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(1.3322
+ ,133.52
+ ,7.4545
+ ,1.4369
+ ,153.2
+ ,7.4583
+ ,1.4975
+ ,163.63
+ ,7.4595
+ ,1.577
+ ,168.45
+ ,7.4599
+ ,1.5553
+ ,166.26
+ ,7.4586
+ ,1.5557
+ ,162.31
+ ,7.4609
+ ,1.575
+ ,161.56
+ ,7.4603
+ ,1.5527
+ ,156.59
+ ,7.4561
+ ,1.4748
+ ,157.97
+ ,7.454
+ ,1.4718
+ ,158.68
+ ,7.4505
+ ,1.457
+ ,163.55
+ ,7.4599
+ ,1.4684
+ ,162.89
+ ,7.4543
+ ,1.4227
+ ,164.95
+ ,7.4534
+ ,1.3896
+ ,159.82
+ ,7.4506
+ ,1.3622
+ ,159.05
+ ,7.4429
+ ,1.3716
+ ,166.76
+ ,7.441
+ ,1.3419
+ ,164.55
+ ,7.4452
+ ,1.3511
+ ,163.22
+ ,7.4519
+ ,1.3516
+ ,160.68
+ ,7.453
+ ,1.3242
+ ,155.24
+ ,7.4494
+ ,1.3074
+ ,157.6
+ ,7.4541
+ ,1.2999
+ ,156.56
+ ,7.4539
+ ,1.3213
+ ,154.82
+ ,7.4549
+ ,1.2881
+ ,151.11
+ ,7.4564
+ ,1.2611
+ ,149.65
+ ,7.4555
+ ,1.2727
+ ,148.99
+ ,7.4601
+ ,1.2811
+ ,148.53
+ ,7.4609
+ ,1.2684
+ ,146.7
+ ,7.4602
+ ,1.265
+ ,145.11
+ ,7.4566
+ ,1.277
+ ,142.7
+ ,7.4565
+ ,1.2271
+ ,143.59
+ ,7.4618
+ ,1.202
+ ,140.96
+ ,7.4612
+ ,1.1938
+ ,140.77
+ ,7.4641
+ ,1.2103
+ ,139.81
+ ,7.4613
+ ,1.1856
+ ,140.58
+ ,7.4541
+ ,1.1786
+ ,139.59
+ ,7.4596
+ ,1.2015
+ ,138.05
+ ,7.462
+ ,1.2256
+ ,136.06
+ ,7.4584
+ ,1.2292
+ ,135.98
+ ,7.4596
+ ,1.2037
+ ,134.75
+ ,7.4584
+ ,1.2165
+ ,132.22
+ ,7.4448
+ ,1.2694
+ ,135.37
+ ,7.4443
+ ,1.2938
+ ,138.84
+ ,7.4499
+ ,1.3201
+ ,138.83
+ ,7.4466
+ ,1.3014
+ ,136.55
+ ,7.4427
+ ,1.3119
+ ,135.63
+ ,7.4405
+ ,1.3408
+ ,139.14
+ ,7.4338
+ ,1.2991
+ ,136.09
+ ,7.4313
+ ,1.249
+ ,135.97
+ ,7.4379
+ ,1.2218
+ ,134.51
+ ,7.4381
+ ,1.2176
+ ,134.54
+ ,7.4365
+ ,1.2266
+ ,134.08
+ ,7.4355
+ ,1.2138
+ ,132.86
+ ,7.4342
+ ,1.2007
+ ,134.48
+ ,7.4405
+ ,1.1985
+ ,129.08
+ ,7.4436
+ ,1.2262
+ ,133.13
+ ,7.4493
+ ,1.2646
+ ,134.78
+ ,7.4511
+ ,1.2613
+ ,134.13
+ ,7.4481
+ ,1.2286
+ ,132.43
+ ,7.4419
+ ,1.1702
+ ,127.84
+ ,7.437
+ ,1.1692
+ ,128.12
+ ,7.4301
+ ,1.1222
+ ,128.94
+ ,7.4273
+ ,1.1139
+ ,132.38
+ ,7.4322
+ ,1.1372
+ ,134.99
+ ,7.4332
+ ,1.1663
+ ,138.05
+ ,7.425
+ ,1.1582
+ ,135.83
+ ,7.4246
+ ,1.0848
+ ,130.12
+ ,7.4255
+ ,1.0807
+ ,128.16
+ ,7.4274
+ ,1.0773
+ ,128.6
+ ,7.4317
+ ,1.0622
+ ,126.12
+ ,7.4324
+ ,1.0183
+ ,124.2
+ ,7.4264
+ ,1.0014
+ ,121.65
+ ,7.428
+ ,0.9811
+ ,121.57
+ ,7.4297
+ ,0.9808
+ ,118.38
+ ,7.4271)
+ ,dim=c(3
+ ,74)
+ ,dimnames=list(c('Dollar'
+ ,'Yen'
+ ,'DeenseKroon')
+ ,1:74))
> y <- array(NA,dim=c(3,74),dimnames=list(c('Dollar','Yen','DeenseKroon'),1:74))
> 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
Dollar Yen DeenseKroon
1 1.3322 133.52 7.4545
2 1.4369 153.20 7.4583
3 1.4975 163.63 7.4595
4 1.5770 168.45 7.4599
5 1.5553 166.26 7.4586
6 1.5557 162.31 7.4609
7 1.5750 161.56 7.4603
8 1.5527 156.59 7.4561
9 1.4748 157.97 7.4540
10 1.4718 158.68 7.4505
11 1.4570 163.55 7.4599
12 1.4684 162.89 7.4543
13 1.4227 164.95 7.4534
14 1.3896 159.82 7.4506
15 1.3622 159.05 7.4429
16 1.3716 166.76 7.4410
17 1.3419 164.55 7.4452
18 1.3511 163.22 7.4519
19 1.3516 160.68 7.4530
20 1.3242 155.24 7.4494
21 1.3074 157.60 7.4541
22 1.2999 156.56 7.4539
23 1.3213 154.82 7.4549
24 1.2881 151.11 7.4564
25 1.2611 149.65 7.4555
26 1.2727 148.99 7.4601
27 1.2811 148.53 7.4609
28 1.2684 146.70 7.4602
29 1.2650 145.11 7.4566
30 1.2770 142.70 7.4565
31 1.2271 143.59 7.4618
32 1.2020 140.96 7.4612
33 1.1938 140.77 7.4641
34 1.2103 139.81 7.4613
35 1.1856 140.58 7.4541
36 1.1786 139.59 7.4596
37 1.2015 138.05 7.4620
38 1.2256 136.06 7.4584
39 1.2292 135.98 7.4596
40 1.2037 134.75 7.4584
41 1.2165 132.22 7.4448
42 1.2694 135.37 7.4443
43 1.2938 138.84 7.4499
44 1.3201 138.83 7.4466
45 1.3014 136.55 7.4427
46 1.3119 135.63 7.4405
47 1.3408 139.14 7.4338
48 1.2991 136.09 7.4313
49 1.2490 135.97 7.4379
50 1.2218 134.51 7.4381
51 1.2176 134.54 7.4365
52 1.2266 134.08 7.4355
53 1.2138 132.86 7.4342
54 1.2007 134.48 7.4405
55 1.1985 129.08 7.4436
56 1.2262 133.13 7.4493
57 1.2646 134.78 7.4511
58 1.2613 134.13 7.4481
59 1.2286 132.43 7.4419
60 1.1702 127.84 7.4370
61 1.1692 128.12 7.4301
62 1.1222 128.94 7.4273
63 1.1139 132.38 7.4322
64 1.1372 134.99 7.4332
65 1.1663 138.05 7.4250
66 1.1582 135.83 7.4246
67 1.0848 130.12 7.4255
68 1.0807 128.16 7.4274
69 1.0773 128.60 7.4317
70 1.0622 126.12 7.4324
71 1.0183 124.20 7.4264
72 1.0014 121.65 7.4280
73 0.9811 121.57 7.4297
74 0.9808 118.38 7.4271
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Yen DeenseKroon
-10.701400 0.008205 1.449960
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.10202 -0.05618 -0.00945 0.05228 0.15828
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -1.070e+01 6.290e+00 -1.701 0.0933 .
Yen 8.205e-03 7.695e-04 10.663 <2e-16 ***
DeenseKroon 1.450e+00 8.537e-01 1.699 0.0938 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.06881 on 71 degrees of freedom
Multiple R-squared: 0.7594, Adjusted R-squared: 0.7526
F-statistic: 112 on 2 and 71 DF, p-value: < 2.2e-16
> 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,] 0.1176197 2.352394e-01 8.823803e-01
[2,] 0.1146405 2.292809e-01 8.853595e-01
[3,] 0.2314222 4.628443e-01 7.685778e-01
[4,] 0.1856434 3.712868e-01 8.143566e-01
[5,] 0.1266167 2.532334e-01 8.733833e-01
[6,] 0.2734952 5.469905e-01 7.265048e-01
[7,] 0.2557136 5.114272e-01 7.442864e-01
[8,] 0.3443875 6.887751e-01 6.556125e-01
[9,] 0.3146860 6.293720e-01 6.853140e-01
[10,] 0.2367913 4.735826e-01 7.632087e-01
[11,] 0.1706968 3.413936e-01 8.293032e-01
[12,] 0.1707151 3.414302e-01 8.292849e-01
[13,] 0.2904755 5.809509e-01 7.095245e-01
[14,] 0.3816431 7.632861e-01 6.183569e-01
[15,] 0.3595462 7.190923e-01 6.404538e-01
[16,] 0.5693315 8.613369e-01 4.306685e-01
[17,] 0.7166835 5.666330e-01 2.833165e-01
[18,] 0.7584921 4.830158e-01 2.415079e-01
[19,] 0.8262106 3.475787e-01 1.737894e-01
[20,] 0.8802098 2.395805e-01 1.197902e-01
[21,] 0.9247995 1.504009e-01 7.520046e-02
[22,] 0.9403778 1.192443e-01 5.962217e-02
[23,] 0.9441778 1.116444e-01 5.582220e-02
[24,] 0.9336274 1.327452e-01 6.637259e-02
[25,] 0.9092632 1.814737e-01 9.073683e-02
[26,] 0.9280083 1.439834e-01 7.199171e-02
[27,] 0.9378867 1.242266e-01 6.211331e-02
[28,] 0.9581763 8.364732e-02 4.182366e-02
[29,] 0.9590907 8.181851e-02 4.090925e-02
[30,] 0.9763816 4.723674e-02 2.361837e-02
[31,] 0.9924770 1.504594e-02 7.522968e-03
[32,] 0.9968689 6.262288e-03 3.131144e-03
[33,] 0.9972330 5.534050e-03 2.767025e-03
[34,] 0.9980638 3.872344e-03 1.936172e-03
[35,] 0.9994278 1.144457e-03 5.722286e-04
[36,] 0.9995233 9.533872e-04 4.766936e-04
[37,] 0.9995114 9.771046e-04 4.885523e-04
[38,] 0.9995296 9.407699e-04 4.703850e-04
[39,] 0.9994079 1.184167e-03 5.920836e-04
[40,] 0.9992545 1.490927e-03 7.454634e-04
[41,] 0.9994864 1.027110e-03 5.135549e-04
[42,] 0.9998008 3.983334e-04 1.991667e-04
[43,] 0.9999814 3.724650e-05 1.862325e-05
[44,] 0.9999625 7.508689e-05 3.754344e-05
[45,] 0.9999157 1.686709e-04 8.433544e-05
[46,] 0.9998252 3.495732e-04 1.747866e-04
[47,] 0.9997615 4.770252e-04 2.385126e-04
[48,] 0.9997710 4.579039e-04 2.289520e-04
[49,] 0.9995166 9.668183e-04 4.834092e-04
[50,] 0.9991197 1.760627e-03 8.803135e-04
[51,] 0.9983459 3.308241e-03 1.654120e-03
[52,] 0.9969124 6.175160e-03 3.087580e-03
[53,] 0.9937294 1.254113e-02 6.270567e-03
[54,] 0.9894409 2.111817e-02 1.055908e-02
[55,] 0.9943341 1.133173e-02 5.665863e-03
[56,] 0.9999669 6.610675e-05 3.305338e-05
[57,] 0.9999979 4.239112e-06 2.119556e-06
[58,] 0.9999887 2.257486e-05 1.128743e-05
[59,] 0.9999485 1.030792e-04 5.153962e-05
[60,] 0.9997854 4.291290e-04 2.145645e-04
[61,] 0.9989558 2.088407e-03 1.044203e-03
[62,] 0.9951870 9.625903e-03 4.812951e-03
[63,] 0.9821671 3.566572e-02 1.783286e-02
> postscript(file="/var/www/html/rcomp/tmp/12f5x1227534485.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2gm2c1227534485.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3ui861227534485.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/43tmk1227534485.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5t6wx1227534485.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 = 74
Frequency = 1
1 2 3 4 5
1.293828e-01 6.710418e-02 4.038909e-02 7.976240e-02 7.791566e-02
6 7 8 9 10
1.073894e-01 1.337129e-01 1.582801e-01 7.210254e-02 6.835205e-02
11 12 13 14 15
-3.451766e-05 2.490037e-02 -3.639638e-02 -2.334632e-02 -3.326400e-02
16 17 18 19 20
-8.436741e-02 -1.020248e-01 -9.162729e-02 -7.188227e-02 -4.942879e-02
21 22 23 24 25
-9.240672e-02 -9.108383e-02 -5.685759e-02 -6.179305e-02 -7.550920e-02
26 27 28 29 30
-6.516391e-02 -5.414971e-02 -5.082011e-02 -3.595477e-02 -4.036417e-03
31 32 33 34 35
-6.892340e-02 -7.157503e-02 -8.242102e-02 -5.398461e-02 -7.456253e-02
36 37 38 39 40
-8.141464e-02 -4.935929e-02 -3.712055e-03 -1.195630e-03 -1.486388e-02
41 42 43 44 45
3.841349e-02 6.619363e-02 5.400350e-02 8.517042e-02 9.083200e-02
46 47 48 49 50
1.120702e-01 1.218864e-01 1.088357e-01 5.015054e-02 3.463943e-02
51 52 53 54 55
3.251322e-02 4.673735e-02 4.583204e-02 1.030567e-02 4.791623e-02
56 57 58 59 60
3.412238e-02 5.637468e-02 6.275762e-02 5.299538e-02 3.935981e-02
61 62 63 64 65
4.606721e-02 -3.600764e-03 -4.722977e-02 -4.679403e-02 -3.091078e-02
66 67 68 69 70
-2.021634e-02 -4.807240e-02 -3.884609e-02 -5.209098e-02 -4.785827e-02
71 72 73 74
-6.730547e-02 -6.560339e-02 -8.771194e-02 -5.806902e-02
> postscript(file="/var/www/html/rcomp/tmp/6h1aa1227534485.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 = 74
Frequency = 1
lag(myerror, k = 1) myerror
0 1.293828e-01 NA
1 6.710418e-02 1.293828e-01
2 4.038909e-02 6.710418e-02
3 7.976240e-02 4.038909e-02
4 7.791566e-02 7.976240e-02
5 1.073894e-01 7.791566e-02
6 1.337129e-01 1.073894e-01
7 1.582801e-01 1.337129e-01
8 7.210254e-02 1.582801e-01
9 6.835205e-02 7.210254e-02
10 -3.451766e-05 6.835205e-02
11 2.490037e-02 -3.451766e-05
12 -3.639638e-02 2.490037e-02
13 -2.334632e-02 -3.639638e-02
14 -3.326400e-02 -2.334632e-02
15 -8.436741e-02 -3.326400e-02
16 -1.020248e-01 -8.436741e-02
17 -9.162729e-02 -1.020248e-01
18 -7.188227e-02 -9.162729e-02
19 -4.942879e-02 -7.188227e-02
20 -9.240672e-02 -4.942879e-02
21 -9.108383e-02 -9.240672e-02
22 -5.685759e-02 -9.108383e-02
23 -6.179305e-02 -5.685759e-02
24 -7.550920e-02 -6.179305e-02
25 -6.516391e-02 -7.550920e-02
26 -5.414971e-02 -6.516391e-02
27 -5.082011e-02 -5.414971e-02
28 -3.595477e-02 -5.082011e-02
29 -4.036417e-03 -3.595477e-02
30 -6.892340e-02 -4.036417e-03
31 -7.157503e-02 -6.892340e-02
32 -8.242102e-02 -7.157503e-02
33 -5.398461e-02 -8.242102e-02
34 -7.456253e-02 -5.398461e-02
35 -8.141464e-02 -7.456253e-02
36 -4.935929e-02 -8.141464e-02
37 -3.712055e-03 -4.935929e-02
38 -1.195630e-03 -3.712055e-03
39 -1.486388e-02 -1.195630e-03
40 3.841349e-02 -1.486388e-02
41 6.619363e-02 3.841349e-02
42 5.400350e-02 6.619363e-02
43 8.517042e-02 5.400350e-02
44 9.083200e-02 8.517042e-02
45 1.120702e-01 9.083200e-02
46 1.218864e-01 1.120702e-01
47 1.088357e-01 1.218864e-01
48 5.015054e-02 1.088357e-01
49 3.463943e-02 5.015054e-02
50 3.251322e-02 3.463943e-02
51 4.673735e-02 3.251322e-02
52 4.583204e-02 4.673735e-02
53 1.030567e-02 4.583204e-02
54 4.791623e-02 1.030567e-02
55 3.412238e-02 4.791623e-02
56 5.637468e-02 3.412238e-02
57 6.275762e-02 5.637468e-02
58 5.299538e-02 6.275762e-02
59 3.935981e-02 5.299538e-02
60 4.606721e-02 3.935981e-02
61 -3.600764e-03 4.606721e-02
62 -4.722977e-02 -3.600764e-03
63 -4.679403e-02 -4.722977e-02
64 -3.091078e-02 -4.679403e-02
65 -2.021634e-02 -3.091078e-02
66 -4.807240e-02 -2.021634e-02
67 -3.884609e-02 -4.807240e-02
68 -5.209098e-02 -3.884609e-02
69 -4.785827e-02 -5.209098e-02
70 -6.730547e-02 -4.785827e-02
71 -6.560339e-02 -6.730547e-02
72 -8.771194e-02 -6.560339e-02
73 -5.806902e-02 -8.771194e-02
74 NA -5.806902e-02
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 6.710418e-02 1.293828e-01
[2,] 4.038909e-02 6.710418e-02
[3,] 7.976240e-02 4.038909e-02
[4,] 7.791566e-02 7.976240e-02
[5,] 1.073894e-01 7.791566e-02
[6,] 1.337129e-01 1.073894e-01
[7,] 1.582801e-01 1.337129e-01
[8,] 7.210254e-02 1.582801e-01
[9,] 6.835205e-02 7.210254e-02
[10,] -3.451766e-05 6.835205e-02
[11,] 2.490037e-02 -3.451766e-05
[12,] -3.639638e-02 2.490037e-02
[13,] -2.334632e-02 -3.639638e-02
[14,] -3.326400e-02 -2.334632e-02
[15,] -8.436741e-02 -3.326400e-02
[16,] -1.020248e-01 -8.436741e-02
[17,] -9.162729e-02 -1.020248e-01
[18,] -7.188227e-02 -9.162729e-02
[19,] -4.942879e-02 -7.188227e-02
[20,] -9.240672e-02 -4.942879e-02
[21,] -9.108383e-02 -9.240672e-02
[22,] -5.685759e-02 -9.108383e-02
[23,] -6.179305e-02 -5.685759e-02
[24,] -7.550920e-02 -6.179305e-02
[25,] -6.516391e-02 -7.550920e-02
[26,] -5.414971e-02 -6.516391e-02
[27,] -5.082011e-02 -5.414971e-02
[28,] -3.595477e-02 -5.082011e-02
[29,] -4.036417e-03 -3.595477e-02
[30,] -6.892340e-02 -4.036417e-03
[31,] -7.157503e-02 -6.892340e-02
[32,] -8.242102e-02 -7.157503e-02
[33,] -5.398461e-02 -8.242102e-02
[34,] -7.456253e-02 -5.398461e-02
[35,] -8.141464e-02 -7.456253e-02
[36,] -4.935929e-02 -8.141464e-02
[37,] -3.712055e-03 -4.935929e-02
[38,] -1.195630e-03 -3.712055e-03
[39,] -1.486388e-02 -1.195630e-03
[40,] 3.841349e-02 -1.486388e-02
[41,] 6.619363e-02 3.841349e-02
[42,] 5.400350e-02 6.619363e-02
[43,] 8.517042e-02 5.400350e-02
[44,] 9.083200e-02 8.517042e-02
[45,] 1.120702e-01 9.083200e-02
[46,] 1.218864e-01 1.120702e-01
[47,] 1.088357e-01 1.218864e-01
[48,] 5.015054e-02 1.088357e-01
[49,] 3.463943e-02 5.015054e-02
[50,] 3.251322e-02 3.463943e-02
[51,] 4.673735e-02 3.251322e-02
[52,] 4.583204e-02 4.673735e-02
[53,] 1.030567e-02 4.583204e-02
[54,] 4.791623e-02 1.030567e-02
[55,] 3.412238e-02 4.791623e-02
[56,] 5.637468e-02 3.412238e-02
[57,] 6.275762e-02 5.637468e-02
[58,] 5.299538e-02 6.275762e-02
[59,] 3.935981e-02 5.299538e-02
[60,] 4.606721e-02 3.935981e-02
[61,] -3.600764e-03 4.606721e-02
[62,] -4.722977e-02 -3.600764e-03
[63,] -4.679403e-02 -4.722977e-02
[64,] -3.091078e-02 -4.679403e-02
[65,] -2.021634e-02 -3.091078e-02
[66,] -4.807240e-02 -2.021634e-02
[67,] -3.884609e-02 -4.807240e-02
[68,] -5.209098e-02 -3.884609e-02
[69,] -4.785827e-02 -5.209098e-02
[70,] -6.730547e-02 -4.785827e-02
[71,] -6.560339e-02 -6.730547e-02
[72,] -8.771194e-02 -6.560339e-02
[73,] -5.806902e-02 -8.771194e-02
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 6.710418e-02 1.293828e-01
2 4.038909e-02 6.710418e-02
3 7.976240e-02 4.038909e-02
4 7.791566e-02 7.976240e-02
5 1.073894e-01 7.791566e-02
6 1.337129e-01 1.073894e-01
7 1.582801e-01 1.337129e-01
8 7.210254e-02 1.582801e-01
9 6.835205e-02 7.210254e-02
10 -3.451766e-05 6.835205e-02
11 2.490037e-02 -3.451766e-05
12 -3.639638e-02 2.490037e-02
13 -2.334632e-02 -3.639638e-02
14 -3.326400e-02 -2.334632e-02
15 -8.436741e-02 -3.326400e-02
16 -1.020248e-01 -8.436741e-02
17 -9.162729e-02 -1.020248e-01
18 -7.188227e-02 -9.162729e-02
19 -4.942879e-02 -7.188227e-02
20 -9.240672e-02 -4.942879e-02
21 -9.108383e-02 -9.240672e-02
22 -5.685759e-02 -9.108383e-02
23 -6.179305e-02 -5.685759e-02
24 -7.550920e-02 -6.179305e-02
25 -6.516391e-02 -7.550920e-02
26 -5.414971e-02 -6.516391e-02
27 -5.082011e-02 -5.414971e-02
28 -3.595477e-02 -5.082011e-02
29 -4.036417e-03 -3.595477e-02
30 -6.892340e-02 -4.036417e-03
31 -7.157503e-02 -6.892340e-02
32 -8.242102e-02 -7.157503e-02
33 -5.398461e-02 -8.242102e-02
34 -7.456253e-02 -5.398461e-02
35 -8.141464e-02 -7.456253e-02
36 -4.935929e-02 -8.141464e-02
37 -3.712055e-03 -4.935929e-02
38 -1.195630e-03 -3.712055e-03
39 -1.486388e-02 -1.195630e-03
40 3.841349e-02 -1.486388e-02
41 6.619363e-02 3.841349e-02
42 5.400350e-02 6.619363e-02
43 8.517042e-02 5.400350e-02
44 9.083200e-02 8.517042e-02
45 1.120702e-01 9.083200e-02
46 1.218864e-01 1.120702e-01
47 1.088357e-01 1.218864e-01
48 5.015054e-02 1.088357e-01
49 3.463943e-02 5.015054e-02
50 3.251322e-02 3.463943e-02
51 4.673735e-02 3.251322e-02
52 4.583204e-02 4.673735e-02
53 1.030567e-02 4.583204e-02
54 4.791623e-02 1.030567e-02
55 3.412238e-02 4.791623e-02
56 5.637468e-02 3.412238e-02
57 6.275762e-02 5.637468e-02
58 5.299538e-02 6.275762e-02
59 3.935981e-02 5.299538e-02
60 4.606721e-02 3.935981e-02
61 -3.600764e-03 4.606721e-02
62 -4.722977e-02 -3.600764e-03
63 -4.679403e-02 -4.722977e-02
64 -3.091078e-02 -4.679403e-02
65 -2.021634e-02 -3.091078e-02
66 -4.807240e-02 -2.021634e-02
67 -3.884609e-02 -4.807240e-02
68 -5.209098e-02 -3.884609e-02
69 -4.785827e-02 -5.209098e-02
70 -6.730547e-02 -4.785827e-02
71 -6.560339e-02 -6.730547e-02
72 -8.771194e-02 -6.560339e-02
73 -5.806902e-02 -8.771194e-02
> 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/7risa1227534485.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/80nwp1227534485.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9iw4i1227534485.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/1077mk1227534485.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11gfs21227534485.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/128vvf1227534485.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/13o23s1227534485.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/14dwlh1227534485.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/15twbr1227534485.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/16fwe91227534485.tab")
+ }
>
> system("convert tmp/12f5x1227534485.ps tmp/12f5x1227534485.png")
> system("convert tmp/2gm2c1227534485.ps tmp/2gm2c1227534485.png")
> system("convert tmp/3ui861227534485.ps tmp/3ui861227534485.png")
> system("convert tmp/43tmk1227534485.ps tmp/43tmk1227534485.png")
> system("convert tmp/5t6wx1227534485.ps tmp/5t6wx1227534485.png")
> system("convert tmp/6h1aa1227534485.ps tmp/6h1aa1227534485.png")
> system("convert tmp/7risa1227534485.ps tmp/7risa1227534485.png")
> system("convert tmp/80nwp1227534485.ps tmp/80nwp1227534485.png")
> system("convert tmp/9iw4i1227534485.ps tmp/9iw4i1227534485.png")
> system("convert tmp/1077mk1227534485.ps tmp/1077mk1227534485.png")
>
>
> proc.time()
user system elapsed
2.618 1.582 3.243