R version 2.12.0 (2010-10-15)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
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> x <- array(list(26
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+ ,4)
+ ,dim=c(7
+ ,162)
+ ,dimnames=list(c('I1'
+ ,'I2'
+ ,'I3'
+ ,'E1'
+ ,'E2'
+ ,'E3'
+ ,'A')
+ ,1:162))
> y <- array(NA,dim=c(7,162),dimnames=list(c('I1','I2','I3','E1','E2','E3','A'),1:162))
> 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 = '6'
> #'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
> 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
E3 I1 I2 I3 E1 E2 A
1 23 26 21 21 23 17 4
2 20 20 16 15 24 17 4
3 20 19 19 18 22 18 6
4 21 19 18 11 20 21 8
5 24 20 16 8 24 20 8
6 22 25 23 19 27 28 4
7 23 25 17 4 28 19 4
8 20 22 12 20 27 22 8
9 25 26 19 16 24 16 5
10 23 22 16 14 23 18 4
11 27 17 19 10 24 25 4
12 27 22 20 13 27 17 4
13 22 19 13 14 27 14 4
14 24 24 20 8 28 11 4
15 25 26 27 23 27 27 4
16 22 21 17 11 23 20 8
17 28 13 8 9 24 22 4
18 28 26 25 24 28 22 4
19 27 20 26 5 27 21 4
20 25 22 13 15 25 23 8
21 16 14 19 5 19 17 4
22 28 21 15 19 24 24 7
23 21 7 5 6 20 14 4
24 24 23 16 13 28 17 4
25 27 17 14 11 26 23 5
26 14 25 24 17 23 24 4
27 14 25 24 17 23 24 4
28 27 19 9 5 20 8 4
29 20 20 19 9 11 22 4
30 21 23 19 15 24 23 4
31 22 22 25 17 25 25 4
32 21 22 19 17 23 21 4
33 12 21 18 20 18 24 15
34 20 15 15 12 20 15 10
35 24 20 12 7 20 22 4
36 19 22 21 16 24 21 8
37 28 18 12 7 23 25 4
38 23 20 15 14 25 16 4
39 27 28 28 24 28 28 4
40 22 22 25 15 26 23 4
41 27 18 19 15 26 21 7
42 26 23 20 10 23 21 4
43 22 20 24 14 22 26 6
44 21 25 26 18 24 22 5
45 19 26 25 12 21 21 4
46 24 15 12 9 20 18 16
47 19 17 12 9 22 12 5
48 26 23 15 8 20 25 12
49 22 21 17 18 25 17 6
50 28 13 14 10 20 24 9
51 21 18 16 17 22 15 9
52 23 19 11 14 23 13 4
53 28 22 20 16 25 26 5
54 10 16 11 10 23 16 4
55 24 24 22 19 23 24 4
56 21 18 20 10 22 21 5
57 21 20 19 14 24 20 4
58 24 24 17 10 25 14 4
59 24 14 21 4 21 25 4
60 25 22 23 19 12 25 5
61 25 24 18 9 17 20 4
62 23 18 17 12 20 22 6
63 21 21 27 16 23 20 4
64 16 23 25 11 23 26 4
65 17 17 19 18 20 18 18
66 25 22 22 11 28 22 4
67 24 24 24 24 24 24 6
68 23 21 20 17 24 17 4
69 25 22 19 18 24 24 4
70 23 16 11 9 24 20 5
71 28 21 22 19 28 19 4
72 26 23 22 18 25 20 4
73 22 22 16 12 21 15 5
74 19 24 20 23 25 23 10
75 26 24 24 22 25 26 5
76 18 16 16 14 18 22 8
77 18 16 16 14 17 20 8
78 25 21 22 16 26 24 5
79 27 26 24 23 28 26 4
80 12 15 16 7 21 21 4
81 15 25 27 10 27 25 4
82 21 18 11 12 22 13 5
83 23 23 21 12 21 20 4
84 22 20 20 12 25 22 4
85 21 17 20 17 22 23 8
86 24 25 27 21 23 28 4
87 27 24 20 16 26 22 5
88 22 17 12 11 19 20 14
89 28 19 8 14 25 6 8
90 26 20 21 13 21 21 8
91 10 15 18 9 13 20 4
92 19 27 24 19 24 18 4
93 22 22 16 13 25 23 6
94 21 23 18 19 26 20 4
95 24 16 20 13 25 24 7
96 25 19 20 13 25 22 7
97 21 25 19 13 22 21 4
98 20 19 17 14 21 18 6
99 21 19 16 12 23 21 4
100 24 26 26 22 25 23 7
101 23 21 15 11 24 23 4
102 18 20 22 5 21 15 4
103 24 24 17 18 21 21 8
104 24 22 23 19 25 24 4
105 19 20 21 14 22 23 4
106 20 18 19 15 20 21 10
107 18 18 14 12 20 21 8
108 20 24 17 19 23 20 6
109 27 24 12 15 28 11 4
110 23 22 24 17 23 22 4
111 26 23 18 8 28 27 4
112 23 22 20 10 24 25 5
113 17 20 16 12 18 18 4
114 21 18 20 12 20 20 6
115 25 25 22 20 28 24 4
116 23 18 12 12 21 10 5
117 27 16 16 12 21 27 7
118 24 20 17 14 25 21 8
119 20 19 22 6 19 21 5
120 27 15 12 10 18 18 8
121 21 19 14 18 21 15 10
122 24 19 23 18 22 24 8
123 21 16 15 7 24 22 5
124 15 17 17 18 15 14 12
125 25 28 28 9 28 28 4
126 25 23 20 17 26 18 5
127 22 25 23 22 23 26 4
128 24 20 13 11 26 17 6
129 21 17 18 15 20 19 4
130 22 23 23 17 22 22 4
131 23 16 19 15 20 18 7
132 22 23 23 22 23 24 7
133 20 11 12 9 22 15 10
134 23 18 16 13 24 18 4
135 25 24 23 20 23 26 5
136 23 23 13 14 22 11 8
137 22 21 22 14 26 26 11
138 25 16 18 12 23 21 7
139 26 24 23 20 27 23 4
140 22 23 20 20 23 23 8
141 24 18 10 8 21 15 6
142 24 20 17 17 26 22 7
143 25 9 18 9 23 26 5
144 20 24 15 18 21 16 4
145 26 25 23 22 27 20 8
146 21 20 17 10 19 18 4
147 26 21 17 13 23 22 8
148 21 25 22 15 25 16 6
149 22 22 20 18 23 19 4
150 16 21 20 18 22 20 9
151 26 21 19 12 22 19 5
152 28 22 18 12 25 23 6
153 18 27 22 20 25 24 4
154 25 24 20 12 28 25 4
155 23 24 22 16 28 21 4
156 21 21 18 16 20 21 5
157 20 18 16 18 25 23 6
158 25 16 16 16 19 27 16
159 22 22 16 13 25 23 6
160 21 20 16 17 22 18 6
161 16 18 17 13 18 16 4
162 18 20 18 17 20 16 4
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) I1 I2 I3 E1 E2
10.3288058 0.0662314 -0.2186223 -0.0256581 0.4893894 0.1868872
A
-0.0001391
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-12.9727 -1.5603 0.1779 2.1231 8.1858
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 10.3288058 2.5742609 4.012 9.33e-05 ***
I1 0.0662314 0.1051989 0.630 0.5299
I2 -0.2186223 0.0890890 -2.454 0.0152 *
I3 -0.0256581 0.0710050 -0.361 0.7183
E1 0.4893894 0.0940830 5.202 6.17e-07 ***
E2 0.1868872 0.0765965 2.440 0.0158 *
A -0.0001391 0.1124078 -0.001 0.9990
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 3.279 on 155 degrees of freedom
Multiple R-squared: 0.2188, Adjusted R-squared: 0.1886
F-statistic: 7.236 on 6 and 155 DF, p-value: 7.983e-07
> 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,] 0.1373702 2.747404e-01 8.626298e-01
[2,] 0.4315744 8.631488e-01 5.684256e-01
[3,] 0.3953931 7.907862e-01 6.046069e-01
[4,] 0.2800744 5.601489e-01 7.199256e-01
[5,] 0.2151573 4.303147e-01 7.848427e-01
[6,] 0.1396420 2.792840e-01 8.603580e-01
[7,] 0.0856540 1.713080e-01 9.143460e-01
[8,] 0.1391739 2.783479e-01 8.608261e-01
[9,] 0.2051648 4.103296e-01 7.948352e-01
[10,] 0.1531946 3.063893e-01 8.468054e-01
[11,] 0.1609924 3.219848e-01 8.390076e-01
[12,] 0.3414608 6.829215e-01 6.585392e-01
[13,] 0.4111524 8.223048e-01 5.888476e-01
[14,] 0.3374315 6.748629e-01 6.625685e-01
[15,] 0.2750724 5.501449e-01 7.249276e-01
[16,] 0.2288535 4.577069e-01 7.711465e-01
[17,] 0.5688987 8.622026e-01 4.311013e-01
[18,] 0.7365578 5.268843e-01 2.634422e-01
[19,] 0.8847650 2.304700e-01 1.152350e-01
[20,] 0.9047547 1.904906e-01 9.524530e-02
[21,] 0.8849841 2.300319e-01 1.150159e-01
[22,] 0.8525333 2.949335e-01 1.474667e-01
[23,] 0.8183616 3.632768e-01 1.816384e-01
[24,] 0.8866753 2.266494e-01 1.133247e-01
[25,] 0.8591181 2.817637e-01 1.408819e-01
[26,] 0.8263773 3.472454e-01 1.736227e-01
[27,] 0.8050331 3.899338e-01 1.949669e-01
[28,] 0.7942782 4.114437e-01 2.057218e-01
[29,] 0.7540681 4.918638e-01 2.459319e-01
[30,] 0.7647925 4.704150e-01 2.352075e-01
[31,] 0.7227153 5.545694e-01 2.772847e-01
[32,] 0.7466354 5.067292e-01 2.533646e-01
[33,] 0.7465935 5.068129e-01 2.534065e-01
[34,] 0.7052502 5.894996e-01 2.947498e-01
[35,] 0.6583929 6.832142e-01 3.416071e-01
[36,] 0.6185680 7.628639e-01 3.814320e-01
[37,] 0.6567595 6.864810e-01 3.432405e-01
[38,] 0.6502302 6.995396e-01 3.497698e-01
[39,] 0.6550121 6.899757e-01 3.449879e-01
[40,] 0.6077854 7.844292e-01 3.922146e-01
[41,] 0.7007125 5.985749e-01 2.992875e-01
[42,] 0.6581198 6.837604e-01 3.418802e-01
[43,] 0.6126704 7.746592e-01 3.873296e-01
[44,] 0.6292506 7.414988e-01 3.707494e-01
[45,] 0.9812748 3.745035e-02 1.872518e-02
[46,] 0.9771886 4.562272e-02 2.281136e-02
[47,] 0.9703117 5.937660e-02 2.968830e-02
[48,] 0.9632769 7.344630e-02 3.672315e-02
[49,] 0.9541483 9.170337e-02 4.585168e-02
[50,] 0.9487560 1.024880e-01 5.124398e-02
[51,] 0.9879276 2.414470e-02 1.207235e-02
[52,] 0.9933846 1.323078e-02 6.615390e-03
[53,] 0.9917641 1.647189e-02 8.235944e-03
[54,] 0.9887839 2.243228e-02 1.121614e-02
[55,] 0.9952658 9.468322e-03 4.734161e-03
[56,] 0.9954332 9.133684e-03 4.566842e-03
[57,] 0.9936390 1.272194e-02 6.360969e-03
[58,] 0.9920865 1.582694e-02 7.913469e-03
[59,] 0.9895655 2.086906e-02 1.043453e-02
[60,] 0.9870358 2.592845e-02 1.296422e-02
[61,] 0.9832299 3.354027e-02 1.677013e-02
[62,] 0.9859555 2.808903e-02 1.404452e-02
[63,] 0.9862752 2.744954e-02 1.372477e-02
[64,] 0.9823382 3.532358e-02 1.766179e-02
[65,] 0.9882566 2.348686e-02 1.174343e-02
[66,] 0.9871875 2.562492e-02 1.281246e-02
[67,] 0.9853140 2.937198e-02 1.468599e-02
[68,] 0.9815176 3.696477e-02 1.848239e-02
[69,] 0.9764847 4.703054e-02 2.351527e-02
[70,] 0.9725673 5.486539e-02 2.743269e-02
[71,] 0.9977541 4.491724e-03 2.245862e-03
[72,] 0.9998557 2.885989e-04 1.442995e-04
[73,] 0.9997827 4.346283e-04 2.173141e-04
[74,] 0.9997438 5.124814e-04 2.562407e-04
[75,] 0.9996358 7.283374e-04 3.641687e-04
[76,] 0.9994712 1.057562e-03 5.287810e-04
[77,] 0.9994070 1.185917e-03 5.929585e-04
[78,] 0.9993978 1.204305e-03 6.021524e-04
[79,] 0.9991318 1.736303e-03 8.681517e-04
[80,] 0.9994207 1.158514e-03 5.792569e-04
[81,] 0.9997068 5.863907e-04 2.931953e-04
[82,] 0.9999503 9.931678e-05 4.965839e-05
[83,] 0.9999375 1.249036e-04 6.245180e-05
[84,] 0.9999245 1.510081e-04 7.550404e-05
[85,] 0.9999168 1.664942e-04 8.324708e-05
[86,] 0.9998677 2.646733e-04 1.323366e-04
[87,] 0.9998083 3.834066e-04 1.917033e-04
[88,] 0.9997054 5.891586e-04 2.945793e-04
[89,] 0.9995656 8.687304e-04 4.343652e-04
[90,] 0.9994315 1.136966e-03 5.684832e-04
[91,] 0.9992349 1.530214e-03 7.651071e-04
[92,] 0.9988966 2.206812e-03 1.103406e-03
[93,] 0.9986208 2.758354e-03 1.379177e-03
[94,] 0.9984213 3.157407e-03 1.578703e-03
[95,] 0.9977460 4.507925e-03 2.253963e-03
[96,] 0.9976260 4.747999e-03 2.374000e-03
[97,] 0.9966470 6.706044e-03 3.353022e-03
[98,] 0.9975962 4.807591e-03 2.403795e-03
[99,] 0.9972041 5.591791e-03 2.795896e-03
[100,] 0.9971079 5.784168e-03 2.892084e-03
[101,] 0.9960974 7.805246e-03 3.902623e-03
[102,] 0.9943963 1.120733e-02 5.603664e-03
[103,] 0.9922378 1.552436e-02 7.762179e-03
[104,] 0.9929566 1.408677e-02 7.043384e-03
[105,] 0.9898507 2.029852e-02 1.014926e-02
[106,] 0.9858451 2.830986e-02 1.415493e-02
[107,] 0.9840879 3.182427e-02 1.591214e-02
[108,] 0.9843883 3.122349e-02 1.561175e-02
[109,] 0.9779219 4.415627e-02 2.207814e-02
[110,] 0.9719509 5.609823e-02 2.804911e-02
[111,] 0.9895882 2.082367e-02 1.041183e-02
[112,] 0.9848435 3.031306e-02 1.515653e-02
[113,] 0.9819827 3.603462e-02 1.801731e-02
[114,] 0.9844008 3.119836e-02 1.559918e-02
[115,] 0.9826925 3.461501e-02 1.730751e-02
[116,] 0.9781542 4.369150e-02 2.184575e-02
[117,] 0.9746865 5.062706e-02 2.531353e-02
[118,] 0.9639258 7.214847e-02 3.607424e-02
[119,] 0.9492880 1.014240e-01 5.071199e-02
[120,] 0.9306285 1.387430e-01 6.937149e-02
[121,] 0.9064196 1.871607e-01 9.358036e-02
[122,] 0.9009741 1.980517e-01 9.902587e-02
[123,] 0.8705097 2.589805e-01 1.294903e-01
[124,] 0.8641131 2.717737e-01 1.358869e-01
[125,] 0.8225230 3.549541e-01 1.774770e-01
[126,] 0.8540323 2.919354e-01 1.459677e-01
[127,] 0.8110405 3.779191e-01 1.889595e-01
[128,] 0.8620814 2.758373e-01 1.379186e-01
[129,] 0.8230029 3.539941e-01 1.769971e-01
[130,] 0.8592883 2.814235e-01 1.407117e-01
[131,] 0.8150263 3.699474e-01 1.849737e-01
[132,] 0.7575537 4.848927e-01 2.424463e-01
[133,] 0.6864272 6.271457e-01 3.135728e-01
[134,] 0.6229676 7.540648e-01 3.770324e-01
[135,] 0.5499877 9.000246e-01 4.500123e-01
[136,] 0.6948644 6.102712e-01 3.051356e-01
[137,] 0.6323010 7.353981e-01 3.676990e-01
[138,] 0.5617397 8.765207e-01 4.382603e-01
[139,] 0.4528993 9.057985e-01 5.471007e-01
[140,] 0.4775096 9.550191e-01 5.224904e-01
[141,] 0.6428225 7.143550e-01 3.571775e-01
[142,] 0.6173665 7.652670e-01 3.826335e-01
[143,] 0.6893578 6.212843e-01 3.106422e-01
> postscript(file="/var/www/rcomp/tmp/1n0wh1321980156.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/2olgx1321980156.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/3f20n1321980156.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/413b81321980156.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/5s28v1321980156.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 = 162
Frequency = 1
1 2 3 4 5
1.646583e+00 -2.692478e+00 -1.101236e+00 -8.106931e-02 5.678100e-01
6 7 8 9 10
-2.914574e+00 -2.418584e+00 -5.973188e+00 2.778685e+00 4.519032e-01
11 12 13 14 15
3.538695e+00 3.530064e+00 -2.215278e+00 9.012449e-01 1.183203e+00
16 17 18 19 20
-7.134355e-01 2.933778e+00 4.216663e+00 4.021448e+00 -9.096453e-02
21 22 23 24 25
-3.448856e+00 3.817507e+00 -9.490187e-01 -9.000461e-01 1.866376e+00
26 27 28 29 30
-8.042161e+00 -8.042161e+00 6.226359e+00 3.237067e+00 -2.356629e+00
31 32 33 34 35
-7.905109e-01 -1.375917e+00 -8.563519e+00 -3.247511e-01 1.250889e+00
36 37 38 39 40
-3.453164e+00 3.354522e+00 -2.392607e-01 2.618744e+00 -9.574420e-01
41 42 43 44 45
3.369941e+00 3.596867e+00 3.279145e-01 -6.947346e-01 -1.478620e+00
46 47 48 49 50
2.382580e+00 -2.608868e+00 3.174171e+00 -9.522242e-01 5.855649e+00
51 52 53 54 55
-1.554505e-01 4.919219e-01 3.903971e+00 -1.297268e+01 1.638141e+00
56 57 58 59 60
-5.824472e-01 -1.622931e+00 1.204201e+00 2.488854e+00 8.185762e+00
61 62 63 64 65
5.190957e+00 1.605032e+00 6.005221e-01 -6.218799e+00 -2.988325e+00
66 67 68 69 70
4.921671e-01 1.714565e+00 1.167096e+00 1.599690e+00 -1.235135e+00
71 72 73 74 75
4.324325e+00 3.447485e+00 9.401666e-01 -4.487528e+00 2.799946e+00
76 77 78 79 80
-2.450754e+00 -1.587590e+00 1.291832e+00 2.224834e+00 -9.845966e+00
81 82 83 84 85
-8.710346e+00 -1.003634e+00 2.032472e+00 -1.318788e+00 -7.099667e-01
86 87 88 89 90
1.968789e+00 3.029668e+00 4.167704e-01 5.166043e+00 5.070493e+00
91 92 93 94 95
-7.255403e+00 -2.491374e+00 -2.486692e+00 -2.890736e+00 5.984380e-01
96 97 98 99 100
1.773518e+00 -1.187854e+00 -1.151723e+00 -1.961380e+00 1.665668e+00
101 102 103 104 105
-1.201288e+00 -1.795382e+00 2.059368e+00 1.010448e+00 -2.767569e+00
106 107 108 109 110
-6.933052e-01 -3.863669e+00 -2.707143e+00 2.331873e+00 1.530307e+00
111 112 113 114 115
-4.599641e-01 -5.737007e-01 -3.020003e+00 6.346740e-01 1.506210e-01
116 117 118 119 120
2.265039e+00 4.095186e+00 2.641041e-01 1.541020e-01 6.385905e+00
121 122 123 124 125
-1.437401e-01 2.652208e+00 -2.785736e+00 -2.231908e+00 2.338731e-01
126 127 128 129 130
1.869106e+00 -5.062679e-01 -4.294781e-01 5.272440e-01 7.348429e-01
131 132 133 134 135
2.999402e+00 3.865257e-04 -1.771445e+00 2.017814e-01 2.508786e+00
136 137 138 139 140
1.527961e+00 -2.132424e+00 2.674976e+00 2.111751e+00 -5.197704e-01
141 142 143 144 145
1.790865e+00 -3.353374e-01 2.126907e+00 -1.443996e+00 2.658054e+00
146 147 148 149 150
6.579137e-01 2.964106e+00 -1.014125e+00 2.421376e-01 -5.388433e+00
151 152 153 154 155
4.425327e+00 3.924895e+00 -5.513674e+00 -6.125441e-01 -1.325118e+00
156 157 158 159 160
-8.565897e-02 -4.093476e+00 3.177849e+00 -2.486692e+00 -8.489922e-01
161 162
-3.269485e+00 -2.059472e+00
> postscript(file="/var/www/rcomp/tmp/6w4hn1321980156.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 = 162
Frequency = 1
lag(myerror, k = 1) myerror
0 1.646583e+00 NA
1 -2.692478e+00 1.646583e+00
2 -1.101236e+00 -2.692478e+00
3 -8.106931e-02 -1.101236e+00
4 5.678100e-01 -8.106931e-02
5 -2.914574e+00 5.678100e-01
6 -2.418584e+00 -2.914574e+00
7 -5.973188e+00 -2.418584e+00
8 2.778685e+00 -5.973188e+00
9 4.519032e-01 2.778685e+00
10 3.538695e+00 4.519032e-01
11 3.530064e+00 3.538695e+00
12 -2.215278e+00 3.530064e+00
13 9.012449e-01 -2.215278e+00
14 1.183203e+00 9.012449e-01
15 -7.134355e-01 1.183203e+00
16 2.933778e+00 -7.134355e-01
17 4.216663e+00 2.933778e+00
18 4.021448e+00 4.216663e+00
19 -9.096453e-02 4.021448e+00
20 -3.448856e+00 -9.096453e-02
21 3.817507e+00 -3.448856e+00
22 -9.490187e-01 3.817507e+00
23 -9.000461e-01 -9.490187e-01
24 1.866376e+00 -9.000461e-01
25 -8.042161e+00 1.866376e+00
26 -8.042161e+00 -8.042161e+00
27 6.226359e+00 -8.042161e+00
28 3.237067e+00 6.226359e+00
29 -2.356629e+00 3.237067e+00
30 -7.905109e-01 -2.356629e+00
31 -1.375917e+00 -7.905109e-01
32 -8.563519e+00 -1.375917e+00
33 -3.247511e-01 -8.563519e+00
34 1.250889e+00 -3.247511e-01
35 -3.453164e+00 1.250889e+00
36 3.354522e+00 -3.453164e+00
37 -2.392607e-01 3.354522e+00
38 2.618744e+00 -2.392607e-01
39 -9.574420e-01 2.618744e+00
40 3.369941e+00 -9.574420e-01
41 3.596867e+00 3.369941e+00
42 3.279145e-01 3.596867e+00
43 -6.947346e-01 3.279145e-01
44 -1.478620e+00 -6.947346e-01
45 2.382580e+00 -1.478620e+00
46 -2.608868e+00 2.382580e+00
47 3.174171e+00 -2.608868e+00
48 -9.522242e-01 3.174171e+00
49 5.855649e+00 -9.522242e-01
50 -1.554505e-01 5.855649e+00
51 4.919219e-01 -1.554505e-01
52 3.903971e+00 4.919219e-01
53 -1.297268e+01 3.903971e+00
54 1.638141e+00 -1.297268e+01
55 -5.824472e-01 1.638141e+00
56 -1.622931e+00 -5.824472e-01
57 1.204201e+00 -1.622931e+00
58 2.488854e+00 1.204201e+00
59 8.185762e+00 2.488854e+00
60 5.190957e+00 8.185762e+00
61 1.605032e+00 5.190957e+00
62 6.005221e-01 1.605032e+00
63 -6.218799e+00 6.005221e-01
64 -2.988325e+00 -6.218799e+00
65 4.921671e-01 -2.988325e+00
66 1.714565e+00 4.921671e-01
67 1.167096e+00 1.714565e+00
68 1.599690e+00 1.167096e+00
69 -1.235135e+00 1.599690e+00
70 4.324325e+00 -1.235135e+00
71 3.447485e+00 4.324325e+00
72 9.401666e-01 3.447485e+00
73 -4.487528e+00 9.401666e-01
74 2.799946e+00 -4.487528e+00
75 -2.450754e+00 2.799946e+00
76 -1.587590e+00 -2.450754e+00
77 1.291832e+00 -1.587590e+00
78 2.224834e+00 1.291832e+00
79 -9.845966e+00 2.224834e+00
80 -8.710346e+00 -9.845966e+00
81 -1.003634e+00 -8.710346e+00
82 2.032472e+00 -1.003634e+00
83 -1.318788e+00 2.032472e+00
84 -7.099667e-01 -1.318788e+00
85 1.968789e+00 -7.099667e-01
86 3.029668e+00 1.968789e+00
87 4.167704e-01 3.029668e+00
88 5.166043e+00 4.167704e-01
89 5.070493e+00 5.166043e+00
90 -7.255403e+00 5.070493e+00
91 -2.491374e+00 -7.255403e+00
92 -2.486692e+00 -2.491374e+00
93 -2.890736e+00 -2.486692e+00
94 5.984380e-01 -2.890736e+00
95 1.773518e+00 5.984380e-01
96 -1.187854e+00 1.773518e+00
97 -1.151723e+00 -1.187854e+00
98 -1.961380e+00 -1.151723e+00
99 1.665668e+00 -1.961380e+00
100 -1.201288e+00 1.665668e+00
101 -1.795382e+00 -1.201288e+00
102 2.059368e+00 -1.795382e+00
103 1.010448e+00 2.059368e+00
104 -2.767569e+00 1.010448e+00
105 -6.933052e-01 -2.767569e+00
106 -3.863669e+00 -6.933052e-01
107 -2.707143e+00 -3.863669e+00
108 2.331873e+00 -2.707143e+00
109 1.530307e+00 2.331873e+00
110 -4.599641e-01 1.530307e+00
111 -5.737007e-01 -4.599641e-01
112 -3.020003e+00 -5.737007e-01
113 6.346740e-01 -3.020003e+00
114 1.506210e-01 6.346740e-01
115 2.265039e+00 1.506210e-01
116 4.095186e+00 2.265039e+00
117 2.641041e-01 4.095186e+00
118 1.541020e-01 2.641041e-01
119 6.385905e+00 1.541020e-01
120 -1.437401e-01 6.385905e+00
121 2.652208e+00 -1.437401e-01
122 -2.785736e+00 2.652208e+00
123 -2.231908e+00 -2.785736e+00
124 2.338731e-01 -2.231908e+00
125 1.869106e+00 2.338731e-01
126 -5.062679e-01 1.869106e+00
127 -4.294781e-01 -5.062679e-01
128 5.272440e-01 -4.294781e-01
129 7.348429e-01 5.272440e-01
130 2.999402e+00 7.348429e-01
131 3.865257e-04 2.999402e+00
132 -1.771445e+00 3.865257e-04
133 2.017814e-01 -1.771445e+00
134 2.508786e+00 2.017814e-01
135 1.527961e+00 2.508786e+00
136 -2.132424e+00 1.527961e+00
137 2.674976e+00 -2.132424e+00
138 2.111751e+00 2.674976e+00
139 -5.197704e-01 2.111751e+00
140 1.790865e+00 -5.197704e-01
141 -3.353374e-01 1.790865e+00
142 2.126907e+00 -3.353374e-01
143 -1.443996e+00 2.126907e+00
144 2.658054e+00 -1.443996e+00
145 6.579137e-01 2.658054e+00
146 2.964106e+00 6.579137e-01
147 -1.014125e+00 2.964106e+00
148 2.421376e-01 -1.014125e+00
149 -5.388433e+00 2.421376e-01
150 4.425327e+00 -5.388433e+00
151 3.924895e+00 4.425327e+00
152 -5.513674e+00 3.924895e+00
153 -6.125441e-01 -5.513674e+00
154 -1.325118e+00 -6.125441e-01
155 -8.565897e-02 -1.325118e+00
156 -4.093476e+00 -8.565897e-02
157 3.177849e+00 -4.093476e+00
158 -2.486692e+00 3.177849e+00
159 -8.489922e-01 -2.486692e+00
160 -3.269485e+00 -8.489922e-01
161 -2.059472e+00 -3.269485e+00
162 NA -2.059472e+00
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -2.692478e+00 1.646583e+00
[2,] -1.101236e+00 -2.692478e+00
[3,] -8.106931e-02 -1.101236e+00
[4,] 5.678100e-01 -8.106931e-02
[5,] -2.914574e+00 5.678100e-01
[6,] -2.418584e+00 -2.914574e+00
[7,] -5.973188e+00 -2.418584e+00
[8,] 2.778685e+00 -5.973188e+00
[9,] 4.519032e-01 2.778685e+00
[10,] 3.538695e+00 4.519032e-01
[11,] 3.530064e+00 3.538695e+00
[12,] -2.215278e+00 3.530064e+00
[13,] 9.012449e-01 -2.215278e+00
[14,] 1.183203e+00 9.012449e-01
[15,] -7.134355e-01 1.183203e+00
[16,] 2.933778e+00 -7.134355e-01
[17,] 4.216663e+00 2.933778e+00
[18,] 4.021448e+00 4.216663e+00
[19,] -9.096453e-02 4.021448e+00
[20,] -3.448856e+00 -9.096453e-02
[21,] 3.817507e+00 -3.448856e+00
[22,] -9.490187e-01 3.817507e+00
[23,] -9.000461e-01 -9.490187e-01
[24,] 1.866376e+00 -9.000461e-01
[25,] -8.042161e+00 1.866376e+00
[26,] -8.042161e+00 -8.042161e+00
[27,] 6.226359e+00 -8.042161e+00
[28,] 3.237067e+00 6.226359e+00
[29,] -2.356629e+00 3.237067e+00
[30,] -7.905109e-01 -2.356629e+00
[31,] -1.375917e+00 -7.905109e-01
[32,] -8.563519e+00 -1.375917e+00
[33,] -3.247511e-01 -8.563519e+00
[34,] 1.250889e+00 -3.247511e-01
[35,] -3.453164e+00 1.250889e+00
[36,] 3.354522e+00 -3.453164e+00
[37,] -2.392607e-01 3.354522e+00
[38,] 2.618744e+00 -2.392607e-01
[39,] -9.574420e-01 2.618744e+00
[40,] 3.369941e+00 -9.574420e-01
[41,] 3.596867e+00 3.369941e+00
[42,] 3.279145e-01 3.596867e+00
[43,] -6.947346e-01 3.279145e-01
[44,] -1.478620e+00 -6.947346e-01
[45,] 2.382580e+00 -1.478620e+00
[46,] -2.608868e+00 2.382580e+00
[47,] 3.174171e+00 -2.608868e+00
[48,] -9.522242e-01 3.174171e+00
[49,] 5.855649e+00 -9.522242e-01
[50,] -1.554505e-01 5.855649e+00
[51,] 4.919219e-01 -1.554505e-01
[52,] 3.903971e+00 4.919219e-01
[53,] -1.297268e+01 3.903971e+00
[54,] 1.638141e+00 -1.297268e+01
[55,] -5.824472e-01 1.638141e+00
[56,] -1.622931e+00 -5.824472e-01
[57,] 1.204201e+00 -1.622931e+00
[58,] 2.488854e+00 1.204201e+00
[59,] 8.185762e+00 2.488854e+00
[60,] 5.190957e+00 8.185762e+00
[61,] 1.605032e+00 5.190957e+00
[62,] 6.005221e-01 1.605032e+00
[63,] -6.218799e+00 6.005221e-01
[64,] -2.988325e+00 -6.218799e+00
[65,] 4.921671e-01 -2.988325e+00
[66,] 1.714565e+00 4.921671e-01
[67,] 1.167096e+00 1.714565e+00
[68,] 1.599690e+00 1.167096e+00
[69,] -1.235135e+00 1.599690e+00
[70,] 4.324325e+00 -1.235135e+00
[71,] 3.447485e+00 4.324325e+00
[72,] 9.401666e-01 3.447485e+00
[73,] -4.487528e+00 9.401666e-01
[74,] 2.799946e+00 -4.487528e+00
[75,] -2.450754e+00 2.799946e+00
[76,] -1.587590e+00 -2.450754e+00
[77,] 1.291832e+00 -1.587590e+00
[78,] 2.224834e+00 1.291832e+00
[79,] -9.845966e+00 2.224834e+00
[80,] -8.710346e+00 -9.845966e+00
[81,] -1.003634e+00 -8.710346e+00
[82,] 2.032472e+00 -1.003634e+00
[83,] -1.318788e+00 2.032472e+00
[84,] -7.099667e-01 -1.318788e+00
[85,] 1.968789e+00 -7.099667e-01
[86,] 3.029668e+00 1.968789e+00
[87,] 4.167704e-01 3.029668e+00
[88,] 5.166043e+00 4.167704e-01
[89,] 5.070493e+00 5.166043e+00
[90,] -7.255403e+00 5.070493e+00
[91,] -2.491374e+00 -7.255403e+00
[92,] -2.486692e+00 -2.491374e+00
[93,] -2.890736e+00 -2.486692e+00
[94,] 5.984380e-01 -2.890736e+00
[95,] 1.773518e+00 5.984380e-01
[96,] -1.187854e+00 1.773518e+00
[97,] -1.151723e+00 -1.187854e+00
[98,] -1.961380e+00 -1.151723e+00
[99,] 1.665668e+00 -1.961380e+00
[100,] -1.201288e+00 1.665668e+00
[101,] -1.795382e+00 -1.201288e+00
[102,] 2.059368e+00 -1.795382e+00
[103,] 1.010448e+00 2.059368e+00
[104,] -2.767569e+00 1.010448e+00
[105,] -6.933052e-01 -2.767569e+00
[106,] -3.863669e+00 -6.933052e-01
[107,] -2.707143e+00 -3.863669e+00
[108,] 2.331873e+00 -2.707143e+00
[109,] 1.530307e+00 2.331873e+00
[110,] -4.599641e-01 1.530307e+00
[111,] -5.737007e-01 -4.599641e-01
[112,] -3.020003e+00 -5.737007e-01
[113,] 6.346740e-01 -3.020003e+00
[114,] 1.506210e-01 6.346740e-01
[115,] 2.265039e+00 1.506210e-01
[116,] 4.095186e+00 2.265039e+00
[117,] 2.641041e-01 4.095186e+00
[118,] 1.541020e-01 2.641041e-01
[119,] 6.385905e+00 1.541020e-01
[120,] -1.437401e-01 6.385905e+00
[121,] 2.652208e+00 -1.437401e-01
[122,] -2.785736e+00 2.652208e+00
[123,] -2.231908e+00 -2.785736e+00
[124,] 2.338731e-01 -2.231908e+00
[125,] 1.869106e+00 2.338731e-01
[126,] -5.062679e-01 1.869106e+00
[127,] -4.294781e-01 -5.062679e-01
[128,] 5.272440e-01 -4.294781e-01
[129,] 7.348429e-01 5.272440e-01
[130,] 2.999402e+00 7.348429e-01
[131,] 3.865257e-04 2.999402e+00
[132,] -1.771445e+00 3.865257e-04
[133,] 2.017814e-01 -1.771445e+00
[134,] 2.508786e+00 2.017814e-01
[135,] 1.527961e+00 2.508786e+00
[136,] -2.132424e+00 1.527961e+00
[137,] 2.674976e+00 -2.132424e+00
[138,] 2.111751e+00 2.674976e+00
[139,] -5.197704e-01 2.111751e+00
[140,] 1.790865e+00 -5.197704e-01
[141,] -3.353374e-01 1.790865e+00
[142,] 2.126907e+00 -3.353374e-01
[143,] -1.443996e+00 2.126907e+00
[144,] 2.658054e+00 -1.443996e+00
[145,] 6.579137e-01 2.658054e+00
[146,] 2.964106e+00 6.579137e-01
[147,] -1.014125e+00 2.964106e+00
[148,] 2.421376e-01 -1.014125e+00
[149,] -5.388433e+00 2.421376e-01
[150,] 4.425327e+00 -5.388433e+00
[151,] 3.924895e+00 4.425327e+00
[152,] -5.513674e+00 3.924895e+00
[153,] -6.125441e-01 -5.513674e+00
[154,] -1.325118e+00 -6.125441e-01
[155,] -8.565897e-02 -1.325118e+00
[156,] -4.093476e+00 -8.565897e-02
[157,] 3.177849e+00 -4.093476e+00
[158,] -2.486692e+00 3.177849e+00
[159,] -8.489922e-01 -2.486692e+00
[160,] -3.269485e+00 -8.489922e-01
[161,] -2.059472e+00 -3.269485e+00
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -2.692478e+00 1.646583e+00
2 -1.101236e+00 -2.692478e+00
3 -8.106931e-02 -1.101236e+00
4 5.678100e-01 -8.106931e-02
5 -2.914574e+00 5.678100e-01
6 -2.418584e+00 -2.914574e+00
7 -5.973188e+00 -2.418584e+00
8 2.778685e+00 -5.973188e+00
9 4.519032e-01 2.778685e+00
10 3.538695e+00 4.519032e-01
11 3.530064e+00 3.538695e+00
12 -2.215278e+00 3.530064e+00
13 9.012449e-01 -2.215278e+00
14 1.183203e+00 9.012449e-01
15 -7.134355e-01 1.183203e+00
16 2.933778e+00 -7.134355e-01
17 4.216663e+00 2.933778e+00
18 4.021448e+00 4.216663e+00
19 -9.096453e-02 4.021448e+00
20 -3.448856e+00 -9.096453e-02
21 3.817507e+00 -3.448856e+00
22 -9.490187e-01 3.817507e+00
23 -9.000461e-01 -9.490187e-01
24 1.866376e+00 -9.000461e-01
25 -8.042161e+00 1.866376e+00
26 -8.042161e+00 -8.042161e+00
27 6.226359e+00 -8.042161e+00
28 3.237067e+00 6.226359e+00
29 -2.356629e+00 3.237067e+00
30 -7.905109e-01 -2.356629e+00
31 -1.375917e+00 -7.905109e-01
32 -8.563519e+00 -1.375917e+00
33 -3.247511e-01 -8.563519e+00
34 1.250889e+00 -3.247511e-01
35 -3.453164e+00 1.250889e+00
36 3.354522e+00 -3.453164e+00
37 -2.392607e-01 3.354522e+00
38 2.618744e+00 -2.392607e-01
39 -9.574420e-01 2.618744e+00
40 3.369941e+00 -9.574420e-01
41 3.596867e+00 3.369941e+00
42 3.279145e-01 3.596867e+00
43 -6.947346e-01 3.279145e-01
44 -1.478620e+00 -6.947346e-01
45 2.382580e+00 -1.478620e+00
46 -2.608868e+00 2.382580e+00
47 3.174171e+00 -2.608868e+00
48 -9.522242e-01 3.174171e+00
49 5.855649e+00 -9.522242e-01
50 -1.554505e-01 5.855649e+00
51 4.919219e-01 -1.554505e-01
52 3.903971e+00 4.919219e-01
53 -1.297268e+01 3.903971e+00
54 1.638141e+00 -1.297268e+01
55 -5.824472e-01 1.638141e+00
56 -1.622931e+00 -5.824472e-01
57 1.204201e+00 -1.622931e+00
58 2.488854e+00 1.204201e+00
59 8.185762e+00 2.488854e+00
60 5.190957e+00 8.185762e+00
61 1.605032e+00 5.190957e+00
62 6.005221e-01 1.605032e+00
63 -6.218799e+00 6.005221e-01
64 -2.988325e+00 -6.218799e+00
65 4.921671e-01 -2.988325e+00
66 1.714565e+00 4.921671e-01
67 1.167096e+00 1.714565e+00
68 1.599690e+00 1.167096e+00
69 -1.235135e+00 1.599690e+00
70 4.324325e+00 -1.235135e+00
71 3.447485e+00 4.324325e+00
72 9.401666e-01 3.447485e+00
73 -4.487528e+00 9.401666e-01
74 2.799946e+00 -4.487528e+00
75 -2.450754e+00 2.799946e+00
76 -1.587590e+00 -2.450754e+00
77 1.291832e+00 -1.587590e+00
78 2.224834e+00 1.291832e+00
79 -9.845966e+00 2.224834e+00
80 -8.710346e+00 -9.845966e+00
81 -1.003634e+00 -8.710346e+00
82 2.032472e+00 -1.003634e+00
83 -1.318788e+00 2.032472e+00
84 -7.099667e-01 -1.318788e+00
85 1.968789e+00 -7.099667e-01
86 3.029668e+00 1.968789e+00
87 4.167704e-01 3.029668e+00
88 5.166043e+00 4.167704e-01
89 5.070493e+00 5.166043e+00
90 -7.255403e+00 5.070493e+00
91 -2.491374e+00 -7.255403e+00
92 -2.486692e+00 -2.491374e+00
93 -2.890736e+00 -2.486692e+00
94 5.984380e-01 -2.890736e+00
95 1.773518e+00 5.984380e-01
96 -1.187854e+00 1.773518e+00
97 -1.151723e+00 -1.187854e+00
98 -1.961380e+00 -1.151723e+00
99 1.665668e+00 -1.961380e+00
100 -1.201288e+00 1.665668e+00
101 -1.795382e+00 -1.201288e+00
102 2.059368e+00 -1.795382e+00
103 1.010448e+00 2.059368e+00
104 -2.767569e+00 1.010448e+00
105 -6.933052e-01 -2.767569e+00
106 -3.863669e+00 -6.933052e-01
107 -2.707143e+00 -3.863669e+00
108 2.331873e+00 -2.707143e+00
109 1.530307e+00 2.331873e+00
110 -4.599641e-01 1.530307e+00
111 -5.737007e-01 -4.599641e-01
112 -3.020003e+00 -5.737007e-01
113 6.346740e-01 -3.020003e+00
114 1.506210e-01 6.346740e-01
115 2.265039e+00 1.506210e-01
116 4.095186e+00 2.265039e+00
117 2.641041e-01 4.095186e+00
118 1.541020e-01 2.641041e-01
119 6.385905e+00 1.541020e-01
120 -1.437401e-01 6.385905e+00
121 2.652208e+00 -1.437401e-01
122 -2.785736e+00 2.652208e+00
123 -2.231908e+00 -2.785736e+00
124 2.338731e-01 -2.231908e+00
125 1.869106e+00 2.338731e-01
126 -5.062679e-01 1.869106e+00
127 -4.294781e-01 -5.062679e-01
128 5.272440e-01 -4.294781e-01
129 7.348429e-01 5.272440e-01
130 2.999402e+00 7.348429e-01
131 3.865257e-04 2.999402e+00
132 -1.771445e+00 3.865257e-04
133 2.017814e-01 -1.771445e+00
134 2.508786e+00 2.017814e-01
135 1.527961e+00 2.508786e+00
136 -2.132424e+00 1.527961e+00
137 2.674976e+00 -2.132424e+00
138 2.111751e+00 2.674976e+00
139 -5.197704e-01 2.111751e+00
140 1.790865e+00 -5.197704e-01
141 -3.353374e-01 1.790865e+00
142 2.126907e+00 -3.353374e-01
143 -1.443996e+00 2.126907e+00
144 2.658054e+00 -1.443996e+00
145 6.579137e-01 2.658054e+00
146 2.964106e+00 6.579137e-01
147 -1.014125e+00 2.964106e+00
148 2.421376e-01 -1.014125e+00
149 -5.388433e+00 2.421376e-01
150 4.425327e+00 -5.388433e+00
151 3.924895e+00 4.425327e+00
152 -5.513674e+00 3.924895e+00
153 -6.125441e-01 -5.513674e+00
154 -1.325118e+00 -6.125441e-01
155 -8.565897e-02 -1.325118e+00
156 -4.093476e+00 -8.565897e-02
157 3.177849e+00 -4.093476e+00
158 -2.486692e+00 3.177849e+00
159 -8.489922e-01 -2.486692e+00
160 -3.269485e+00 -8.489922e-01
161 -2.059472e+00 -3.269485e+00
> 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/rcomp/tmp/708cd1321980156.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/8c3rz1321980156.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/94oht1321980156.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/rcomp/tmp/109xrp1321980156.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/rcomp/tmp/110rc11321980156.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/rcomp/tmp/12uoan1321980156.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/rcomp/tmp/13qijm1321980156.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/rcomp/tmp/14m0an1321980156.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/rcomp/tmp/159m1l1321980156.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/rcomp/tmp/16qslv1321980156.tab")
+ }
>
> try(system("convert tmp/1n0wh1321980156.ps tmp/1n0wh1321980156.png",intern=TRUE))
character(0)
> try(system("convert tmp/2olgx1321980156.ps tmp/2olgx1321980156.png",intern=TRUE))
character(0)
> try(system("convert tmp/3f20n1321980156.ps tmp/3f20n1321980156.png",intern=TRUE))
character(0)
> try(system("convert tmp/413b81321980156.ps tmp/413b81321980156.png",intern=TRUE))
character(0)
> try(system("convert tmp/5s28v1321980156.ps tmp/5s28v1321980156.png",intern=TRUE))
character(0)
> try(system("convert tmp/6w4hn1321980156.ps tmp/6w4hn1321980156.png",intern=TRUE))
character(0)
> try(system("convert tmp/708cd1321980156.ps tmp/708cd1321980156.png",intern=TRUE))
character(0)
> try(system("convert tmp/8c3rz1321980156.ps tmp/8c3rz1321980156.png",intern=TRUE))
character(0)
> try(system("convert tmp/94oht1321980156.ps tmp/94oht1321980156.png",intern=TRUE))
character(0)
> try(system("convert tmp/109xrp1321980156.ps tmp/109xrp1321980156.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
4.530 0.290 4.872