R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
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Type 'license()' or 'licence()' for distribution details.
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'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(9/06/2002
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+ ,169585
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+ ,203702
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+ ,220658
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+ ,194472
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+ ,195724
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+ ,4.86
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+ ,4.91
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+ ,189615
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+ ,31/10/2004
+ ,136295
+ ,2.72
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+ ,113425
+ ,2.71
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+ ,21/11/2004
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+ ,1.08
+ ,0.94
+ ,4.85
+ ,28/11/2004
+ ,97048
+ ,2.82
+ ,1.05
+ ,0.92
+ ,4.87
+ ,5/12/2004
+ ,98750
+ ,2.76
+ ,1.04
+ ,0.91
+ ,4.88
+ ,12/12/2004
+ ,98235
+ ,2.77
+ ,1.04
+ ,0.91
+ ,4.87
+ ,19/12/2004
+ ,101254
+ ,2.77
+ ,1.04
+ ,0.90
+ ,4.93
+ ,26/12/2004
+ ,139589
+ ,2.81
+ ,1.04
+ ,0.89
+ ,4.93
+ ,2/01/2005
+ ,134921
+ ,2.77
+ ,1.06
+ ,0.91
+ ,4.74
+ ,9/01/2005
+ ,80355
+ ,2.76
+ ,1.08
+ ,0.93
+ ,4.77
+ ,16/01/2005
+ ,80396
+ ,2.73
+ ,1.08
+ ,0.94
+ ,4.81
+ ,23/01/2005
+ ,82183
+ ,2.72
+ ,1.08
+ ,0.93
+ ,4.82
+ ,30/01/2005
+ ,79709
+ ,2.73
+ ,1.07
+ ,0.91
+ ,4.79
+ ,6/02/2005
+ ,90781
+ ,2.71
+ ,1.06
+ ,0.92
+ ,4.75)
+ ,dim=c(6
+ ,140)
+ ,dimnames=list(c('Tijd'
+ ,'QBEFRU'
+ ,'PBEFRU'
+ ,'PSOCOLA'
+ ,'PSOORA'
+ ,'PSTIM')
+ ,1:140))
> y <- array(NA,dim=c(6,140),dimnames=list(c('Tijd','QBEFRU','PBEFRU','PSOCOLA','PSOORA','PSTIM'),1:140))
> 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'
> library(lattice)
> library(lmtest)
Loading required package: zoo
> 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
Tijd QBEFRU PBEFRU PSOCOLA PSOORA PSTIM
1 7.492507e-04 169498 2.47 0.97 0.80 5.06
2 1.332001e-03 125451 2.51 0.95 0.80 5.07
3 1.914752e-03 140449 2.51 0.96 0.80 5.04
4 2.497502e-03 141653 2.51 0.97 0.81 5.08
5 4.995005e-04 136394 2.49 0.96 0.81 5.15
6 9.990010e-04 167588 2.52 0.96 0.83 5.16
7 1.498501e-03 191807 2.51 0.94 0.79 5.09
8 1.998002e-03 149736 2.54 0.95 0.80 5.14
9 2.497502e-04 196066 2.53 0.95 0.81 5.17
10 6.868132e-04 239155 2.55 0.95 0.80 5.13
11 1.123876e-03 178421 2.50 0.95 0.81 5.19
12 1.560939e-03 139871 2.59 0.97 0.81 5.17
13 5.550006e-05 118159 2.56 0.97 0.82 5.17
14 4.440004e-04 109763 2.59 0.95 0.81 5.21
15 8.325008e-04 97415 2.58 0.96 0.82 5.21
16 1.221001e-03 119190 2.62 0.96 0.82 5.23
17 1.609502e-03 97903 2.59 0.94 0.80 5.17
18 2.997003e-04 96953 2.58 0.96 0.79 5.16
19 6.493506e-04 87888 2.57 0.98 0.79 5.15
20 9.990010e-04 84637 2.57 0.97 0.80 5.12
21 1.348651e-03 90549 2.55 0.96 0.80 5.12
22 1.362274e-04 95680 2.51 0.95 0.80 5.10
23 4.540914e-04 99371 2.50 0.96 0.80 5.13
24 7.719553e-04 79984 2.59 0.96 0.80 5.14
25 1.089819e-03 86752 2.63 0.97 0.80 5.16
26 4.162504e-05 85733 2.63 0.96 0.80 5.17
27 3.330003e-04 84906 2.61 0.95 0.78 5.15
28 6.243756e-04 78356 2.64 0.95 0.78 5.12
29 9.157509e-04 108895 2.67 0.94 0.76 5.08
30 1.207126e-03 101768 2.63 0.94 0.77 5.07
31 2.496256e-03 73285 2.58 0.98 0.82 5.16
32 5.991013e-03 65724 2.56 0.93 0.81 5.14
33 9.485771e-03 67457 2.57 0.93 0.81 5.13
34 1.298053e-02 67203 2.55 0.96 0.80 5.11
35 4.992511e-04 69273 2.58 0.97 0.79 5.12
36 2.246630e-03 80807 2.50 0.97 0.81 5.09
37 3.994009e-03 75129 2.56 0.95 0.81 5.10
38 5.741388e-03 74991 2.62 0.95 0.81 4.95
39 3.328341e-04 68157 2.71 0.96 0.81 5.11
40 1.497753e-03 73858 2.74 0.98 0.82 5.11
41 2.662673e-03 71349 2.76 0.98 0.81 5.10
42 3.827592e-03 85634 2.66 0.97 0.80 5.11
43 4.992511e-03 91624 2.61 0.98 0.83 5.12
44 7.488767e-04 116014 2.68 0.98 0.81 5.09
45 1.622566e-03 120033 2.70 0.99 0.83 5.10
46 2.496256e-03 108651 2.70 0.99 0.84 5.06
47 3.369945e-03 105378 2.72 0.97 0.84 5.03
48 3.994009e-04 138939 2.77 0.98 0.85 5.05
49 1.098352e-03 132974 2.76 0.97 0.85 5.04
50 1.797304e-03 135277 2.72 0.97 0.86 5.02
51 2.496256e-03 152741 2.69 0.97 0.85 4.97
52 8.320852e-05 158417 2.70 0.98 0.87 4.91
53 6.656682e-04 157460 2.69 0.97 0.86 4.91
54 1.248128e-03 193997 2.66 0.97 0.87 4.98
55 1.830587e-03 154089 2.74 0.98 0.87 4.98
56 2.413047e-03 147570 2.76 0.98 0.86 4.97
57 4.279295e-04 162924 2.79 0.95 0.87 4.97
58 9.271807e-04 153629 2.78 0.97 0.88 4.90
59 1.426432e-03 155907 2.80 0.97 0.87 4.91
60 1.925683e-03 197675 2.78 0.97 0.87 4.88
61 1.872192e-04 250708 2.76 0.97 0.86 4.86
62 6.240639e-04 266652 2.73 0.98 0.86 4.87
63 1.060909e-03 209842 2.72 0.98 0.88 4.86
64 1.497753e-03 165826 2.73 0.98 0.88 4.89
65 1.934598e-03 137152 2.74 0.96 0.87 4.90
66 3.883064e-04 150581 2.72 0.98 0.88 4.88
67 7.766129e-04 145973 2.71 1.00 0.89 4.85
68 1.164919e-03 126532 2.66 1.01 0.89 4.85
69 1.553226e-03 115437 2.68 1.02 0.88 4.84
70 2.496256e-04 119526 2.67 1.01 0.88 4.91
71 5.991013e-04 110856 2.68 1.01 0.88 4.94
72 9.485771e-04 97243 2.67 1.02 0.88 4.92
73 1.298053e-03 103876 2.71 1.01 0.87 4.93
74 9.077293e-05 116370 2.69 1.01 0.87 4.97
75 4.084782e-04 109616 2.64 1.01 0.86 4.89
76 7.261835e-04 98365 2.66 1.02 0.88 4.88
77 1.043889e-03 90440 2.70 1.02 0.87 4.93
78 1.361594e-03 88899 2.69 1.02 0.86 4.94
79 2.912298e-04 92358 2.71 1.01 0.85 4.99
80 5.824596e-04 88394 2.74 1.01 0.86 5.00
81 8.736895e-04 98219 2.78 0.99 0.84 5.02
82 1.164919e-03 113546 2.79 1.00 0.85 5.06
83 1.996008e-03 107168 2.75 1.01 0.88 5.01
84 5.489022e-03 77540 2.69 0.99 0.88 5.02
85 8.982036e-03 74944 2.69 1.00 0.89 4.97
86 1.247505e-02 75641 2.69 1.02 0.88 4.96
87 2.495010e-04 75910 2.72 1.01 0.88 4.95
88 1.996008e-03 87384 2.69 1.01 0.88 4.92
89 3.742515e-03 84615 2.70 1.01 0.89 4.88
90 5.489022e-03 80420 2.68 1.03 0.89 4.86
91 7.235529e-03 80784 2.70 1.02 0.89 4.94
92 1.164338e-03 79933 2.72 1.02 0.88 4.83
93 2.328676e-03 82118 2.70 1.03 0.89 4.95
94 3.493014e-03 91420 2.66 1.03 0.89 4.95
95 4.657352e-03 112426 2.68 1.02 0.89 4.94
96 4.990020e-04 114528 2.65 1.02 0.89 4.93
97 1.372255e-03 131025 2.69 1.02 0.90 4.97
98 2.245509e-03 116460 2.66 1.02 0.88 4.95
99 3.118762e-03 111258 2.69 1.03 0.90 4.92
100 1.996008e-04 155318 2.69 1.02 0.88 4.82
101 8.982036e-04 155078 2.65 1.02 0.90 4.82
102 1.596806e-03 134794 2.66 1.02 0.89 4.84
103 2.295409e-03 139985 2.63 1.03 0.89 4.83
104 2.994012e-03 198778 2.65 1.02 0.88 4.79
105 4.990020e-04 172436 2.60 1.02 0.89 4.81
106 1.081171e-03 169585 2.57 1.02 0.91 4.85
107 1.663340e-03 203702 2.65 1.02 0.91 4.84
108 2.245509e-03 282392 2.69 1.02 0.90 4.82
109 2.851440e-04 220658 2.71 1.00 0.93 4.92
110 7.841460e-04 194472 2.72 1.04 0.94 4.92
111 1.283148e-03 269246 2.73 1.04 0.95 4.90
112 1.782150e-03 215340 2.72 1.03 0.95 4.91
113 6.237525e-05 218319 2.73 1.02 0.93 4.85
114 4.990020e-04 195724 2.72 1.04 0.95 4.86
115 9.356287e-04 174614 2.70 1.05 0.95 4.88
116 1.372255e-03 172085 2.72 1.03 0.94 4.85
117 1.808882e-03 152347 2.70 0.99 0.92 4.91
118 2.772233e-04 189615 2.72 1.03 0.94 4.89
119 6.653360e-04 173804 2.70 1.08 0.95 4.92
120 1.053449e-03 145683 2.65 1.09 0.97 4.82
121 1.441561e-03 133550 2.66 1.08 0.96 4.82
122 1.497006e-04 121156 2.69 1.05 0.92 4.87
123 4.990020e-04 112040 2.70 1.06 0.94 4.88
124 8.483034e-04 120767 2.71 1.04 0.94 4.90
125 1.197605e-03 127019 2.69 1.06 0.92 4.88
126 1.546906e-03 136295 2.72 1.06 0.91 4.89
127 3.175467e-04 113425 2.71 1.07 0.93 4.88
128 6.350934e-04 107815 2.71 1.08 0.93 4.87
129 9.526402e-04 100298 2.74 1.08 0.94 4.85
130 1.270187e-03 97048 2.82 1.05 0.92 4.87
131 2.079175e-04 98750 2.76 1.04 0.91 4.88
132 4.990020e-04 98235 2.77 1.04 0.91 4.87
133 7.900865e-04 101254 2.77 1.04 0.90 4.93
134 1.081171e-03 139589 2.81 1.04 0.89 4.93
135 9.975062e-04 134921 2.77 1.06 0.91 4.74
136 4.488778e-03 80355 2.76 1.08 0.93 4.77
137 7.980050e-03 80396 2.73 1.08 0.94 4.81
138 1.147132e-02 82183 2.72 1.08 0.93 4.82
139 1.496259e-02 79709 2.73 1.07 0.91 4.79
140 1.496259e-03 90781 2.71 1.06 0.92 4.75
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) QBEFRU PBEFRU PSOCOLA PSOORA PSTIM
4.969e-02 -2.641e-08 -5.549e-03 -1.813e-02 1.626e-02 -5.134e-03
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.0029257 -0.0014690 -0.0005304 0.0007194 0.0117215
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 4.969e-02 2.589e-02 1.919 0.0571 .
QBEFRU -2.641e-08 5.444e-09 -4.851 3.35e-06 ***
PBEFRU -5.549e-03 3.346e-03 -1.658 0.0996 .
PSOCOLA -1.813e-02 1.277e-02 -1.419 0.1581
PSOORA 1.626e-02 1.190e-02 1.367 0.1740
PSTIM -5.134e-03 3.246e-03 -1.582 0.1161
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.002372 on 134 degrees of freedom
Multiple R-squared: 0.167, Adjusted R-squared: 0.1359
F-statistic: 5.373 on 5 and 134 DF, p-value: 0.0001553
> 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,] 2.249055e-02 4.498110e-02 0.9775095
[2,] 7.781734e-03 1.556347e-02 0.9922183
[3,] 4.528563e-03 9.057127e-03 0.9954714
[4,] 1.435382e-03 2.870764e-03 0.9985646
[5,] 1.714077e-03 3.428155e-03 0.9982859
[6,] 6.291281e-04 1.258256e-03 0.9993709
[7,] 1.749397e-04 3.498795e-04 0.9998251
[8,] 5.417417e-05 1.083483e-04 0.9999458
[9,] 1.412303e-05 2.824605e-05 0.9999859
[10,] 6.255902e-06 1.251180e-05 0.9999937
[11,] 1.580557e-06 3.161114e-06 0.9999984
[12,] 4.156499e-07 8.312997e-07 0.9999996
[13,] 9.731326e-08 1.946265e-07 0.9999999
[14,] 1.181945e-07 2.363891e-07 0.9999999
[15,] 3.102387e-08 6.204773e-08 1.0000000
[16,] 9.640975e-09 1.928195e-08 1.0000000
[17,] 2.289110e-09 4.578220e-09 1.0000000
[18,] 2.082502e-09 4.165004e-09 1.0000000
[19,] 6.136343e-10 1.227269e-09 1.0000000
[20,] 1.837396e-10 3.674792e-10 1.0000000
[21,] 4.385586e-11 8.771171e-11 1.0000000
[22,] 1.021223e-11 2.042446e-11 1.0000000
[23,] 2.031910e-11 4.063820e-11 1.0000000
[24,] 7.424573e-08 1.484915e-07 0.9999999
[25,] 9.090265e-05 1.818053e-04 0.9999091
[26,] 4.508451e-01 9.016902e-01 0.5491549
[27,] 4.065369e-01 8.130737e-01 0.5934631
[28,] 3.616625e-01 7.233251e-01 0.6383375
[29,] 3.164091e-01 6.328183e-01 0.6835909
[30,] 2.975887e-01 5.951773e-01 0.7024113
[31,] 2.972276e-01 5.944551e-01 0.7027724
[32,] 2.526222e-01 5.052444e-01 0.7473778
[33,] 2.295249e-01 4.590497e-01 0.7704751
[34,] 2.303379e-01 4.606758e-01 0.7696621
[35,] 2.346200e-01 4.692399e-01 0.7653800
[36,] 1.944888e-01 3.889776e-01 0.8055112
[37,] 1.587180e-01 3.174361e-01 0.8412820
[38,] 1.301136e-01 2.602273e-01 0.8698864
[39,] 1.126075e-01 2.252150e-01 0.8873925
[40,] 1.056011e-01 2.112022e-01 0.8943989
[41,] 9.416864e-02 1.883373e-01 0.9058314
[42,] 8.241813e-02 1.648363e-01 0.9175819
[43,] 6.657778e-02 1.331556e-01 0.9334222
[44,] 7.573263e-02 1.514653e-01 0.9242674
[45,] 6.897120e-02 1.379424e-01 0.9310288
[46,] 5.405126e-02 1.081025e-01 0.9459487
[47,] 4.151350e-02 8.302700e-02 0.9584865
[48,] 3.317643e-02 6.635285e-02 0.9668236
[49,] 2.919944e-02 5.839887e-02 0.9708006
[50,] 2.376711e-02 4.753422e-02 0.9762329
[51,] 1.737371e-02 3.474742e-02 0.9826263
[52,] 1.378513e-02 2.757026e-02 0.9862149
[53,] 1.041812e-02 2.083624e-02 0.9895819
[54,] 9.412259e-03 1.882452e-02 0.9905877
[55,] 6.832296e-03 1.366459e-02 0.9931677
[56,] 4.915925e-03 9.831851e-03 0.9950841
[57,] 3.722651e-03 7.445302e-03 0.9962773
[58,] 3.261717e-03 6.523433e-03 0.9967383
[59,] 2.480002e-03 4.960004e-03 0.9975200
[60,] 1.834620e-03 3.669240e-03 0.9981654
[61,] 1.243144e-03 2.486289e-03 0.9987569
[62,] 9.878372e-04 1.975674e-03 0.9990122
[63,] 7.171434e-04 1.434287e-03 0.9992829
[64,] 5.078579e-04 1.015716e-03 0.9994921
[65,] 3.314610e-04 6.629220e-04 0.9996685
[66,] 2.348986e-04 4.697973e-04 0.9997651
[67,] 1.808872e-04 3.617744e-04 0.9998191
[68,] 1.404997e-04 2.809994e-04 0.9998595
[69,] 9.712286e-05 1.942457e-04 0.9999029
[70,] 6.629575e-05 1.325915e-04 0.9999337
[71,] 4.957418e-05 9.914836e-05 0.9999504
[72,] 3.562167e-05 7.124333e-05 0.9999644
[73,] 2.336442e-05 4.672884e-05 0.9999766
[74,] 1.565370e-05 3.130739e-05 0.9999843
[75,] 1.024627e-05 2.049254e-05 0.9999898
[76,] 1.100545e-05 2.201090e-05 0.9999890
[77,] 1.770775e-04 3.541550e-04 0.9998229
[78,] 6.570997e-02 1.314199e-01 0.9342900
[79,] 6.705773e-02 1.341155e-01 0.9329423
[80,] 5.330114e-02 1.066023e-01 0.9466989
[81,] 4.161108e-02 8.322217e-02 0.9583889
[82,] 4.151691e-02 8.303382e-02 0.9584831
[83,] 8.420636e-02 1.684127e-01 0.9157936
[84,] 7.733369e-02 1.546674e-01 0.9226663
[85,] 6.012659e-02 1.202532e-01 0.9398734
[86,] 4.982390e-02 9.964780e-02 0.9501761
[87,] 5.770283e-02 1.154057e-01 0.9422972
[88,] 4.825721e-02 9.651442e-02 0.9517428
[89,] 3.796287e-02 7.592574e-02 0.9620371
[90,] 3.060172e-02 6.120345e-02 0.9693983
[91,] 2.667760e-02 5.335520e-02 0.9733224
[92,] 2.251454e-02 4.502908e-02 0.9774855
[93,] 1.728380e-02 3.456761e-02 0.9827162
[94,] 1.230686e-02 2.461372e-02 0.9876931
[95,] 8.615343e-03 1.723069e-02 0.9913847
[96,] 7.448229e-03 1.489646e-02 0.9925518
[97,] 6.008709e-03 1.201742e-02 0.9939913
[98,] 4.304990e-03 8.609979e-03 0.9956950
[99,] 2.858520e-03 5.717041e-03 0.9971415
[100,] 2.766888e-03 5.533777e-03 0.9972331
[101,] 1.967480e-03 3.934959e-03 0.9980325
[102,] 1.286901e-03 2.573802e-03 0.9987131
[103,] 1.332243e-03 2.664487e-03 0.9986678
[104,] 1.576549e-03 3.153098e-03 0.9984235
[105,] 1.049493e-03 2.098985e-03 0.9989505
[106,] 7.329716e-04 1.465943e-03 0.9992670
[107,] 4.992992e-04 9.985983e-04 0.9995007
[108,] 3.661762e-04 7.323525e-04 0.9996338
[109,] 5.590614e-04 1.118123e-03 0.9994409
[110,] 4.079212e-03 8.158425e-03 0.9959208
[111,] 4.762907e-03 9.525814e-03 0.9952371
[112,] 3.523940e-03 7.047879e-03 0.9964761
[113,] 2.993154e-03 5.986308e-03 0.9970068
[114,] 1.868752e-03 3.737505e-03 0.9981312
[115,] 1.070227e-03 2.140453e-03 0.9989298
[116,] 4.926736e-02 9.853471e-02 0.9507326
[117,] 5.176782e-02 1.035356e-01 0.9482322
[118,] 4.086476e-02 8.172952e-02 0.9591352
[119,] 2.832419e-02 5.664837e-02 0.9716758
[120,] 4.218744e-02 8.437488e-02 0.9578126
[121,] 4.963545e-02 9.927091e-02 0.9503645
[122,] 6.912162e-02 1.382432e-01 0.9308784
[123,] 4.016322e-02 8.032645e-02 0.9598368
> postscript(file="/var/wessaorg/rcomp/tmp/14zyt1324665240.ps",horizontal=F,onefile=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/wessaorg/rcomp/tmp/2ap4g1324665240.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/3t3gy1324665240.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4bgbh1324665240.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5m4nr1324665240.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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 = 140
Frequency = 1
1 2 3 4 5
-2.007021e-04 -8.705145e-04 1.355836e-04 9.741529e-04 -1.095580e-03
6 7 8 9 10
1.203969e-04 1.132591e-03 9.627593e-04 3.740880e-04 2.017414e-03
11 12 13 14 15
7.184004e-04 8.965227e-04 -1.511440e-03 -1.172755e-03 -1.147226e-03
16 17 18 19 20
1.410281e-04 -5.445143e-04 -1.461120e-03 -1.095211e-03 -1.329317e-03
21 22 23 24 25
-1.115755e-03 -2.698559e-03 -2.003414e-03 -1.646848e-03 -6.443329e-04
26 27 28 29 30
-1.849353e-03 -1.649523e-03 -1.518706e-03 -3.156912e-04 -6.484583e-04
31 32 33 34 35
-1.498711e-05 2.322740e-03 5.867415e-03 9.848175e-03 -2.016758e-03
36 37 38 39 40
-8.879048e-04 7.312752e-04 2.037799e-03 -2.049108e-03 -3.672465e-04
41 42 43 44 45
9.536493e-04 1.973664e-03 2.764118e-03 -2.757282e-04 7.224695e-04
46 47 48 49 50
9.275624e-04 1.309245e-03 -3.761219e-04 -1.228028e-04 1.497246e-04
51 52 53 54 55
1.049354e-03 -1.610310e-03 -1.127263e-03 4.505226e-04 6.041161e-04
56 57 58 59 60
1.236642e-03 -8.828598e-04 -8.440913e-04 4.025446e-05 1.377658e-03
61 62 63 64 65
9.888237e-04 1.912906e-03 4.172606e-04 -9.890900e-05 -5.124608e-04
66 67 68 69 70
-1.717832e-03 -1.460846e-03 -1.682196e-03 -1.183428e-03 -2.256375e-03
71 72 73 74 75
-1.926370e-03 -1.913354e-03 -1.134039e-03 -1.916938e-03 -2.303198e-03
76 77 78 79 80
-2.366975e-03 -1.617302e-03 -1.181835e-03 -1.811796e-03 -1.570060e-03
81 82 83 84 85
-7.319894e-04 2.435590e-04 1.209549e-04 2.187345e-03 5.373727e-03
86 87 88 89 90
9.358925e-03 -2.925650e-03 -1.196593e-03 1.642898e-04 1.948847e-03
91 92 93 94 95
4.045434e-03 -2.339420e-03 -5.935873e-04 5.944753e-04 2.191995e-03
96 97 98 99 100
-2.128648e-03 -5.549631e-04 -1.033096e-05 5.940067e-04 -1.530929e-03
101 102 103 104 105
-1.385838e-03 -9.021843e-04 -1.030335e-04 2.035344e-03 -1.492767e-03
106 107 108 109 110
-1.272209e-03 6.036134e-04 3.545988e-03 -2.707972e-04 1.544937e-04
111 112 113 114 115
2.418590e-03 1.308448e-03 -4.412546e-04 -5.682489e-04 -5.162073e-04
116 117 118 119 120
-3.893291e-04 -6.767399e-04 -8.159944e-04 -5.875521e-05 -1.348198e-03
121 122 123 124 125
-1.243696e-03 -2.333053e-03 -2.261649e-03 -1.886190e-03 -8.976997e-04
126 127 128 129 130
7.701357e-05 -2.007172e-03 -1.707881e-03 -1.687698e-03 -1.127941e-03
131 132 133 134 135
-2.445496e-03 -2.163867e-03 -1.322380e-03 3.657563e-04 -1.001375e-03
136 137 138 139 140
1.184556e-03 4.553208e-03 8.250139e-03 1.172149e-02 -2.112629e-03
> postscript(file="/var/wessaorg/rcomp/tmp/6tlto1324665240.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 140
Frequency = 1
lag(myerror, k = 1) myerror
0 -2.007021e-04 NA
1 -8.705145e-04 -2.007021e-04
2 1.355836e-04 -8.705145e-04
3 9.741529e-04 1.355836e-04
4 -1.095580e-03 9.741529e-04
5 1.203969e-04 -1.095580e-03
6 1.132591e-03 1.203969e-04
7 9.627593e-04 1.132591e-03
8 3.740880e-04 9.627593e-04
9 2.017414e-03 3.740880e-04
10 7.184004e-04 2.017414e-03
11 8.965227e-04 7.184004e-04
12 -1.511440e-03 8.965227e-04
13 -1.172755e-03 -1.511440e-03
14 -1.147226e-03 -1.172755e-03
15 1.410281e-04 -1.147226e-03
16 -5.445143e-04 1.410281e-04
17 -1.461120e-03 -5.445143e-04
18 -1.095211e-03 -1.461120e-03
19 -1.329317e-03 -1.095211e-03
20 -1.115755e-03 -1.329317e-03
21 -2.698559e-03 -1.115755e-03
22 -2.003414e-03 -2.698559e-03
23 -1.646848e-03 -2.003414e-03
24 -6.443329e-04 -1.646848e-03
25 -1.849353e-03 -6.443329e-04
26 -1.649523e-03 -1.849353e-03
27 -1.518706e-03 -1.649523e-03
28 -3.156912e-04 -1.518706e-03
29 -6.484583e-04 -3.156912e-04
30 -1.498711e-05 -6.484583e-04
31 2.322740e-03 -1.498711e-05
32 5.867415e-03 2.322740e-03
33 9.848175e-03 5.867415e-03
34 -2.016758e-03 9.848175e-03
35 -8.879048e-04 -2.016758e-03
36 7.312752e-04 -8.879048e-04
37 2.037799e-03 7.312752e-04
38 -2.049108e-03 2.037799e-03
39 -3.672465e-04 -2.049108e-03
40 9.536493e-04 -3.672465e-04
41 1.973664e-03 9.536493e-04
42 2.764118e-03 1.973664e-03
43 -2.757282e-04 2.764118e-03
44 7.224695e-04 -2.757282e-04
45 9.275624e-04 7.224695e-04
46 1.309245e-03 9.275624e-04
47 -3.761219e-04 1.309245e-03
48 -1.228028e-04 -3.761219e-04
49 1.497246e-04 -1.228028e-04
50 1.049354e-03 1.497246e-04
51 -1.610310e-03 1.049354e-03
52 -1.127263e-03 -1.610310e-03
53 4.505226e-04 -1.127263e-03
54 6.041161e-04 4.505226e-04
55 1.236642e-03 6.041161e-04
56 -8.828598e-04 1.236642e-03
57 -8.440913e-04 -8.828598e-04
58 4.025446e-05 -8.440913e-04
59 1.377658e-03 4.025446e-05
60 9.888237e-04 1.377658e-03
61 1.912906e-03 9.888237e-04
62 4.172606e-04 1.912906e-03
63 -9.890900e-05 4.172606e-04
64 -5.124608e-04 -9.890900e-05
65 -1.717832e-03 -5.124608e-04
66 -1.460846e-03 -1.717832e-03
67 -1.682196e-03 -1.460846e-03
68 -1.183428e-03 -1.682196e-03
69 -2.256375e-03 -1.183428e-03
70 -1.926370e-03 -2.256375e-03
71 -1.913354e-03 -1.926370e-03
72 -1.134039e-03 -1.913354e-03
73 -1.916938e-03 -1.134039e-03
74 -2.303198e-03 -1.916938e-03
75 -2.366975e-03 -2.303198e-03
76 -1.617302e-03 -2.366975e-03
77 -1.181835e-03 -1.617302e-03
78 -1.811796e-03 -1.181835e-03
79 -1.570060e-03 -1.811796e-03
80 -7.319894e-04 -1.570060e-03
81 2.435590e-04 -7.319894e-04
82 1.209549e-04 2.435590e-04
83 2.187345e-03 1.209549e-04
84 5.373727e-03 2.187345e-03
85 9.358925e-03 5.373727e-03
86 -2.925650e-03 9.358925e-03
87 -1.196593e-03 -2.925650e-03
88 1.642898e-04 -1.196593e-03
89 1.948847e-03 1.642898e-04
90 4.045434e-03 1.948847e-03
91 -2.339420e-03 4.045434e-03
92 -5.935873e-04 -2.339420e-03
93 5.944753e-04 -5.935873e-04
94 2.191995e-03 5.944753e-04
95 -2.128648e-03 2.191995e-03
96 -5.549631e-04 -2.128648e-03
97 -1.033096e-05 -5.549631e-04
98 5.940067e-04 -1.033096e-05
99 -1.530929e-03 5.940067e-04
100 -1.385838e-03 -1.530929e-03
101 -9.021843e-04 -1.385838e-03
102 -1.030335e-04 -9.021843e-04
103 2.035344e-03 -1.030335e-04
104 -1.492767e-03 2.035344e-03
105 -1.272209e-03 -1.492767e-03
106 6.036134e-04 -1.272209e-03
107 3.545988e-03 6.036134e-04
108 -2.707972e-04 3.545988e-03
109 1.544937e-04 -2.707972e-04
110 2.418590e-03 1.544937e-04
111 1.308448e-03 2.418590e-03
112 -4.412546e-04 1.308448e-03
113 -5.682489e-04 -4.412546e-04
114 -5.162073e-04 -5.682489e-04
115 -3.893291e-04 -5.162073e-04
116 -6.767399e-04 -3.893291e-04
117 -8.159944e-04 -6.767399e-04
118 -5.875521e-05 -8.159944e-04
119 -1.348198e-03 -5.875521e-05
120 -1.243696e-03 -1.348198e-03
121 -2.333053e-03 -1.243696e-03
122 -2.261649e-03 -2.333053e-03
123 -1.886190e-03 -2.261649e-03
124 -8.976997e-04 -1.886190e-03
125 7.701357e-05 -8.976997e-04
126 -2.007172e-03 7.701357e-05
127 -1.707881e-03 -2.007172e-03
128 -1.687698e-03 -1.707881e-03
129 -1.127941e-03 -1.687698e-03
130 -2.445496e-03 -1.127941e-03
131 -2.163867e-03 -2.445496e-03
132 -1.322380e-03 -2.163867e-03
133 3.657563e-04 -1.322380e-03
134 -1.001375e-03 3.657563e-04
135 1.184556e-03 -1.001375e-03
136 4.553208e-03 1.184556e-03
137 8.250139e-03 4.553208e-03
138 1.172149e-02 8.250139e-03
139 -2.112629e-03 1.172149e-02
140 NA -2.112629e-03
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -8.705145e-04 -2.007021e-04
[2,] 1.355836e-04 -8.705145e-04
[3,] 9.741529e-04 1.355836e-04
[4,] -1.095580e-03 9.741529e-04
[5,] 1.203969e-04 -1.095580e-03
[6,] 1.132591e-03 1.203969e-04
[7,] 9.627593e-04 1.132591e-03
[8,] 3.740880e-04 9.627593e-04
[9,] 2.017414e-03 3.740880e-04
[10,] 7.184004e-04 2.017414e-03
[11,] 8.965227e-04 7.184004e-04
[12,] -1.511440e-03 8.965227e-04
[13,] -1.172755e-03 -1.511440e-03
[14,] -1.147226e-03 -1.172755e-03
[15,] 1.410281e-04 -1.147226e-03
[16,] -5.445143e-04 1.410281e-04
[17,] -1.461120e-03 -5.445143e-04
[18,] -1.095211e-03 -1.461120e-03
[19,] -1.329317e-03 -1.095211e-03
[20,] -1.115755e-03 -1.329317e-03
[21,] -2.698559e-03 -1.115755e-03
[22,] -2.003414e-03 -2.698559e-03
[23,] -1.646848e-03 -2.003414e-03
[24,] -6.443329e-04 -1.646848e-03
[25,] -1.849353e-03 -6.443329e-04
[26,] -1.649523e-03 -1.849353e-03
[27,] -1.518706e-03 -1.649523e-03
[28,] -3.156912e-04 -1.518706e-03
[29,] -6.484583e-04 -3.156912e-04
[30,] -1.498711e-05 -6.484583e-04
[31,] 2.322740e-03 -1.498711e-05
[32,] 5.867415e-03 2.322740e-03
[33,] 9.848175e-03 5.867415e-03
[34,] -2.016758e-03 9.848175e-03
[35,] -8.879048e-04 -2.016758e-03
[36,] 7.312752e-04 -8.879048e-04
[37,] 2.037799e-03 7.312752e-04
[38,] -2.049108e-03 2.037799e-03
[39,] -3.672465e-04 -2.049108e-03
[40,] 9.536493e-04 -3.672465e-04
[41,] 1.973664e-03 9.536493e-04
[42,] 2.764118e-03 1.973664e-03
[43,] -2.757282e-04 2.764118e-03
[44,] 7.224695e-04 -2.757282e-04
[45,] 9.275624e-04 7.224695e-04
[46,] 1.309245e-03 9.275624e-04
[47,] -3.761219e-04 1.309245e-03
[48,] -1.228028e-04 -3.761219e-04
[49,] 1.497246e-04 -1.228028e-04
[50,] 1.049354e-03 1.497246e-04
[51,] -1.610310e-03 1.049354e-03
[52,] -1.127263e-03 -1.610310e-03
[53,] 4.505226e-04 -1.127263e-03
[54,] 6.041161e-04 4.505226e-04
[55,] 1.236642e-03 6.041161e-04
[56,] -8.828598e-04 1.236642e-03
[57,] -8.440913e-04 -8.828598e-04
[58,] 4.025446e-05 -8.440913e-04
[59,] 1.377658e-03 4.025446e-05
[60,] 9.888237e-04 1.377658e-03
[61,] 1.912906e-03 9.888237e-04
[62,] 4.172606e-04 1.912906e-03
[63,] -9.890900e-05 4.172606e-04
[64,] -5.124608e-04 -9.890900e-05
[65,] -1.717832e-03 -5.124608e-04
[66,] -1.460846e-03 -1.717832e-03
[67,] -1.682196e-03 -1.460846e-03
[68,] -1.183428e-03 -1.682196e-03
[69,] -2.256375e-03 -1.183428e-03
[70,] -1.926370e-03 -2.256375e-03
[71,] -1.913354e-03 -1.926370e-03
[72,] -1.134039e-03 -1.913354e-03
[73,] -1.916938e-03 -1.134039e-03
[74,] -2.303198e-03 -1.916938e-03
[75,] -2.366975e-03 -2.303198e-03
[76,] -1.617302e-03 -2.366975e-03
[77,] -1.181835e-03 -1.617302e-03
[78,] -1.811796e-03 -1.181835e-03
[79,] -1.570060e-03 -1.811796e-03
[80,] -7.319894e-04 -1.570060e-03
[81,] 2.435590e-04 -7.319894e-04
[82,] 1.209549e-04 2.435590e-04
[83,] 2.187345e-03 1.209549e-04
[84,] 5.373727e-03 2.187345e-03
[85,] 9.358925e-03 5.373727e-03
[86,] -2.925650e-03 9.358925e-03
[87,] -1.196593e-03 -2.925650e-03
[88,] 1.642898e-04 -1.196593e-03
[89,] 1.948847e-03 1.642898e-04
[90,] 4.045434e-03 1.948847e-03
[91,] -2.339420e-03 4.045434e-03
[92,] -5.935873e-04 -2.339420e-03
[93,] 5.944753e-04 -5.935873e-04
[94,] 2.191995e-03 5.944753e-04
[95,] -2.128648e-03 2.191995e-03
[96,] -5.549631e-04 -2.128648e-03
[97,] -1.033096e-05 -5.549631e-04
[98,] 5.940067e-04 -1.033096e-05
[99,] -1.530929e-03 5.940067e-04
[100,] -1.385838e-03 -1.530929e-03
[101,] -9.021843e-04 -1.385838e-03
[102,] -1.030335e-04 -9.021843e-04
[103,] 2.035344e-03 -1.030335e-04
[104,] -1.492767e-03 2.035344e-03
[105,] -1.272209e-03 -1.492767e-03
[106,] 6.036134e-04 -1.272209e-03
[107,] 3.545988e-03 6.036134e-04
[108,] -2.707972e-04 3.545988e-03
[109,] 1.544937e-04 -2.707972e-04
[110,] 2.418590e-03 1.544937e-04
[111,] 1.308448e-03 2.418590e-03
[112,] -4.412546e-04 1.308448e-03
[113,] -5.682489e-04 -4.412546e-04
[114,] -5.162073e-04 -5.682489e-04
[115,] -3.893291e-04 -5.162073e-04
[116,] -6.767399e-04 -3.893291e-04
[117,] -8.159944e-04 -6.767399e-04
[118,] -5.875521e-05 -8.159944e-04
[119,] -1.348198e-03 -5.875521e-05
[120,] -1.243696e-03 -1.348198e-03
[121,] -2.333053e-03 -1.243696e-03
[122,] -2.261649e-03 -2.333053e-03
[123,] -1.886190e-03 -2.261649e-03
[124,] -8.976997e-04 -1.886190e-03
[125,] 7.701357e-05 -8.976997e-04
[126,] -2.007172e-03 7.701357e-05
[127,] -1.707881e-03 -2.007172e-03
[128,] -1.687698e-03 -1.707881e-03
[129,] -1.127941e-03 -1.687698e-03
[130,] -2.445496e-03 -1.127941e-03
[131,] -2.163867e-03 -2.445496e-03
[132,] -1.322380e-03 -2.163867e-03
[133,] 3.657563e-04 -1.322380e-03
[134,] -1.001375e-03 3.657563e-04
[135,] 1.184556e-03 -1.001375e-03
[136,] 4.553208e-03 1.184556e-03
[137,] 8.250139e-03 4.553208e-03
[138,] 1.172149e-02 8.250139e-03
[139,] -2.112629e-03 1.172149e-02
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -8.705145e-04 -2.007021e-04
2 1.355836e-04 -8.705145e-04
3 9.741529e-04 1.355836e-04
4 -1.095580e-03 9.741529e-04
5 1.203969e-04 -1.095580e-03
6 1.132591e-03 1.203969e-04
7 9.627593e-04 1.132591e-03
8 3.740880e-04 9.627593e-04
9 2.017414e-03 3.740880e-04
10 7.184004e-04 2.017414e-03
11 8.965227e-04 7.184004e-04
12 -1.511440e-03 8.965227e-04
13 -1.172755e-03 -1.511440e-03
14 -1.147226e-03 -1.172755e-03
15 1.410281e-04 -1.147226e-03
16 -5.445143e-04 1.410281e-04
17 -1.461120e-03 -5.445143e-04
18 -1.095211e-03 -1.461120e-03
19 -1.329317e-03 -1.095211e-03
20 -1.115755e-03 -1.329317e-03
21 -2.698559e-03 -1.115755e-03
22 -2.003414e-03 -2.698559e-03
23 -1.646848e-03 -2.003414e-03
24 -6.443329e-04 -1.646848e-03
25 -1.849353e-03 -6.443329e-04
26 -1.649523e-03 -1.849353e-03
27 -1.518706e-03 -1.649523e-03
28 -3.156912e-04 -1.518706e-03
29 -6.484583e-04 -3.156912e-04
30 -1.498711e-05 -6.484583e-04
31 2.322740e-03 -1.498711e-05
32 5.867415e-03 2.322740e-03
33 9.848175e-03 5.867415e-03
34 -2.016758e-03 9.848175e-03
35 -8.879048e-04 -2.016758e-03
36 7.312752e-04 -8.879048e-04
37 2.037799e-03 7.312752e-04
38 -2.049108e-03 2.037799e-03
39 -3.672465e-04 -2.049108e-03
40 9.536493e-04 -3.672465e-04
41 1.973664e-03 9.536493e-04
42 2.764118e-03 1.973664e-03
43 -2.757282e-04 2.764118e-03
44 7.224695e-04 -2.757282e-04
45 9.275624e-04 7.224695e-04
46 1.309245e-03 9.275624e-04
47 -3.761219e-04 1.309245e-03
48 -1.228028e-04 -3.761219e-04
49 1.497246e-04 -1.228028e-04
50 1.049354e-03 1.497246e-04
51 -1.610310e-03 1.049354e-03
52 -1.127263e-03 -1.610310e-03
53 4.505226e-04 -1.127263e-03
54 6.041161e-04 4.505226e-04
55 1.236642e-03 6.041161e-04
56 -8.828598e-04 1.236642e-03
57 -8.440913e-04 -8.828598e-04
58 4.025446e-05 -8.440913e-04
59 1.377658e-03 4.025446e-05
60 9.888237e-04 1.377658e-03
61 1.912906e-03 9.888237e-04
62 4.172606e-04 1.912906e-03
63 -9.890900e-05 4.172606e-04
64 -5.124608e-04 -9.890900e-05
65 -1.717832e-03 -5.124608e-04
66 -1.460846e-03 -1.717832e-03
67 -1.682196e-03 -1.460846e-03
68 -1.183428e-03 -1.682196e-03
69 -2.256375e-03 -1.183428e-03
70 -1.926370e-03 -2.256375e-03
71 -1.913354e-03 -1.926370e-03
72 -1.134039e-03 -1.913354e-03
73 -1.916938e-03 -1.134039e-03
74 -2.303198e-03 -1.916938e-03
75 -2.366975e-03 -2.303198e-03
76 -1.617302e-03 -2.366975e-03
77 -1.181835e-03 -1.617302e-03
78 -1.811796e-03 -1.181835e-03
79 -1.570060e-03 -1.811796e-03
80 -7.319894e-04 -1.570060e-03
81 2.435590e-04 -7.319894e-04
82 1.209549e-04 2.435590e-04
83 2.187345e-03 1.209549e-04
84 5.373727e-03 2.187345e-03
85 9.358925e-03 5.373727e-03
86 -2.925650e-03 9.358925e-03
87 -1.196593e-03 -2.925650e-03
88 1.642898e-04 -1.196593e-03
89 1.948847e-03 1.642898e-04
90 4.045434e-03 1.948847e-03
91 -2.339420e-03 4.045434e-03
92 -5.935873e-04 -2.339420e-03
93 5.944753e-04 -5.935873e-04
94 2.191995e-03 5.944753e-04
95 -2.128648e-03 2.191995e-03
96 -5.549631e-04 -2.128648e-03
97 -1.033096e-05 -5.549631e-04
98 5.940067e-04 -1.033096e-05
99 -1.530929e-03 5.940067e-04
100 -1.385838e-03 -1.530929e-03
101 -9.021843e-04 -1.385838e-03
102 -1.030335e-04 -9.021843e-04
103 2.035344e-03 -1.030335e-04
104 -1.492767e-03 2.035344e-03
105 -1.272209e-03 -1.492767e-03
106 6.036134e-04 -1.272209e-03
107 3.545988e-03 6.036134e-04
108 -2.707972e-04 3.545988e-03
109 1.544937e-04 -2.707972e-04
110 2.418590e-03 1.544937e-04
111 1.308448e-03 2.418590e-03
112 -4.412546e-04 1.308448e-03
113 -5.682489e-04 -4.412546e-04
114 -5.162073e-04 -5.682489e-04
115 -3.893291e-04 -5.162073e-04
116 -6.767399e-04 -3.893291e-04
117 -8.159944e-04 -6.767399e-04
118 -5.875521e-05 -8.159944e-04
119 -1.348198e-03 -5.875521e-05
120 -1.243696e-03 -1.348198e-03
121 -2.333053e-03 -1.243696e-03
122 -2.261649e-03 -2.333053e-03
123 -1.886190e-03 -2.261649e-03
124 -8.976997e-04 -1.886190e-03
125 7.701357e-05 -8.976997e-04
126 -2.007172e-03 7.701357e-05
127 -1.707881e-03 -2.007172e-03
128 -1.687698e-03 -1.707881e-03
129 -1.127941e-03 -1.687698e-03
130 -2.445496e-03 -1.127941e-03
131 -2.163867e-03 -2.445496e-03
132 -1.322380e-03 -2.163867e-03
133 3.657563e-04 -1.322380e-03
134 -1.001375e-03 3.657563e-04
135 1.184556e-03 -1.001375e-03
136 4.553208e-03 1.184556e-03
137 8.250139e-03 4.553208e-03
138 1.172149e-02 8.250139e-03
139 -2.112629e-03 1.172149e-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/wessaorg/rcomp/tmp/7j7ua1324665240.ps",horizontal=F,onefile=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/wessaorg/rcomp/tmp/864zb1324665240.ps",horizontal=F,onefile=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/wessaorg/rcomp/tmp/94x4f1324665240.ps",horizontal=F,onefile=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/wessaorg/rcomp/tmp/10n8wg1324665240.ps",horizontal=F,onefile=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/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/11bcfn1324665240.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/12tq4f1324665240.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$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$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/13us6n1324665240.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/14d0cw1324665240.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/wessaorg/rcomp/tmp/15776e1324665240.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/wessaorg/rcomp/tmp/16c6pg1324665240.tab")
+ }
>
> try(system("convert tmp/14zyt1324665240.ps tmp/14zyt1324665240.png",intern=TRUE))
character(0)
> try(system("convert tmp/2ap4g1324665240.ps tmp/2ap4g1324665240.png",intern=TRUE))
character(0)
> try(system("convert tmp/3t3gy1324665240.ps tmp/3t3gy1324665240.png",intern=TRUE))
character(0)
> try(system("convert tmp/4bgbh1324665240.ps tmp/4bgbh1324665240.png",intern=TRUE))
character(0)
> try(system("convert tmp/5m4nr1324665240.ps tmp/5m4nr1324665240.png",intern=TRUE))
character(0)
> try(system("convert tmp/6tlto1324665240.ps tmp/6tlto1324665240.png",intern=TRUE))
character(0)
> try(system("convert tmp/7j7ua1324665240.ps tmp/7j7ua1324665240.png",intern=TRUE))
character(0)
> try(system("convert tmp/864zb1324665240.ps tmp/864zb1324665240.png",intern=TRUE))
character(0)
> try(system("convert tmp/94x4f1324665240.ps tmp/94x4f1324665240.png",intern=TRUE))
character(0)
> try(system("convert tmp/10n8wg1324665240.ps tmp/10n8wg1324665240.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
4.507 0.810 5.322