Home » date » 2009 » Dec » 15 »
*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: Tue, 15 Dec 2009 08:08:14 -0700

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Dec/15/t1260889790c2e5s4uudl6gn6s.htm/, Retrieved Wed, 19 Jun 2013 07:14:13 +0000

Original text written by user:

IsPrivate?
No (this computation is public)

User-defined keywords:

System-generated keywords (parent):
t1258546792kjxr91v06m32f9k (pk = 57439)
Estimated Impact
43

Dataseries X:
» Textfile « » CSV « » Correlation Matrix « » Notched Boxplots «

Output produced by software:

Enter (or paste) a matrix (table) containing all data (time) series. Every column represents a different variable and must be delimited by a space or Tab. Every row represents a period in time (or category) and must be delimited by hard returns. The easiest way to enter data is to copy and paste a block of spreadsheet cells. Please, do not use commas or spaces to seperate groups of digits!

 Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 12 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135

 Multiple Linear Regression - Estimated Regression Equation Y[t] = -3.03750610467177e-17 + 1.44281539971909e-16X[t] + 1Y1[t] + 1.80407309583598e-16Y2[t] -1.34871633389605e-16Y3[t] + 1.25242085042886e-17Y4[t] -1.18735169270795e-17M1[t] -4.29542034326534e-17M2[t] + 1.71068599226658e-16M3[t] -2.53276152719436e-17M4[t] -3.45439284701359e-17M5[t] -1.26583126706111e-17M6[t] + 7.21379251138558e-17M7[t] -3.62069740559273e-17M8[t] -2.76317048100518e-17M9[t] -3.29487196717181e-17M10[t] -1.64934388509514e-17M11[t] -4.39099679542517e-18t + e[t]

 Multiple Linear Regression - Ordinary Least Squares Variable Parameter S.D. T-STATH0: parameter = 0 2-tail p-value 1-tail p-value (Intercept) -3.03750610467177e-17 0 -0.0513 0.95932 0.47966 X 1.44281539971909e-16 0 1.6918 0.098658 0.049329 Y1 1 0 8017416243731516 0 0 Y2 1.80407309583598e-16 0 0.7839 0.437815 0.218908 Y3 -1.34871633389605e-16 0 -0.5951 0.555196 0.277598 Y4 1.25242085042886e-17 0 0.1014 0.919765 0.459882 M1 -1.18735169270795e-17 0 -0.1279 0.898895 0.449447 M2 -4.29542034326534e-17 0 -0.4253 0.672957 0.336478 M3 1.71068599226658e-16 0 1.7027 0.096591 0.048296 M4 -2.53276152719436e-17 0 -0.2642 0.793024 0.396512 M5 -3.45439284701359e-17 0 -0.3574 0.722727 0.361363 M6 -1.26583126706111e-17 0 -0.1384 0.890627 0.445314 M7 7.21379251138558e-17 0 0.6876 0.495752 0.247876 M8 -3.62069740559273e-17 0 -0.2724 0.786738 0.393369 M9 -2.76317048100518e-17 0 -0.2365 0.814295 0.407148 M10 -3.29487196717181e-17 0 -0.3279 0.744737 0.372368 M11 -1.64934388509514e-17 0 -0.1703 0.865629 0.432815 t -4.39099679542517e-18 0 -1.3506 0.184613 0.092306

 Multiple Linear Regression - Regression Statistics Multiple R 1 R-squared 1 Adjusted R-squared 1 F-TEST (value) 8.20700486715373e+31 F-TEST (DF numerator) 17 F-TEST (DF denominator) 39 p-value 0 Multiple Linear Regression - Residual Statistics Residual Standard Deviation 1.32513466822904e-16 Sum Squared Residuals 6.84832936687566e-31

 Multiple Linear Regression - Actuals, Interpolation, and Residuals Time or Index Actuals InterpolationForecast ResidualsPrediction Error 1 8.5 8.5 -7.6991384674347e-17 2 8.6 8.6 -6.43709360977525e-17 3 8.5 8.5 6.5756488250235e-16 4 8.2 8.2 -5.67866034633681e-17 5 8.1 8.1 -6.34876583350881e-18 6 7.9 7.9 -6.39936729524118e-17 7 8.6 8.6 -3.07938464271981e-17 8 8.7 8.7 -1.50779618795439e-16 9 8.7 8.7 -7.60896371306682e-17 10 8.5 8.5 -1.12544189552567e-17 11 8.4 8.4 -1.87973185793847e-17 12 8.5 8.5 -9.52569968939496e-18 13 8.7 8.7 -7.26912276957142e-17 14 8.7 8.7 -5.85614221220454e-17 15 8.6 8.6 -1.61756676361002e-16 16 8.5 8.5 2.42587675254507e-17 17 8.3 8.3 3.73154830395712e-17 18 8 8 1.31687079577835e-18 19 8.2 8.2 -3.86450271428722e-17 20 8.1 8.1 -2.49932245985543e-18 21 8.1 8.1 4.20887252772615e-17 22 8 8 2.63137569411794e-17 23 7.9 7.9 2.40516497712711e-17 24 7.9 7.9 1.65027753351442e-17 25 8 8 3.00235215224727e-17 26 8 8 4.87068947155409e-17 27 7.9 7.9 -1.56928722762741e-16 28 8 8 7.01377735925727e-17 29 7.7 7.7 2.37442644288036e-17 30 7.2 7.2 -2.09157096049553e-17 31 7.5 7.5 3.80917633257233e-17 32 7.3 7.3 8.34339014046975e-17 33 7 7 -3.98905873177544e-17 34 7 7 -6.79197201479108e-18 35 7 7 -5.68129043561564e-17 36 7.2 7.2 -4.54277053024157e-18 37 7.3 7.3 1.16970240403136e-16 38 7.1 7.1 1.00760206093542e-16 39 6.8 6.8 -1.52730786210754e-16 40 6.4 6.4 -4.72787562303053e-17 41 6.1 6.1 -9.03881407145042e-17 42 6.5 6.5 1.72786690122292e-17 43 7.7 7.7 2.64171238617347e-17 44 7.9 7.9 -6.47885859535384e-19 45 7.5 7.5 9.18365444334975e-17 46 6.9 6.9 -8.2673659711316e-18 47 6.6 6.6 5.15585731642701e-17 48 6.9 6.9 -2.43430511550802e-18 49 7.7 7.7 2.68885044445246e-18 50 8 8 -2.65347425892852e-17 51 8 8 -1.86148697167854e-16 52 7.7 7.7 9.6688185756501e-18 53 7.3 7.3 3.56771590796384e-17 54 7.4 7.4 6.63138427493595e-17 55 8.1 8.1 4.92998638261233e-18 56 8.3 8.3 7.04929257101326e-17 57 8.2 8.2 -1.79450452623363e-17

 Goldfeld-Quandt test for Heteroskedasticity p-values Alternative Hypothesis breakpoint index greater 2-sided less 21 0.158294841147041 0.316589682294082 0.841705158852959 22 0.472545462453909 0.945090924907818 0.527454537546091 23 0.0113339049571471 0.0226678099142943 0.988666095042853 24 0.00327250994365368 0.00654501988730735 0.996727490056346 25 3.15455655968536e-05 6.30911311937072e-05 0.999968454434403 26 0.800661376100752 0.398677247798496 0.199338623899248 27 4.1744642165599e-13 8.3489284331198e-13 0.999999999999583 28 8.48769212319241e-06 1.69753842463848e-05 0.999991512307877 29 0.000103362618003300 0.000206725236006601 0.999896637381997 30 0 0 1 31 3.04215469987899e-20 6.08430939975798e-20 1 32 0.887069516552428 0.225860966895143 0.112930483447572 33 3.59512425445158e-05 7.19024850890317e-05 0.999964048757455 34 0.980176438260019 0.0396471234799623 0.0198235617399812 35 0.0192602136189009 0.0385204272378017 0.9807397863811 36 0.000106107607578102 0.000212215215156204 0.999893892392422

 Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity Description # significant tests % significant tests OK/NOK 1% type I error level 9 0.5625 NOK 5% type I error level 12 0.75 NOK 10% type I error level 12 0.75 NOK

Charts produced by software:
 http://www.freestatistics.org/blog/date/2009/Dec/15/t1260889790c2e5s4uudl6gn6s/10gzee1260889681.png (opens in new window) http://www.freestatistics.org/blog/date/2009/Dec/15/t1260889790c2e5s4uudl6gn6s/10gzee1260889681.ps (opens in new window) Click here to open pdf file.

 http://www.freestatistics.org/blog/date/2009/Dec/15/t1260889790c2e5s4uudl6gn6s/1aafu1260889681.png (opens in new window) http://www.freestatistics.org/blog/date/2009/Dec/15/t1260889790c2e5s4uudl6gn6s/1aafu1260889681.ps (opens in new window) Click here to open pdf file.

 http://www.freestatistics.org/blog/date/2009/Dec/15/t1260889790c2e5s4uudl6gn6s/2klpx1260889681.png (opens in new window) http://www.freestatistics.org/blog/date/2009/Dec/15/t1260889790c2e5s4uudl6gn6s/2klpx1260889681.ps (opens in new window) Click here to open pdf file.

 http://www.freestatistics.org/blog/date/2009/Dec/15/t1260889790c2e5s4uudl6gn6s/37z491260889681.png (opens in new window) http://www.freestatistics.org/blog/date/2009/Dec/15/t1260889790c2e5s4uudl6gn6s/37z491260889681.ps (opens in new window) Click here to open pdf file.

 http://www.freestatistics.org/blog/date/2009/Dec/15/t1260889790c2e5s4uudl6gn6s/4ji391260889681.png (opens in new window) http://www.freestatistics.org/blog/date/2009/Dec/15/t1260889790c2e5s4uudl6gn6s/4ji391260889681.ps (opens in new window) Click here to open pdf file.

 http://www.freestatistics.org/blog/date/2009/Dec/15/t1260889790c2e5s4uudl6gn6s/5v0ds1260889681.png (opens in new window) http://www.freestatistics.org/blog/date/2009/Dec/15/t1260889790c2e5s4uudl6gn6s/5v0ds1260889681.ps (opens in new window) Click here to open pdf file.

 http://www.freestatistics.org/blog/date/2009/Dec/15/t1260889790c2e5s4uudl6gn6s/69giy1260889681.png (opens in new window) http://www.freestatistics.org/blog/date/2009/Dec/15/t1260889790c2e5s4uudl6gn6s/69giy1260889681.ps (opens in new window) Click here to open pdf file.

 http://www.freestatistics.org/blog/date/2009/Dec/15/t1260889790c2e5s4uudl6gn6s/72sqz1260889681.png (opens in new window) http://www.freestatistics.org/blog/date/2009/Dec/15/t1260889790c2e5s4uudl6gn6s/72sqz1260889681.ps (opens in new window) Click here to open pdf file.

 http://www.freestatistics.org/blog/date/2009/Dec/15/t1260889790c2e5s4uudl6gn6s/8jwcv1260889681.png (opens in new window) http://www.freestatistics.org/blog/date/2009/Dec/15/t1260889790c2e5s4uudl6gn6s/8jwcv1260889681.ps (opens in new window) Click here to open pdf file.

 http://www.freestatistics.org/blog/date/2009/Dec/15/t1260889790c2e5s4uudl6gn6s/9xos81260889681.png (opens in new window) http://www.freestatistics.org/blog/date/2009/Dec/15/t1260889790c2e5s4uudl6gn6s/9xos81260889681.ps (opens in new window) Click here to open pdf file.

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):