315245 | 338268.507298667 | -23023.5072986668 | 100 | 315380 | 338448.737679394 | -23068.7376793936 | 101 | 315380 | 338448.737679394 | -23068.7376793936 | 102 | 315236 | 338254.216343808 | -23018.2163438084 | 103 | 336425 | 338044.727961672 | -1619.72796167245 | 104 | 315380 | 338448.737679394 | -23068.7376793936 | 105 | 315380 | 338448.737679394 | -23068.7376793936 | 106 | 315380 | 338507.172806377 | -23127.1728063769 | 107 | 315380 | 338448.737679394 | -23068.7376793936 | 108 | 306268 | 337915.29669245 | -31647.2966924499 | 109 | 302187 | 341180.756786482 | -38993.7567864821 | 110 | 314882 | 334045.079060742 | -19163.0790607421 | 111 | 315380 | 320992.058784077 | -5612.05878407691 | 112 | 382712 | 318303.935433164 | 64408.064566836 | 113 | 341570 | 325627.66456269 | 15942.3354373103 | 114 | 315380 | 327391.806267069 | -12011.8062670686 | 115 | 315380 | 320734.119626448 | -5354.11962644816 | 116 | 312412 | 330961.527336611 | -18549.5273366113 | 117 | 315380 | 350979.153183858 | -35599.1531838582 | 118 | 309596 | 333304.476566308 | -23708.4765663079 | 119 | 315380 | 274495.423590946 | 40884.5764090538 | 120 | 315547 | 311659.343514829 | 3887.65648517125 | 121 | 315380 | 281705.137725248 | 33674.8622747519 | 122 | 359335 | 284428.073183927 | 74906.926816073 | 123 | 313332 | 278781.734182577 | 34550.2658174232 | 124 | 315380 | 278726.205857769 | 36653.794142231 | 125 | 315380 | 282932.552311677 | 32447.4476883233 | 126 | 315380 | 282613.813861573 | 32766.1861384267 | 127 | 315380 | 282858.429914012 | 32521.570085988 | 128 | 330059 | 282284.984177566 | 47774.0158224341 | 129 | 304485 | 278041.761596925 | 26443.2384030751 | 130 | 315688 | 282879.636612303 | 32808.3633876971 | 131 | 315380 | 282571.609957932 | 32808.3900420678 | 132 | 296656 | 280736.984993503 | 15919.0150064971 | 133 | 315354 | 282857.089232798 | 32496.9107672019 | 134 | 315576 | 281558.039584292 | 34017.9604157081 | 135 | 314551 | 282290.81581859 | 32260.1841814103 | 136 | 312339 | 283567.516471407 | 28771.4835285927 | 137 | 298700 | 283311.474653656 | 15388.5253463435 | 138 | 315380 | 282580.726149139 | 32799.2738508614 | 139 | 315380 | 280303.868893120 | 35076.1311068797 | 140 | 315380 | 282873.933986894 | 32506.0660131063 | 141 | 315380 | 282830.508206718 | 32549.4917932818 | 142 | 315380 | 282860.290142231 | 32519.7098577687 | 143 | 315380 | 282303.993042273 | 33076.0069577274 | 144 | 324385 | 284182.174038002 | 40202.8259619982 | 145 | 296702 | 280290.745402626 | 16411.2545973735 | 146 | 304376 | 283218.630970892 | 21157.3690291085 | 147 | 315380 | 269088.930189127 | 46291.0698108733 | 148 | 298466 | 279094.365691580 | 19371.6343084204 | 149 | 343929 | 284832.521642401 | 59096.4783575987 | 150 | 315380 | 284973.603695805 | 30406.3963041949 | 151 | 331420 | 294465.300929155 | 36954.6990708448 | 152 | 315380 | 281804.829088683 | 33575.1709113171 | 153 | 320398 | 283621.275321732 | 36776.7246782681 | 154 | 310670 | 284056.83735358 | 26613.1626464199 | 155 | 313491 | 282157.643657088 | 31333.3563429123 | 156 | 331323 | 284459.175135717 | 46863.824864283 | 157 | 318098 | 283076.569927666 | 35021.4300723344 | 158 | 325176 | 279172.164704309 | 46003.8352956913 | 159 | 315380 | 290079.912834131 | 25300.0871658690 | 160 | 315380 | 280701.660648711 | 34678.3393512891 | 161 | 315380 | 282872.218244085 | 32507.7817559155 | 162 | 315380 | 280127.864570736 | 35252.1354292638 | 163 | 315394 | 286862.901794641 | 28531.0982053589 | 164 | 346611 | 285683.477226552 | 60927.5227734476 | 165 | 339445 | 283733.605671857 | 55711.3943281434 | 166 | 297141 | 282738.352222342 | 14402.6477776582 | 167 | 315380 | 282850.327635258 | 32529.6723647419 | 168 | 315380 | 282860.290142231 | 32519.7098577687 | 169 | 315380 | 282860.290142231 | 32519.7098577687 | 170 | 315380 | 282365.678583704 | 33014.3214162955 | 171 | 315380 | 282860.290142231 | 32519.7098577687 | 172 | 315380 | 282860.290142231 | 32519.7098577687 | 173 | 315388 | 282436.820387985 | 32951.1796120154 | 174 | 296139 | 282153.808856644 | 13985.1911433558 | 175 | 313880 | 282883.514795407 | 30996.4852045932 | 176 | 295580 | 283313.254984609 | 12266.7450153908 | 177 | 315380 | 282860.290142231 | 32519.7098577687 | 178 | 308256 | 282699.780428827 | 25556.2195711730 | 179 | 303677 | 282563.137914667 | 21113.8620853334 | 180 | 315380 | 282860.290142231 | 32519.7098577687 | 181 | 318690 | 280406.396150678 | 38283.603849322 | 182 | 325699 | 282197.066792654 | 43501.9332073458 | 183 | 315380 | 282447.923924857 | 32932.0760751428 | 184 | 322378 | 285743.830979948 | 36634.1690200522 | 185 | 315380 | 282860.290142231 | 32519.7098577687 | 186 | 315398 | 282865.638725498 | 32532.3612745015 | 187 | 315380 | 282860.290142231 | 32519.7098577687 | 188 | 315380 | 282711.907046688 | 32668.0929533115 | 189 | 315380 | 282860.290142231 | 32519.7098577687 | 190 | 315553 | 282807.172797519 | 32745.8272024807 | 191 | 323361 | 282584.803176177 | 40776.1968238227 | 192 | 307424 | 286460.923851188 | 20963.0761488121 | 193 | 315380 | 282860.290142231 | 32519.7098577687 | 194 | 322340 | 279264.411154068 | 43075.5888459324 | 195 | 315380 | 279905.149705361 | 35474.8502946394 | 196 | 317291 | 284851.831488303 | 32439.1685116966 | 197 | 315380 | 276377.137912151 | 39002.8620878495 | 198 | 238125 | 283527.781560574 | -45402.7815605739 | 199 | 309038 | 283891.11207748 | 25146.8879225197 | 200 | 307930 | 282042.109921024 | 25887.8900789761 | 201 | 292136 | 282936.617472857 | 9199.38252714262 | 202 | 367655 | 274583.16809847 | 93071.83190153 | 203 | 243650 | 274186.439762199 | -30536.4397621989 | 204 | 304252 | 280252.986788380 | 23999.0132116204 | 205 | 296919 | 284016.84174787 | 12902.1582521303 | 206 | 327007 | 277096.965776278 | 49910.0342237223 | 207 | 304555 | 281505.787566893 | 23049.2124331066 | 208 | 231861 | 280724.549264398 | -48863.5492643981 | 209 | 165404 | 282249.399741708 | -116845.399741708 | 210 | 407159 | 258465.170930492 | 148693.829069508 | 211 | 246541 | 275033.045523332 | -28492.0455233315 | 212 | 240897 | 272620.816182501 | -31723.816182501 | 213 | 272713 | 213762.323580354 | 58950.6764196462 | 214 | 306275 | 239189.238392579 | 67085.7616074209 | 215 | 372631 | 256227.924179603 | 116403.075820397 | 216 | 428 | 257564.258039626 | -257136.258039626 | 217 | 263 | -21969.8338981798 | 22232.8338981798 | 218 | 104 | 129505.748567640 | -129401.748567640 | 219 | 122 | -211518.353025776 | 211640.353025776 | 220 | 190 | 144866.704110924 | -144676.704110924 | 221 | 63 | -53723.2948016171 | 53786.2948016171 | 222 | 102 | -212716.141675543 | 212818.141675543 | 223 | 277 | -164235.210940987 | 164512.210940987 | 224 | 103 | 51449.0636211344 | -51346.0636211344 | 225 | 290 | 115923.717401175 | -115633.717401175 | 226 | 83 | -40042.8431092119 | 40125.8431092119 | 227 | 56 | -98731.738398664 | 98787.738398664 | 228 | 73 | 173678.312558966 | -173605.312558966 | 229 | 34 | 79789.852734521 | -79755.852734521 | 230 | 139 | 180582.323467718 | -180443.323467718 | 231 | 12 | 99380.0970008096 | -99368.0970008096 | 232 | 211 | -223764.250789174 | 223975.250789174 | 233 | 74 | -25860.2831023028 | 25934.2831023028 | 234 | 131 | 69441.9358854201 | -69310.9358854201 | 235 | 203 | -16450.9152401901 | 16653.9152401901 | 236 | 56 | -79468.3993138574 | 79524.3993138574 | 237 | 89 | -170877.626249708 | 170966.626249708 | 238 | 88 | 9258.82070805076 | -9170.82070805076 | 239 | 39 | -226784.104979216 | 226823.104979216 | 240 | 58 | -34490.1062344309 | 34548.1062344309 | 241 | 41 | -52034.5727725343 | 52075.5727725343 | 242 | 77 | -76298.8642506317 | 76375.8642506317 | 243 | 6 | -107276.038910319 | 107282.038910319 | 244 | 47 | 18951.4454158887 | -18904.4454158887 | 245 | 51 | -89920.587606071 | 89971.587606071 | 246 | 32 | -7758.09731799426 | 7790.09731799426 | 247 | 54 | 7057.42292501879 | -7003.42292501879 | 248 | 251 | 54400.6403338394 | -54149.6403338394 | 249 | 15 | 15480.0917810509 | -15465.0917810509 | 250 | 73 | -15323.8574365786 | 15396.8574365786 | 251 | 38 | -62774.7165568412 | 62812.7165568412 | 252 | 35 | 183794.286766723 | -183759.286766723 | 253 | 9 | -6506.51111611216 | 6515.51111611216 | 254 | 34 | -31128.9506914681 | 31162.9506914681 | 255 | 29 | -31892.8915029272 | 31921.8915029272 | 256 | 11 | 13092.3657215099 | -13081.3657215099 | 257 | 52 | 18387.6549844214 | -18335.6549844214 | 258 | 29 | -34720.6880450767 | 34749.6880450767 | 259 | 33 | 92652.148356001 | -92619.148356001 | 260 | 15 | -32740.2823298162 | 32755.2823298162 | 261 | 15 | 93751.8358049122 | -93736.8358049122 | 262 | 100 | 15713.6678613108 | -15613.6678613108 | 263 | 13 | 69510.7604234897 | -69497.7604234897 | 264 | 45 | -27718.3294652671 | 27763.3294652671 | 265 | 14 | 473.954845069442 | -459.954845069442 | 266 | 36 | 60911.9536096299 | -60875.9536096299 | 267 | 68 | 30488.0174874022 | -30420.0174874022 | 268 | 43 | 111246.430434004 | -111203.430434004 | 269 | 9 | 98888.547936298 | -98879.547936298 | 270 | 19 | -44091.3268868011 | 44110.3268868011 | 271 | 19 | -625.074874186696 | 644.074874186696 | 272 | 55 | 11421.7896583771 | -11366.7896583771 | 273 | 8 | 17240.6736292006 | -17232.6736292006 | 274 | 28 | -4346.60331713202 | 4374.60331713202 | 275 | 29 | 66247.2491614364 | -66218.2491614364 | 276 | 47 | 68322.7296009797 | -68275.7296009797 | 277 | 22 | 31257.0167415481 | -31235.0167415481 | 278 | 44 | 91057.7207463243 | -91013.7207463243 | 279 | 35 | 47633.1276172119 | -47598.1276172119 | 280 | 8 | 10275.4804851494 | -10267.4804851494 | 281 | 17 | 58041.4153349828 | -58024.4153349828 | 282 | 21 | 68464.5503927448 | -68443.5503927448 | 283 | 92 | 67974.82640078 | -67882.82640078 | 284 | 12 | 27309.0759557184 | -27297.0759557184 | 285 | 112 | 82758.835820639 | -82646.835820639 | 286 | 0 | 47266.1107786785 | -47266.1107786785 | 287 | 10 | 102888.015300807 | -102878.015300807 | 288 | 23 | 42764.0095163302 | -42741.0095163302 | 289 | 0 | 89286.6672857551 | -89286.6672857551 | 290 | 7 | 78339.2431908924 | -78332.2431908924 | 291 | 25 | 88211.5296266852 | -88186.5296266852 | 292 | 0 | 122266.761955558 | -122266.761955558 | 293 | 20 | 86575.043488173 | -86555.043488173 | 294 | 4 | 86721.0630318439 | -86717.0630318439 | 295 | 4 | 86397.8634602392 | -86393.8634602392 | 296 | 10 | 86900.0708955345 | -86890.0708955345 | 297 | 1 | 86752.665769077 | -86751.665769077 | 298 | 4 | 87614.2805730364 | -87610.2805730364 | 299 | 0 | 86429.5738002719 | -86429.5738002719 | 300 | 8 | 87019.2669388662 | -87011.2669388662 | 301 | 0 | 90547.9920783832 | -90547.9920783832 | 302 | 11 | 87831.7032095363 | -87820.7032095363 | 303 | 4 | 89474.6232947689 | -89470.6232947689 | 304 | 15 | 86940.3453190541 | -86925.3453190541 | 305 | 9 | 85500.8979143952 | -85491.8979143952 | 306 | 0 | 92001.3994835032 | -92001.3994835032 | 307 | 7 | 86141.522574072 | -86134.522574072 | 308 | 2 | 75581.2288429532 | -75579.2288429532 | 309 | 0 | 87917.739010875 | -87917.739010875 | 310 | 7 | 86848.3301264028 | -86841.3301264028 | 311 | 46 | 87992.9831698062 | -87946.9831698062 |
Goldfeld-Quandt test for Heteroskedasticity | p-values | Alternative Hypothesis | breakpoint index | greater | 2-sided | less | 11 | 0.999999999990053 | 1.98939031053075e-11 | 9.94695155265375e-12 | 12 | 0.999999999955833 | 8.83330798872256e-11 | 4.41665399436128e-11 | 13 | 1 | 1.69579813478768e-17 | 8.47899067393842e-18 | 14 | 1 | 2.03313096252139e-19 | 1.01656548126070e-19 | 15 | 1 | 7.84899398222554e-19 | 3.92449699111277e-19 | 16 | 1 | 1.80089072423458e-18 | 9.00445362117292e-19 | 17 | 1 | 3.30384233612051e-18 | 1.65192116806025e-18 | 18 | 1 | 4.9285667247331e-18 | 2.46428336236655e-18 | 19 | 1 | 3.89209491805206e-23 | 1.94604745902603e-23 | 20 | 1 | 1.2735024826007e-23 | 6.3675124130035e-24 | 21 | 1 | 1.48134077801267e-23 | 7.40670389006335e-24 | 22 | 1 | 2.17885244074118e-23 | 1.08942622037059e-23 | 23 | 1 | 5.76415903120445e-23 | 2.88207951560222e-23 | 24 | 1 | 2.12792775360289e-23 | 1.06396387680145e-23 | 25 | 1 | 3.1896692467638e-23 | 1.5948346233819e-23 | 26 | 1 | 1.99414847366742e-27 | 9.97074236833708e-28 | 27 | 1 | 5.52519507313979e-27 | 2.76259753656989e-27 | 28 | 1 | 2.08136686241564e-28 | 1.04068343120782e-28 | 29 | 1 | 2.68013765219201e-29 | 1.34006882609601e-29 | 30 | 1 | 8.00510788480518e-30 | 4.00255394240259e-30 | 31 | 1 | 7.63310878514441e-35 | 3.81655439257221e-35 | 32 | 1 | 1.46935006810636e-34 | 7.3467503405318e-35 | 33 | 1 | 1.57846601818602e-34 | 7.89233009093009e-35 | 34 | 1 | 1.24578289399709e-35 | 6.22891446998547e-36 | 35 | 1 | 1.82404474364608e-35 | 9.12022371823038e-36 | 36 | 1 | 3.9859028703892e-35 | 1.9929514351946e-35 | 37 | 1 | 5.19989514115839e-35 | 2.59994757057919e-35 | 38 | 1 | 7.01370556223792e-35 | 3.50685278111896e-35 | 39 | 1 | 1.51696414471907e-34 | 7.58482072359534e-35 | 40 | 1 | 2.72054370657526e-34 | 1.36027185328763e-34 | 41 | 1 | 3.8730077791703e-35 | 1.93650388958515e-35 | 42 | 1 | 9.79480823416722e-35 | 4.89740411708361e-35 | 43 | 1 | 2.61360730910108e-34 | 1.30680365455054e-34 | 44 | 1 | 4.95041830311730e-34 | 2.47520915155865e-34 | 45 | 1 | 1.26770580981142e-33 | 6.3385290490571e-34 | 46 | 1 | 3.06876612112828e-33 | 1.53438306056414e-33 | 47 | 1 | 6.68813127489034e-35 | 3.34406563744517e-35 | 48 | 1 | 7.65985145516956e-35 | 3.82992572758478e-35 | 49 | 1 | 1.81075281041119e-34 | 9.05376405205597e-35 | 50 | 1 | 1.09998936850538e-34 | 5.49994684252688e-35 | 51 | 1 | 1.60982078328348e-34 | 8.04910391641739e-35 | 52 | 1 | 2.59966553901452e-34 | 1.29983276950726e-34 | 53 | 1 | 2.55448495100293e-34 | 1.27724247550147e-34 | 54 | 1 | 6.4281304738404e-34 | 3.2140652369202e-34 | 55 | 1 | 1.42648742213811e-33 | 7.13243711069057e-34 | 56 | 1 | 1.74807036404674e-33 | 8.7403518202337e-34 | 57 | 1 | 3.93197405757291e-33 | 1.96598702878646e-33 | 58 | 1 | 6.81062977083531e-33 | 3.40531488541766e-33 | 59 | 1 | 1.47544639510642e-32 | 7.37723197553212e-33 | 60 | 1 | 1.96120344848865e-32 | 9.80601724244327e-33 | 61 | 1 | 5.57182742302002e-32 | 2.78591371151001e-32 | 62 | 1 | 1.23908412123841e-31 | 6.19542060619203e-32 | 63 | 1 | 3.07033974092692e-31 | 1.53516987046346e-31 | 64 | 1 | 7.02253006055957e-31 | 3.51126503027978e-31 | 65 | 1 | 1.76063218238479e-30 | 8.80316091192394e-31 | 66 | 1 | 1.35142352584699e-30 | 6.75711762923495e-31 | 67 | 1 | 2.99839356818089e-30 | 1.49919678409044e-30 | 68 | 1 | 3.84843633451117e-30 | 1.92421816725558e-30 | 69 | 1 | 1.01260721115639e-29 | 5.06303605578196e-30 | 70 | 1 | 2.33340505788728e-29 | 1.16670252894364e-29 | 71 | 1 | 5.37467128266573e-29 | 2.68733564133287e-29 | 72 | 1 | 1.24726339021220e-28 | 6.23631695106101e-29 | 73 | 1 | 3.07495870094555e-28 | 1.53747935047278e-28 | 74 | 1 | 7.24251720941003e-28 | 3.62125860470502e-28 | 75 | 1 | 1.70876784398862e-27 | 8.54383921994312e-28 | 76 | 1 | 4.43934953817923e-27 | 2.21967476908961e-27 | 77 | 1 | 1.05024688619083e-26 | 5.25123443095414e-27 | 78 | 1 | 2.44099949225698e-26 | 1.22049974612849e-26 | 79 | 1 | 5.67964543754471e-26 | 2.83982271877235e-26 | 80 | 1 | 1.32330149552607e-25 | 6.61650747763036e-26 | 81 | 1 | 3.11597615709183e-25 | 1.55798807854591e-25 | 82 | 1 | 7.0971498250134e-25 | 3.5485749125067e-25 | 83 | 1 | 1.64908128122486e-24 | 8.24540640612432e-25 | 84 | 1 | 3.71999405780352e-24 | 1.85999702890176e-24 | 85 | 1 | 8.79638788348072e-24 | 4.39819394174036e-24 | 86 | 1 | 1.95862067803258e-23 | 9.7931033901629e-24 | 87 | 1 | 4.01142374959023e-23 | 2.00571187479511e-23 | 88 | 1 | 8.84908958287088e-23 | 4.42454479143544e-23 | 89 | 1 | 2.04882781146379e-22 | 1.02441390573189e-22 | 90 | 1 | 4.42207408135864e-22 | 2.21103704067932e-22 | 91 | 1 | 9.48960010756933e-22 | 4.74480005378466e-22 | 92 | 1 | 2.02691260575919e-21 | 1.01345630287960e-21 | 93 | 1 | 4.49294051709747e-21 | 2.24647025854874e-21 | 94 | 1 | 9.36496769753766e-21 | 4.68248384876883e-21 | 95 | 1 | 1.66523713893369e-20 | 8.32618569466846e-21 | 96 | 1 | 3.39878737777811e-20 | 1.69939368888906e-20 | 97 | 1 | 6.04841540515661e-20 | 3.02420770257831e-20 | 98 | 1 | 1.08158609594109e-19 | 5.40793047970543e-20 | 99 | 1 | 2.15312738425364e-19 | 1.07656369212682e-19 | 100 | 1 | 4.21770937559499e-19 | 2.10885468779749e-19 | 101 | 1 | 8.14840627927652e-19 | 4.07420313963826e-19 | 102 | 1 | 1.53158685756049e-18 | 7.65793428780243e-19 | 103 | 1 | 3.17372000663903e-18 | 1.58686000331952e-18 | 104 | 1 | 5.87165451136821e-18 | 2.93582725568411e-18 | 105 | 1 | 1.06394625176328e-17 | 5.31973125881638e-18 | 106 | 1 | 1.82305824722392e-17 | 9.11529123611962e-18 | 107 | 1 | 3.13062898853754e-17 | 1.56531449426877e-17 | 108 | 1 | 4.81901349762827e-17 | 2.40950674881413e-17 | 109 | 1 | 6.68116597791256e-17 | 3.34058298895628e-17 | 110 | 1 | 1.03887848467059e-16 | 5.19439242335297e-17 | 111 | 1 | 2.08476892264046e-16 | 1.04238446132023e-16 | 112 | 1 | 2.30653029965826e-16 | 1.15326514982913e-16 | 113 | 1 | 4.17615345881021e-16 | 2.08807672940510e-16 | 114 | 1 | 7.53973767385175e-16 | 3.76986883692588e-16 | 115 | 1 | 1.26335651560587e-15 | 6.31678257802934e-16 | 116 | 1 | 1.89408842144253e-15 | 9.47044210721264e-16 | 117 | 1 | 2.34748210018831e-18 | 1.17374105009416e-18 | 118 | 1 | 1.89503876689227e-22 | 9.47519383446133e-23 | 119 | 1 | 1.76394160986471e-29 | 8.81970804932355e-30 | 120 | 1 | 5.62619312867788e-39 | 2.81309656433894e-39 | 121 | 1 | 1.55140664906424e-38 | 7.7570332453212e-39 | 122 | 1 | 1.00208374930301e-38 | 5.01041874651507e-39 | 123 | 1 | 2.12388968626785e-39 | 1.06194484313393e-39 | 124 | 1 | 5.32885795657431e-39 | 2.66442897828716e-39 | 125 | 1 | 1.48629567898835e-38 | 7.43147839494174e-39 | 126 | 1 | 4.10039886603301e-38 | 2.05019943301650e-38 | 127 | 1 | 1.12507215845812e-37 | 5.62536079229059e-38 | 128 | 1 | 2.02487569746680e-37 | 1.01243784873340e-37 | 129 | 1 | 5.98742751182013e-37 | 2.99371375591007e-37 | 130 | 1 | 1.60790872672705e-36 | 8.03954363363526e-37 | 131 | 1 | 4.28194955958485e-36 | 2.14097477979242e-36 | 132 | 1 | 1.25150504700851e-35 | 6.25752523504254e-36 | 133 | 1 | 3.28360824793584e-35 | 1.64180412396792e-35 | 134 | 1 | 8.52347298730114e-35 | 4.26173649365057e-35 | 135 | 1 | 2.21488187913615e-34 | 1.10744093956807e-34 | 136 | 1 | 6.36509945875317e-34 | 3.18254972937658e-34 | 137 | 1 | 1.79380805941476e-33 | 8.9690402970738e-34 | 138 | 1 | 4.55205771484647e-33 | 2.27602885742323e-33 | 139 | 1 | 1.13130544641745e-32 | 5.65652723208724e-33 | 140 | 1 | 2.81995884713614e-32 | 1.40997942356807e-32 | 141 | 1 | 6.97174725844981e-32 | 3.48587362922491e-32 | 142 | 1 | 1.70917075031789e-31 | 8.54585375158947e-32 | 143 | 1 | 4.14522578933098e-31 | 2.07261289466549e-31 | 144 | 1 | 1.12758812905472e-30 | 5.6379406452736e-31 | 145 | 1 | 2.36658840034269e-30 | 1.18329420017134e-30 | 146 | 1 | 5.3524755035238e-30 | 2.6762377517619e-30 | 147 | 1 | 1.19441465375059e-29 | 5.97207326875295e-30 | 148 | 1 | 1.64017469887036e-29 | 8.20087349435178e-30 | 149 | 1 | 4.22762074317802e-29 | 2.11381037158901e-29 | 150 | 1 | 9.91810746624762e-29 | 4.95905373312381e-29 | 151 | 1 | 2.60952571928691e-28 | 1.30476285964345e-28 | 152 | 1 | 5.93322151167451e-28 | 2.96661075583725e-28 | 153 | 1 | 1.44134734109253e-27 | 7.20673670546265e-28 | 154 | 1 | 3.74410813215030e-27 | 1.87205406607515e-27 | 155 | 1 | 7.03516458984806e-27 | 3.51758229492403e-27 | 156 | 1 | 1.78784535581176e-26 | 8.93922677905879e-27 | 157 | 1 | 4.01572634625179e-26 | 2.00786317312590e-26 | 158 | 1 | 8.25618606188832e-26 | 4.12809303094416e-26 | 159 | 1 | 1.8124639978962e-25 | 9.062319989481e-26 | 160 | 1 | 3.82596953385622e-25 | 1.91298476692811e-25 | 161 | 1 | 8.08646590692327e-25 | 4.04323295346164e-25 | 162 | 1 | 1.66850696707814e-24 | 8.3425348353907e-25 | 163 | 1 | 3.52552572325634e-24 | 1.76276286162817e-24 | 164 | 1 | 6.99330118200573e-24 | 3.49665059100287e-24 | 165 | 1 | 1.33450328367476e-23 | 6.6725164183738e-24 | 166 | 1 | 3.15200162208959e-23 | 1.57600081104480e-23 | 167 | 1 | 6.36090629732608e-23 | 3.18045314866304e-23 | 168 | 1 | 1.26915800518335e-22 | 6.34579002591677e-23 | 169 | 1 | 2.50275995912969e-22 | 1.25137997956484e-22 | 170 | 1 | 4.86409803135157e-22 | 2.43204901567579e-22 | 171 | 1 | 9.35872710676737e-22 | 4.67936355338368e-22 | 172 | 1 | 1.77750274856971e-21 | 8.88751374284853e-22 | 173 | 1 | 3.32557048950815e-21 | 1.66278524475407e-21 | 174 | 1 | 7.34405609862106e-21 | 3.67202804931053e-21 | 175 | 1 | 1.38165280101166e-20 | 6.9082640050583e-21 | 176 | 1 | 3.13281947206285e-20 | 1.56640973603143e-20 | 177 | 1 | 5.61206207138304e-20 | 2.80603103569152e-20 | 178 | 1 | 1.07381232740821e-19 | 5.36906163704104e-20 | 179 | 1 | 2.00859085262147e-19 | 1.00429542631073e-19 | 180 | 1 | 3.43638281213137e-19 | 1.71819140606569e-19 | 181 | 1 | 4.76779504582041e-19 | 2.38389752291020e-19 | 182 | 1 | 5.97480696060416e-19 | 2.98740348030208e-19 | 183 | 1 | 9.52201372464865e-19 | 4.76100686232432e-19 | 184 | 1 | 2.12815174634930e-18 | 1.06407587317465e-18 | 185 | 1 | 3.32669333031092e-18 | 1.66334666515546e-18 | 186 | 1 | 5.06802648950115e-18 | 2.53401324475058e-18 | 187 | 1 | 7.50956760875717e-18 | 3.75478380437859e-18 | 188 | 1 | 1.07910260227570e-17 | 5.39551301137852e-18 | 189 | 1 | 1.49966993292696e-17 | 7.4983496646348e-18 | 190 | 1 | 1.99509210331674e-17 | 9.97546051658369e-18 | 191 | 1 | 1.98144520757703e-17 | 9.90722603788514e-18 | 192 | 1 | 3.49953644740791e-17 | 1.74976822370396e-17 | 193 | 1 | 4.10678115369672e-17 | 2.05339057684836e-17 | 194 | 1 | 3.59964631412078e-17 | 1.79982315706039e-17 | 195 | 1 | 3.63330805660398e-17 | 1.81665402830199e-17 | 196 | 1 | 7.04361773091049e-17 | 3.52180886545525e-17 | 197 | 1 | 6.08642514752176e-17 | 3.04321257376088e-17 | 198 | 1 | 1.04682726248411e-16 | 5.23413631242053e-17 | 199 | 1 | 8.69748321049748e-17 | 4.34874160524874e-17 | 200 | 1 | 6.52178737833093e-17 | 3.26089368916546e-17 | 201 | 1 | 7.05195278182216e-17 | 3.52597639091108e-17 | 202 | 1 | 9.27040242905078e-18 | 4.63520121452539e-18 | 203 | 1 | 1.29656673432831e-17 | 6.48283367164153e-18 | 204 | 1 | 1.62276864634414e-17 | 8.11384323172072e-18 | 205 | 1 | 7.8457829942043e-18 | 3.92289149710215e-18 | 206 | 1 | 2.98383333358854e-18 | 1.49191666679427e-18 | 207 | 1 | 4.08287225134448e-19 | 2.04143612567224e-19 | 208 | 1 | 8.78355424951752e-19 | 4.39177712475876e-19 | 209 | 1 | 1.95391902186785e-19 | 9.76959510933923e-20 | 210 | 1 | 2.07686049823586e-34 | 1.03843024911793e-34 | 211 | 1 | 1.15109607494291e-34 | 5.75548037471455e-35 | 212 | 1 | 1.83702480680389e-34 | 9.18512403401944e-35 | 213 | 1 | 7.35313604743165e-40 | 3.67656802371583e-40 | 214 | 1 | 1.1127496807936e-216 | 5.563748403968e-217 | 215 | 1 | 2.90768190688507e-279 | 1.45384095344253e-279 | 216 | 1 | 1.18972806152775e-276 | 5.94864030763873e-277 | 217 | 1 | 2.91253161364289e-273 | 1.45626580682144e-273 | 218 | 1 | 1.91372013442228e-270 | 9.5686006721114e-271 | 219 | 1 | 1.27334407601447e-268 | 6.36672038007235e-269 | 220 | 1 | 3.50002609375744e-268 | 1.75001304687872e-268 | 221 | 1 | 6.02758070436885e-265 | 3.01379035218442e-265 | 222 | 1 | 1.03972517295265e-261 | 5.19862586476324e-262 | 223 | 1 | 5.38029126669854e-259 | 2.69014563334927e-259 | 224 | 1 | 3.33234892714785e-257 | 1.66617446357392e-257 | 225 | 1 | 7.70481364831399e-256 | 3.85240682415699e-256 | 226 | 1 | 2.16616958686197e-252 | 1.08308479343098e-252 | 227 | 1 | 1.80325354602916e-250 | 9.0162677301458e-251 | 228 | 1 | 1.49216305664019e-247 | 7.46081528320096e-248 | 229 | 1 | 5.83093285103614e-246 | 2.91546642551807e-246 | 230 | 1 | 7.2671500379413e-246 | 3.63357501897065e-246 | 231 | 1 | 3.3823546155305e-243 | 1.69117730776525e-243 | 232 | 1 | 1.11341432104947e-239 | 5.56707160524733e-240 | 233 | 1 | 1.08244874681018e-238 | 5.41224373405088e-239 | 234 | 1 | 5.17844883504777e-236 | 2.58922441752388e-236 | 235 | 1 | 4.99808337676118e-235 | 2.49904168838059e-235 | 236 | 1 | 5.72040719935368e-235 | 2.86020359967684e-235 | 237 | 1 | 4.11870497683385e-232 | 2.05935248841692e-232 | 238 | 1 | 1.91130059081844e-228 | 9.55650295409222e-229 | 239 | 1 | 5.69374429874012e-225 | 2.84687214937006e-225 | 240 | 1 | 3.00098594790385e-221 | 1.50049297395193e-221 | 241 | 1 | 1.38307788644446e-217 | 6.91538943222228e-218 | 242 | 1 | 6.67645750565103e-214 | 3.33822875282551e-214 | 243 | 1 | 2.51944396139757e-210 | 1.25972198069878e-210 | 244 | 1 | 4.14537726313617e-207 | 2.07268863156808e-207 | 245 | 1 | 2.08180028615966e-203 | 1.04090014307983e-203 | 246 | 1 | 7.43622160292219e-200 | 3.71811080146109e-200 | 247 | 1 | 3.67585511760638e-196 | 1.83792755880319e-196 | 248 | 1 | 1.53948415897422e-194 | 7.69742079487108e-195 | 249 | 1 | 7.28596764641777e-191 | 3.64298382320889e-191 | 250 | 1 | 4.15119938676423e-188 | 2.07559969338212e-188 | 251 | 1 | 1.00699402229711e-184 | 5.03497011148555e-185 | 252 | 1 | 3.60713159131209e-181 | 1.80356579565605e-181 | 253 | 1 | 1.93729460080941e-177 | 9.68647300404706e-178 | 254 | 1 | 9.89066508342692e-174 | 4.94533254171346e-174 | 255 | 1 | 5.03975668347157e-170 | 2.51987834173579e-170 | 256 | 1 | 1.89446872212687e-166 | 9.47234361063435e-167 | 257 | 1 | 7.40537128836771e-163 | 3.70268564418386e-163 | 258 | 1 | 4.10150082226802e-159 | 2.05075041113401e-159 | 259 | 1 | 1.53395860289371e-155 | 7.66979301446854e-156 | 260 | 1 | 7.7826901449839e-152 | 3.89134507249195e-152 | 261 | 1 | 3.66825947998316e-148 | 1.83412973999158e-148 | 262 | 1 | 7.96300851839794e-146 | 3.98150425919897e-146 | 263 | 1 | 3.39133907922023e-142 | 1.69566953961012e-142 | 264 | 1 | 9.57408378461819e-139 | 4.78704189230909e-139 | 265 | 1 | 4.53600751629864e-135 | 2.26800375814932e-135 | 266 | 1 | 1.73028912356001e-131 | 8.65144561780004e-132 | 267 | 1 | 2.33040494347991e-128 | 1.16520247173996e-128 | 268 | 1 | 5.6977850825367e-125 | 2.84889254126835e-125 | 269 | 1 | 2.07089896325101e-121 | 1.03544948162550e-121 | 270 | 1 | 1.18759103771437e-117 | 5.93795518857185e-118 | 271 | 1 | 6.66383575448994e-114 | 3.33191787724497e-114 | 272 | 1 | 3.43791957875374e-110 | 1.71895978937687e-110 | 273 | 1 | 1.77898018446027e-106 | 8.89490092230134e-107 | 274 | 1 | 9.33141053638371e-103 | 4.66570526819185e-103 | 275 | 1 | 4.09016976596085e-99 | 2.04508488298042e-99 | 276 | 1 | 1.69935620369548e-95 | 8.49678101847738e-96 | 277 | 1 | 8.4392664092729e-92 | 4.21963320463645e-92 | 278 | 1 | 3.58721837301722e-88 | 1.79360918650861e-88 | 279 | 1 | 1.5204371295568e-84 | 7.602185647784e-85 | 280 | 1 | 6.71236211737688e-81 | 3.35618105868844e-81 | 281 | 1 | 2.54261213989410e-77 | 1.27130606994705e-77 | 282 | 1 | 1.12392999308806e-73 | 5.6196499654403e-74 | 283 | 1 | 5.99426573254061e-72 | 2.99713286627030e-72 | 284 | 1 | 2.10915530987952e-68 | 1.05457765493976e-68 | 285 | 1 | 2.01382046930686e-71 | 1.00691023465343e-71 | 286 | 1 | 2.64675416701645e-67 | 1.32337708350822e-67 | 287 | 1 | 1.89075117361492e-63 | 9.45375586807462e-64 | 288 | 1 | 1.16055776511553e-59 | 5.80278882557767e-60 | 289 | 1 | 1.47411172583823e-55 | 7.37055862919115e-56 | 290 | 1 | 6.63037217549785e-53 | 3.31518608774892e-53 | 291 | 1 | 1.00302228723831e-48 | 5.01511143619157e-49 | 292 | 1 | 1.43468717661184e-44 | 7.17343588305918e-45 | 293 | 1 | 1.70378691837838e-40 | 8.51893459189192e-41 | 294 | 1 | 1.07728949048304e-36 | 5.3864474524152e-37 | 295 | 1 | 1.21659675344931e-32 | 6.08298376724653e-33 | 296 | 1 | 1.3508890308322e-28 | 6.754445154161e-29 | 297 | 1 | 1.94196574155904e-24 | 9.70982870779522e-25 | 298 | 1 | 3.96898224860111e-21 | 1.98449112430055e-21 | 299 | 1 | 6.35197411366206e-17 | 3.17598705683103e-17 | 300 | 0.999999999999503 | 9.94709982515159e-13 | 4.97354991257579e-13 |
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity | Description | # significant tests | % significant tests | OK/NOK | 1% type I error level | 290 | 1 | NOK | 5% type I error level | 290 | 1 | NOK | 10% type I error level | 290 | 1 | NOK |
| | Charts produced by software: | | http://www.freestatistics.org/blog/date/2010/Dec/01/t1291216977cah4z8nchqh8wkb/10jmd31291217005.png (open in new window) | http://www.freestatistics.org/blog/date/2010/Dec/01/t1291216977cah4z8nchqh8wkb/10jmd31291217005.ps (open in new window) |
| http://www.freestatistics.org/blog/date/2010/Dec/01/t1291216977cah4z8nchqh8wkb/1ndxd1291217005.png (open in new window) | http://www.freestatistics.org/blog/date/2010/Dec/01/t1291216977cah4z8nchqh8wkb/1ndxd1291217005.ps (open in new window) |
| http://www.freestatistics.org/blog/date/2010/Dec/01/t1291216977cah4z8nchqh8wkb/2ndxd1291217005.png (open in new window) | http://www.freestatistics.org/blog/date/2010/Dec/01/t1291216977cah4z8nchqh8wkb/2ndxd1291217005.ps (open in new window) |
| http://www.freestatistics.org/blog/date/2010/Dec/01/t1291216977cah4z8nchqh8wkb/3ndxd1291217005.png (open in new window) | http://www.freestatistics.org/blog/date/2010/Dec/01/t1291216977cah4z8nchqh8wkb/3ndxd1291217005.ps (open in new window) |
| http://www.freestatistics.org/blog/date/2010/Dec/01/t1291216977cah4z8nchqh8wkb/4fmef1291217005.png (open in new window) | http://www.freestatistics.org/blog/date/2010/Dec/01/t1291216977cah4z8nchqh8wkb/4fmef1291217005.ps (open in new window) |
| http://www.freestatistics.org/blog/date/2010/Dec/01/t1291216977cah4z8nchqh8wkb/5fmef1291217005.png (open in new window) | http://www.freestatistics.org/blog/date/2010/Dec/01/t1291216977cah4z8nchqh8wkb/5fmef1291217005.ps (open in new window) |
| http://www.freestatistics.org/blog/date/2010/Dec/01/t1291216977cah4z8nchqh8wkb/6fmef1291217005.png (open in new window) | http://www.freestatistics.org/blog/date/2010/Dec/01/t1291216977cah4z8nchqh8wkb/6fmef1291217005.ps (open in new window) |
| http://www.freestatistics.org/blog/date/2010/Dec/01/t1291216977cah4z8nchqh8wkb/78vd01291217005.png (open in new window) | http://www.freestatistics.org/blog/date/2010/Dec/01/t1291216977cah4z8nchqh8wkb/78vd01291217005.ps (open in new window) |
| http://www.freestatistics.org/blog/date/2010/Dec/01/t1291216977cah4z8nchqh8wkb/8jmd31291217005.png (open in new window) | http://www.freestatistics.org/blog/date/2010/Dec/01/t1291216977cah4z8nchqh8wkb/8jmd31291217005.ps (open in new window) |
| http://www.freestatistics.org/blog/date/2010/Dec/01/t1291216977cah4z8nchqh8wkb/9jmd31291217005.png (open in new window) | http://www.freestatistics.org/blog/date/2010/Dec/01/t1291216977cah4z8nchqh8wkb/9jmd31291217005.ps (open in new window) |
| | Parameters (Session): | par1 = 8 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ; | | Parameters (R input): | par1 = 8 ; 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')
}
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