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.
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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(235.1
+ ,1
+ ,280.7
+ ,1
+ ,264.6
+ ,2
+ ,240.7
+ ,0
+ ,201.4
+ ,1
+ ,240.8
+ ,0
+ ,241.1
+ ,-1
+ ,223.8
+ ,-3
+ ,206.1
+ ,-3
+ ,174.7
+ ,-3
+ ,203.3
+ ,-4
+ ,220.5
+ ,-8
+ ,299.5
+ ,-9
+ ,347.4
+ ,-13
+ ,338.3
+ ,-18
+ ,327.7
+ ,-11
+ ,351.6
+ ,-9
+ ,396.6
+ ,-10
+ ,438.8
+ ,-13
+ ,395.6
+ ,-11
+ ,363.5
+ ,-5
+ ,378.8
+ ,-15
+ ,357
+ ,-6
+ ,369
+ ,-6
+ ,464.8
+ ,-3
+ ,479.1
+ ,-1
+ ,431.3
+ ,-3
+ ,366.5
+ ,-4
+ ,326.3
+ ,-6
+ ,355.1
+ ,0
+ ,331.6
+ ,-4
+ ,261.3
+ ,-2
+ ,249
+ ,-2
+ ,205.5
+ ,-6
+ ,235.6
+ ,-7
+ ,240.9
+ ,-6
+ ,264.9
+ ,-6
+ ,253.8
+ ,-3
+ ,232.3
+ ,-2
+ ,193.8
+ ,-5
+ ,177
+ ,-11
+ ,213.2
+ ,-11
+ ,207.2
+ ,-11
+ ,180.6
+ ,-10
+ ,188.6
+ ,-14
+ ,175.4
+ ,-8
+ ,199
+ ,-9
+ ,179.6
+ ,-5
+ ,225.8
+ ,-1
+ ,234
+ ,-2
+ ,200.2
+ ,-5
+ ,183.6
+ ,-4
+ ,178.2
+ ,-6
+ ,203.2
+ ,-2
+ ,208.5
+ ,-2
+ ,191.8
+ ,-2
+ ,172.8
+ ,-2
+ ,148
+ ,2
+ ,159.4
+ ,1
+ ,154.5
+ ,-8
+ ,213.2
+ ,-1
+ ,196.4
+ ,1
+ ,182.8
+ ,-1
+ ,176.4
+ ,2
+ ,153.6
+ ,2
+ ,173.2
+ ,1
+ ,171
+ ,-1
+ ,151.2
+ ,-2
+ ,161.9
+ ,-2
+ ,157.2
+ ,-1
+ ,201.7
+ ,-8
+ ,236.4
+ ,-4
+ ,356.1
+ ,-6
+ ,398.3
+ ,-3
+ ,403.7
+ ,-3
+ ,384.6
+ ,-7
+ ,365.8
+ ,-9
+ ,368.1
+ ,-11
+ ,367.9
+ ,-13
+ ,347
+ ,-11
+ ,343.3
+ ,-9
+ ,292.9
+ ,-17
+ ,311.5
+ ,-22
+ ,300.9
+ ,-25
+ ,366.9
+ ,-20
+ ,356.9
+ ,-24
+ ,329.7
+ ,-24
+ ,316.2
+ ,-22
+ ,269
+ ,-19
+ ,289.3
+ ,-18
+ ,266.2
+ ,-17
+ ,253.6
+ ,-11
+ ,233.8
+ ,-11
+ ,228.4
+ ,-12
+ ,253.6
+ ,-10
+ ,260.1
+ ,-15
+ ,306.6
+ ,-15
+ ,309.2
+ ,-15
+ ,309.5
+ ,-13
+ ,271
+ ,-8
+ ,279.9
+ ,-13
+ ,317.9
+ ,-9
+ ,298.4
+ ,-7
+ ,246.7
+ ,-4
+ ,227.3
+ ,-4
+ ,209.1
+ ,-2)
+ ,dim=c(2
+ ,106)
+ ,dimnames=list(c('Y'
+ ,'X')
+ ,1:106))
> y <- array(NA,dim=c(2,106),dimnames=list(c('Y','X'),1:106))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'Linear Trend'
> par2 = 'Include Monthly 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
Y X M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 235.1 1 1 0 0 0 0 0 0 0 0 0 0 1
2 280.7 1 0 1 0 0 0 0 0 0 0 0 0 2
3 264.6 2 0 0 1 0 0 0 0 0 0 0 0 3
4 240.7 0 0 0 0 1 0 0 0 0 0 0 0 4
5 201.4 1 0 0 0 0 1 0 0 0 0 0 0 5
6 240.8 0 0 0 0 0 0 1 0 0 0 0 0 6
7 241.1 -1 0 0 0 0 0 0 1 0 0 0 0 7
8 223.8 -3 0 0 0 0 0 0 0 1 0 0 0 8
9 206.1 -3 0 0 0 0 0 0 0 0 1 0 0 9
10 174.7 -3 0 0 0 0 0 0 0 0 0 1 0 10
11 203.3 -4 0 0 0 0 0 0 0 0 0 0 1 11
12 220.5 -8 0 0 0 0 0 0 0 0 0 0 0 12
13 299.5 -9 1 0 0 0 0 0 0 0 0 0 0 13
14 347.4 -13 0 1 0 0 0 0 0 0 0 0 0 14
15 338.3 -18 0 0 1 0 0 0 0 0 0 0 0 15
16 327.7 -11 0 0 0 1 0 0 0 0 0 0 0 16
17 351.6 -9 0 0 0 0 1 0 0 0 0 0 0 17
18 396.6 -10 0 0 0 0 0 1 0 0 0 0 0 18
19 438.8 -13 0 0 0 0 0 0 1 0 0 0 0 19
20 395.6 -11 0 0 0 0 0 0 0 1 0 0 0 20
21 363.5 -5 0 0 0 0 0 0 0 0 1 0 0 21
22 378.8 -15 0 0 0 0 0 0 0 0 0 1 0 22
23 357.0 -6 0 0 0 0 0 0 0 0 0 0 1 23
24 369.0 -6 0 0 0 0 0 0 0 0 0 0 0 24
25 464.8 -3 1 0 0 0 0 0 0 0 0 0 0 25
26 479.1 -1 0 1 0 0 0 0 0 0 0 0 0 26
27 431.3 -3 0 0 1 0 0 0 0 0 0 0 0 27
28 366.5 -4 0 0 0 1 0 0 0 0 0 0 0 28
29 326.3 -6 0 0 0 0 1 0 0 0 0 0 0 29
30 355.1 0 0 0 0 0 0 1 0 0 0 0 0 30
31 331.6 -4 0 0 0 0 0 0 1 0 0 0 0 31
32 261.3 -2 0 0 0 0 0 0 0 1 0 0 0 32
33 249.0 -2 0 0 0 0 0 0 0 0 1 0 0 33
34 205.5 -6 0 0 0 0 0 0 0 0 0 1 0 34
35 235.6 -7 0 0 0 0 0 0 0 0 0 0 1 35
36 240.9 -6 0 0 0 0 0 0 0 0 0 0 0 36
37 264.9 -6 1 0 0 0 0 0 0 0 0 0 0 37
38 253.8 -3 0 1 0 0 0 0 0 0 0 0 0 38
39 232.3 -2 0 0 1 0 0 0 0 0 0 0 0 39
40 193.8 -5 0 0 0 1 0 0 0 0 0 0 0 40
41 177.0 -11 0 0 0 0 1 0 0 0 0 0 0 41
42 213.2 -11 0 0 0 0 0 1 0 0 0 0 0 42
43 207.2 -11 0 0 0 0 0 0 1 0 0 0 0 43
44 180.6 -10 0 0 0 0 0 0 0 1 0 0 0 44
45 188.6 -14 0 0 0 0 0 0 0 0 1 0 0 45
46 175.4 -8 0 0 0 0 0 0 0 0 0 1 0 46
47 199.0 -9 0 0 0 0 0 0 0 0 0 0 1 47
48 179.6 -5 0 0 0 0 0 0 0 0 0 0 0 48
49 225.8 -1 1 0 0 0 0 0 0 0 0 0 0 49
50 234.0 -2 0 1 0 0 0 0 0 0 0 0 0 50
51 200.2 -5 0 0 1 0 0 0 0 0 0 0 0 51
52 183.6 -4 0 0 0 1 0 0 0 0 0 0 0 52
53 178.2 -6 0 0 0 0 1 0 0 0 0 0 0 53
54 203.2 -2 0 0 0 0 0 1 0 0 0 0 0 54
55 208.5 -2 0 0 0 0 0 0 1 0 0 0 0 55
56 191.8 -2 0 0 0 0 0 0 0 1 0 0 0 56
57 172.8 -2 0 0 0 0 0 0 0 0 1 0 0 57
58 148.0 2 0 0 0 0 0 0 0 0 0 1 0 58
59 159.4 1 0 0 0 0 0 0 0 0 0 0 1 59
60 154.5 -8 0 0 0 0 0 0 0 0 0 0 0 60
61 213.2 -1 1 0 0 0 0 0 0 0 0 0 0 61
62 196.4 1 0 1 0 0 0 0 0 0 0 0 0 62
63 182.8 -1 0 0 1 0 0 0 0 0 0 0 0 63
64 176.4 2 0 0 0 1 0 0 0 0 0 0 0 64
65 153.6 2 0 0 0 0 1 0 0 0 0 0 0 65
66 173.2 1 0 0 0 0 0 1 0 0 0 0 0 66
67 171.0 -1 0 0 0 0 0 0 1 0 0 0 0 67
68 151.2 -2 0 0 0 0 0 0 0 1 0 0 0 68
69 161.9 -2 0 0 0 0 0 0 0 0 1 0 0 69
70 157.2 -1 0 0 0 0 0 0 0 0 0 1 0 70
71 201.7 -8 0 0 0 0 0 0 0 0 0 0 1 71
72 236.4 -4 0 0 0 0 0 0 0 0 0 0 0 72
73 356.1 -6 1 0 0 0 0 0 0 0 0 0 0 73
74 398.3 -3 0 1 0 0 0 0 0 0 0 0 0 74
75 403.7 -3 0 0 1 0 0 0 0 0 0 0 0 75
76 384.6 -7 0 0 0 1 0 0 0 0 0 0 0 76
77 365.8 -9 0 0 0 0 1 0 0 0 0 0 0 77
78 368.1 -11 0 0 0 0 0 1 0 0 0 0 0 78
79 367.9 -13 0 0 0 0 0 0 1 0 0 0 0 79
80 347.0 -11 0 0 0 0 0 0 0 1 0 0 0 80
81 343.3 -9 0 0 0 0 0 0 0 0 1 0 0 81
82 292.9 -17 0 0 0 0 0 0 0 0 0 1 0 82
83 311.5 -22 0 0 0 0 0 0 0 0 0 0 1 83
84 300.9 -25 0 0 0 0 0 0 0 0 0 0 0 84
85 366.9 -20 1 0 0 0 0 0 0 0 0 0 0 85
86 356.9 -24 0 1 0 0 0 0 0 0 0 0 0 86
87 329.7 -24 0 0 1 0 0 0 0 0 0 0 0 87
88 316.2 -22 0 0 0 1 0 0 0 0 0 0 0 88
89 269.0 -19 0 0 0 0 1 0 0 0 0 0 0 89
90 289.3 -18 0 0 0 0 0 1 0 0 0 0 0 90
91 266.2 -17 0 0 0 0 0 0 1 0 0 0 0 91
92 253.6 -11 0 0 0 0 0 0 0 1 0 0 0 92
93 233.8 -11 0 0 0 0 0 0 0 0 1 0 0 93
94 228.4 -12 0 0 0 0 0 0 0 0 0 1 0 94
95 253.6 -10 0 0 0 0 0 0 0 0 0 0 1 95
96 260.1 -15 0 0 0 0 0 0 0 0 0 0 0 96
97 306.6 -15 1 0 0 0 0 0 0 0 0 0 0 97
98 309.2 -15 0 1 0 0 0 0 0 0 0 0 0 98
99 309.5 -13 0 0 1 0 0 0 0 0 0 0 0 99
100 271.0 -8 0 0 0 1 0 0 0 0 0 0 0 100
101 279.9 -13 0 0 0 0 1 0 0 0 0 0 0 101
102 317.9 -9 0 0 0 0 0 1 0 0 0 0 0 102
103 298.4 -7 0 0 0 0 0 0 1 0 0 0 0 103
104 246.7 -4 0 0 0 0 0 0 0 1 0 0 0 104
105 227.3 -4 0 0 0 0 0 0 0 0 1 0 0 105
106 209.1 -2 0 0 0 0 0 0 0 0 0 1 0 106
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X M1 M2 M3 M4
218.876 -5.769 72.783 87.620 64.877 44.778
M5 M6 M7 M8 M9 M10
20.745 55.983 47.788 25.649 17.053 -8.405
M11 t
3.013 -0.540
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-103.93 -44.85 -21.23 42.07 180.88
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 218.8763 28.6189 7.648 1.93e-11 ***
X -5.7686 1.1859 -4.864 4.73e-06 ***
M1 72.7833 34.7361 2.095 0.0389 *
M2 87.6198 34.7504 2.521 0.0134 *
M3 64.8766 34.6693 1.871 0.0645 .
M4 44.7776 34.7608 1.288 0.2009
M5 20.7449 34.6512 0.599 0.5509
M6 55.9834 34.7648 1.610 0.1107
M7 47.7882 34.6729 1.378 0.1715
M8 25.6494 34.8488 0.736 0.4636
M9 17.0532 34.9344 0.488 0.6266
M10 -8.4051 34.7910 -0.242 0.8096
M11 3.0128 35.6304 0.085 0.9328
t -0.5400 0.2482 -2.176 0.0321 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 71.18 on 92 degrees of freedom
Multiple R-squared: 0.3111, Adjusted R-squared: 0.2137
F-statistic: 3.195 on 13 and 92 DF, p-value: 0.0005449
> 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,] 0.054900441 1.098009e-01 9.450996e-01
[2,] 0.036310986 7.262197e-02 9.636890e-01
[3,] 0.063955759 1.279115e-01 9.360442e-01
[4,] 0.032915216 6.583043e-02 9.670848e-01
[5,] 0.016137584 3.227517e-02 9.838624e-01
[6,] 0.021871027 4.374205e-02 9.781290e-01
[7,] 0.011870534 2.374107e-02 9.881295e-01
[8,] 0.007400716 1.480143e-02 9.925993e-01
[9,] 0.006808391 1.361678e-02 9.931916e-01
[10,] 0.010302797 2.060559e-02 9.896972e-01
[11,] 0.018342289 3.668458e-02 9.816577e-01
[12,] 0.049816277 9.963255e-02 9.501837e-01
[13,] 0.140893991 2.817880e-01 8.591060e-01
[14,] 0.265635686 5.312714e-01 7.343643e-01
[15,] 0.504106042 9.917879e-01 4.958940e-01
[16,] 0.717782686 5.644346e-01 2.822173e-01
[17,] 0.830537879 3.389242e-01 1.694621e-01
[18,] 0.906043581 1.879128e-01 9.395642e-02
[19,] 0.943936129 1.121277e-01 5.606387e-02
[20,] 0.963744579 7.251084e-02 3.625542e-02
[21,] 0.983732220 3.253556e-02 1.626778e-02
[22,] 0.992715447 1.456911e-02 7.284553e-03
[23,] 0.994229885 1.154023e-02 5.770115e-03
[24,] 0.996123912 7.752176e-03 3.876088e-03
[25,] 0.998139675 3.720649e-03 1.860325e-03
[26,] 0.998897053 2.205894e-03 1.102947e-03
[27,] 0.999142950 1.714100e-03 8.570502e-04
[28,] 0.999118472 1.763055e-03 8.815276e-04
[29,] 0.999022452 1.955096e-03 9.775478e-04
[30,] 0.998459943 3.080113e-03 1.540057e-03
[31,] 0.997623908 4.752184e-03 2.376092e-03
[32,] 0.996475998 7.048004e-03 3.524002e-03
[33,] 0.994496884 1.100623e-02 5.503116e-03
[34,] 0.991899637 1.620073e-02 8.100363e-03
[35,] 0.989738582 2.052284e-02 1.026142e-02
[36,] 0.986393963 2.721207e-02 1.360604e-02
[37,] 0.981339965 3.732007e-02 1.866004e-02
[38,] 0.973358508 5.328298e-02 2.664149e-02
[39,] 0.961654466 7.669107e-02 3.834553e-02
[40,] 0.946090752 1.078185e-01 5.390925e-02
[41,] 0.926835132 1.463297e-01 7.316487e-02
[42,] 0.902028267 1.959435e-01 9.797173e-02
[43,] 0.870796419 2.584072e-01 1.292036e-01
[44,] 0.853362648 2.932747e-01 1.466374e-01
[45,] 0.826767731 3.464645e-01 1.732323e-01
[46,] 0.815062409 3.698752e-01 1.849376e-01
[47,] 0.826204118 3.475918e-01 1.737959e-01
[48,] 0.825083519 3.498330e-01 1.749165e-01
[49,] 0.836304688 3.273906e-01 1.636953e-01
[50,] 0.872922910 2.541542e-01 1.270771e-01
[51,] 0.919050104 1.618998e-01 8.094990e-02
[52,] 0.967813321 6.437336e-02 3.218668e-02
[53,] 0.990783984 1.843203e-02 9.216016e-03
[54,] 0.998607854 2.784293e-03 1.392146e-03
[55,] 0.999896348 2.073048e-04 1.036524e-04
[56,] 0.999996464 7.072124e-06 3.536062e-06
[57,] 0.999998929 2.141918e-06 1.070959e-06
[58,] 0.999999044 1.911000e-06 9.555002e-07
[59,] 0.999998983 2.033675e-06 1.016838e-06
[60,] 0.999997932 4.136568e-06 2.068284e-06
[61,] 0.999995281 9.438954e-06 4.719477e-06
[62,] 0.999992138 1.572351e-05 7.861757e-06
[63,] 0.999976155 4.769072e-05 2.384536e-05
[64,] 0.999934156 1.316872e-04 6.584359e-05
[65,] 0.999918007 1.639861e-04 8.199305e-05
[66,] 0.999899526 2.009485e-04 1.004743e-04
[67,] 0.999780411 4.391775e-04 2.195888e-04
[68,] 0.999401066 1.197869e-03 5.989344e-04
[69,] 0.999622138 7.557233e-04 3.778617e-04
[70,] 0.999550196 8.996086e-04 4.498043e-04
[71,] 0.997963626 4.072749e-03 2.036374e-03
[72,] 0.996421650 7.156701e-03 3.578350e-03
[73,] 0.984054826 3.189035e-02 1.594517e-02
> postscript(file="/var/www/html/rcomp/tmp/1k3171291027904.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2k3171291027904.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3k3171291027904.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4uu0s1291027904.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5uu0s1291027904.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 = 106
Frequency = 1
1 2 3 4 5 6
-50.2509360 -18.9474416 -5.9957352 -20.7937698 -29.7525466 -30.8194864
7 8 9 10 11 12
-27.5528197 -33.7111600 -42.2749602 -47.6765708 -35.7230464 -38.0444224
13 14 15 16 17 18
-37.0562067 -26.5269139 -41.1865100 9.2324092 69.2421827 73.7752429
19 20 21 22 23 24
107.4048088 98.4206701 110.0681724 93.6810577 112.9200862 128.4729118
25 26 27 28 29 30
169.3353292 180.8759244 144.8219795 94.8924954 67.7280673 96.4409804
31 32 33 34 35 36
58.6019958 22.5178572 19.3540570 -21.2217553 -7.7682309 6.8531452
37 38 39 40 41 42
-41.3900887 -49.4809430 -41.9292367 -77.0958216 -103.9344514 -102.4328407
43 44 45 46 47 48
-99.6976236 -97.8503127 -103.7883145 -56.3786227 -49.4250983 -42.1980711
49 50 51 52 53 54
-45.1671032 -57.0321593 -84.8546546 -75.0470378 -67.4114659 -54.0356537
55 56 57 58 59 60
-40.0004366 -34.0216761 -43.8854762 -19.6128853 -24.8593608 -78.1234889
61 62 63 64 65 66
-51.2868699 -70.8462747 -72.7002196 -41.1555020 -39.3828293 -60.2497691
67 68 69 70 71 72
-65.2516528 -68.1414427 -48.3052429 -21.2383031 -27.9960811 33.3309461
73 74 75 76 77 78
69.2506115 114.4597571 143.1429130 121.6077777 115.8433496 71.9078594
79 80 81 82 83 84
68.9059757 82.2218370 99.1951377 28.6451238 7.5244466 -16.8283791
85 86 87 88 89 90
5.7711392 -41.5995681 -45.5164121 -26.8402450 -32.1619211 -40.7917600
91 92 93 94 95 96
-49.3879925 -4.6979296 -15.3617298 -0.5318908 25.3272848 6.5373584
97 98 99 100 101 102
-19.2058754 -30.9023810 4.2178757 15.1996941 19.8296147 46.2054270
103 104 105 106
46.9777449 35.2621567 24.9983565 44.3338466
> postscript(file="/var/www/html/rcomp/tmp/6uu0s1291027904.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 = 106
Frequency = 1
lag(myerror, k = 1) myerror
0 -50.2509360 NA
1 -18.9474416 -50.2509360
2 -5.9957352 -18.9474416
3 -20.7937698 -5.9957352
4 -29.7525466 -20.7937698
5 -30.8194864 -29.7525466
6 -27.5528197 -30.8194864
7 -33.7111600 -27.5528197
8 -42.2749602 -33.7111600
9 -47.6765708 -42.2749602
10 -35.7230464 -47.6765708
11 -38.0444224 -35.7230464
12 -37.0562067 -38.0444224
13 -26.5269139 -37.0562067
14 -41.1865100 -26.5269139
15 9.2324092 -41.1865100
16 69.2421827 9.2324092
17 73.7752429 69.2421827
18 107.4048088 73.7752429
19 98.4206701 107.4048088
20 110.0681724 98.4206701
21 93.6810577 110.0681724
22 112.9200862 93.6810577
23 128.4729118 112.9200862
24 169.3353292 128.4729118
25 180.8759244 169.3353292
26 144.8219795 180.8759244
27 94.8924954 144.8219795
28 67.7280673 94.8924954
29 96.4409804 67.7280673
30 58.6019958 96.4409804
31 22.5178572 58.6019958
32 19.3540570 22.5178572
33 -21.2217553 19.3540570
34 -7.7682309 -21.2217553
35 6.8531452 -7.7682309
36 -41.3900887 6.8531452
37 -49.4809430 -41.3900887
38 -41.9292367 -49.4809430
39 -77.0958216 -41.9292367
40 -103.9344514 -77.0958216
41 -102.4328407 -103.9344514
42 -99.6976236 -102.4328407
43 -97.8503127 -99.6976236
44 -103.7883145 -97.8503127
45 -56.3786227 -103.7883145
46 -49.4250983 -56.3786227
47 -42.1980711 -49.4250983
48 -45.1671032 -42.1980711
49 -57.0321593 -45.1671032
50 -84.8546546 -57.0321593
51 -75.0470378 -84.8546546
52 -67.4114659 -75.0470378
53 -54.0356537 -67.4114659
54 -40.0004366 -54.0356537
55 -34.0216761 -40.0004366
56 -43.8854762 -34.0216761
57 -19.6128853 -43.8854762
58 -24.8593608 -19.6128853
59 -78.1234889 -24.8593608
60 -51.2868699 -78.1234889
61 -70.8462747 -51.2868699
62 -72.7002196 -70.8462747
63 -41.1555020 -72.7002196
64 -39.3828293 -41.1555020
65 -60.2497691 -39.3828293
66 -65.2516528 -60.2497691
67 -68.1414427 -65.2516528
68 -48.3052429 -68.1414427
69 -21.2383031 -48.3052429
70 -27.9960811 -21.2383031
71 33.3309461 -27.9960811
72 69.2506115 33.3309461
73 114.4597571 69.2506115
74 143.1429130 114.4597571
75 121.6077777 143.1429130
76 115.8433496 121.6077777
77 71.9078594 115.8433496
78 68.9059757 71.9078594
79 82.2218370 68.9059757
80 99.1951377 82.2218370
81 28.6451238 99.1951377
82 7.5244466 28.6451238
83 -16.8283791 7.5244466
84 5.7711392 -16.8283791
85 -41.5995681 5.7711392
86 -45.5164121 -41.5995681
87 -26.8402450 -45.5164121
88 -32.1619211 -26.8402450
89 -40.7917600 -32.1619211
90 -49.3879925 -40.7917600
91 -4.6979296 -49.3879925
92 -15.3617298 -4.6979296
93 -0.5318908 -15.3617298
94 25.3272848 -0.5318908
95 6.5373584 25.3272848
96 -19.2058754 6.5373584
97 -30.9023810 -19.2058754
98 4.2178757 -30.9023810
99 15.1996941 4.2178757
100 19.8296147 15.1996941
101 46.2054270 19.8296147
102 46.9777449 46.2054270
103 35.2621567 46.9777449
104 24.9983565 35.2621567
105 44.3338466 24.9983565
106 NA 44.3338466
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -18.9474416 -50.2509360
[2,] -5.9957352 -18.9474416
[3,] -20.7937698 -5.9957352
[4,] -29.7525466 -20.7937698
[5,] -30.8194864 -29.7525466
[6,] -27.5528197 -30.8194864
[7,] -33.7111600 -27.5528197
[8,] -42.2749602 -33.7111600
[9,] -47.6765708 -42.2749602
[10,] -35.7230464 -47.6765708
[11,] -38.0444224 -35.7230464
[12,] -37.0562067 -38.0444224
[13,] -26.5269139 -37.0562067
[14,] -41.1865100 -26.5269139
[15,] 9.2324092 -41.1865100
[16,] 69.2421827 9.2324092
[17,] 73.7752429 69.2421827
[18,] 107.4048088 73.7752429
[19,] 98.4206701 107.4048088
[20,] 110.0681724 98.4206701
[21,] 93.6810577 110.0681724
[22,] 112.9200862 93.6810577
[23,] 128.4729118 112.9200862
[24,] 169.3353292 128.4729118
[25,] 180.8759244 169.3353292
[26,] 144.8219795 180.8759244
[27,] 94.8924954 144.8219795
[28,] 67.7280673 94.8924954
[29,] 96.4409804 67.7280673
[30,] 58.6019958 96.4409804
[31,] 22.5178572 58.6019958
[32,] 19.3540570 22.5178572
[33,] -21.2217553 19.3540570
[34,] -7.7682309 -21.2217553
[35,] 6.8531452 -7.7682309
[36,] -41.3900887 6.8531452
[37,] -49.4809430 -41.3900887
[38,] -41.9292367 -49.4809430
[39,] -77.0958216 -41.9292367
[40,] -103.9344514 -77.0958216
[41,] -102.4328407 -103.9344514
[42,] -99.6976236 -102.4328407
[43,] -97.8503127 -99.6976236
[44,] -103.7883145 -97.8503127
[45,] -56.3786227 -103.7883145
[46,] -49.4250983 -56.3786227
[47,] -42.1980711 -49.4250983
[48,] -45.1671032 -42.1980711
[49,] -57.0321593 -45.1671032
[50,] -84.8546546 -57.0321593
[51,] -75.0470378 -84.8546546
[52,] -67.4114659 -75.0470378
[53,] -54.0356537 -67.4114659
[54,] -40.0004366 -54.0356537
[55,] -34.0216761 -40.0004366
[56,] -43.8854762 -34.0216761
[57,] -19.6128853 -43.8854762
[58,] -24.8593608 -19.6128853
[59,] -78.1234889 -24.8593608
[60,] -51.2868699 -78.1234889
[61,] -70.8462747 -51.2868699
[62,] -72.7002196 -70.8462747
[63,] -41.1555020 -72.7002196
[64,] -39.3828293 -41.1555020
[65,] -60.2497691 -39.3828293
[66,] -65.2516528 -60.2497691
[67,] -68.1414427 -65.2516528
[68,] -48.3052429 -68.1414427
[69,] -21.2383031 -48.3052429
[70,] -27.9960811 -21.2383031
[71,] 33.3309461 -27.9960811
[72,] 69.2506115 33.3309461
[73,] 114.4597571 69.2506115
[74,] 143.1429130 114.4597571
[75,] 121.6077777 143.1429130
[76,] 115.8433496 121.6077777
[77,] 71.9078594 115.8433496
[78,] 68.9059757 71.9078594
[79,] 82.2218370 68.9059757
[80,] 99.1951377 82.2218370
[81,] 28.6451238 99.1951377
[82,] 7.5244466 28.6451238
[83,] -16.8283791 7.5244466
[84,] 5.7711392 -16.8283791
[85,] -41.5995681 5.7711392
[86,] -45.5164121 -41.5995681
[87,] -26.8402450 -45.5164121
[88,] -32.1619211 -26.8402450
[89,] -40.7917600 -32.1619211
[90,] -49.3879925 -40.7917600
[91,] -4.6979296 -49.3879925
[92,] -15.3617298 -4.6979296
[93,] -0.5318908 -15.3617298
[94,] 25.3272848 -0.5318908
[95,] 6.5373584 25.3272848
[96,] -19.2058754 6.5373584
[97,] -30.9023810 -19.2058754
[98,] 4.2178757 -30.9023810
[99,] 15.1996941 4.2178757
[100,] 19.8296147 15.1996941
[101,] 46.2054270 19.8296147
[102,] 46.9777449 46.2054270
[103,] 35.2621567 46.9777449
[104,] 24.9983565 35.2621567
[105,] 44.3338466 24.9983565
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -18.9474416 -50.2509360
2 -5.9957352 -18.9474416
3 -20.7937698 -5.9957352
4 -29.7525466 -20.7937698
5 -30.8194864 -29.7525466
6 -27.5528197 -30.8194864
7 -33.7111600 -27.5528197
8 -42.2749602 -33.7111600
9 -47.6765708 -42.2749602
10 -35.7230464 -47.6765708
11 -38.0444224 -35.7230464
12 -37.0562067 -38.0444224
13 -26.5269139 -37.0562067
14 -41.1865100 -26.5269139
15 9.2324092 -41.1865100
16 69.2421827 9.2324092
17 73.7752429 69.2421827
18 107.4048088 73.7752429
19 98.4206701 107.4048088
20 110.0681724 98.4206701
21 93.6810577 110.0681724
22 112.9200862 93.6810577
23 128.4729118 112.9200862
24 169.3353292 128.4729118
25 180.8759244 169.3353292
26 144.8219795 180.8759244
27 94.8924954 144.8219795
28 67.7280673 94.8924954
29 96.4409804 67.7280673
30 58.6019958 96.4409804
31 22.5178572 58.6019958
32 19.3540570 22.5178572
33 -21.2217553 19.3540570
34 -7.7682309 -21.2217553
35 6.8531452 -7.7682309
36 -41.3900887 6.8531452
37 -49.4809430 -41.3900887
38 -41.9292367 -49.4809430
39 -77.0958216 -41.9292367
40 -103.9344514 -77.0958216
41 -102.4328407 -103.9344514
42 -99.6976236 -102.4328407
43 -97.8503127 -99.6976236
44 -103.7883145 -97.8503127
45 -56.3786227 -103.7883145
46 -49.4250983 -56.3786227
47 -42.1980711 -49.4250983
48 -45.1671032 -42.1980711
49 -57.0321593 -45.1671032
50 -84.8546546 -57.0321593
51 -75.0470378 -84.8546546
52 -67.4114659 -75.0470378
53 -54.0356537 -67.4114659
54 -40.0004366 -54.0356537
55 -34.0216761 -40.0004366
56 -43.8854762 -34.0216761
57 -19.6128853 -43.8854762
58 -24.8593608 -19.6128853
59 -78.1234889 -24.8593608
60 -51.2868699 -78.1234889
61 -70.8462747 -51.2868699
62 -72.7002196 -70.8462747
63 -41.1555020 -72.7002196
64 -39.3828293 -41.1555020
65 -60.2497691 -39.3828293
66 -65.2516528 -60.2497691
67 -68.1414427 -65.2516528
68 -48.3052429 -68.1414427
69 -21.2383031 -48.3052429
70 -27.9960811 -21.2383031
71 33.3309461 -27.9960811
72 69.2506115 33.3309461
73 114.4597571 69.2506115
74 143.1429130 114.4597571
75 121.6077777 143.1429130
76 115.8433496 121.6077777
77 71.9078594 115.8433496
78 68.9059757 71.9078594
79 82.2218370 68.9059757
80 99.1951377 82.2218370
81 28.6451238 99.1951377
82 7.5244466 28.6451238
83 -16.8283791 7.5244466
84 5.7711392 -16.8283791
85 -41.5995681 5.7711392
86 -45.5164121 -41.5995681
87 -26.8402450 -45.5164121
88 -32.1619211 -26.8402450
89 -40.7917600 -32.1619211
90 -49.3879925 -40.7917600
91 -4.6979296 -49.3879925
92 -15.3617298 -4.6979296
93 -0.5318908 -15.3617298
94 25.3272848 -0.5318908
95 6.5373584 25.3272848
96 -19.2058754 6.5373584
97 -30.9023810 -19.2058754
98 4.2178757 -30.9023810
99 15.1996941 4.2178757
100 19.8296147 15.1996941
101 46.2054270 19.8296147
102 46.9777449 46.2054270
103 35.2621567 46.9777449
104 24.9983565 35.2621567
105 44.3338466 24.9983565
> 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/754id1291027904.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/854id1291027904.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9gdhy1291027904.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10gdhy1291027904.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/111vxm1291027904.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/125eea1291027904.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/13bxbl1291027904.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/14m6s61291027904.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/157pru1291027904.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/16ly6l1291027904.tab")
+ }
>
> try(system("convert tmp/1k3171291027904.ps tmp/1k3171291027904.png",intern=TRUE))
character(0)
> try(system("convert tmp/2k3171291027904.ps tmp/2k3171291027904.png",intern=TRUE))
character(0)
> try(system("convert tmp/3k3171291027904.ps tmp/3k3171291027904.png",intern=TRUE))
character(0)
> try(system("convert tmp/4uu0s1291027904.ps tmp/4uu0s1291027904.png",intern=TRUE))
character(0)
> try(system("convert tmp/5uu0s1291027904.ps tmp/5uu0s1291027904.png",intern=TRUE))
character(0)
> try(system("convert tmp/6uu0s1291027904.ps tmp/6uu0s1291027904.png",intern=TRUE))
character(0)
> try(system("convert tmp/754id1291027904.ps tmp/754id1291027904.png",intern=TRUE))
character(0)
> try(system("convert tmp/854id1291027904.ps tmp/854id1291027904.png",intern=TRUE))
character(0)
> try(system("convert tmp/9gdhy1291027904.ps tmp/9gdhy1291027904.png",intern=TRUE))
character(0)
> try(system("convert tmp/10gdhy1291027904.ps tmp/10gdhy1291027904.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.147 1.644 6.799