R version 2.8.0 (2008-10-20)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(32.68
+ ,10967.87
+ ,31.54
+ ,10433.56
+ ,32.43
+ ,10665.78
+ ,26.54
+ ,10666.71
+ ,25.85
+ ,10682.74
+ ,27.6
+ ,10777.22
+ ,25.71
+ ,10052.6
+ ,25.38
+ ,10213.97
+ ,28.57
+ ,10546.82
+ ,27.64
+ ,10767.2
+ ,25.36
+ ,10444.5
+ ,25.9
+ ,10314.68
+ ,26.29
+ ,9042.56
+ ,21.74
+ ,9220.75
+ ,19.2
+ ,9721.84
+ ,19.32
+ ,9978.53
+ ,19.82
+ ,9923.81
+ ,20.36
+ ,9892.56
+ ,24.31
+ ,10500.98
+ ,25.97
+ ,10179.35
+ ,25.61
+ ,10080.48
+ ,24.67
+ ,9492.44
+ ,25.59
+ ,8616.49
+ ,26.09
+ ,8685.4
+ ,28.37
+ ,8160.67
+ ,27.34
+ ,8048.1
+ ,24.46
+ ,8641.21
+ ,27.46
+ ,8526.63
+ ,30.23
+ ,8474.21
+ ,32.33
+ ,7916.13
+ ,29.87
+ ,7977.64
+ ,24.87
+ ,8334.59
+ ,25.48
+ ,8623.36
+ ,27.28
+ ,9098.03
+ ,28.24
+ ,9154.34
+ ,29.58
+ ,9284.73
+ ,26.95
+ ,9492.49
+ ,29.08
+ ,9682.35
+ ,28.76
+ ,9762.12
+ ,29.59
+ ,10124.63
+ ,30.7
+ ,10540.05
+ ,30.52
+ ,10601.61
+ ,32.67
+ ,10323.73
+ ,33.19
+ ,10418.4
+ ,37.13
+ ,10092.96
+ ,35.54
+ ,10364.91
+ ,37.75
+ ,10152.09
+ ,41.84
+ ,10032.8
+ ,42.94
+ ,10204.59
+ ,49.14
+ ,10001.6
+ ,44.61
+ ,10411.75
+ ,40.22
+ ,10673.38
+ ,44.23
+ ,10539.51
+ ,45.85
+ ,10723.78
+ ,53.38
+ ,10682.06
+ ,53.26
+ ,10283.19
+ ,51.8
+ ,10377.18
+ ,55.3
+ ,10486.64
+ ,57.81
+ ,10545.38
+ ,63.96
+ ,10554.27
+ ,63.77
+ ,10532.54
+ ,59.15
+ ,10324.31
+ ,56.12
+ ,10695.25
+ ,57.42
+ ,10827.81
+ ,63.52
+ ,10872.48
+ ,61.71
+ ,10971.19
+ ,63.01
+ ,11145.65
+ ,68.18
+ ,11234.68
+ ,72.03
+ ,11333.88
+ ,69.75
+ ,10997.97
+ ,74.41
+ ,11036.89
+ ,74.33
+ ,11257.35
+ ,64.24
+ ,11533.59
+ ,60.03
+ ,11963.12
+ ,59.44
+ ,12185.15
+ ,62.5
+ ,12377.62
+ ,55.04
+ ,12512.89
+ ,58.34
+ ,12631.48
+ ,61.92
+ ,12268.53
+ ,67.65
+ ,12754.8
+ ,67.68
+ ,13407.75
+ ,70.3
+ ,13480.21
+ ,75.26
+ ,13673.28
+ ,71.44
+ ,13239.71
+ ,76.36
+ ,13557.69
+ ,81.71
+ ,13901.28
+ ,92.6
+ ,13200.58
+ ,90.6
+ ,13406.97
+ ,92.23
+ ,12538.12
+ ,94.09
+ ,12419.57
+ ,102.79
+ ,12193.88
+ ,109.65
+ ,12656.63
+ ,124.05
+ ,12812.48
+ ,132.69
+ ,12056.67
+ ,135.81
+ ,11322.38
+ ,116.07
+ ,11530.75
+ ,101.42
+ ,11114.08
+ ,75.73
+ ,9181.73
+ ,55.48
+ ,8614.55)
+ ,dim=c(2
+ ,99)
+ ,dimnames=list(c('Olieprijs'
+ ,'DowJones')
+ ,1:99))
> y <- array(NA,dim=c(2,99),dimnames=list(c('Olieprijs','DowJones'),1:99))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from package:base :
as.Date.numeric
> 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
Olieprijs DowJones
1 32.68 10967.87
2 31.54 10433.56
3 32.43 10665.78
4 26.54 10666.71
5 25.85 10682.74
6 27.60 10777.22
7 25.71 10052.60
8 25.38 10213.97
9 28.57 10546.82
10 27.64 10767.20
11 25.36 10444.50
12 25.90 10314.68
13 26.29 9042.56
14 21.74 9220.75
15 19.20 9721.84
16 19.32 9978.53
17 19.82 9923.81
18 20.36 9892.56
19 24.31 10500.98
20 25.97 10179.35
21 25.61 10080.48
22 24.67 9492.44
23 25.59 8616.49
24 26.09 8685.40
25 28.37 8160.67
26 27.34 8048.10
27 24.46 8641.21
28 27.46 8526.63
29 30.23 8474.21
30 32.33 7916.13
31 29.87 7977.64
32 24.87 8334.59
33 25.48 8623.36
34 27.28 9098.03
35 28.24 9154.34
36 29.58 9284.73
37 26.95 9492.49
38 29.08 9682.35
39 28.76 9762.12
40 29.59 10124.63
41 30.70 10540.05
42 30.52 10601.61
43 32.67 10323.73
44 33.19 10418.40
45 37.13 10092.96
46 35.54 10364.91
47 37.75 10152.09
48 41.84 10032.80
49 42.94 10204.59
50 49.14 10001.60
51 44.61 10411.75
52 40.22 10673.38
53 44.23 10539.51
54 45.85 10723.78
55 53.38 10682.06
56 53.26 10283.19
57 51.80 10377.18
58 55.30 10486.64
59 57.81 10545.38
60 63.96 10554.27
61 63.77 10532.54
62 59.15 10324.31
63 56.12 10695.25
64 57.42 10827.81
65 63.52 10872.48
66 61.71 10971.19
67 63.01 11145.65
68 68.18 11234.68
69 72.03 11333.88
70 69.75 10997.97
71 74.41 11036.89
72 74.33 11257.35
73 64.24 11533.59
74 60.03 11963.12
75 59.44 12185.15
76 62.50 12377.62
77 55.04 12512.89
78 58.34 12631.48
79 61.92 12268.53
80 67.65 12754.80
81 67.68 13407.75
82 70.30 13480.21
83 75.26 13673.28
84 71.44 13239.71
85 76.36 13557.69
86 81.71 13901.28
87 92.60 13200.58
88 90.60 13406.97
89 92.23 12538.12
90 94.09 12419.57
91 102.79 12193.88
92 109.65 12656.63
93 124.05 12812.48
94 132.69 12056.67
95 135.81 11322.38
96 116.07 11530.75
97 101.42 11114.08
98 75.73 9181.73
99 55.48 8614.55
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) DowJones
-91.02199 0.01327
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-24.852 -15.487 -2.575 8.879 76.622
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -91.02200 15.36990 -5.922 4.82e-08 ***
DowJones 0.01327 0.00143 9.278 4.86e-15 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 20.05 on 97 degrees of freedom
Multiple R-squared: 0.4702, Adjusted R-squared: 0.4647
F-statistic: 86.08 on 1 and 97 DF, p-value: 4.863e-15
> 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
+ }
[,1] [,2] [,3]
[1,] 9.327890e-03 1.865578e-02 0.9906721
[2,] 1.821574e-03 3.643149e-03 0.9981784
[3,] 3.019532e-04 6.039064e-04 0.9996980
[4,] 4.885762e-05 9.771524e-05 0.9999511
[5,] 6.745274e-06 1.349055e-05 0.9999933
[6,] 1.151332e-06 2.302665e-06 0.9999988
[7,] 2.220620e-07 4.441240e-07 0.9999998
[8,] 3.056270e-08 6.112541e-08 1.0000000
[9,] 8.790757e-09 1.758151e-08 1.0000000
[10,] 1.862253e-09 3.724505e-09 1.0000000
[11,] 2.295927e-09 4.591855e-09 1.0000000
[12,] 2.416426e-09 4.832853e-09 1.0000000
[13,] 1.228831e-09 2.457661e-09 1.0000000
[14,] 4.244147e-10 8.488293e-10 1.0000000
[15,] 1.164611e-10 2.329222e-10 1.0000000
[16,] 2.292223e-11 4.584446e-11 1.0000000
[17,] 4.463572e-12 8.927144e-12 1.0000000
[18,] 1.045095e-12 2.090190e-12 1.0000000
[19,] 8.159073e-13 1.631815e-12 1.0000000
[20,] 3.159577e-13 6.319153e-13 1.0000000
[21,] 2.552639e-13 5.105279e-13 1.0000000
[22,] 7.730918e-14 1.546184e-13 1.0000000
[23,] 1.358579e-14 2.717159e-14 1.0000000
[24,] 3.151427e-15 6.302854e-15 1.0000000
[25,] 1.493965e-15 2.987931e-15 1.0000000
[26,] 1.315891e-15 2.631781e-15 1.0000000
[27,] 3.499047e-16 6.998094e-16 1.0000000
[28,] 6.737142e-17 1.347428e-16 1.0000000
[29,] 1.195759e-17 2.391518e-17 1.0000000
[30,] 2.164074e-18 4.328148e-18 1.0000000
[31,] 4.285315e-19 8.570630e-19 1.0000000
[32,] 1.099803e-19 2.199606e-19 1.0000000
[33,] 2.088651e-20 4.177302e-20 1.0000000
[34,] 5.328151e-21 1.065630e-20 1.0000000
[35,] 1.327618e-21 2.655236e-21 1.0000000
[36,] 4.523246e-22 9.046491e-22 1.0000000
[37,] 2.485774e-22 4.971547e-22 1.0000000
[38,] 1.329383e-22 2.658766e-22 1.0000000
[39,] 1.302087e-22 2.604175e-22 1.0000000
[40,] 1.501432e-22 3.002864e-22 1.0000000
[41,] 1.007487e-21 2.014973e-21 1.0000000
[42,] 2.109094e-21 4.218189e-21 1.0000000
[43,] 9.614389e-21 1.922878e-20 1.0000000
[44,] 2.370895e-19 4.741790e-19 1.0000000
[45,] 4.118268e-18 8.236536e-18 1.0000000
[46,] 6.150580e-16 1.230116e-15 1.0000000
[47,] 3.620591e-15 7.241181e-15 1.0000000
[48,] 6.045481e-15 1.209096e-14 1.0000000
[49,] 2.037098e-14 4.074196e-14 1.0000000
[50,] 7.599272e-14 1.519854e-13 1.0000000
[51,] 1.302835e-12 2.605670e-12 1.0000000
[52,] 1.345043e-11 2.690087e-11 1.0000000
[53,] 6.068384e-11 1.213677e-10 1.0000000
[54,] 3.499324e-10 6.998647e-10 1.0000000
[55,] 1.995403e-09 3.990806e-09 1.0000000
[56,] 1.984478e-08 3.968956e-08 1.0000000
[57,] 1.048602e-07 2.097205e-07 0.9999999
[58,] 2.592171e-07 5.184341e-07 0.9999997
[59,] 3.897295e-07 7.794590e-07 0.9999996
[60,] 5.711166e-07 1.142233e-06 0.9999994
[61,] 1.073240e-06 2.146481e-06 0.9999989
[62,] 1.548804e-06 3.097608e-06 0.9999985
[63,] 2.036437e-06 4.072875e-06 0.9999980
[64,] 2.958578e-06 5.917156e-06 0.9999970
[65,] 4.365733e-06 8.731466e-06 0.9999956
[66,] 6.196376e-06 1.239275e-05 0.9999938
[67,] 9.786367e-06 1.957273e-05 0.9999902
[68,] 1.163759e-05 2.327518e-05 0.9999884
[69,] 9.965093e-06 1.993019e-05 0.9999900
[70,] 9.454576e-06 1.890915e-05 0.9999905
[71,] 9.989500e-06 1.997900e-05 0.9999900
[72,] 9.564250e-06 1.912850e-05 0.9999904
[73,] 1.871296e-05 3.742592e-05 0.9999813
[74,] 3.224546e-05 6.449092e-05 0.9999678
[75,] 4.886824e-05 9.773649e-05 0.9999511
[76,] 5.592963e-05 1.118593e-04 0.9999441
[77,] 7.583189e-05 1.516638e-04 0.9999242
[78,] 1.046616e-04 2.093232e-04 0.9998953
[79,] 1.300095e-04 2.600190e-04 0.9998700
[80,] 2.886880e-04 5.773760e-04 0.9997113
[81,] 7.136478e-04 1.427296e-03 0.9992864
[82,] 2.571007e-03 5.142014e-03 0.9974290
[83,] 4.642378e-03 9.284757e-03 0.9953576
[84,] 1.917949e-02 3.835899e-02 0.9808205
[85,] 5.149553e-02 1.029911e-01 0.9485045
[86,] 1.434826e-01 2.869652e-01 0.8565174
[87,] 2.210458e-01 4.420916e-01 0.7789542
[88,] 4.328008e-01 8.656016e-01 0.5671992
[89,] 6.542372e-01 6.915256e-01 0.3457628
[90,] 5.712331e-01 8.575338e-01 0.4287669
> postscript(file="/var/www/html/rcomp/tmp/17fx71229180856.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/221be1229180856.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3lmpl1229180856.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/45gpn1229180856.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5ahrg1229180856.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> qqline(mysum$resid)
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 99
Frequency = 1
1 2 3 4 5 6
-21.8049556 -15.8564490 -18.0472317 -23.9495697 -24.8522342 -24.3556677
7 8 9 10 11 12
-16.6323840 -19.1032242 -20.3290304 -24.1827359 -22.1815862 -19.9193090
13 14 15 16 17 18
-2.6525315 -9.5665168 -18.7543051 -22.0397229 -20.8137715 -19.8591885
19 20 21 22 23 24
-23.9808869 -18.0539326 -17.1022584 -10.2409344 2.2999923 1.8857871
25 26 27 28 29 30
11.1271991 11.5906265 0.8420406 5.3621339 8.8275720 18.3314270
31 32 33 34 35 36
15.0553950 5.3198624 2.0988504 -2.3984329 -2.1854782 -2.5753174
37 38 39 40 41 42
-7.9615977 -8.3504049 -9.7286860 -13.7079812 -18.1092151 -19.1059104
43 44 45 46 47 48
-13.2693723 -14.0053265 -5.7478262 -10.9456931 -5.9122835 -0.2397042
49 50 51 52 53 54
-1.4187829 7.4742154 -2.4971032 -10.3580583 -4.5720511 -5.3966977
55 56 57 58 59 60
2.6867872 7.8584580 5.1515250 7.1993569 8.9300736 14.9621330
61 62 63 64 65 66
15.0604175 13.2029331 5.2518000 4.7931722 10.3005507 7.1809991
67 68 69 70 71 72
6.1664984 10.1553681 12.6893159 14.8657181 19.0093799 16.0046131
73 74 75 76 77 78
2.2498322 -7.6585942 -11.1941897 -10.6876228 -19.9422033 -18.2154960
79 80 81 82 83 84
-9.8203634 -10.5415399 -19.1740024 -17.5153043 -15.1166974 -13.1846737
85 86 87 88 89 90
-12.4832047 -11.6914948 8.4944505 3.7563456 16.9130790 20.3458410
91 92 93 94 95 96
32.0399924 32.7608477 45.0932394 63.7603102 76.6218825 54.1175095
97 98 99
44.9953268 44.9411481 32.2157296
> postscript(file="/var/www/html/rcomp/tmp/6e1cm1229180856.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 99
Frequency = 1
lag(myerror, k = 1) myerror
0 -21.8049556 NA
1 -15.8564490 -21.8049556
2 -18.0472317 -15.8564490
3 -23.9495697 -18.0472317
4 -24.8522342 -23.9495697
5 -24.3556677 -24.8522342
6 -16.6323840 -24.3556677
7 -19.1032242 -16.6323840
8 -20.3290304 -19.1032242
9 -24.1827359 -20.3290304
10 -22.1815862 -24.1827359
11 -19.9193090 -22.1815862
12 -2.6525315 -19.9193090
13 -9.5665168 -2.6525315
14 -18.7543051 -9.5665168
15 -22.0397229 -18.7543051
16 -20.8137715 -22.0397229
17 -19.8591885 -20.8137715
18 -23.9808869 -19.8591885
19 -18.0539326 -23.9808869
20 -17.1022584 -18.0539326
21 -10.2409344 -17.1022584
22 2.2999923 -10.2409344
23 1.8857871 2.2999923
24 11.1271991 1.8857871
25 11.5906265 11.1271991
26 0.8420406 11.5906265
27 5.3621339 0.8420406
28 8.8275720 5.3621339
29 18.3314270 8.8275720
30 15.0553950 18.3314270
31 5.3198624 15.0553950
32 2.0988504 5.3198624
33 -2.3984329 2.0988504
34 -2.1854782 -2.3984329
35 -2.5753174 -2.1854782
36 -7.9615977 -2.5753174
37 -8.3504049 -7.9615977
38 -9.7286860 -8.3504049
39 -13.7079812 -9.7286860
40 -18.1092151 -13.7079812
41 -19.1059104 -18.1092151
42 -13.2693723 -19.1059104
43 -14.0053265 -13.2693723
44 -5.7478262 -14.0053265
45 -10.9456931 -5.7478262
46 -5.9122835 -10.9456931
47 -0.2397042 -5.9122835
48 -1.4187829 -0.2397042
49 7.4742154 -1.4187829
50 -2.4971032 7.4742154
51 -10.3580583 -2.4971032
52 -4.5720511 -10.3580583
53 -5.3966977 -4.5720511
54 2.6867872 -5.3966977
55 7.8584580 2.6867872
56 5.1515250 7.8584580
57 7.1993569 5.1515250
58 8.9300736 7.1993569
59 14.9621330 8.9300736
60 15.0604175 14.9621330
61 13.2029331 15.0604175
62 5.2518000 13.2029331
63 4.7931722 5.2518000
64 10.3005507 4.7931722
65 7.1809991 10.3005507
66 6.1664984 7.1809991
67 10.1553681 6.1664984
68 12.6893159 10.1553681
69 14.8657181 12.6893159
70 19.0093799 14.8657181
71 16.0046131 19.0093799
72 2.2498322 16.0046131
73 -7.6585942 2.2498322
74 -11.1941897 -7.6585942
75 -10.6876228 -11.1941897
76 -19.9422033 -10.6876228
77 -18.2154960 -19.9422033
78 -9.8203634 -18.2154960
79 -10.5415399 -9.8203634
80 -19.1740024 -10.5415399
81 -17.5153043 -19.1740024
82 -15.1166974 -17.5153043
83 -13.1846737 -15.1166974
84 -12.4832047 -13.1846737
85 -11.6914948 -12.4832047
86 8.4944505 -11.6914948
87 3.7563456 8.4944505
88 16.9130790 3.7563456
89 20.3458410 16.9130790
90 32.0399924 20.3458410
91 32.7608477 32.0399924
92 45.0932394 32.7608477
93 63.7603102 45.0932394
94 76.6218825 63.7603102
95 54.1175095 76.6218825
96 44.9953268 54.1175095
97 44.9411481 44.9953268
98 32.2157296 44.9411481
99 NA 32.2157296
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -15.8564490 -21.8049556
[2,] -18.0472317 -15.8564490
[3,] -23.9495697 -18.0472317
[4,] -24.8522342 -23.9495697
[5,] -24.3556677 -24.8522342
[6,] -16.6323840 -24.3556677
[7,] -19.1032242 -16.6323840
[8,] -20.3290304 -19.1032242
[9,] -24.1827359 -20.3290304
[10,] -22.1815862 -24.1827359
[11,] -19.9193090 -22.1815862
[12,] -2.6525315 -19.9193090
[13,] -9.5665168 -2.6525315
[14,] -18.7543051 -9.5665168
[15,] -22.0397229 -18.7543051
[16,] -20.8137715 -22.0397229
[17,] -19.8591885 -20.8137715
[18,] -23.9808869 -19.8591885
[19,] -18.0539326 -23.9808869
[20,] -17.1022584 -18.0539326
[21,] -10.2409344 -17.1022584
[22,] 2.2999923 -10.2409344
[23,] 1.8857871 2.2999923
[24,] 11.1271991 1.8857871
[25,] 11.5906265 11.1271991
[26,] 0.8420406 11.5906265
[27,] 5.3621339 0.8420406
[28,] 8.8275720 5.3621339
[29,] 18.3314270 8.8275720
[30,] 15.0553950 18.3314270
[31,] 5.3198624 15.0553950
[32,] 2.0988504 5.3198624
[33,] -2.3984329 2.0988504
[34,] -2.1854782 -2.3984329
[35,] -2.5753174 -2.1854782
[36,] -7.9615977 -2.5753174
[37,] -8.3504049 -7.9615977
[38,] -9.7286860 -8.3504049
[39,] -13.7079812 -9.7286860
[40,] -18.1092151 -13.7079812
[41,] -19.1059104 -18.1092151
[42,] -13.2693723 -19.1059104
[43,] -14.0053265 -13.2693723
[44,] -5.7478262 -14.0053265
[45,] -10.9456931 -5.7478262
[46,] -5.9122835 -10.9456931
[47,] -0.2397042 -5.9122835
[48,] -1.4187829 -0.2397042
[49,] 7.4742154 -1.4187829
[50,] -2.4971032 7.4742154
[51,] -10.3580583 -2.4971032
[52,] -4.5720511 -10.3580583
[53,] -5.3966977 -4.5720511
[54,] 2.6867872 -5.3966977
[55,] 7.8584580 2.6867872
[56,] 5.1515250 7.8584580
[57,] 7.1993569 5.1515250
[58,] 8.9300736 7.1993569
[59,] 14.9621330 8.9300736
[60,] 15.0604175 14.9621330
[61,] 13.2029331 15.0604175
[62,] 5.2518000 13.2029331
[63,] 4.7931722 5.2518000
[64,] 10.3005507 4.7931722
[65,] 7.1809991 10.3005507
[66,] 6.1664984 7.1809991
[67,] 10.1553681 6.1664984
[68,] 12.6893159 10.1553681
[69,] 14.8657181 12.6893159
[70,] 19.0093799 14.8657181
[71,] 16.0046131 19.0093799
[72,] 2.2498322 16.0046131
[73,] -7.6585942 2.2498322
[74,] -11.1941897 -7.6585942
[75,] -10.6876228 -11.1941897
[76,] -19.9422033 -10.6876228
[77,] -18.2154960 -19.9422033
[78,] -9.8203634 -18.2154960
[79,] -10.5415399 -9.8203634
[80,] -19.1740024 -10.5415399
[81,] -17.5153043 -19.1740024
[82,] -15.1166974 -17.5153043
[83,] -13.1846737 -15.1166974
[84,] -12.4832047 -13.1846737
[85,] -11.6914948 -12.4832047
[86,] 8.4944505 -11.6914948
[87,] 3.7563456 8.4944505
[88,] 16.9130790 3.7563456
[89,] 20.3458410 16.9130790
[90,] 32.0399924 20.3458410
[91,] 32.7608477 32.0399924
[92,] 45.0932394 32.7608477
[93,] 63.7603102 45.0932394
[94,] 76.6218825 63.7603102
[95,] 54.1175095 76.6218825
[96,] 44.9953268 54.1175095
[97,] 44.9411481 44.9953268
[98,] 32.2157296 44.9411481
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -15.8564490 -21.8049556
2 -18.0472317 -15.8564490
3 -23.9495697 -18.0472317
4 -24.8522342 -23.9495697
5 -24.3556677 -24.8522342
6 -16.6323840 -24.3556677
7 -19.1032242 -16.6323840
8 -20.3290304 -19.1032242
9 -24.1827359 -20.3290304
10 -22.1815862 -24.1827359
11 -19.9193090 -22.1815862
12 -2.6525315 -19.9193090
13 -9.5665168 -2.6525315
14 -18.7543051 -9.5665168
15 -22.0397229 -18.7543051
16 -20.8137715 -22.0397229
17 -19.8591885 -20.8137715
18 -23.9808869 -19.8591885
19 -18.0539326 -23.9808869
20 -17.1022584 -18.0539326
21 -10.2409344 -17.1022584
22 2.2999923 -10.2409344
23 1.8857871 2.2999923
24 11.1271991 1.8857871
25 11.5906265 11.1271991
26 0.8420406 11.5906265
27 5.3621339 0.8420406
28 8.8275720 5.3621339
29 18.3314270 8.8275720
30 15.0553950 18.3314270
31 5.3198624 15.0553950
32 2.0988504 5.3198624
33 -2.3984329 2.0988504
34 -2.1854782 -2.3984329
35 -2.5753174 -2.1854782
36 -7.9615977 -2.5753174
37 -8.3504049 -7.9615977
38 -9.7286860 -8.3504049
39 -13.7079812 -9.7286860
40 -18.1092151 -13.7079812
41 -19.1059104 -18.1092151
42 -13.2693723 -19.1059104
43 -14.0053265 -13.2693723
44 -5.7478262 -14.0053265
45 -10.9456931 -5.7478262
46 -5.9122835 -10.9456931
47 -0.2397042 -5.9122835
48 -1.4187829 -0.2397042
49 7.4742154 -1.4187829
50 -2.4971032 7.4742154
51 -10.3580583 -2.4971032
52 -4.5720511 -10.3580583
53 -5.3966977 -4.5720511
54 2.6867872 -5.3966977
55 7.8584580 2.6867872
56 5.1515250 7.8584580
57 7.1993569 5.1515250
58 8.9300736 7.1993569
59 14.9621330 8.9300736
60 15.0604175 14.9621330
61 13.2029331 15.0604175
62 5.2518000 13.2029331
63 4.7931722 5.2518000
64 10.3005507 4.7931722
65 7.1809991 10.3005507
66 6.1664984 7.1809991
67 10.1553681 6.1664984
68 12.6893159 10.1553681
69 14.8657181 12.6893159
70 19.0093799 14.8657181
71 16.0046131 19.0093799
72 2.2498322 16.0046131
73 -7.6585942 2.2498322
74 -11.1941897 -7.6585942
75 -10.6876228 -11.1941897
76 -19.9422033 -10.6876228
77 -18.2154960 -19.9422033
78 -9.8203634 -18.2154960
79 -10.5415399 -9.8203634
80 -19.1740024 -10.5415399
81 -17.5153043 -19.1740024
82 -15.1166974 -17.5153043
83 -13.1846737 -15.1166974
84 -12.4832047 -13.1846737
85 -11.6914948 -12.4832047
86 8.4944505 -11.6914948
87 3.7563456 8.4944505
88 16.9130790 3.7563456
89 20.3458410 16.9130790
90 32.0399924 20.3458410
91 32.7608477 32.0399924
92 45.0932394 32.7608477
93 63.7603102 45.0932394
94 76.6218825 63.7603102
95 54.1175095 76.6218825
96 44.9953268 54.1175095
97 44.9411481 44.9953268
98 32.2157296 44.9411481
> 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()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/7z7211229180856.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8xoqk1229180856.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/94qti1229180856.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/103iik1229180856.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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="/var/www/html/rcomp/tmp/112d5c1229180856.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
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="/var/www/html/rcomp/tmp/12gnr01229180856.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="/var/www/html/rcomp/tmp/13th751229180856.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
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
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="/var/www/html/rcomp/tmp/14mzfc1229180856.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="/var/www/html/rcomp/tmp/15z45h1229180856.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="/var/www/html/rcomp/tmp/163w0x1229180856.tab")
+ }
>
> system("convert tmp/17fx71229180856.ps tmp/17fx71229180856.png")
> system("convert tmp/221be1229180856.ps tmp/221be1229180856.png")
> system("convert tmp/3lmpl1229180856.ps tmp/3lmpl1229180856.png")
> system("convert tmp/45gpn1229180856.ps tmp/45gpn1229180856.png")
> system("convert tmp/5ahrg1229180856.ps tmp/5ahrg1229180856.png")
> system("convert tmp/6e1cm1229180856.ps tmp/6e1cm1229180856.png")
> system("convert tmp/7z7211229180856.ps tmp/7z7211229180856.png")
> system("convert tmp/8xoqk1229180856.ps tmp/8xoqk1229180856.png")
> system("convert tmp/94qti1229180856.ps tmp/94qti1229180856.png")
> system("convert tmp/103iik1229180856.ps tmp/103iik1229180856.png")
>
>
> proc.time()
user system elapsed
2.907 1.671 4.020