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(6340.5
+ ,0
+ ,7901.5
+ ,0
+ ,8191.1
+ ,0
+ ,7181.7
+ ,0
+ ,7594.4
+ ,0
+ ,7384.7
+ ,0
+ ,7876.7
+ ,0
+ ,8463.4
+ ,0
+ ,8317.2
+ ,0
+ ,7778.7
+ ,0
+ ,8532.8
+ ,0
+ ,7272.2
+ ,0
+ ,6680.1
+ ,0
+ ,8427.6
+ ,0
+ ,8752.8
+ ,0
+ ,7952.7
+ ,0
+ ,8694.3
+ ,0
+ ,7787
+ ,0
+ ,8474.2
+ ,0
+ ,9154.7
+ ,0
+ ,8557.2
+ ,0
+ ,7951.1
+ ,0
+ ,9156.7
+ ,0
+ ,7865.7
+ ,0
+ ,7337.4
+ ,0
+ ,9131.7
+ ,0
+ ,8814.6
+ ,0
+ ,8598.8
+ ,0
+ ,8439.6
+ ,0
+ ,7451.8
+ ,0
+ ,8016.2
+ ,0
+ ,9544.1
+ ,0
+ ,8270.7
+ ,0
+ ,8102.2
+ ,0
+ ,9369
+ ,0
+ ,7657.7
+ ,0
+ ,7816.6
+ ,0
+ ,9391.3
+ ,0
+ ,9445.4
+ ,0
+ ,9533.1
+ ,0
+ ,10068.7
+ ,0
+ ,8955.5
+ ,0
+ ,10423.9
+ ,0
+ ,11617.2
+ ,0
+ ,9391.1
+ ,0
+ ,10872
+ ,0
+ ,10230.4
+ ,0
+ ,9221
+ ,0
+ ,9428.6
+ ,0
+ ,10934.5
+ ,0
+ ,10986
+ ,0
+ ,11724.6
+ ,0
+ ,11180.9
+ ,0
+ ,11163.2
+ ,0
+ ,11240.9
+ ,0
+ ,12107.1
+ ,0
+ ,10762.3
+ ,0
+ ,11340.4
+ ,0
+ ,11266.8
+ ,0
+ ,9542.7
+ ,0
+ ,9227.7
+ ,0
+ ,10571.9
+ ,1
+ ,10774.4
+ ,1
+ ,10392.8
+ ,1
+ ,9920.2
+ ,1
+ ,9884.9
+ ,1
+ ,10174.5
+ ,1
+ ,11395.4
+ ,1
+ ,10760.2
+ ,1
+ ,10570.1
+ ,1
+ ,10536
+ ,1
+ ,9902.6
+ ,1
+ ,8889
+ ,1
+ ,10837.3
+ ,1
+ ,11624.1
+ ,1
+ ,10509
+ ,1
+ ,10984.9
+ ,1
+ ,10649.1
+ ,1
+ ,10855.7
+ ,1
+ ,11677.4
+ ,1
+ ,10760.2
+ ,1
+ ,10046.2
+ ,1
+ ,10772.8
+ ,1
+ ,9987.7
+ ,1
+ ,8638.7
+ ,1
+ ,11063.7
+ ,1
+ ,11855.7
+ ,1
+ ,10684.5
+ ,1
+ ,11337.4
+ ,1
+ ,10478
+ ,1
+ ,11123.9
+ ,1
+ ,12909.3
+ ,1
+ ,11339.9
+ ,1
+ ,10462.2
+ ,1
+ ,12733.5
+ ,1
+ ,10519.2
+ ,1
+ ,10414.9
+ ,1
+ ,12476.8
+ ,1
+ ,12384.6
+ ,1
+ ,12266.7
+ ,1
+ ,12919.9
+ ,1
+ ,11497.3
+ ,1
+ ,12142
+ ,1
+ ,13919.4
+ ,1
+ ,12656.8
+ ,1
+ ,12034.1
+ ,1
+ ,13199.7
+ ,1
+ ,10881.3
+ ,1
+ ,11301.2
+ ,1
+ ,13643.9
+ ,1
+ ,12517
+ ,1
+ ,13981.1
+ ,1
+ ,14275.7
+ ,1
+ ,13435
+ ,1
+ ,13565.7
+ ,1
+ ,16216.3
+ ,1
+ ,12970
+ ,1
+ ,14079.9
+ ,1
+ ,14235
+ ,1
+ ,12213.4
+ ,1
+ ,12581
+ ,1)
+ ,dim=c(2
+ ,121)
+ ,dimnames=list(c('y'
+ ,'x')
+ ,1:121))
> y <- array(NA,dim=c(2,121),dimnames=list(c('y','x'),1:121))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from package:base :
as.Date.numeric
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
y x
1 6340.5 0
2 7901.5 0
3 8191.1 0
4 7181.7 0
5 7594.4 0
6 7384.7 0
7 7876.7 0
8 8463.4 0
9 8317.2 0
10 7778.7 0
11 8532.8 0
12 7272.2 0
13 6680.1 0
14 8427.6 0
15 8752.8 0
16 7952.7 0
17 8694.3 0
18 7787.0 0
19 8474.2 0
20 9154.7 0
21 8557.2 0
22 7951.1 0
23 9156.7 0
24 7865.7 0
25 7337.4 0
26 9131.7 0
27 8814.6 0
28 8598.8 0
29 8439.6 0
30 7451.8 0
31 8016.2 0
32 9544.1 0
33 8270.7 0
34 8102.2 0
35 9369.0 0
36 7657.7 0
37 7816.6 0
38 9391.3 0
39 9445.4 0
40 9533.1 0
41 10068.7 0
42 8955.5 0
43 10423.9 0
44 11617.2 0
45 9391.1 0
46 10872.0 0
47 10230.4 0
48 9221.0 0
49 9428.6 0
50 10934.5 0
51 10986.0 0
52 11724.6 0
53 11180.9 0
54 11163.2 0
55 11240.9 0
56 12107.1 0
57 10762.3 0
58 11340.4 0
59 11266.8 0
60 9542.7 0
61 9227.7 0
62 10571.9 1
63 10774.4 1
64 10392.8 1
65 9920.2 1
66 9884.9 1
67 10174.5 1
68 11395.4 1
69 10760.2 1
70 10570.1 1
71 10536.0 1
72 9902.6 1
73 8889.0 1
74 10837.3 1
75 11624.1 1
76 10509.0 1
77 10984.9 1
78 10649.1 1
79 10855.7 1
80 11677.4 1
81 10760.2 1
82 10046.2 1
83 10772.8 1
84 9987.7 1
85 8638.7 1
86 11063.7 1
87 11855.7 1
88 10684.5 1
89 11337.4 1
90 10478.0 1
91 11123.9 1
92 12909.3 1
93 11339.9 1
94 10462.2 1
95 12733.5 1
96 10519.2 1
97 10414.9 1
98 12476.8 1
99 12384.6 1
100 12266.7 1
101 12919.9 1
102 11497.3 1
103 12142.0 1
104 13919.4 1
105 12656.8 1
106 12034.1 1
107 13199.7 1
108 10881.3 1
109 11301.2 1
110 13643.9 1
111 12517.0 1
112 13981.1 1
113 14275.7 1
114 13435.0 1
115 13565.7 1
116 16216.3 1
117 12970.0 1
118 14079.9 1
119 14235.0 1
120 12213.4 1
121 12581.0 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) x
9031 2593
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-2985.2 -1080.0 -286.5 957.1 4592.4
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 9031.1 183.6 49.177 <2e-16 ***
x 2592.8 260.8 9.942 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1434 on 119 degrees of freedom
Multiple R-squared: 0.4537, Adjusted R-squared: 0.4491
F-statistic: 98.84 on 1 and 119 DF, p-value: < 2.2e-16
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 2.068952e-01 4.137904e-01 0.7931048
[2,] 9.714454e-02 1.942891e-01 0.9028555
[3,] 4.894396e-02 9.788793e-02 0.9510560
[4,] 4.330869e-02 8.661738e-02 0.9566913
[5,] 2.798157e-02 5.596314e-02 0.9720184
[6,] 1.275137e-02 2.550274e-02 0.9872486
[7,] 9.857934e-03 1.971587e-02 0.9901421
[8,] 5.737244e-03 1.147449e-02 0.9942628
[9,] 7.206726e-03 1.441345e-02 0.9927933
[10,] 5.329433e-03 1.065887e-02 0.9946706
[11,] 5.462660e-03 1.092532e-02 0.9945373
[12,] 2.835139e-03 5.670278e-03 0.9971649
[13,] 2.443574e-03 4.887148e-03 0.9975564
[14,] 1.268899e-03 2.537798e-03 0.9987311
[15,] 8.314943e-04 1.662989e-03 0.9991685
[16,] 1.262807e-03 2.525614e-03 0.9987372
[17,] 8.249354e-04 1.649871e-03 0.9991751
[18,] 4.407676e-04 8.815351e-04 0.9995592
[19,] 5.595318e-04 1.119064e-03 0.9994405
[20,] 3.176285e-04 6.352570e-04 0.9996824
[21,] 2.695600e-04 5.391200e-04 0.9997304
[22,] 3.191288e-04 6.382576e-04 0.9996809
[23,] 2.457780e-04 4.915559e-04 0.9997542
[24,] 1.587385e-04 3.174770e-04 0.9998413
[25,] 9.477579e-05 1.895516e-04 0.9999052
[26,] 8.527750e-05 1.705550e-04 0.9999147
[27,] 5.279118e-05 1.055824e-04 0.9999472
[28,] 1.079584e-04 2.159168e-04 0.9998920
[29,] 6.817583e-05 1.363517e-04 0.9999318
[30,] 4.512532e-05 9.025064e-05 0.9999549
[31,] 6.293803e-05 1.258761e-04 0.9999371
[32,] 6.042116e-05 1.208423e-04 0.9999396
[33,] 5.416966e-05 1.083393e-04 0.9999458
[34,] 7.814077e-05 1.562815e-04 0.9999219
[35,] 1.106877e-04 2.213755e-04 0.9998893
[36,] 1.601489e-04 3.202977e-04 0.9998399
[37,] 4.113993e-04 8.227986e-04 0.9995886
[38,] 3.581688e-04 7.163377e-04 0.9996418
[39,] 1.138558e-03 2.277115e-03 0.9988614
[40,] 1.279269e-02 2.558539e-02 0.9872073
[41,] 1.184901e-02 2.369801e-02 0.9881510
[42,] 2.452942e-02 4.905884e-02 0.9754706
[43,] 2.894871e-02 5.789743e-02 0.9710513
[44,] 2.606514e-02 5.213027e-02 0.9739349
[45,] 2.426010e-02 4.852021e-02 0.9757399
[46,] 3.953863e-02 7.907726e-02 0.9604614
[47,] 5.878577e-02 1.175715e-01 0.9412142
[48,] 1.171904e-01 2.343807e-01 0.8828096
[49,] 1.513858e-01 3.027716e-01 0.8486142
[50,] 1.831681e-01 3.663362e-01 0.8168319
[51,] 2.173641e-01 4.347282e-01 0.7826359
[52,] 3.307212e-01 6.614424e-01 0.6692788
[53,] 3.293365e-01 6.586730e-01 0.6706635
[54,] 3.685368e-01 7.370736e-01 0.6314632
[55,] 4.107391e-01 8.214782e-01 0.5892609
[56,] 3.642753e-01 7.285505e-01 0.6357247
[57,] 3.165118e-01 6.330237e-01 0.6834882
[58,] 2.823637e-01 5.647275e-01 0.7176363
[59,] 2.469786e-01 4.939572e-01 0.7530214
[60,] 2.221160e-01 4.442321e-01 0.7778840
[61,] 2.149205e-01 4.298410e-01 0.7850795
[62,] 2.098358e-01 4.196716e-01 0.7901642
[63,] 1.955877e-01 3.911753e-01 0.8044123
[64,] 1.708888e-01 3.417776e-01 0.8291112
[65,] 1.479140e-01 2.958280e-01 0.8520860
[66,] 1.299458e-01 2.598917e-01 0.8700542
[67,] 1.145795e-01 2.291589e-01 0.8854205
[68,] 1.166165e-01 2.332330e-01 0.8833835
[69,] 1.788624e-01 3.577247e-01 0.8211376
[70,] 1.593146e-01 3.186292e-01 0.8406854
[71,] 1.399872e-01 2.799743e-01 0.8600128
[72,] 1.295050e-01 2.590099e-01 0.8704950
[73,] 1.125824e-01 2.251649e-01 0.8874176
[74,] 1.022612e-01 2.045225e-01 0.8977388
[75,] 9.015984e-02 1.803197e-01 0.9098402
[76,] 7.630731e-02 1.526146e-01 0.9236927
[77,] 6.815764e-02 1.363153e-01 0.9318424
[78,] 7.678745e-02 1.535749e-01 0.9232125
[79,] 7.039410e-02 1.407882e-01 0.9296059
[80,] 8.608643e-02 1.721729e-01 0.9139136
[81,] 2.415489e-01 4.830978e-01 0.7584511
[82,] 2.320739e-01 4.641477e-01 0.7679261
[83,] 2.094556e-01 4.189112e-01 0.7905444
[84,] 2.220438e-01 4.440876e-01 0.7779562
[85,] 2.084152e-01 4.168304e-01 0.7915848
[86,] 2.470382e-01 4.940764e-01 0.7529618
[87,] 2.493461e-01 4.986921e-01 0.7506539
[88,] 2.434483e-01 4.868966e-01 0.7565517
[89,] 2.359791e-01 4.719582e-01 0.7640209
[90,] 3.069525e-01 6.139050e-01 0.6930475
[91,] 2.842278e-01 5.684556e-01 0.7157722
[92,] 3.757616e-01 7.515232e-01 0.6242384
[93,] 5.288670e-01 9.422660e-01 0.4711330
[94,] 4.946806e-01 9.893612e-01 0.5053194
[95,] 4.599889e-01 9.199779e-01 0.5400111
[96,] 4.280213e-01 8.560425e-01 0.5719787
[97,] 3.888210e-01 7.776420e-01 0.6111790
[98,] 4.165074e-01 8.330149e-01 0.5834926
[99,] 3.946276e-01 7.892553e-01 0.6053724
[100,] 3.954924e-01 7.909847e-01 0.6045076
[101,] 3.458625e-01 6.917250e-01 0.6541375
[102,] 3.295272e-01 6.590544e-01 0.6704728
[103,] 2.781943e-01 5.563886e-01 0.7218057
[104,] 4.547599e-01 9.095198e-01 0.5452401
[105,] 6.389009e-01 7.221982e-01 0.3610991
[106,] 5.684011e-01 8.631978e-01 0.4315989
[107,] 5.575446e-01 8.849108e-01 0.4424554
[108,] 4.787486e-01 9.574972e-01 0.5212514
[109,] 4.132228e-01 8.264455e-01 0.5867772
[110,] 3.107866e-01 6.215731e-01 0.6892134
[111,] 2.120050e-01 4.240099e-01 0.7879950
[112,] 6.539059e-01 6.921883e-01 0.3460941
> postscript(file="/var/www/html/freestat/rcomp/tmp/1qcia1229349354.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/250lo1229349354.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3ki741229349354.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/4h8u21229349354.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/5y5cv1229349354.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 = 121
Frequency = 1
1 2 3 4 5
-2690.5606557 -1129.5606557 -839.9606557 -1849.3606557 -1436.6606557
6 7 8 9 10
-1646.3606557 -1154.3606557 -567.6606557 -713.8606557 -1252.3606557
11 12 13 14 15
-498.2606557 -1758.8606557 -2350.9606557 -603.4606557 -278.2606557
16 17 18 19 20
-1078.3606557 -336.7606557 -1244.0606557 -556.8606557 123.6393443
21 22 23 24 25
-473.8606557 -1079.9606557 125.6393443 -1165.3606557 -1693.6606557
26 27 28 29 30
100.6393443 -216.4606557 -432.2606557 -591.4606557 -1579.2606557
31 32 33 34 35
-1014.8606557 513.0393443 -760.3606557 -928.8606557 337.9393443
36 37 38 39 40
-1373.3606557 -1214.4606557 360.2393443 414.3393443 502.0393443
41 42 43 44 45
1037.6393443 -75.5606557 1392.8393443 2586.1393443 360.0393443
46 47 48 49 50
1840.9393443 1199.3393443 189.9393443 397.5393443 1903.4393443
51 52 53 54 55
1954.9393443 2693.5393443 2149.8393443 2132.1393443 2209.8393443
56 57 58 59 60
3076.0393443 1731.2393443 2309.3393443 2235.7393443 511.6393443
61 62 63 64 65
196.6393443 -1051.9516667 -849.4516667 -1231.0516667 -1703.6516667
66 67 68 69 70
-1738.9516667 -1449.3516667 -228.4516667 -863.6516667 -1053.7516667
71 72 73 74 75
-1087.8516667 -1721.2516667 -2734.8516667 -786.5516667 0.2483333
76 77 78 79 80
-1114.8516667 -638.9516667 -974.7516667 -768.1516667 53.5483333
81 82 83 84 85
-863.6516667 -1577.6516667 -851.0516667 -1636.1516667 -2985.1516667
86 87 88 89 90
-560.1516667 231.8483333 -939.3516667 -286.4516667 -1145.8516667
91 92 93 94 95
-499.9516667 1285.4483333 -283.9516667 -1161.6516667 1109.6483333
96 97 98 99 100
-1104.6516667 -1208.9516667 852.9483333 760.7483333 642.8483333
101 102 103 104 105
1296.0483333 -126.5516667 518.1483333 2295.5483333 1032.9483333
106 107 108 109 110
410.2483333 1575.8483333 -742.5516667 -322.6516667 2020.0483333
111 112 113 114 115
893.1483333 2357.2483333 2651.8483333 1811.1483333 1941.8483333
116 117 118 119 120
4592.4483333 1346.1483333 2456.0483333 2611.1483333 589.5483333
121
957.1483333
> postscript(file="/var/www/html/freestat/rcomp/tmp/64rne1229349354.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 = 121
Frequency = 1
lag(myerror, k = 1) myerror
0 -2690.5606557 NA
1 -1129.5606557 -2690.5606557
2 -839.9606557 -1129.5606557
3 -1849.3606557 -839.9606557
4 -1436.6606557 -1849.3606557
5 -1646.3606557 -1436.6606557
6 -1154.3606557 -1646.3606557
7 -567.6606557 -1154.3606557
8 -713.8606557 -567.6606557
9 -1252.3606557 -713.8606557
10 -498.2606557 -1252.3606557
11 -1758.8606557 -498.2606557
12 -2350.9606557 -1758.8606557
13 -603.4606557 -2350.9606557
14 -278.2606557 -603.4606557
15 -1078.3606557 -278.2606557
16 -336.7606557 -1078.3606557
17 -1244.0606557 -336.7606557
18 -556.8606557 -1244.0606557
19 123.6393443 -556.8606557
20 -473.8606557 123.6393443
21 -1079.9606557 -473.8606557
22 125.6393443 -1079.9606557
23 -1165.3606557 125.6393443
24 -1693.6606557 -1165.3606557
25 100.6393443 -1693.6606557
26 -216.4606557 100.6393443
27 -432.2606557 -216.4606557
28 -591.4606557 -432.2606557
29 -1579.2606557 -591.4606557
30 -1014.8606557 -1579.2606557
31 513.0393443 -1014.8606557
32 -760.3606557 513.0393443
33 -928.8606557 -760.3606557
34 337.9393443 -928.8606557
35 -1373.3606557 337.9393443
36 -1214.4606557 -1373.3606557
37 360.2393443 -1214.4606557
38 414.3393443 360.2393443
39 502.0393443 414.3393443
40 1037.6393443 502.0393443
41 -75.5606557 1037.6393443
42 1392.8393443 -75.5606557
43 2586.1393443 1392.8393443
44 360.0393443 2586.1393443
45 1840.9393443 360.0393443
46 1199.3393443 1840.9393443
47 189.9393443 1199.3393443
48 397.5393443 189.9393443
49 1903.4393443 397.5393443
50 1954.9393443 1903.4393443
51 2693.5393443 1954.9393443
52 2149.8393443 2693.5393443
53 2132.1393443 2149.8393443
54 2209.8393443 2132.1393443
55 3076.0393443 2209.8393443
56 1731.2393443 3076.0393443
57 2309.3393443 1731.2393443
58 2235.7393443 2309.3393443
59 511.6393443 2235.7393443
60 196.6393443 511.6393443
61 -1051.9516667 196.6393443
62 -849.4516667 -1051.9516667
63 -1231.0516667 -849.4516667
64 -1703.6516667 -1231.0516667
65 -1738.9516667 -1703.6516667
66 -1449.3516667 -1738.9516667
67 -228.4516667 -1449.3516667
68 -863.6516667 -228.4516667
69 -1053.7516667 -863.6516667
70 -1087.8516667 -1053.7516667
71 -1721.2516667 -1087.8516667
72 -2734.8516667 -1721.2516667
73 -786.5516667 -2734.8516667
74 0.2483333 -786.5516667
75 -1114.8516667 0.2483333
76 -638.9516667 -1114.8516667
77 -974.7516667 -638.9516667
78 -768.1516667 -974.7516667
79 53.5483333 -768.1516667
80 -863.6516667 53.5483333
81 -1577.6516667 -863.6516667
82 -851.0516667 -1577.6516667
83 -1636.1516667 -851.0516667
84 -2985.1516667 -1636.1516667
85 -560.1516667 -2985.1516667
86 231.8483333 -560.1516667
87 -939.3516667 231.8483333
88 -286.4516667 -939.3516667
89 -1145.8516667 -286.4516667
90 -499.9516667 -1145.8516667
91 1285.4483333 -499.9516667
92 -283.9516667 1285.4483333
93 -1161.6516667 -283.9516667
94 1109.6483333 -1161.6516667
95 -1104.6516667 1109.6483333
96 -1208.9516667 -1104.6516667
97 852.9483333 -1208.9516667
98 760.7483333 852.9483333
99 642.8483333 760.7483333
100 1296.0483333 642.8483333
101 -126.5516667 1296.0483333
102 518.1483333 -126.5516667
103 2295.5483333 518.1483333
104 1032.9483333 2295.5483333
105 410.2483333 1032.9483333
106 1575.8483333 410.2483333
107 -742.5516667 1575.8483333
108 -322.6516667 -742.5516667
109 2020.0483333 -322.6516667
110 893.1483333 2020.0483333
111 2357.2483333 893.1483333
112 2651.8483333 2357.2483333
113 1811.1483333 2651.8483333
114 1941.8483333 1811.1483333
115 4592.4483333 1941.8483333
116 1346.1483333 4592.4483333
117 2456.0483333 1346.1483333
118 2611.1483333 2456.0483333
119 589.5483333 2611.1483333
120 957.1483333 589.5483333
121 NA 957.1483333
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -1129.5606557 -2690.5606557
[2,] -839.9606557 -1129.5606557
[3,] -1849.3606557 -839.9606557
[4,] -1436.6606557 -1849.3606557
[5,] -1646.3606557 -1436.6606557
[6,] -1154.3606557 -1646.3606557
[7,] -567.6606557 -1154.3606557
[8,] -713.8606557 -567.6606557
[9,] -1252.3606557 -713.8606557
[10,] -498.2606557 -1252.3606557
[11,] -1758.8606557 -498.2606557
[12,] -2350.9606557 -1758.8606557
[13,] -603.4606557 -2350.9606557
[14,] -278.2606557 -603.4606557
[15,] -1078.3606557 -278.2606557
[16,] -336.7606557 -1078.3606557
[17,] -1244.0606557 -336.7606557
[18,] -556.8606557 -1244.0606557
[19,] 123.6393443 -556.8606557
[20,] -473.8606557 123.6393443
[21,] -1079.9606557 -473.8606557
[22,] 125.6393443 -1079.9606557
[23,] -1165.3606557 125.6393443
[24,] -1693.6606557 -1165.3606557
[25,] 100.6393443 -1693.6606557
[26,] -216.4606557 100.6393443
[27,] -432.2606557 -216.4606557
[28,] -591.4606557 -432.2606557
[29,] -1579.2606557 -591.4606557
[30,] -1014.8606557 -1579.2606557
[31,] 513.0393443 -1014.8606557
[32,] -760.3606557 513.0393443
[33,] -928.8606557 -760.3606557
[34,] 337.9393443 -928.8606557
[35,] -1373.3606557 337.9393443
[36,] -1214.4606557 -1373.3606557
[37,] 360.2393443 -1214.4606557
[38,] 414.3393443 360.2393443
[39,] 502.0393443 414.3393443
[40,] 1037.6393443 502.0393443
[41,] -75.5606557 1037.6393443
[42,] 1392.8393443 -75.5606557
[43,] 2586.1393443 1392.8393443
[44,] 360.0393443 2586.1393443
[45,] 1840.9393443 360.0393443
[46,] 1199.3393443 1840.9393443
[47,] 189.9393443 1199.3393443
[48,] 397.5393443 189.9393443
[49,] 1903.4393443 397.5393443
[50,] 1954.9393443 1903.4393443
[51,] 2693.5393443 1954.9393443
[52,] 2149.8393443 2693.5393443
[53,] 2132.1393443 2149.8393443
[54,] 2209.8393443 2132.1393443
[55,] 3076.0393443 2209.8393443
[56,] 1731.2393443 3076.0393443
[57,] 2309.3393443 1731.2393443
[58,] 2235.7393443 2309.3393443
[59,] 511.6393443 2235.7393443
[60,] 196.6393443 511.6393443
[61,] -1051.9516667 196.6393443
[62,] -849.4516667 -1051.9516667
[63,] -1231.0516667 -849.4516667
[64,] -1703.6516667 -1231.0516667
[65,] -1738.9516667 -1703.6516667
[66,] -1449.3516667 -1738.9516667
[67,] -228.4516667 -1449.3516667
[68,] -863.6516667 -228.4516667
[69,] -1053.7516667 -863.6516667
[70,] -1087.8516667 -1053.7516667
[71,] -1721.2516667 -1087.8516667
[72,] -2734.8516667 -1721.2516667
[73,] -786.5516667 -2734.8516667
[74,] 0.2483333 -786.5516667
[75,] -1114.8516667 0.2483333
[76,] -638.9516667 -1114.8516667
[77,] -974.7516667 -638.9516667
[78,] -768.1516667 -974.7516667
[79,] 53.5483333 -768.1516667
[80,] -863.6516667 53.5483333
[81,] -1577.6516667 -863.6516667
[82,] -851.0516667 -1577.6516667
[83,] -1636.1516667 -851.0516667
[84,] -2985.1516667 -1636.1516667
[85,] -560.1516667 -2985.1516667
[86,] 231.8483333 -560.1516667
[87,] -939.3516667 231.8483333
[88,] -286.4516667 -939.3516667
[89,] -1145.8516667 -286.4516667
[90,] -499.9516667 -1145.8516667
[91,] 1285.4483333 -499.9516667
[92,] -283.9516667 1285.4483333
[93,] -1161.6516667 -283.9516667
[94,] 1109.6483333 -1161.6516667
[95,] -1104.6516667 1109.6483333
[96,] -1208.9516667 -1104.6516667
[97,] 852.9483333 -1208.9516667
[98,] 760.7483333 852.9483333
[99,] 642.8483333 760.7483333
[100,] 1296.0483333 642.8483333
[101,] -126.5516667 1296.0483333
[102,] 518.1483333 -126.5516667
[103,] 2295.5483333 518.1483333
[104,] 1032.9483333 2295.5483333
[105,] 410.2483333 1032.9483333
[106,] 1575.8483333 410.2483333
[107,] -742.5516667 1575.8483333
[108,] -322.6516667 -742.5516667
[109,] 2020.0483333 -322.6516667
[110,] 893.1483333 2020.0483333
[111,] 2357.2483333 893.1483333
[112,] 2651.8483333 2357.2483333
[113,] 1811.1483333 2651.8483333
[114,] 1941.8483333 1811.1483333
[115,] 4592.4483333 1941.8483333
[116,] 1346.1483333 4592.4483333
[117,] 2456.0483333 1346.1483333
[118,] 2611.1483333 2456.0483333
[119,] 589.5483333 2611.1483333
[120,] 957.1483333 589.5483333
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -1129.5606557 -2690.5606557
2 -839.9606557 -1129.5606557
3 -1849.3606557 -839.9606557
4 -1436.6606557 -1849.3606557
5 -1646.3606557 -1436.6606557
6 -1154.3606557 -1646.3606557
7 -567.6606557 -1154.3606557
8 -713.8606557 -567.6606557
9 -1252.3606557 -713.8606557
10 -498.2606557 -1252.3606557
11 -1758.8606557 -498.2606557
12 -2350.9606557 -1758.8606557
13 -603.4606557 -2350.9606557
14 -278.2606557 -603.4606557
15 -1078.3606557 -278.2606557
16 -336.7606557 -1078.3606557
17 -1244.0606557 -336.7606557
18 -556.8606557 -1244.0606557
19 123.6393443 -556.8606557
20 -473.8606557 123.6393443
21 -1079.9606557 -473.8606557
22 125.6393443 -1079.9606557
23 -1165.3606557 125.6393443
24 -1693.6606557 -1165.3606557
25 100.6393443 -1693.6606557
26 -216.4606557 100.6393443
27 -432.2606557 -216.4606557
28 -591.4606557 -432.2606557
29 -1579.2606557 -591.4606557
30 -1014.8606557 -1579.2606557
31 513.0393443 -1014.8606557
32 -760.3606557 513.0393443
33 -928.8606557 -760.3606557
34 337.9393443 -928.8606557
35 -1373.3606557 337.9393443
36 -1214.4606557 -1373.3606557
37 360.2393443 -1214.4606557
38 414.3393443 360.2393443
39 502.0393443 414.3393443
40 1037.6393443 502.0393443
41 -75.5606557 1037.6393443
42 1392.8393443 -75.5606557
43 2586.1393443 1392.8393443
44 360.0393443 2586.1393443
45 1840.9393443 360.0393443
46 1199.3393443 1840.9393443
47 189.9393443 1199.3393443
48 397.5393443 189.9393443
49 1903.4393443 397.5393443
50 1954.9393443 1903.4393443
51 2693.5393443 1954.9393443
52 2149.8393443 2693.5393443
53 2132.1393443 2149.8393443
54 2209.8393443 2132.1393443
55 3076.0393443 2209.8393443
56 1731.2393443 3076.0393443
57 2309.3393443 1731.2393443
58 2235.7393443 2309.3393443
59 511.6393443 2235.7393443
60 196.6393443 511.6393443
61 -1051.9516667 196.6393443
62 -849.4516667 -1051.9516667
63 -1231.0516667 -849.4516667
64 -1703.6516667 -1231.0516667
65 -1738.9516667 -1703.6516667
66 -1449.3516667 -1738.9516667
67 -228.4516667 -1449.3516667
68 -863.6516667 -228.4516667
69 -1053.7516667 -863.6516667
70 -1087.8516667 -1053.7516667
71 -1721.2516667 -1087.8516667
72 -2734.8516667 -1721.2516667
73 -786.5516667 -2734.8516667
74 0.2483333 -786.5516667
75 -1114.8516667 0.2483333
76 -638.9516667 -1114.8516667
77 -974.7516667 -638.9516667
78 -768.1516667 -974.7516667
79 53.5483333 -768.1516667
80 -863.6516667 53.5483333
81 -1577.6516667 -863.6516667
82 -851.0516667 -1577.6516667
83 -1636.1516667 -851.0516667
84 -2985.1516667 -1636.1516667
85 -560.1516667 -2985.1516667
86 231.8483333 -560.1516667
87 -939.3516667 231.8483333
88 -286.4516667 -939.3516667
89 -1145.8516667 -286.4516667
90 -499.9516667 -1145.8516667
91 1285.4483333 -499.9516667
92 -283.9516667 1285.4483333
93 -1161.6516667 -283.9516667
94 1109.6483333 -1161.6516667
95 -1104.6516667 1109.6483333
96 -1208.9516667 -1104.6516667
97 852.9483333 -1208.9516667
98 760.7483333 852.9483333
99 642.8483333 760.7483333
100 1296.0483333 642.8483333
101 -126.5516667 1296.0483333
102 518.1483333 -126.5516667
103 2295.5483333 518.1483333
104 1032.9483333 2295.5483333
105 410.2483333 1032.9483333
106 1575.8483333 410.2483333
107 -742.5516667 1575.8483333
108 -322.6516667 -742.5516667
109 2020.0483333 -322.6516667
110 893.1483333 2020.0483333
111 2357.2483333 893.1483333
112 2651.8483333 2357.2483333
113 1811.1483333 2651.8483333
114 1941.8483333 1811.1483333
115 4592.4483333 1941.8483333
116 1346.1483333 4592.4483333
117 2456.0483333 1346.1483333
118 2611.1483333 2456.0483333
119 589.5483333 2611.1483333
120 957.1483333 589.5483333
> 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/7ih1a1229349354.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/8jps01229349354.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/9l3uc1229349354.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/10dn6l1229349354.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11dmv41229349354.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/12sqjb1229349354.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/135w7k1229349355.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/149phr1229349355.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/15hbhl1229349355.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/1639301229349355.tab")
+ }
>
> system("convert tmp/1qcia1229349354.ps tmp/1qcia1229349354.png")
> system("convert tmp/250lo1229349354.ps tmp/250lo1229349354.png")
> system("convert tmp/3ki741229349354.ps tmp/3ki741229349354.png")
> system("convert tmp/4h8u21229349354.ps tmp/4h8u21229349354.png")
> system("convert tmp/5y5cv1229349354.ps tmp/5y5cv1229349354.png")
> system("convert tmp/64rne1229349354.ps tmp/64rne1229349354.png")
> system("convert tmp/7ih1a1229349354.ps tmp/7ih1a1229349354.png")
> system("convert tmp/8jps01229349354.ps tmp/8jps01229349354.png")
> system("convert tmp/9l3uc1229349354.ps tmp/9l3uc1229349354.png")
> system("convert tmp/10dn6l1229349354.ps tmp/10dn6l1229349354.png")
>
>
> proc.time()
user system elapsed
4.510 2.584 4.953