R version 2.9.0 (2009-04-17)
Copyright (C) 2009 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(3,0,3.21,0,3.37,0,3.51,0,3.75,0,4.11,0,4.25,0,4.25,0,4.5,0,4.7,0,4.75,0,4.75,0,4.75,0,4.75,0,4.75,0,4.75,0,4.58,0,4.5,0,4.5,0,4.49,0,4.03,0,3.75,0,3.39,0,3.25,0,3.25,0,3.25,0,3.25,0,3.25,0,3.25,0,3.25,0,3.25,0,3.25,0,3.25,0,3.25,0,3.25,0,2.85,0,2.75,0,2.75,0,2.55,0,2.5,0,2.5,0,2.1,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2,0,2.21,0,2.25,0,2.25,0,2.45,0,2.5,0,2.5,0,2.64,0,2.75,0,2.93,0,3,0,3.17,0,3.25,0,3.39,0,3.5,0,3.5,0,3.65,0,3.75,0,3.75,0,3.9,0,4,0,4,0,4,0,4,0,4,0,4,0,4,0,4,0,4,0,4,0,4,0,4,0,4.18,0,4.25,0,4.25,0,3.97,1,3.42,1,2.75,1,2.31,1,2,1,1.66,1,1.31,1,1.09,1,1,1,1,1,1,1,1,1,1,1),dim=c(2,118),dimnames=list(c('Rente','Crisis'),1:118))
> y <- array(NA,dim=c(2,118),dimnames=list(c('Rente','Crisis'),1:118))
> 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
Rente Crisis
1 3.00 0
2 3.21 0
3 3.37 0
4 3.51 0
5 3.75 0
6 4.11 0
7 4.25 0
8 4.25 0
9 4.50 0
10 4.70 0
11 4.75 0
12 4.75 0
13 4.75 0
14 4.75 0
15 4.75 0
16 4.75 0
17 4.58 0
18 4.50 0
19 4.50 0
20 4.49 0
21 4.03 0
22 3.75 0
23 3.39 0
24 3.25 0
25 3.25 0
26 3.25 0
27 3.25 0
28 3.25 0
29 3.25 0
30 3.25 0
31 3.25 0
32 3.25 0
33 3.25 0
34 3.25 0
35 3.25 0
36 2.85 0
37 2.75 0
38 2.75 0
39 2.55 0
40 2.50 0
41 2.50 0
42 2.10 0
43 2.00 0
44 2.00 0
45 2.00 0
46 2.00 0
47 2.00 0
48 2.00 0
49 2.00 0
50 2.00 0
51 2.00 0
52 2.00 0
53 2.00 0
54 2.00 0
55 2.00 0
56 2.00 0
57 2.00 0
58 2.00 0
59 2.00 0
60 2.00 0
61 2.00 0
62 2.00 0
63 2.00 0
64 2.00 0
65 2.00 0
66 2.00 0
67 2.00 0
68 2.00 0
69 2.00 0
70 2.00 0
71 2.00 0
72 2.21 0
73 2.25 0
74 2.25 0
75 2.45 0
76 2.50 0
77 2.50 0
78 2.64 0
79 2.75 0
80 2.93 0
81 3.00 0
82 3.17 0
83 3.25 0
84 3.39 0
85 3.50 0
86 3.50 0
87 3.65 0
88 3.75 0
89 3.75 0
90 3.90 0
91 4.00 0
92 4.00 0
93 4.00 0
94 4.00 0
95 4.00 0
96 4.00 0
97 4.00 0
98 4.00 0
99 4.00 0
100 4.00 0
101 4.00 0
102 4.00 0
103 4.18 0
104 4.25 0
105 4.25 0
106 3.97 1
107 3.42 1
108 2.75 1
109 2.31 1
110 2.00 1
111 1.66 1
112 1.31 1
113 1.09 1
114 1.00 1
115 1.00 1
116 1.00 1
117 1.00 1
118 1.00 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Crisis
3.137 -1.329
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1.1372 -1.0097 0.1128 0.8628 2.1615
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 3.13724 0.09248 33.924 < 2e-16 ***
Crisis -1.32878 0.27862 -4.769 5.42e-06 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.9476 on 116 degrees of freedom
Multiple R-squared: 0.1639, Adjusted R-squared: 0.1567
F-statistic: 22.75 on 1 and 116 DF, p-value: 5.424e-06
> 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,] 0.04982274 9.964548e-02 9.501773e-01
[2,] 0.06788632 1.357726e-01 9.321137e-01
[3,] 0.07412821 1.482564e-01 9.258718e-01
[4,] 0.06273027 1.254605e-01 9.372697e-01
[5,] 0.07136448 1.427290e-01 9.286355e-01
[6,] 0.09304698 1.860940e-01 9.069530e-01
[7,] 0.10885849 2.177170e-01 8.911415e-01
[8,] 0.11526034 2.305207e-01 8.847397e-01
[9,] 0.11590267 2.318053e-01 8.840973e-01
[10,] 0.11333995 2.266799e-01 8.866601e-01
[11,] 0.10928364 2.185673e-01 8.907164e-01
[12,] 0.10487169 2.097434e-01 8.951283e-01
[13,] 0.08897760 1.779552e-01 9.110224e-01
[14,] 0.07247455 1.449491e-01 9.275254e-01
[15,] 0.05950579 1.190116e-01 9.404942e-01
[16,] 0.04913816 9.827633e-02 9.508618e-01
[17,] 0.03720893 7.441786e-02 9.627911e-01
[18,] 0.03144985 6.289970e-02 9.685501e-01
[19,] 0.03596458 7.192917e-02 9.640354e-01
[20,] 0.04489622 8.979244e-02 9.551038e-01
[21,] 0.05171283 1.034257e-01 9.482872e-01
[22,] 0.05622303 1.124461e-01 9.437770e-01
[23,] 0.05853048 1.170610e-01 9.414695e-01
[24,] 0.05889745 1.177949e-01 9.411026e-01
[25,] 0.05765603 1.153121e-01 9.423440e-01
[26,] 0.05515428 1.103086e-01 9.448457e-01
[27,] 0.05172510 1.034502e-01 9.482749e-01
[28,] 0.04766936 9.533871e-02 9.523306e-01
[29,] 0.04324767 8.649535e-02 9.567523e-01
[30,] 0.03867758 7.735516e-02 9.613224e-01
[31,] 0.03413394 6.826787e-02 9.658661e-01
[32,] 0.03905238 7.810476e-02 9.609476e-01
[33,] 0.04644561 9.289122e-02 9.535544e-01
[34,] 0.05252375 1.050475e-01 9.474762e-01
[35,] 0.06688506 1.337701e-01 9.331149e-01
[36,] 0.08325370 1.665074e-01 9.167463e-01
[37,] 0.09808271 1.961654e-01 9.019173e-01
[38,] 0.14839988 2.967998e-01 8.516001e-01
[39,] 0.21590993 4.318199e-01 7.840901e-01
[40,] 0.28472948 5.694590e-01 7.152705e-01
[41,] 0.35065893 7.013179e-01 6.493411e-01
[42,] 0.41132601 8.226520e-01 5.886740e-01
[43,] 0.46573560 9.314712e-01 5.342644e-01
[44,] 0.51377608 9.724478e-01 4.862239e-01
[45,] 0.55583311 8.883338e-01 4.441669e-01
[46,] 0.59253109 8.149378e-01 4.074689e-01
[47,] 0.62457693 7.508461e-01 3.754231e-01
[48,] 0.65267380 6.946524e-01 3.473262e-01
[49,] 0.67747867 6.450427e-01 3.225213e-01
[50,] 0.69958528 6.008294e-01 3.004147e-01
[51,] 0.71952096 5.609581e-01 2.804790e-01
[52,] 0.73775014 5.244997e-01 2.622499e-01
[53,] 0.75468065 4.906387e-01 2.453194e-01
[54,] 0.77067030 4.586594e-01 2.293297e-01
[55,] 0.78603252 4.279350e-01 2.139675e-01
[56,] 0.80104033 3.979193e-01 1.989597e-01
[57,] 0.81592794 3.681441e-01 1.840721e-01
[58,] 0.83088984 3.382203e-01 1.691102e-01
[59,] 0.84607667 3.078467e-01 1.539233e-01
[60,] 0.86158764 2.768247e-01 1.384124e-01
[61,] 0.87745918 2.450816e-01 1.225408e-01
[62,] 0.89364971 2.127006e-01 1.063503e-01
[63,] 0.91002158 1.799568e-01 8.997842e-02
[64,] 0.92632246 1.473551e-01 7.367754e-02
[65,] 0.94217157 1.156569e-01 5.782843e-02
[66,] 0.95706044 8.587913e-02 4.293956e-02
[67,] 0.97038332 5.923336e-02 2.961668e-02
[68,] 0.97663417 4.673167e-02 2.336583e-02
[69,] 0.98199676 3.600649e-02 1.800324e-02
[70,] 0.98716832 2.566336e-02 1.283168e-02
[71,] 0.98943910 2.112179e-02 1.056090e-02
[72,] 0.99141083 1.717835e-02 8.589173e-03
[73,] 0.99354627 1.290746e-02 6.453729e-03
[74,] 0.99471119 1.057763e-02 5.288814e-03
[75,] 0.99540718 9.185640e-03 4.592820e-03
[76,] 0.99541186 9.176275e-03 4.588137e-03
[77,] 0.99530212 9.395754e-03 4.697877e-03
[78,] 0.99460014 1.079972e-02 5.399860e-03
[79,] 0.99358721 1.282559e-02 6.412794e-03
[80,] 0.99186070 1.627861e-02 8.139304e-03
[81,] 0.98929857 2.140287e-02 1.070143e-02
[82,] 0.98616883 2.766234e-02 1.383117e-02
[83,] 0.98146138 3.707723e-02 1.853862e-02
[84,] 0.97497810 5.004380e-02 2.502190e-02
[85,] 0.96663218 6.673564e-02 3.336782e-02
[86,] 0.95552156 8.895688e-02 4.447844e-02
[87,] 0.94156429 1.168714e-01 5.843571e-02
[88,] 0.92386305 1.522739e-01 7.613695e-02
[89,] 0.90171972 1.965606e-01 9.828028e-02
[90,] 0.87443406 2.511319e-01 1.255659e-01
[91,] 0.84136171 3.172766e-01 1.586383e-01
[92,] 0.80198993 3.960201e-01 1.980101e-01
[93,] 0.75602833 4.879433e-01 2.439717e-01
[94,] 0.70350827 5.929835e-01 2.964917e-01
[95,] 0.64488149 7.102370e-01 3.551185e-01
[96,] 0.58110911 8.377818e-01 4.188909e-01
[97,] 0.51374342 9.725132e-01 4.862566e-01
[98,] 0.44506334 8.901267e-01 5.549367e-01
[99,] 0.37681843 7.536369e-01 6.231816e-01
[100,] 0.31103122 6.220624e-01 6.889688e-01
[101,] 0.24836316 4.967263e-01 7.516368e-01
[102,] 0.58787851 8.242430e-01 4.121215e-01
[103,] 0.87151712 2.569658e-01 1.284829e-01
[104,] 0.96303123 7.393754e-02 3.696877e-02
[105,] 0.98980909 2.038182e-02 1.019091e-02
[106,] 0.99823887 3.522268e-03 1.761134e-03
[107,] 0.99986047 2.790639e-04 1.395319e-04
[108,] 0.99999258 1.483139e-05 7.415693e-06
[109,] 1.00000000 5.580344e-47 2.790172e-47
> postscript(file="/var/www/html/rcomp/tmp/1gh8p1258734625.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2vq5w1258734625.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3fgai1258734625.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4cxmo1258734625.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5vv9o1258734625.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 = 118
Frequency = 1
1 2 3 4 5 6
-0.13723810 0.07276190 0.23276190 0.37276190 0.61276190 0.97276190
7 8 9 10 11 12
1.11276190 1.11276190 1.36276190 1.56276190 1.61276190 1.61276190
13 14 15 16 17 18
1.61276190 1.61276190 1.61276190 1.61276190 1.44276190 1.36276190
19 20 21 22 23 24
1.36276190 1.35276190 0.89276190 0.61276190 0.25276190 0.11276190
25 26 27 28 29 30
0.11276190 0.11276190 0.11276190 0.11276190 0.11276190 0.11276190
31 32 33 34 35 36
0.11276190 0.11276190 0.11276190 0.11276190 0.11276190 -0.28723810
37 38 39 40 41 42
-0.38723810 -0.38723810 -0.58723810 -0.63723810 -0.63723810 -1.03723810
43 44 45 46 47 48
-1.13723810 -1.13723810 -1.13723810 -1.13723810 -1.13723810 -1.13723810
49 50 51 52 53 54
-1.13723810 -1.13723810 -1.13723810 -1.13723810 -1.13723810 -1.13723810
55 56 57 58 59 60
-1.13723810 -1.13723810 -1.13723810 -1.13723810 -1.13723810 -1.13723810
61 62 63 64 65 66
-1.13723810 -1.13723810 -1.13723810 -1.13723810 -1.13723810 -1.13723810
67 68 69 70 71 72
-1.13723810 -1.13723810 -1.13723810 -1.13723810 -1.13723810 -0.92723810
73 74 75 76 77 78
-0.88723810 -0.88723810 -0.68723810 -0.63723810 -0.63723810 -0.49723810
79 80 81 82 83 84
-0.38723810 -0.20723810 -0.13723810 0.03276190 0.11276190 0.25276190
85 86 87 88 89 90
0.36276190 0.36276190 0.51276190 0.61276190 0.61276190 0.76276190
91 92 93 94 95 96
0.86276190 0.86276190 0.86276190 0.86276190 0.86276190 0.86276190
97 98 99 100 101 102
0.86276190 0.86276190 0.86276190 0.86276190 0.86276190 0.86276190
103 104 105 106 107 108
1.04276190 1.11276190 1.11276190 2.16153846 1.61153846 0.94153846
109 110 111 112 113 114
0.50153846 0.19153846 -0.14846154 -0.49846154 -0.71846154 -0.80846154
115 116 117 118
-0.80846154 -0.80846154 -0.80846154 -0.80846154
> postscript(file="/var/www/html/rcomp/tmp/6wccv1258734625.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 = 118
Frequency = 1
lag(myerror, k = 1) myerror
0 -0.13723810 NA
1 0.07276190 -0.13723810
2 0.23276190 0.07276190
3 0.37276190 0.23276190
4 0.61276190 0.37276190
5 0.97276190 0.61276190
6 1.11276190 0.97276190
7 1.11276190 1.11276190
8 1.36276190 1.11276190
9 1.56276190 1.36276190
10 1.61276190 1.56276190
11 1.61276190 1.61276190
12 1.61276190 1.61276190
13 1.61276190 1.61276190
14 1.61276190 1.61276190
15 1.61276190 1.61276190
16 1.44276190 1.61276190
17 1.36276190 1.44276190
18 1.36276190 1.36276190
19 1.35276190 1.36276190
20 0.89276190 1.35276190
21 0.61276190 0.89276190
22 0.25276190 0.61276190
23 0.11276190 0.25276190
24 0.11276190 0.11276190
25 0.11276190 0.11276190
26 0.11276190 0.11276190
27 0.11276190 0.11276190
28 0.11276190 0.11276190
29 0.11276190 0.11276190
30 0.11276190 0.11276190
31 0.11276190 0.11276190
32 0.11276190 0.11276190
33 0.11276190 0.11276190
34 0.11276190 0.11276190
35 -0.28723810 0.11276190
36 -0.38723810 -0.28723810
37 -0.38723810 -0.38723810
38 -0.58723810 -0.38723810
39 -0.63723810 -0.58723810
40 -0.63723810 -0.63723810
41 -1.03723810 -0.63723810
42 -1.13723810 -1.03723810
43 -1.13723810 -1.13723810
44 -1.13723810 -1.13723810
45 -1.13723810 -1.13723810
46 -1.13723810 -1.13723810
47 -1.13723810 -1.13723810
48 -1.13723810 -1.13723810
49 -1.13723810 -1.13723810
50 -1.13723810 -1.13723810
51 -1.13723810 -1.13723810
52 -1.13723810 -1.13723810
53 -1.13723810 -1.13723810
54 -1.13723810 -1.13723810
55 -1.13723810 -1.13723810
56 -1.13723810 -1.13723810
57 -1.13723810 -1.13723810
58 -1.13723810 -1.13723810
59 -1.13723810 -1.13723810
60 -1.13723810 -1.13723810
61 -1.13723810 -1.13723810
62 -1.13723810 -1.13723810
63 -1.13723810 -1.13723810
64 -1.13723810 -1.13723810
65 -1.13723810 -1.13723810
66 -1.13723810 -1.13723810
67 -1.13723810 -1.13723810
68 -1.13723810 -1.13723810
69 -1.13723810 -1.13723810
70 -1.13723810 -1.13723810
71 -0.92723810 -1.13723810
72 -0.88723810 -0.92723810
73 -0.88723810 -0.88723810
74 -0.68723810 -0.88723810
75 -0.63723810 -0.68723810
76 -0.63723810 -0.63723810
77 -0.49723810 -0.63723810
78 -0.38723810 -0.49723810
79 -0.20723810 -0.38723810
80 -0.13723810 -0.20723810
81 0.03276190 -0.13723810
82 0.11276190 0.03276190
83 0.25276190 0.11276190
84 0.36276190 0.25276190
85 0.36276190 0.36276190
86 0.51276190 0.36276190
87 0.61276190 0.51276190
88 0.61276190 0.61276190
89 0.76276190 0.61276190
90 0.86276190 0.76276190
91 0.86276190 0.86276190
92 0.86276190 0.86276190
93 0.86276190 0.86276190
94 0.86276190 0.86276190
95 0.86276190 0.86276190
96 0.86276190 0.86276190
97 0.86276190 0.86276190
98 0.86276190 0.86276190
99 0.86276190 0.86276190
100 0.86276190 0.86276190
101 0.86276190 0.86276190
102 1.04276190 0.86276190
103 1.11276190 1.04276190
104 1.11276190 1.11276190
105 2.16153846 1.11276190
106 1.61153846 2.16153846
107 0.94153846 1.61153846
108 0.50153846 0.94153846
109 0.19153846 0.50153846
110 -0.14846154 0.19153846
111 -0.49846154 -0.14846154
112 -0.71846154 -0.49846154
113 -0.80846154 -0.71846154
114 -0.80846154 -0.80846154
115 -0.80846154 -0.80846154
116 -0.80846154 -0.80846154
117 -0.80846154 -0.80846154
118 NA -0.80846154
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.07276190 -0.13723810
[2,] 0.23276190 0.07276190
[3,] 0.37276190 0.23276190
[4,] 0.61276190 0.37276190
[5,] 0.97276190 0.61276190
[6,] 1.11276190 0.97276190
[7,] 1.11276190 1.11276190
[8,] 1.36276190 1.11276190
[9,] 1.56276190 1.36276190
[10,] 1.61276190 1.56276190
[11,] 1.61276190 1.61276190
[12,] 1.61276190 1.61276190
[13,] 1.61276190 1.61276190
[14,] 1.61276190 1.61276190
[15,] 1.61276190 1.61276190
[16,] 1.44276190 1.61276190
[17,] 1.36276190 1.44276190
[18,] 1.36276190 1.36276190
[19,] 1.35276190 1.36276190
[20,] 0.89276190 1.35276190
[21,] 0.61276190 0.89276190
[22,] 0.25276190 0.61276190
[23,] 0.11276190 0.25276190
[24,] 0.11276190 0.11276190
[25,] 0.11276190 0.11276190
[26,] 0.11276190 0.11276190
[27,] 0.11276190 0.11276190
[28,] 0.11276190 0.11276190
[29,] 0.11276190 0.11276190
[30,] 0.11276190 0.11276190
[31,] 0.11276190 0.11276190
[32,] 0.11276190 0.11276190
[33,] 0.11276190 0.11276190
[34,] 0.11276190 0.11276190
[35,] -0.28723810 0.11276190
[36,] -0.38723810 -0.28723810
[37,] -0.38723810 -0.38723810
[38,] -0.58723810 -0.38723810
[39,] -0.63723810 -0.58723810
[40,] -0.63723810 -0.63723810
[41,] -1.03723810 -0.63723810
[42,] -1.13723810 -1.03723810
[43,] -1.13723810 -1.13723810
[44,] -1.13723810 -1.13723810
[45,] -1.13723810 -1.13723810
[46,] -1.13723810 -1.13723810
[47,] -1.13723810 -1.13723810
[48,] -1.13723810 -1.13723810
[49,] -1.13723810 -1.13723810
[50,] -1.13723810 -1.13723810
[51,] -1.13723810 -1.13723810
[52,] -1.13723810 -1.13723810
[53,] -1.13723810 -1.13723810
[54,] -1.13723810 -1.13723810
[55,] -1.13723810 -1.13723810
[56,] -1.13723810 -1.13723810
[57,] -1.13723810 -1.13723810
[58,] -1.13723810 -1.13723810
[59,] -1.13723810 -1.13723810
[60,] -1.13723810 -1.13723810
[61,] -1.13723810 -1.13723810
[62,] -1.13723810 -1.13723810
[63,] -1.13723810 -1.13723810
[64,] -1.13723810 -1.13723810
[65,] -1.13723810 -1.13723810
[66,] -1.13723810 -1.13723810
[67,] -1.13723810 -1.13723810
[68,] -1.13723810 -1.13723810
[69,] -1.13723810 -1.13723810
[70,] -1.13723810 -1.13723810
[71,] -0.92723810 -1.13723810
[72,] -0.88723810 -0.92723810
[73,] -0.88723810 -0.88723810
[74,] -0.68723810 -0.88723810
[75,] -0.63723810 -0.68723810
[76,] -0.63723810 -0.63723810
[77,] -0.49723810 -0.63723810
[78,] -0.38723810 -0.49723810
[79,] -0.20723810 -0.38723810
[80,] -0.13723810 -0.20723810
[81,] 0.03276190 -0.13723810
[82,] 0.11276190 0.03276190
[83,] 0.25276190 0.11276190
[84,] 0.36276190 0.25276190
[85,] 0.36276190 0.36276190
[86,] 0.51276190 0.36276190
[87,] 0.61276190 0.51276190
[88,] 0.61276190 0.61276190
[89,] 0.76276190 0.61276190
[90,] 0.86276190 0.76276190
[91,] 0.86276190 0.86276190
[92,] 0.86276190 0.86276190
[93,] 0.86276190 0.86276190
[94,] 0.86276190 0.86276190
[95,] 0.86276190 0.86276190
[96,] 0.86276190 0.86276190
[97,] 0.86276190 0.86276190
[98,] 0.86276190 0.86276190
[99,] 0.86276190 0.86276190
[100,] 0.86276190 0.86276190
[101,] 0.86276190 0.86276190
[102,] 1.04276190 0.86276190
[103,] 1.11276190 1.04276190
[104,] 1.11276190 1.11276190
[105,] 2.16153846 1.11276190
[106,] 1.61153846 2.16153846
[107,] 0.94153846 1.61153846
[108,] 0.50153846 0.94153846
[109,] 0.19153846 0.50153846
[110,] -0.14846154 0.19153846
[111,] -0.49846154 -0.14846154
[112,] -0.71846154 -0.49846154
[113,] -0.80846154 -0.71846154
[114,] -0.80846154 -0.80846154
[115,] -0.80846154 -0.80846154
[116,] -0.80846154 -0.80846154
[117,] -0.80846154 -0.80846154
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.07276190 -0.13723810
2 0.23276190 0.07276190
3 0.37276190 0.23276190
4 0.61276190 0.37276190
5 0.97276190 0.61276190
6 1.11276190 0.97276190
7 1.11276190 1.11276190
8 1.36276190 1.11276190
9 1.56276190 1.36276190
10 1.61276190 1.56276190
11 1.61276190 1.61276190
12 1.61276190 1.61276190
13 1.61276190 1.61276190
14 1.61276190 1.61276190
15 1.61276190 1.61276190
16 1.44276190 1.61276190
17 1.36276190 1.44276190
18 1.36276190 1.36276190
19 1.35276190 1.36276190
20 0.89276190 1.35276190
21 0.61276190 0.89276190
22 0.25276190 0.61276190
23 0.11276190 0.25276190
24 0.11276190 0.11276190
25 0.11276190 0.11276190
26 0.11276190 0.11276190
27 0.11276190 0.11276190
28 0.11276190 0.11276190
29 0.11276190 0.11276190
30 0.11276190 0.11276190
31 0.11276190 0.11276190
32 0.11276190 0.11276190
33 0.11276190 0.11276190
34 0.11276190 0.11276190
35 -0.28723810 0.11276190
36 -0.38723810 -0.28723810
37 -0.38723810 -0.38723810
38 -0.58723810 -0.38723810
39 -0.63723810 -0.58723810
40 -0.63723810 -0.63723810
41 -1.03723810 -0.63723810
42 -1.13723810 -1.03723810
43 -1.13723810 -1.13723810
44 -1.13723810 -1.13723810
45 -1.13723810 -1.13723810
46 -1.13723810 -1.13723810
47 -1.13723810 -1.13723810
48 -1.13723810 -1.13723810
49 -1.13723810 -1.13723810
50 -1.13723810 -1.13723810
51 -1.13723810 -1.13723810
52 -1.13723810 -1.13723810
53 -1.13723810 -1.13723810
54 -1.13723810 -1.13723810
55 -1.13723810 -1.13723810
56 -1.13723810 -1.13723810
57 -1.13723810 -1.13723810
58 -1.13723810 -1.13723810
59 -1.13723810 -1.13723810
60 -1.13723810 -1.13723810
61 -1.13723810 -1.13723810
62 -1.13723810 -1.13723810
63 -1.13723810 -1.13723810
64 -1.13723810 -1.13723810
65 -1.13723810 -1.13723810
66 -1.13723810 -1.13723810
67 -1.13723810 -1.13723810
68 -1.13723810 -1.13723810
69 -1.13723810 -1.13723810
70 -1.13723810 -1.13723810
71 -0.92723810 -1.13723810
72 -0.88723810 -0.92723810
73 -0.88723810 -0.88723810
74 -0.68723810 -0.88723810
75 -0.63723810 -0.68723810
76 -0.63723810 -0.63723810
77 -0.49723810 -0.63723810
78 -0.38723810 -0.49723810
79 -0.20723810 -0.38723810
80 -0.13723810 -0.20723810
81 0.03276190 -0.13723810
82 0.11276190 0.03276190
83 0.25276190 0.11276190
84 0.36276190 0.25276190
85 0.36276190 0.36276190
86 0.51276190 0.36276190
87 0.61276190 0.51276190
88 0.61276190 0.61276190
89 0.76276190 0.61276190
90 0.86276190 0.76276190
91 0.86276190 0.86276190
92 0.86276190 0.86276190
93 0.86276190 0.86276190
94 0.86276190 0.86276190
95 0.86276190 0.86276190
96 0.86276190 0.86276190
97 0.86276190 0.86276190
98 0.86276190 0.86276190
99 0.86276190 0.86276190
100 0.86276190 0.86276190
101 0.86276190 0.86276190
102 1.04276190 0.86276190
103 1.11276190 1.04276190
104 1.11276190 1.11276190
105 2.16153846 1.11276190
106 1.61153846 2.16153846
107 0.94153846 1.61153846
108 0.50153846 0.94153846
109 0.19153846 0.50153846
110 -0.14846154 0.19153846
111 -0.49846154 -0.14846154
112 -0.71846154 -0.49846154
113 -0.80846154 -0.71846154
114 -0.80846154 -0.80846154
115 -0.80846154 -0.80846154
116 -0.80846154 -0.80846154
117 -0.80846154 -0.80846154
> 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/78d0z1258734625.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8itze1258734625.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9otfk1258734625.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10y24c1258734625.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11s8tn1258734625.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/12njyp1258734625.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/136qlb1258734625.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/145sxp1258734625.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/15r0np1258734625.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/16jx821258734625.tab")
+ }
>
> system("convert tmp/1gh8p1258734625.ps tmp/1gh8p1258734625.png")
> system("convert tmp/2vq5w1258734625.ps tmp/2vq5w1258734625.png")
> system("convert tmp/3fgai1258734625.ps tmp/3fgai1258734625.png")
> system("convert tmp/4cxmo1258734625.ps tmp/4cxmo1258734625.png")
> system("convert tmp/5vv9o1258734625.ps tmp/5vv9o1258734625.png")
> system("convert tmp/6wccv1258734625.ps tmp/6wccv1258734625.png")
> system("convert tmp/78d0z1258734625.ps tmp/78d0z1258734625.png")
> system("convert tmp/8itze1258734625.ps tmp/8itze1258734625.png")
> system("convert tmp/9otfk1258734625.ps tmp/9otfk1258734625.png")
> system("convert tmp/10y24c1258734625.ps tmp/10y24c1258734625.png")
>
>
> proc.time()
user system elapsed
3.137 1.626 3.592