R version 2.8.0 (2008-10-20)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(1721
+ ,0
+ ,0.44
+ ,1476
+ ,0
+ ,0.09
+ ,1842
+ ,0
+ ,0.2
+ ,2171
+ ,0
+ ,0.82
+ ,1670
+ ,0
+ ,0.5
+ ,1540
+ ,0
+ ,0.2
+ ,1266
+ ,0
+ ,1
+ ,897
+ ,0
+ ,0.47
+ ,1266
+ ,0
+ ,0.49
+ ,1519
+ ,0
+ ,0.82
+ ,1074
+ ,0
+ ,0.39
+ ,1435
+ ,0
+ ,0.6
+ ,1385
+ ,0
+ ,0.59
+ ,1440
+ ,0
+ ,0.72
+ ,1883
+ ,0
+ ,0.97
+ ,1822
+ ,0
+ ,0.58
+ ,1661
+ ,0
+ ,0.27
+ ,1774
+ ,0
+ ,0.84
+ ,1133
+ ,0
+ ,0.51
+ ,1361
+ ,0
+ ,0.13
+ ,1688
+ ,0
+ ,0.65
+ ,2216
+ ,0
+ ,0.51
+ ,2896
+ ,0
+ ,1.06
+ ,1382
+ ,0
+ ,0.81
+ ,1330
+ ,0
+ ,0.54
+ ,1419
+ ,0
+ ,0.85
+ ,1662
+ ,0
+ ,0.93
+ ,2040
+ ,0
+ ,0.29
+ ,2126
+ ,0
+ ,1.01
+ ,1649
+ ,0
+ ,0.65
+ ,1610
+ ,0
+ ,0.88
+ ,1952
+ ,0
+ ,0.45
+ ,2102
+ ,0
+ ,0.74
+ ,1749
+ ,0
+ ,1.08
+ ,2091
+ ,0
+ ,0.27
+ ,3036
+ ,0
+ ,0.24
+ ,2414
+ ,0
+ ,0.27
+ ,2097
+ ,0
+ ,0.25
+ ,2705
+ ,0
+ ,0.69
+ ,2431
+ ,0
+ ,0.73
+ ,4192
+ ,1
+ ,1.04
+ ,3990
+ ,0
+ ,1.04
+ ,2854
+ ,0
+ ,0.3
+ ,1966
+ ,0
+ ,0.59
+ ,2431
+ ,0
+ ,0.72
+ ,2763
+ ,0
+ ,0.22
+ ,2831
+ ,0
+ ,1.12
+ ,2023
+ ,0
+ ,0.93
+ ,2934
+ ,0
+ ,0.99
+ ,2489
+ ,0
+ ,0.56
+ ,3252
+ ,0
+ ,1
+ ,3018
+ ,0
+ ,0.57
+ ,3193
+ ,0
+ ,1
+ ,3976
+ ,0
+ ,0.97
+ ,2584
+ ,0
+ ,0.3
+ ,2512
+ ,0
+ ,0.45
+ ,2169
+ ,0
+ ,0.73
+ ,2504
+ ,0
+ ,1.13
+ ,1843
+ ,0
+ ,0.65
+ ,1408
+ ,-1
+ ,0.64
+ ,2179
+ ,0
+ ,0.68
+ ,3690
+ ,0
+ ,0.41
+ ,2372
+ ,0
+ ,0.98
+ ,2494
+ ,0
+ ,0.3
+ ,3872
+ ,0
+ ,0.37
+ ,2786
+ ,0
+ ,1.12
+ ,2312
+ ,0
+ ,0.4
+ ,1599
+ ,0
+ ,0.5
+ ,3167
+ ,0
+ ,1.23
+ ,3433
+ ,0
+ ,0.94
+ ,2648
+ ,0
+ ,1.08
+ ,1978
+ ,0
+ ,1.12
+ ,1947
+ ,0
+ ,0.83
+ ,3113
+ ,0
+ ,1.22
+ ,2856
+ ,0
+ ,0.55
+ ,3174
+ ,0
+ ,0.38
+ ,3507
+ ,0
+ ,1.26
+ ,4174
+ ,0
+ ,0.49
+ ,2978
+ ,0
+ ,1.13
+ ,4428
+ ,0
+ ,1.07
+ ,2832
+ ,0
+ ,0.86
+ ,2930
+ ,0
+ ,0.94
+ ,3681
+ ,0
+ ,0.45
+ ,3253
+ ,0
+ ,0.66
+ ,1660
+ ,-1
+ ,0.71
+ ,2208
+ ,0
+ ,0.54
+ ,3139
+ ,0
+ ,0.9
+ ,3409
+ ,0
+ ,1.23
+ ,3445
+ ,0
+ ,0.46
+ ,2410
+ ,0
+ ,1.33
+ ,3262
+ ,0
+ ,0.64
+ ,2897
+ ,0
+ ,0.9
+ ,2526
+ ,0
+ ,0.5
+ ,3982
+ ,0
+ ,1.37
+ ,4097
+ ,0
+ ,0.96
+ ,3403
+ ,0
+ ,0.62
+ ,3362
+ ,0
+ ,1.24
+ ,2708
+ ,0
+ ,1.1
+ ,3129
+ ,0
+ ,0.86
+ ,3550
+ ,0
+ ,1.2
+ ,2696
+ ,0
+ ,0.77
+ ,2885
+ ,0
+ ,0.67
+ ,2945
+ ,0
+ ,1.05
+ ,3600
+ ,0
+ ,1.32
+ ,3808
+ ,0
+ ,0.6
+ ,3671
+ ,0
+ ,1.31
+ ,4005
+ ,0
+ ,1.41)
+ ,dim=c(3
+ ,107)
+ ,dimnames=list(c('Y'
+ ,'D'
+ ,'X')
+ ,1:107))
> y <- array(NA,dim=c(3,107),dimnames=list(c('Y','D','X'),1:107))
> 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 D X M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 1721 0 0.44 1 0 0 0 0 0 0 0 0 0 0 1
2 1476 0 0.09 0 1 0 0 0 0 0 0 0 0 0 2
3 1842 0 0.20 0 0 1 0 0 0 0 0 0 0 0 3
4 2171 0 0.82 0 0 0 1 0 0 0 0 0 0 0 4
5 1670 0 0.50 0 0 0 0 1 0 0 0 0 0 0 5
6 1540 0 0.20 0 0 0 0 0 1 0 0 0 0 0 6
7 1266 0 1.00 0 0 0 0 0 0 1 0 0 0 0 7
8 897 0 0.47 0 0 0 0 0 0 0 1 0 0 0 8
9 1266 0 0.49 0 0 0 0 0 0 0 0 1 0 0 9
10 1519 0 0.82 0 0 0 0 0 0 0 0 0 1 0 10
11 1074 0 0.39 0 0 0 0 0 0 0 0 0 0 1 11
12 1435 0 0.60 0 0 0 0 0 0 0 0 0 0 0 12
13 1385 0 0.59 1 0 0 0 0 0 0 0 0 0 0 13
14 1440 0 0.72 0 1 0 0 0 0 0 0 0 0 0 14
15 1883 0 0.97 0 0 1 0 0 0 0 0 0 0 0 15
16 1822 0 0.58 0 0 0 1 0 0 0 0 0 0 0 16
17 1661 0 0.27 0 0 0 0 1 0 0 0 0 0 0 17
18 1774 0 0.84 0 0 0 0 0 1 0 0 0 0 0 18
19 1133 0 0.51 0 0 0 0 0 0 1 0 0 0 0 19
20 1361 0 0.13 0 0 0 0 0 0 0 1 0 0 0 20
21 1688 0 0.65 0 0 0 0 0 0 0 0 1 0 0 21
22 2216 0 0.51 0 0 0 0 0 0 0 0 0 1 0 22
23 2896 0 1.06 0 0 0 0 0 0 0 0 0 0 1 23
24 1382 0 0.81 0 0 0 0 0 0 0 0 0 0 0 24
25 1330 0 0.54 1 0 0 0 0 0 0 0 0 0 0 25
26 1419 0 0.85 0 1 0 0 0 0 0 0 0 0 0 26
27 1662 0 0.93 0 0 1 0 0 0 0 0 0 0 0 27
28 2040 0 0.29 0 0 0 1 0 0 0 0 0 0 0 28
29 2126 0 1.01 0 0 0 0 1 0 0 0 0 0 0 29
30 1649 0 0.65 0 0 0 0 0 1 0 0 0 0 0 30
31 1610 0 0.88 0 0 0 0 0 0 1 0 0 0 0 31
32 1952 0 0.45 0 0 0 0 0 0 0 1 0 0 0 32
33 2102 0 0.74 0 0 0 0 0 0 0 0 1 0 0 33
34 1749 0 1.08 0 0 0 0 0 0 0 0 0 1 0 34
35 2091 0 0.27 0 0 0 0 0 0 0 0 0 0 1 35
36 3036 0 0.24 0 0 0 0 0 0 0 0 0 0 0 36
37 2414 0 0.27 1 0 0 0 0 0 0 0 0 0 0 37
38 2097 0 0.25 0 1 0 0 0 0 0 0 0 0 0 38
39 2705 0 0.69 0 0 1 0 0 0 0 0 0 0 0 39
40 2431 0 0.73 0 0 0 1 0 0 0 0 0 0 0 40
41 4192 1 1.04 0 0 0 0 1 0 0 0 0 0 0 41
42 3990 0 1.04 0 0 0 0 0 1 0 0 0 0 0 42
43 2854 0 0.30 0 0 0 0 0 0 1 0 0 0 0 43
44 1966 0 0.59 0 0 0 0 0 0 0 1 0 0 0 44
45 2431 0 0.72 0 0 0 0 0 0 0 0 1 0 0 45
46 2763 0 0.22 0 0 0 0 0 0 0 0 0 1 0 46
47 2831 0 1.12 0 0 0 0 0 0 0 0 0 0 1 47
48 2023 0 0.93 0 0 0 0 0 0 0 0 0 0 0 48
49 2934 0 0.99 1 0 0 0 0 0 0 0 0 0 0 49
50 2489 0 0.56 0 1 0 0 0 0 0 0 0 0 0 50
51 3252 0 1.00 0 0 1 0 0 0 0 0 0 0 0 51
52 3018 0 0.57 0 0 0 1 0 0 0 0 0 0 0 52
53 3193 0 1.00 0 0 0 0 1 0 0 0 0 0 0 53
54 3976 0 0.97 0 0 0 0 0 1 0 0 0 0 0 54
55 2584 0 0.30 0 0 0 0 0 0 1 0 0 0 0 55
56 2512 0 0.45 0 0 0 0 0 0 0 1 0 0 0 56
57 2169 0 0.73 0 0 0 0 0 0 0 0 1 0 0 57
58 2504 0 1.13 0 0 0 0 0 0 0 0 0 1 0 58
59 1843 0 0.65 0 0 0 0 0 0 0 0 0 0 1 59
60 1408 -1 0.64 0 0 0 0 0 0 0 0 0 0 0 60
61 2179 0 0.68 1 0 0 0 0 0 0 0 0 0 0 61
62 3690 0 0.41 0 1 0 0 0 0 0 0 0 0 0 62
63 2372 0 0.98 0 0 1 0 0 0 0 0 0 0 0 63
64 2494 0 0.30 0 0 0 1 0 0 0 0 0 0 0 64
65 3872 0 0.37 0 0 0 0 1 0 0 0 0 0 0 65
66 2786 0 1.12 0 0 0 0 0 1 0 0 0 0 0 66
67 2312 0 0.40 0 0 0 0 0 0 1 0 0 0 0 67
68 1599 0 0.50 0 0 0 0 0 0 0 1 0 0 0 68
69 3167 0 1.23 0 0 0 0 0 0 0 0 1 0 0 69
70 3433 0 0.94 0 0 0 0 0 0 0 0 0 1 0 70
71 2648 0 1.08 0 0 0 0 0 0 0 0 0 0 1 71
72 1978 0 1.12 0 0 0 0 0 0 0 0 0 0 0 72
73 1947 0 0.83 1 0 0 0 0 0 0 0 0 0 0 73
74 3113 0 1.22 0 1 0 0 0 0 0 0 0 0 0 74
75 2856 0 0.55 0 0 1 0 0 0 0 0 0 0 0 75
76 3174 0 0.38 0 0 0 1 0 0 0 0 0 0 0 76
77 3507 0 1.26 0 0 0 0 1 0 0 0 0 0 0 77
78 4174 0 0.49 0 0 0 0 0 1 0 0 0 0 0 78
79 2978 0 1.13 0 0 0 0 0 0 1 0 0 0 0 79
80 4428 0 1.07 0 0 0 0 0 0 0 1 0 0 0 80
81 2832 0 0.86 0 0 0 0 0 0 0 0 1 0 0 81
82 2930 0 0.94 0 0 0 0 0 0 0 0 0 1 0 82
83 3681 0 0.45 0 0 0 0 0 0 0 0 0 0 1 83
84 3253 0 0.66 0 0 0 0 0 0 0 0 0 0 0 84
85 1660 -1 0.71 1 0 0 0 0 0 0 0 0 0 0 85
86 2208 0 0.54 0 1 0 0 0 0 0 0 0 0 0 86
87 3139 0 0.90 0 0 1 0 0 0 0 0 0 0 0 87
88 3409 0 1.23 0 0 0 1 0 0 0 0 0 0 0 88
89 3445 0 0.46 0 0 0 0 1 0 0 0 0 0 0 89
90 2410 0 1.33 0 0 0 0 0 1 0 0 0 0 0 90
91 3262 0 0.64 0 0 0 0 0 0 1 0 0 0 0 91
92 2897 0 0.90 0 0 0 0 0 0 0 1 0 0 0 92
93 2526 0 0.50 0 0 0 0 0 0 0 0 1 0 0 93
94 3982 0 1.37 0 0 0 0 0 0 0 0 0 1 0 94
95 4097 0 0.96 0 0 0 0 0 0 0 0 0 0 1 95
96 3403 0 0.62 0 0 0 0 0 0 0 0 0 0 0 96
97 3362 0 1.24 1 0 0 0 0 0 0 0 0 0 0 97
98 2708 0 1.10 0 1 0 0 0 0 0 0 0 0 0 98
99 3129 0 0.86 0 0 1 0 0 0 0 0 0 0 0 99
100 3550 0 1.20 0 0 0 1 0 0 0 0 0 0 0 100
101 2696 0 0.77 0 0 0 0 1 0 0 0 0 0 0 101
102 2885 0 0.67 0 0 0 0 0 1 0 0 0 0 0 102
103 2945 0 1.05 0 0 0 0 0 0 1 0 0 0 0 103
104 3600 0 1.32 0 0 0 0 0 0 0 1 0 0 0 104
105 3808 0 0.60 0 0 0 0 0 0 0 0 1 0 0 105
106 3671 0 1.31 0 0 0 0 0 0 0 0 0 1 0 106
107 4005 0 1.41 0 0 0 0 0 0 0 0 0 0 1 107
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) D X M1 M2 M3
1289.31 1344.84 84.79 -56.51 -30.59 181.62
M4 M5 M6 M7 M8 M9
312.24 388.07 381.06 -99.29 -86.02 -25.33
M10 M11 t
246.77 280.26 19.61
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1138.1 -300.8 -54.9 283.8 1565.1
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1289.310 236.229 5.458 4.05e-07 ***
D 1344.841 341.437 3.939 0.000159 ***
X 84.794 189.530 0.447 0.655643
M1 -56.513 266.836 -0.212 0.832739
M2 -30.591 270.338 -0.113 0.910152
M3 181.618 270.282 0.672 0.503295
M4 312.240 270.085 1.156 0.250642
M5 388.072 278.349 1.394 0.166617
M6 381.063 270.436 1.409 0.162186
M7 -99.295 270.162 -0.368 0.714063
M8 -86.019 270.568 -0.318 0.751267
M9 -25.326 270.154 -0.094 0.925515
M10 246.771 272.238 0.906 0.367063
M11 280.256 270.579 1.036 0.303026
t 19.611 1.939 10.112 < 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 548.8 on 92 degrees of freedom
Multiple R-squared: 0.6405, Adjusted R-squared: 0.5858
F-statistic: 11.71 on 14 and 92 DF, p-value: 5.53e-15
> 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,] 0.02731568 0.05463136 0.97268432
[2,] 0.00778041 0.01556082 0.99221959
[3,] 0.02054294 0.04108589 0.97945706
[4,] 0.01442042 0.02884083 0.98557958
[5,] 0.02014594 0.04029189 0.97985406
[6,] 0.24166446 0.48332893 0.75833554
[7,] 0.18063295 0.36126589 0.81936705
[8,] 0.14984563 0.29969126 0.85015437
[9,] 0.11459179 0.22918359 0.88540821
[10,] 0.09106239 0.18212477 0.90893761
[11,] 0.05865971 0.11731943 0.94134029
[12,] 0.03909994 0.07819988 0.96090006
[13,] 0.02951828 0.05903656 0.97048172
[14,] 0.02139080 0.04278160 0.97860920
[15,] 0.02314147 0.04628293 0.97685853
[16,] 0.01720799 0.03441599 0.98279201
[17,] 0.01644501 0.03289002 0.98355499
[18,] 0.01045831 0.02091662 0.98954169
[19,] 0.07127573 0.14255147 0.92872427
[20,] 0.06095355 0.12190709 0.93904645
[21,] 0.04261461 0.08522923 0.95738539
[22,] 0.03328244 0.06656489 0.96671756
[23,] 0.02251348 0.04502695 0.97748652
[24,] 0.01439669 0.02879339 0.98560331
[25,] 0.14434486 0.28868971 0.85565514
[26,] 0.16411184 0.32822369 0.83588816
[27,] 0.13469557 0.26939115 0.86530443
[28,] 0.10117312 0.20234623 0.89882688
[29,] 0.07558125 0.15116250 0.92441875
[30,] 0.05483141 0.10966283 0.94516859
[31,] 0.05124772 0.10249545 0.94875228
[32,] 0.04587740 0.09175480 0.95412260
[33,] 0.03195850 0.06391700 0.96804150
[34,] 0.02835431 0.05670861 0.97164569
[35,] 0.01989554 0.03979107 0.98010446
[36,] 0.01419935 0.02839870 0.98580065
[37,] 0.03096615 0.06193230 0.96903385
[38,] 0.02211252 0.04422505 0.97788748
[39,] 0.01479217 0.02958433 0.98520783
[40,] 0.01411917 0.02823834 0.98588083
[41,] 0.01203322 0.02406645 0.98796678
[42,] 0.04377052 0.08754104 0.95622948
[43,] 0.03111517 0.06223034 0.96888483
[44,] 0.03066155 0.06132309 0.96933845
[45,] 0.06956164 0.13912327 0.93043836
[46,] 0.07512254 0.15024507 0.92487746
[47,] 0.07469561 0.14939122 0.92530439
[48,] 0.10085226 0.20170452 0.89914774
[49,] 0.09075472 0.18150945 0.90924528
[50,] 0.07488048 0.14976097 0.92511952
[51,] 0.22281739 0.44563478 0.77718261
[52,] 0.19097319 0.38194638 0.80902681
[53,] 0.15462848 0.30925695 0.84537152
[54,] 0.19039026 0.38078053 0.80960974
[55,] 0.34050369 0.68100739 0.65949631
[56,] 0.49214585 0.98429170 0.50785415
[57,] 0.45737265 0.91474531 0.54262735
[58,] 0.39904731 0.79809462 0.60095269
[59,] 0.33735570 0.67471140 0.66264430
[60,] 0.29270761 0.58541521 0.70729239
[61,] 0.62406670 0.75186660 0.37593330
[62,] 0.53892194 0.92215612 0.46107806
[63,] 0.90965334 0.18069333 0.09034666
[64,] 0.86424590 0.27150820 0.13575410
[65,] 0.86278141 0.27443719 0.13721859
[66,] 0.80575625 0.38848749 0.19424375
[67,] 0.71985601 0.56028799 0.28014399
[68,] 0.61350886 0.77298229 0.38649114
[69,] 0.57562173 0.84875654 0.42437827
[70,] 0.45342222 0.90684443 0.54657778
[71,] 0.31704687 0.63409374 0.68295313
[72,] 0.33301829 0.66603658 0.66698171
> postscript(file="/var/www/html/freestat/rcomp/tmp/1mtpd1229539183.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/2turv1229539183.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/freestat/rcomp/tmp/330ct1229539183.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/46gpa1229539183.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/5gv8l1229539183.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 = 107
Frequency = 1
1 2 3 4 5 6
431.28275 170.42789 295.28101 421.47531 -147.83252 -264.99647
7 8 9 10 11 12
-146.08464 -503.03051 -216.02991 -282.71985 -744.35368 -140.51503
13 14 15 16 17 18
-152.76459 -154.32076 35.66114 -142.50222 -372.65800 -320.59307
19 20 21 22 23 24
-472.86357 -245.52860 -42.92520 205.23823 785.50589 -446.65004
25 26 27 28 29 30
-438.85306 -421.67222 -417.27527 -135.24002 -205.73404 -664.81032
31 32 33 34 35 36
-262.56568 83.00901 128.11512 -545.42276 -187.83472 1020.35458
37 38 39 40 41 42
432.71324 71.87624 410.74720 -16.87775 277.55310 1407.79168
43 44 45 46 47 48
795.28689 -150.19039 223.48283 306.17224 244.76186 -286.48174
49 50 51 52 53 54
656.33309 202.26179 696.13275 348.36117 391.45754 1164.39911
55 56 57 58 59 60
289.95870 172.35264 -274.69330 -265.31885 -938.71296 232.62129
61 62 63 64 65 66
-307.70883 1180.65276 -417.49955 -388.07252 888.54982 -273.64824
67 68 69 70 71 72
-225.84892 -980.21527 445.58131 444.46390 -405.50273 -818.24904
73 74 75 76 77 78
-787.75617 299.64111 -132.36614 49.81574 212.75462 932.44405
79 80 81 82 83 84
142.92298 1565.12374 -93.37294 -293.86428 445.58955 260.42820
85 86 87 88 89 90
44.93181 -783.02688 -114.37236 -22.58768 -16.73804 -1138.11143
91 92 93 94 95 96
233.14406 -186.78939 -604.17514 486.34594 583.01622 178.49179
97 98 99 100 101 102
121.82175 -565.83993 -356.30877 -114.37204 -1027.35249 -842.47531
103 104 105 106 107
-353.94983 245.26877 434.01723 -54.89458 217.53056
> postscript(file="/var/www/html/freestat/rcomp/tmp/62wij1229539183.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 = 107
Frequency = 1
lag(myerror, k = 1) myerror
0 431.28275 NA
1 170.42789 431.28275
2 295.28101 170.42789
3 421.47531 295.28101
4 -147.83252 421.47531
5 -264.99647 -147.83252
6 -146.08464 -264.99647
7 -503.03051 -146.08464
8 -216.02991 -503.03051
9 -282.71985 -216.02991
10 -744.35368 -282.71985
11 -140.51503 -744.35368
12 -152.76459 -140.51503
13 -154.32076 -152.76459
14 35.66114 -154.32076
15 -142.50222 35.66114
16 -372.65800 -142.50222
17 -320.59307 -372.65800
18 -472.86357 -320.59307
19 -245.52860 -472.86357
20 -42.92520 -245.52860
21 205.23823 -42.92520
22 785.50589 205.23823
23 -446.65004 785.50589
24 -438.85306 -446.65004
25 -421.67222 -438.85306
26 -417.27527 -421.67222
27 -135.24002 -417.27527
28 -205.73404 -135.24002
29 -664.81032 -205.73404
30 -262.56568 -664.81032
31 83.00901 -262.56568
32 128.11512 83.00901
33 -545.42276 128.11512
34 -187.83472 -545.42276
35 1020.35458 -187.83472
36 432.71324 1020.35458
37 71.87624 432.71324
38 410.74720 71.87624
39 -16.87775 410.74720
40 277.55310 -16.87775
41 1407.79168 277.55310
42 795.28689 1407.79168
43 -150.19039 795.28689
44 223.48283 -150.19039
45 306.17224 223.48283
46 244.76186 306.17224
47 -286.48174 244.76186
48 656.33309 -286.48174
49 202.26179 656.33309
50 696.13275 202.26179
51 348.36117 696.13275
52 391.45754 348.36117
53 1164.39911 391.45754
54 289.95870 1164.39911
55 172.35264 289.95870
56 -274.69330 172.35264
57 -265.31885 -274.69330
58 -938.71296 -265.31885
59 232.62129 -938.71296
60 -307.70883 232.62129
61 1180.65276 -307.70883
62 -417.49955 1180.65276
63 -388.07252 -417.49955
64 888.54982 -388.07252
65 -273.64824 888.54982
66 -225.84892 -273.64824
67 -980.21527 -225.84892
68 445.58131 -980.21527
69 444.46390 445.58131
70 -405.50273 444.46390
71 -818.24904 -405.50273
72 -787.75617 -818.24904
73 299.64111 -787.75617
74 -132.36614 299.64111
75 49.81574 -132.36614
76 212.75462 49.81574
77 932.44405 212.75462
78 142.92298 932.44405
79 1565.12374 142.92298
80 -93.37294 1565.12374
81 -293.86428 -93.37294
82 445.58955 -293.86428
83 260.42820 445.58955
84 44.93181 260.42820
85 -783.02688 44.93181
86 -114.37236 -783.02688
87 -22.58768 -114.37236
88 -16.73804 -22.58768
89 -1138.11143 -16.73804
90 233.14406 -1138.11143
91 -186.78939 233.14406
92 -604.17514 -186.78939
93 486.34594 -604.17514
94 583.01622 486.34594
95 178.49179 583.01622
96 121.82175 178.49179
97 -565.83993 121.82175
98 -356.30877 -565.83993
99 -114.37204 -356.30877
100 -1027.35249 -114.37204
101 -842.47531 -1027.35249
102 -353.94983 -842.47531
103 245.26877 -353.94983
104 434.01723 245.26877
105 -54.89458 434.01723
106 217.53056 -54.89458
107 NA 217.53056
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 170.42789 431.28275
[2,] 295.28101 170.42789
[3,] 421.47531 295.28101
[4,] -147.83252 421.47531
[5,] -264.99647 -147.83252
[6,] -146.08464 -264.99647
[7,] -503.03051 -146.08464
[8,] -216.02991 -503.03051
[9,] -282.71985 -216.02991
[10,] -744.35368 -282.71985
[11,] -140.51503 -744.35368
[12,] -152.76459 -140.51503
[13,] -154.32076 -152.76459
[14,] 35.66114 -154.32076
[15,] -142.50222 35.66114
[16,] -372.65800 -142.50222
[17,] -320.59307 -372.65800
[18,] -472.86357 -320.59307
[19,] -245.52860 -472.86357
[20,] -42.92520 -245.52860
[21,] 205.23823 -42.92520
[22,] 785.50589 205.23823
[23,] -446.65004 785.50589
[24,] -438.85306 -446.65004
[25,] -421.67222 -438.85306
[26,] -417.27527 -421.67222
[27,] -135.24002 -417.27527
[28,] -205.73404 -135.24002
[29,] -664.81032 -205.73404
[30,] -262.56568 -664.81032
[31,] 83.00901 -262.56568
[32,] 128.11512 83.00901
[33,] -545.42276 128.11512
[34,] -187.83472 -545.42276
[35,] 1020.35458 -187.83472
[36,] 432.71324 1020.35458
[37,] 71.87624 432.71324
[38,] 410.74720 71.87624
[39,] -16.87775 410.74720
[40,] 277.55310 -16.87775
[41,] 1407.79168 277.55310
[42,] 795.28689 1407.79168
[43,] -150.19039 795.28689
[44,] 223.48283 -150.19039
[45,] 306.17224 223.48283
[46,] 244.76186 306.17224
[47,] -286.48174 244.76186
[48,] 656.33309 -286.48174
[49,] 202.26179 656.33309
[50,] 696.13275 202.26179
[51,] 348.36117 696.13275
[52,] 391.45754 348.36117
[53,] 1164.39911 391.45754
[54,] 289.95870 1164.39911
[55,] 172.35264 289.95870
[56,] -274.69330 172.35264
[57,] -265.31885 -274.69330
[58,] -938.71296 -265.31885
[59,] 232.62129 -938.71296
[60,] -307.70883 232.62129
[61,] 1180.65276 -307.70883
[62,] -417.49955 1180.65276
[63,] -388.07252 -417.49955
[64,] 888.54982 -388.07252
[65,] -273.64824 888.54982
[66,] -225.84892 -273.64824
[67,] -980.21527 -225.84892
[68,] 445.58131 -980.21527
[69,] 444.46390 445.58131
[70,] -405.50273 444.46390
[71,] -818.24904 -405.50273
[72,] -787.75617 -818.24904
[73,] 299.64111 -787.75617
[74,] -132.36614 299.64111
[75,] 49.81574 -132.36614
[76,] 212.75462 49.81574
[77,] 932.44405 212.75462
[78,] 142.92298 932.44405
[79,] 1565.12374 142.92298
[80,] -93.37294 1565.12374
[81,] -293.86428 -93.37294
[82,] 445.58955 -293.86428
[83,] 260.42820 445.58955
[84,] 44.93181 260.42820
[85,] -783.02688 44.93181
[86,] -114.37236 -783.02688
[87,] -22.58768 -114.37236
[88,] -16.73804 -22.58768
[89,] -1138.11143 -16.73804
[90,] 233.14406 -1138.11143
[91,] -186.78939 233.14406
[92,] -604.17514 -186.78939
[93,] 486.34594 -604.17514
[94,] 583.01622 486.34594
[95,] 178.49179 583.01622
[96,] 121.82175 178.49179
[97,] -565.83993 121.82175
[98,] -356.30877 -565.83993
[99,] -114.37204 -356.30877
[100,] -1027.35249 -114.37204
[101,] -842.47531 -1027.35249
[102,] -353.94983 -842.47531
[103,] 245.26877 -353.94983
[104,] 434.01723 245.26877
[105,] -54.89458 434.01723
[106,] 217.53056 -54.89458
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 170.42789 431.28275
2 295.28101 170.42789
3 421.47531 295.28101
4 -147.83252 421.47531
5 -264.99647 -147.83252
6 -146.08464 -264.99647
7 -503.03051 -146.08464
8 -216.02991 -503.03051
9 -282.71985 -216.02991
10 -744.35368 -282.71985
11 -140.51503 -744.35368
12 -152.76459 -140.51503
13 -154.32076 -152.76459
14 35.66114 -154.32076
15 -142.50222 35.66114
16 -372.65800 -142.50222
17 -320.59307 -372.65800
18 -472.86357 -320.59307
19 -245.52860 -472.86357
20 -42.92520 -245.52860
21 205.23823 -42.92520
22 785.50589 205.23823
23 -446.65004 785.50589
24 -438.85306 -446.65004
25 -421.67222 -438.85306
26 -417.27527 -421.67222
27 -135.24002 -417.27527
28 -205.73404 -135.24002
29 -664.81032 -205.73404
30 -262.56568 -664.81032
31 83.00901 -262.56568
32 128.11512 83.00901
33 -545.42276 128.11512
34 -187.83472 -545.42276
35 1020.35458 -187.83472
36 432.71324 1020.35458
37 71.87624 432.71324
38 410.74720 71.87624
39 -16.87775 410.74720
40 277.55310 -16.87775
41 1407.79168 277.55310
42 795.28689 1407.79168
43 -150.19039 795.28689
44 223.48283 -150.19039
45 306.17224 223.48283
46 244.76186 306.17224
47 -286.48174 244.76186
48 656.33309 -286.48174
49 202.26179 656.33309
50 696.13275 202.26179
51 348.36117 696.13275
52 391.45754 348.36117
53 1164.39911 391.45754
54 289.95870 1164.39911
55 172.35264 289.95870
56 -274.69330 172.35264
57 -265.31885 -274.69330
58 -938.71296 -265.31885
59 232.62129 -938.71296
60 -307.70883 232.62129
61 1180.65276 -307.70883
62 -417.49955 1180.65276
63 -388.07252 -417.49955
64 888.54982 -388.07252
65 -273.64824 888.54982
66 -225.84892 -273.64824
67 -980.21527 -225.84892
68 445.58131 -980.21527
69 444.46390 445.58131
70 -405.50273 444.46390
71 -818.24904 -405.50273
72 -787.75617 -818.24904
73 299.64111 -787.75617
74 -132.36614 299.64111
75 49.81574 -132.36614
76 212.75462 49.81574
77 932.44405 212.75462
78 142.92298 932.44405
79 1565.12374 142.92298
80 -93.37294 1565.12374
81 -293.86428 -93.37294
82 445.58955 -293.86428
83 260.42820 445.58955
84 44.93181 260.42820
85 -783.02688 44.93181
86 -114.37236 -783.02688
87 -22.58768 -114.37236
88 -16.73804 -22.58768
89 -1138.11143 -16.73804
90 233.14406 -1138.11143
91 -186.78939 233.14406
92 -604.17514 -186.78939
93 486.34594 -604.17514
94 583.01622 486.34594
95 178.49179 583.01622
96 121.82175 178.49179
97 -565.83993 121.82175
98 -356.30877 -565.83993
99 -114.37204 -356.30877
100 -1027.35249 -114.37204
101 -842.47531 -1027.35249
102 -353.94983 -842.47531
103 245.26877 -353.94983
104 434.01723 245.26877
105 -54.89458 434.01723
106 217.53056 -54.89458
> 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/freestat/rcomp/tmp/7vkdq1229539183.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/8i2yh1229539183.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/9pmfe1229539183.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/10ki831229539183.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/freestat/rcomp/tmp/11c8dl1229539183.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/freestat/rcomp/tmp/12f6en1229539184.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/freestat/rcomp/tmp/13p4g41229539184.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/freestat/rcomp/tmp/14fc2i1229539184.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/freestat/rcomp/tmp/15zt211229539184.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/freestat/rcomp/tmp/16w85l1229539184.tab")
+ }
>
> system("convert tmp/1mtpd1229539183.ps tmp/1mtpd1229539183.png")
> system("convert tmp/2turv1229539183.ps tmp/2turv1229539183.png")
> system("convert tmp/330ct1229539183.ps tmp/330ct1229539183.png")
> system("convert tmp/46gpa1229539183.ps tmp/46gpa1229539183.png")
> system("convert tmp/5gv8l1229539183.ps tmp/5gv8l1229539183.png")
> system("convert tmp/62wij1229539183.ps tmp/62wij1229539183.png")
> system("convert tmp/7vkdq1229539183.ps tmp/7vkdq1229539183.png")
> system("convert tmp/8i2yh1229539183.ps tmp/8i2yh1229539183.png")
> system("convert tmp/9pmfe1229539183.ps tmp/9pmfe1229539183.png")
> system("convert tmp/10ki831229539183.ps tmp/10ki831229539183.png")
>
>
> proc.time()
user system elapsed
4.498 2.622 4.868