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.
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(423.4
+ ,0
+ ,404.1
+ ,0
+ ,500
+ ,0
+ ,472.6
+ ,0
+ ,496.1
+ ,0
+ ,562
+ ,0
+ ,434.8
+ ,0
+ ,538.2
+ ,0
+ ,577.6
+ ,0
+ ,518.1
+ ,0
+ ,625.2
+ ,0
+ ,561.2
+ ,0
+ ,523.3
+ ,0
+ ,536.1
+ ,0
+ ,607.3
+ ,0
+ ,637.3
+ ,0
+ ,606.9
+ ,0
+ ,652.9
+ ,0
+ ,617.2
+ ,0
+ ,670.4
+ ,0
+ ,729.9
+ ,0
+ ,677.2
+ ,0
+ ,710
+ ,0
+ ,844.3
+ ,0
+ ,748.2
+ ,0
+ ,653.9
+ ,0
+ ,742.6
+ ,0
+ ,854.2
+ ,0
+ ,808.4
+ ,0
+ ,1819
+ ,1
+ ,1936.5
+ ,1
+ ,1966.1
+ ,1
+ ,2083.1
+ ,1
+ ,1620.1
+ ,1
+ ,1527.6
+ ,1
+ ,1795
+ ,1
+ ,1685.1
+ ,1
+ ,1851.8
+ ,1
+ ,2164.4
+ ,1
+ ,1981.8
+ ,1
+ ,1726.5
+ ,1
+ ,2144.6
+ ,1
+ ,1758.2
+ ,1
+ ,1672.9
+ ,1
+ ,1837.3
+ ,1
+ ,1596.1
+ ,1
+ ,1446
+ ,1
+ ,1898.4
+ ,1
+ ,1964.1
+ ,1
+ ,1755.9
+ ,1
+ ,2255.3
+ ,1
+ ,1881.2
+ ,1
+ ,2117.9
+ ,1
+ ,1656.5
+ ,1
+ ,1544.1
+ ,1
+ ,2098.9
+ ,1
+ ,2133.3
+ ,1
+ ,1963.5
+ ,1
+ ,1801.2
+ ,1
+ ,2365.4
+ ,1
+ ,1936.5
+ ,1
+ ,1667.6
+ ,1
+ ,1983.5
+ ,1
+ ,2058.6
+ ,1
+ ,2448.3
+ ,1
+ ,1858.1
+ ,1
+ ,1625.4
+ ,1
+ ,2130.6
+ ,1
+ ,2515.7
+ ,1
+ ,2230.2
+ ,1
+ ,2086.9
+ ,1
+ ,2235
+ ,1
+ ,2100.2
+ ,1
+ ,2288.6
+ ,1
+ ,2490
+ ,1
+ ,2573.7
+ ,1
+ ,2543.8
+ ,1
+ ,2004.7
+ ,1
+ ,2390
+ ,1
+ ,2338.4
+ ,1
+ ,2724.5
+ ,1
+ ,2292.5
+ ,1
+ ,2386
+ ,1
+ ,2477.9
+ ,1
+ ,2337
+ ,1
+ ,2605.1
+ ,1
+ ,2560.8
+ ,1
+ ,2839.3
+ ,1
+ ,2407.2
+ ,1
+ ,2085.2
+ ,1
+ ,2735.6
+ ,1
+ ,2798.7
+ ,1
+ ,3053.2
+ ,1
+ ,2405
+ ,1
+ ,2471.9
+ ,1
+ ,2727.3
+ ,1
+ ,2790.7
+ ,1
+ ,2385.4
+ ,1
+ ,3206.6
+ ,1
+ ,2705.6
+ ,1
+ ,3518.4
+ ,1
+ ,1954.9
+ ,1
+ ,2584.3
+ ,1
+ ,2535.8
+ ,1
+ ,2685.9
+ ,1
+ ,2866
+ ,1
+ ,2236.6
+ ,1
+ ,2934.9
+ ,1
+ ,2668.6
+ ,1
+ ,2371.2
+ ,1
+ ,3165.9
+ ,1
+ ,2887.2
+ ,1
+ ,3112.2
+ ,1
+ ,2671.2
+ ,1
+ ,2432.6
+ ,1
+ ,2812.3
+ ,1
+ ,3095.7
+ ,1
+ ,2862.9
+ ,1
+ ,2607.3
+ ,1
+ ,2862.5
+ ,1)
+ ,dim=c(2
+ ,120)
+ ,dimnames=list(c('Y(Export_farma_prod)'
+ ,'X(sprong)')
+ ,1:120))
> y <- array(NA,dim=c(2,120),dimnames=list(c('Y(Export_farma_prod)','X(sprong)'),1:120))
> 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(Export_farma_prod) X(sprong)
1 423.4 0
2 404.1 0
3 500.0 0
4 472.6 0
5 496.1 0
6 562.0 0
7 434.8 0
8 538.2 0
9 577.6 0
10 518.1 0
11 625.2 0
12 561.2 0
13 523.3 0
14 536.1 0
15 607.3 0
16 637.3 0
17 606.9 0
18 652.9 0
19 617.2 0
20 670.4 0
21 729.9 0
22 677.2 0
23 710.0 0
24 844.3 0
25 748.2 0
26 653.9 0
27 742.6 0
28 854.2 0
29 808.4 0
30 1819.0 1
31 1936.5 1
32 1966.1 1
33 2083.1 1
34 1620.1 1
35 1527.6 1
36 1795.0 1
37 1685.1 1
38 1851.8 1
39 2164.4 1
40 1981.8 1
41 1726.5 1
42 2144.6 1
43 1758.2 1
44 1672.9 1
45 1837.3 1
46 1596.1 1
47 1446.0 1
48 1898.4 1
49 1964.1 1
50 1755.9 1
51 2255.3 1
52 1881.2 1
53 2117.9 1
54 1656.5 1
55 1544.1 1
56 2098.9 1
57 2133.3 1
58 1963.5 1
59 1801.2 1
60 2365.4 1
61 1936.5 1
62 1667.6 1
63 1983.5 1
64 2058.6 1
65 2448.3 1
66 1858.1 1
67 1625.4 1
68 2130.6 1
69 2515.7 1
70 2230.2 1
71 2086.9 1
72 2235.0 1
73 2100.2 1
74 2288.6 1
75 2490.0 1
76 2573.7 1
77 2543.8 1
78 2004.7 1
79 2390.0 1
80 2338.4 1
81 2724.5 1
82 2292.5 1
83 2386.0 1
84 2477.9 1
85 2337.0 1
86 2605.1 1
87 2560.8 1
88 2839.3 1
89 2407.2 1
90 2085.2 1
91 2735.6 1
92 2798.7 1
93 3053.2 1
94 2405.0 1
95 2471.9 1
96 2727.3 1
97 2790.7 1
98 2385.4 1
99 3206.6 1
100 2705.6 1
101 3518.4 1
102 1954.9 1
103 2584.3 1
104 2535.8 1
105 2685.9 1
106 2866.0 1
107 2236.6 1
108 2934.9 1
109 2668.6 1
110 2371.2 1
111 3165.9 1
112 2887.2 1
113 3112.2 1
114 2671.2 1
115 2432.6 1
116 2812.3 1
117 3095.7 1
118 2862.9 1
119 2607.3 1
120 2862.5 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) `X(sprong)`
611.5 1678.8
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-844.280 -245.155 -2.938 235.278 1228.120
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 611.50 74.32 8.228 2.88e-13 ***
`X(sprong)` 1678.78 85.34 19.671 < 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 400.2 on 118 degrees of freedom
Multiple R-squared: 0.7663, Adjusted R-squared: 0.7643
F-statistic: 386.9 on 1 and 118 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,] 2.548261e-03 5.096523e-03 0.99745174
[2,] 1.170038e-03 2.340075e-03 0.99882996
[3,] 1.919847e-04 3.839694e-04 0.99980802
[4,] 4.431028e-05 8.862055e-05 0.99995569
[5,] 1.813938e-05 3.627876e-05 0.99998186
[6,] 2.860458e-06 5.720916e-06 0.99999714
[7,] 2.410336e-06 4.820673e-06 0.99999759
[8,] 5.154779e-07 1.030956e-06 0.99999948
[9,] 8.253626e-08 1.650725e-07 0.99999992
[10,] 1.332699e-08 2.665397e-08 0.99999999
[11,] 5.089337e-09 1.017867e-08 0.99999999
[12,] 2.996809e-09 5.993618e-09 1.00000000
[13,] 8.660370e-10 1.732074e-09 1.00000000
[14,] 4.973506e-10 9.947013e-10 1.00000000
[15,] 1.404435e-10 2.808869e-10 1.00000000
[16,] 8.516494e-11 1.703299e-10 1.00000000
[17,] 1.365399e-10 2.730798e-10 1.00000000
[18,] 6.226509e-11 1.245302e-10 1.00000000
[19,] 4.145553e-11 8.291105e-11 1.00000000
[20,] 2.819457e-10 5.638913e-10 1.00000000
[21,] 1.943610e-10 3.887219e-10 1.00000000
[22,] 5.521354e-11 1.104271e-10 1.00000000
[23,] 3.141158e-11 6.282316e-11 1.00000000
[24,] 7.403204e-11 1.480641e-10 1.00000000
[25,] 6.685609e-11 1.337122e-10 1.00000000
[26,] 2.038779e-11 4.077557e-11 1.00000000
[27,] 7.171148e-12 1.434230e-11 1.00000000
[28,] 2.349513e-12 4.699026e-12 1.00000000
[29,] 1.305054e-12 2.610107e-12 1.00000000
[30,] 6.559325e-12 1.311865e-11 1.00000000
[31,] 4.411426e-11 8.822852e-11 1.00000000
[32,] 1.727491e-11 3.454982e-11 1.00000000
[33,] 1.111095e-11 2.222190e-11 1.00000000
[34,] 4.379753e-12 8.759506e-12 1.00000000
[35,] 1.716696e-11 3.433393e-11 1.00000000
[36,] 8.793051e-12 1.758610e-11 1.00000000
[37,] 5.811583e-12 1.162317e-11 1.00000000
[38,] 1.001837e-11 2.003673e-11 1.00000000
[39,] 6.145068e-12 1.229014e-11 1.00000000
[40,] 6.785917e-12 1.357183e-11 1.00000000
[41,] 3.229131e-12 6.458262e-12 1.00000000
[42,] 7.578706e-12 1.515741e-11 1.00000000
[43,] 1.057571e-10 2.115143e-10 1.00000000
[44,] 6.373493e-11 1.274699e-10 1.00000000
[45,] 4.446733e-11 8.893465e-11 1.00000000
[46,] 3.558052e-11 7.116103e-11 1.00000000
[47,] 2.133708e-10 4.267417e-10 1.00000000
[48,] 1.406816e-10 2.813632e-10 1.00000000
[49,] 1.802962e-10 3.605923e-10 1.00000000
[50,] 3.602506e-10 7.205012e-10 1.00000000
[51,] 2.220153e-09 4.440306e-09 1.00000000
[52,] 2.806089e-09 5.612177e-09 1.00000000
[53,] 3.903088e-09 7.806177e-09 1.00000000
[54,] 3.391405e-09 6.782809e-09 1.00000000
[55,] 4.362968e-09 8.725936e-09 1.00000000
[56,] 2.810158e-08 5.620316e-08 0.99999997
[57,] 2.792649e-08 5.585298e-08 0.99999997
[58,] 1.072170e-07 2.144340e-07 0.99999989
[59,] 1.230732e-07 2.461463e-07 0.99999988
[60,] 1.487757e-07 2.975514e-07 0.99999985
[61,] 1.027696e-06 2.055393e-06 0.99999897
[62,] 1.858533e-06 3.717066e-06 0.99999814
[63,] 1.812577e-05 3.625155e-05 0.99998187
[64,] 2.653034e-05 5.306067e-05 0.99997347
[65,] 1.324586e-04 2.649173e-04 0.99986754
[66,] 1.853626e-04 3.707252e-04 0.99981464
[67,] 2.628789e-04 5.257578e-04 0.99973712
[68,] 3.692247e-04 7.384494e-04 0.99963078
[69,] 5.545441e-04 1.109088e-03 0.99944546
[70,] 8.112520e-04 1.622504e-03 0.99918875
[71,] 1.650054e-03 3.300108e-03 0.99834995
[72,] 3.617986e-03 7.235972e-03 0.99638201
[73,] 6.040315e-03 1.208063e-02 0.99395968
[74,] 1.115744e-02 2.231487e-02 0.98884256
[75,] 1.355497e-02 2.710995e-02 0.98644503
[76,] 1.601683e-02 3.203366e-02 0.98398317
[77,] 3.055846e-02 6.111692e-02 0.96944154
[78,] 3.483024e-02 6.966048e-02 0.96516976
[79,] 3.832702e-02 7.665404e-02 0.96167298
[80,] 4.215503e-02 8.431006e-02 0.95784497
[81,] 4.699969e-02 9.399939e-02 0.95300031
[82,] 5.412752e-02 1.082550e-01 0.94587248
[83,] 5.793064e-02 1.158613e-01 0.94206936
[84,] 8.544905e-02 1.708981e-01 0.91455095
[85,] 8.626067e-02 1.725213e-01 0.91373933
[86,] 1.424509e-01 2.849017e-01 0.85754914
[87,] 1.550190e-01 3.100380e-01 0.84498098
[88,] 1.728663e-01 3.457326e-01 0.82713371
[89,] 2.653121e-01 5.306243e-01 0.73468787
[90,] 2.624611e-01 5.249223e-01 0.73753886
[91,] 2.517361e-01 5.034722e-01 0.74826388
[92,] 2.392155e-01 4.784309e-01 0.76078454
[93,] 2.313130e-01 4.626261e-01 0.76868696
[94,] 2.327483e-01 4.654966e-01 0.76725168
[95,] 3.656073e-01 7.312145e-01 0.63439273
[96,] 3.280170e-01 6.560340e-01 0.67198299
[97,] 7.244818e-01 5.510365e-01 0.27551823
[98,] 9.187834e-01 1.624332e-01 0.08121662
[99,] 8.972725e-01 2.054550e-01 0.10272752
[100,] 8.788602e-01 2.422796e-01 0.12113982
[101,] 8.408636e-01 3.182728e-01 0.15913638
[102,] 8.030386e-01 3.939228e-01 0.19696139
[103,] 8.983810e-01 2.032379e-01 0.10161896
[104,] 8.698448e-01 2.603103e-01 0.13015516
[105,] 8.225339e-01 3.549323e-01 0.17746614
[106,] 8.873508e-01 2.252985e-01 0.11264924
[107,] 9.108944e-01 1.782111e-01 0.08910556
[108,] 8.561522e-01 2.876956e-01 0.14384780
[109,] 8.745474e-01 2.509052e-01 0.12545261
[110,] 7.840467e-01 4.319066e-01 0.21595330
[111,] 8.497770e-01 3.004460e-01 0.15022302
> postscript(file="/var/www/html/rcomp/tmp/1yra21258766393.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2fg881258766393.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3uchu1258766393.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/48pat1258766393.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5uo941258766393.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 = 120
Frequency = 1
1 2 3 4 5 6
-188.096552 -207.396552 -111.496552 -138.896552 -115.396552 -49.496552
7 8 9 10 11 12
-176.696552 -73.296552 -33.896552 -93.396552 13.703448 -50.296552
13 14 15 16 17 18
-88.196552 -75.396552 -4.196552 25.803448 -4.596552 41.403448
19 20 21 22 23 24
5.703448 58.903448 118.403448 65.703448 98.503448 232.803448
25 26 27 28 29 30
136.703448 42.403448 131.103448 242.703448 196.903448 -471.280220
31 32 33 34 35 36
-353.780220 -324.180220 -207.180220 -670.180220 -762.680220 -495.280220
37 38 39 40 41 42
-605.180220 -438.480220 -125.880220 -308.480220 -563.780220 -145.680220
43 44 45 46 47 48
-532.080220 -617.380220 -452.980220 -694.180220 -844.280220 -391.880220
49 50 51 52 53 54
-326.180220 -534.380220 -34.980220 -409.080220 -172.380220 -633.780220
55 56 57 58 59 60
-746.180220 -191.380220 -156.980220 -326.780220 -489.080220 75.119780
61 62 63 64 65 66
-353.780220 -622.680220 -306.780220 -231.680220 158.019780 -432.180220
67 68 69 70 71 72
-664.880220 -159.680220 225.419780 -60.080220 -203.380220 -55.280220
73 74 75 76 77 78
-190.080220 -1.680220 199.719780 283.419780 253.519780 -285.580220
79 80 81 82 83 84
99.719780 48.119780 434.219780 2.219780 95.719780 187.619780
85 86 87 88 89 90
46.719780 314.819780 270.519780 549.019780 116.919780 -205.080220
91 92 93 94 95 96
445.319780 508.419780 762.919780 114.719780 181.619780 437.019780
97 98 99 100 101 102
500.419780 95.119780 916.319780 415.319780 1228.119780 -335.380220
103 104 105 106 107 108
294.019780 245.519780 395.619780 575.719780 -53.680220 644.619780
109 110 111 112 113 114
378.319780 80.919780 875.619780 596.919780 821.919780 380.919780
115 116 117 118 119 120
142.319780 522.019780 805.419780 572.619780 317.019780 572.219780
> postscript(file="/var/www/html/rcomp/tmp/623gw1258766393.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 = 120
Frequency = 1
lag(myerror, k = 1) myerror
0 -188.096552 NA
1 -207.396552 -188.096552
2 -111.496552 -207.396552
3 -138.896552 -111.496552
4 -115.396552 -138.896552
5 -49.496552 -115.396552
6 -176.696552 -49.496552
7 -73.296552 -176.696552
8 -33.896552 -73.296552
9 -93.396552 -33.896552
10 13.703448 -93.396552
11 -50.296552 13.703448
12 -88.196552 -50.296552
13 -75.396552 -88.196552
14 -4.196552 -75.396552
15 25.803448 -4.196552
16 -4.596552 25.803448
17 41.403448 -4.596552
18 5.703448 41.403448
19 58.903448 5.703448
20 118.403448 58.903448
21 65.703448 118.403448
22 98.503448 65.703448
23 232.803448 98.503448
24 136.703448 232.803448
25 42.403448 136.703448
26 131.103448 42.403448
27 242.703448 131.103448
28 196.903448 242.703448
29 -471.280220 196.903448
30 -353.780220 -471.280220
31 -324.180220 -353.780220
32 -207.180220 -324.180220
33 -670.180220 -207.180220
34 -762.680220 -670.180220
35 -495.280220 -762.680220
36 -605.180220 -495.280220
37 -438.480220 -605.180220
38 -125.880220 -438.480220
39 -308.480220 -125.880220
40 -563.780220 -308.480220
41 -145.680220 -563.780220
42 -532.080220 -145.680220
43 -617.380220 -532.080220
44 -452.980220 -617.380220
45 -694.180220 -452.980220
46 -844.280220 -694.180220
47 -391.880220 -844.280220
48 -326.180220 -391.880220
49 -534.380220 -326.180220
50 -34.980220 -534.380220
51 -409.080220 -34.980220
52 -172.380220 -409.080220
53 -633.780220 -172.380220
54 -746.180220 -633.780220
55 -191.380220 -746.180220
56 -156.980220 -191.380220
57 -326.780220 -156.980220
58 -489.080220 -326.780220
59 75.119780 -489.080220
60 -353.780220 75.119780
61 -622.680220 -353.780220
62 -306.780220 -622.680220
63 -231.680220 -306.780220
64 158.019780 -231.680220
65 -432.180220 158.019780
66 -664.880220 -432.180220
67 -159.680220 -664.880220
68 225.419780 -159.680220
69 -60.080220 225.419780
70 -203.380220 -60.080220
71 -55.280220 -203.380220
72 -190.080220 -55.280220
73 -1.680220 -190.080220
74 199.719780 -1.680220
75 283.419780 199.719780
76 253.519780 283.419780
77 -285.580220 253.519780
78 99.719780 -285.580220
79 48.119780 99.719780
80 434.219780 48.119780
81 2.219780 434.219780
82 95.719780 2.219780
83 187.619780 95.719780
84 46.719780 187.619780
85 314.819780 46.719780
86 270.519780 314.819780
87 549.019780 270.519780
88 116.919780 549.019780
89 -205.080220 116.919780
90 445.319780 -205.080220
91 508.419780 445.319780
92 762.919780 508.419780
93 114.719780 762.919780
94 181.619780 114.719780
95 437.019780 181.619780
96 500.419780 437.019780
97 95.119780 500.419780
98 916.319780 95.119780
99 415.319780 916.319780
100 1228.119780 415.319780
101 -335.380220 1228.119780
102 294.019780 -335.380220
103 245.519780 294.019780
104 395.619780 245.519780
105 575.719780 395.619780
106 -53.680220 575.719780
107 644.619780 -53.680220
108 378.319780 644.619780
109 80.919780 378.319780
110 875.619780 80.919780
111 596.919780 875.619780
112 821.919780 596.919780
113 380.919780 821.919780
114 142.319780 380.919780
115 522.019780 142.319780
116 805.419780 522.019780
117 572.619780 805.419780
118 317.019780 572.619780
119 572.219780 317.019780
120 NA 572.219780
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -207.396552 -188.096552
[2,] -111.496552 -207.396552
[3,] -138.896552 -111.496552
[4,] -115.396552 -138.896552
[5,] -49.496552 -115.396552
[6,] -176.696552 -49.496552
[7,] -73.296552 -176.696552
[8,] -33.896552 -73.296552
[9,] -93.396552 -33.896552
[10,] 13.703448 -93.396552
[11,] -50.296552 13.703448
[12,] -88.196552 -50.296552
[13,] -75.396552 -88.196552
[14,] -4.196552 -75.396552
[15,] 25.803448 -4.196552
[16,] -4.596552 25.803448
[17,] 41.403448 -4.596552
[18,] 5.703448 41.403448
[19,] 58.903448 5.703448
[20,] 118.403448 58.903448
[21,] 65.703448 118.403448
[22,] 98.503448 65.703448
[23,] 232.803448 98.503448
[24,] 136.703448 232.803448
[25,] 42.403448 136.703448
[26,] 131.103448 42.403448
[27,] 242.703448 131.103448
[28,] 196.903448 242.703448
[29,] -471.280220 196.903448
[30,] -353.780220 -471.280220
[31,] -324.180220 -353.780220
[32,] -207.180220 -324.180220
[33,] -670.180220 -207.180220
[34,] -762.680220 -670.180220
[35,] -495.280220 -762.680220
[36,] -605.180220 -495.280220
[37,] -438.480220 -605.180220
[38,] -125.880220 -438.480220
[39,] -308.480220 -125.880220
[40,] -563.780220 -308.480220
[41,] -145.680220 -563.780220
[42,] -532.080220 -145.680220
[43,] -617.380220 -532.080220
[44,] -452.980220 -617.380220
[45,] -694.180220 -452.980220
[46,] -844.280220 -694.180220
[47,] -391.880220 -844.280220
[48,] -326.180220 -391.880220
[49,] -534.380220 -326.180220
[50,] -34.980220 -534.380220
[51,] -409.080220 -34.980220
[52,] -172.380220 -409.080220
[53,] -633.780220 -172.380220
[54,] -746.180220 -633.780220
[55,] -191.380220 -746.180220
[56,] -156.980220 -191.380220
[57,] -326.780220 -156.980220
[58,] -489.080220 -326.780220
[59,] 75.119780 -489.080220
[60,] -353.780220 75.119780
[61,] -622.680220 -353.780220
[62,] -306.780220 -622.680220
[63,] -231.680220 -306.780220
[64,] 158.019780 -231.680220
[65,] -432.180220 158.019780
[66,] -664.880220 -432.180220
[67,] -159.680220 -664.880220
[68,] 225.419780 -159.680220
[69,] -60.080220 225.419780
[70,] -203.380220 -60.080220
[71,] -55.280220 -203.380220
[72,] -190.080220 -55.280220
[73,] -1.680220 -190.080220
[74,] 199.719780 -1.680220
[75,] 283.419780 199.719780
[76,] 253.519780 283.419780
[77,] -285.580220 253.519780
[78,] 99.719780 -285.580220
[79,] 48.119780 99.719780
[80,] 434.219780 48.119780
[81,] 2.219780 434.219780
[82,] 95.719780 2.219780
[83,] 187.619780 95.719780
[84,] 46.719780 187.619780
[85,] 314.819780 46.719780
[86,] 270.519780 314.819780
[87,] 549.019780 270.519780
[88,] 116.919780 549.019780
[89,] -205.080220 116.919780
[90,] 445.319780 -205.080220
[91,] 508.419780 445.319780
[92,] 762.919780 508.419780
[93,] 114.719780 762.919780
[94,] 181.619780 114.719780
[95,] 437.019780 181.619780
[96,] 500.419780 437.019780
[97,] 95.119780 500.419780
[98,] 916.319780 95.119780
[99,] 415.319780 916.319780
[100,] 1228.119780 415.319780
[101,] -335.380220 1228.119780
[102,] 294.019780 -335.380220
[103,] 245.519780 294.019780
[104,] 395.619780 245.519780
[105,] 575.719780 395.619780
[106,] -53.680220 575.719780
[107,] 644.619780 -53.680220
[108,] 378.319780 644.619780
[109,] 80.919780 378.319780
[110,] 875.619780 80.919780
[111,] 596.919780 875.619780
[112,] 821.919780 596.919780
[113,] 380.919780 821.919780
[114,] 142.319780 380.919780
[115,] 522.019780 142.319780
[116,] 805.419780 522.019780
[117,] 572.619780 805.419780
[118,] 317.019780 572.619780
[119,] 572.219780 317.019780
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -207.396552 -188.096552
2 -111.496552 -207.396552
3 -138.896552 -111.496552
4 -115.396552 -138.896552
5 -49.496552 -115.396552
6 -176.696552 -49.496552
7 -73.296552 -176.696552
8 -33.896552 -73.296552
9 -93.396552 -33.896552
10 13.703448 -93.396552
11 -50.296552 13.703448
12 -88.196552 -50.296552
13 -75.396552 -88.196552
14 -4.196552 -75.396552
15 25.803448 -4.196552
16 -4.596552 25.803448
17 41.403448 -4.596552
18 5.703448 41.403448
19 58.903448 5.703448
20 118.403448 58.903448
21 65.703448 118.403448
22 98.503448 65.703448
23 232.803448 98.503448
24 136.703448 232.803448
25 42.403448 136.703448
26 131.103448 42.403448
27 242.703448 131.103448
28 196.903448 242.703448
29 -471.280220 196.903448
30 -353.780220 -471.280220
31 -324.180220 -353.780220
32 -207.180220 -324.180220
33 -670.180220 -207.180220
34 -762.680220 -670.180220
35 -495.280220 -762.680220
36 -605.180220 -495.280220
37 -438.480220 -605.180220
38 -125.880220 -438.480220
39 -308.480220 -125.880220
40 -563.780220 -308.480220
41 -145.680220 -563.780220
42 -532.080220 -145.680220
43 -617.380220 -532.080220
44 -452.980220 -617.380220
45 -694.180220 -452.980220
46 -844.280220 -694.180220
47 -391.880220 -844.280220
48 -326.180220 -391.880220
49 -534.380220 -326.180220
50 -34.980220 -534.380220
51 -409.080220 -34.980220
52 -172.380220 -409.080220
53 -633.780220 -172.380220
54 -746.180220 -633.780220
55 -191.380220 -746.180220
56 -156.980220 -191.380220
57 -326.780220 -156.980220
58 -489.080220 -326.780220
59 75.119780 -489.080220
60 -353.780220 75.119780
61 -622.680220 -353.780220
62 -306.780220 -622.680220
63 -231.680220 -306.780220
64 158.019780 -231.680220
65 -432.180220 158.019780
66 -664.880220 -432.180220
67 -159.680220 -664.880220
68 225.419780 -159.680220
69 -60.080220 225.419780
70 -203.380220 -60.080220
71 -55.280220 -203.380220
72 -190.080220 -55.280220
73 -1.680220 -190.080220
74 199.719780 -1.680220
75 283.419780 199.719780
76 253.519780 283.419780
77 -285.580220 253.519780
78 99.719780 -285.580220
79 48.119780 99.719780
80 434.219780 48.119780
81 2.219780 434.219780
82 95.719780 2.219780
83 187.619780 95.719780
84 46.719780 187.619780
85 314.819780 46.719780
86 270.519780 314.819780
87 549.019780 270.519780
88 116.919780 549.019780
89 -205.080220 116.919780
90 445.319780 -205.080220
91 508.419780 445.319780
92 762.919780 508.419780
93 114.719780 762.919780
94 181.619780 114.719780
95 437.019780 181.619780
96 500.419780 437.019780
97 95.119780 500.419780
98 916.319780 95.119780
99 415.319780 916.319780
100 1228.119780 415.319780
101 -335.380220 1228.119780
102 294.019780 -335.380220
103 245.519780 294.019780
104 395.619780 245.519780
105 575.719780 395.619780
106 -53.680220 575.719780
107 644.619780 -53.680220
108 378.319780 644.619780
109 80.919780 378.319780
110 875.619780 80.919780
111 596.919780 875.619780
112 821.919780 596.919780
113 380.919780 821.919780
114 142.319780 380.919780
115 522.019780 142.319780
116 805.419780 522.019780
117 572.619780 805.419780
118 317.019780 572.619780
119 572.219780 317.019780
> 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/7kpki1258766393.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8qksk1258766393.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9r8dv1258766393.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/1041d71258766393.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11nkg41258766393.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/129d7m1258766394.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/13ytmn1258766394.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/147fqd1258766394.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/15p6xl1258766394.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/160ni11258766394.tab")
+ }
> system("convert tmp/1yra21258766393.ps tmp/1yra21258766393.png")
> system("convert tmp/2fg881258766393.ps tmp/2fg881258766393.png")
> system("convert tmp/3uchu1258766393.ps tmp/3uchu1258766393.png")
> system("convert tmp/48pat1258766393.ps tmp/48pat1258766393.png")
> system("convert tmp/5uo941258766393.ps tmp/5uo941258766393.png")
> system("convert tmp/623gw1258766393.ps tmp/623gw1258766393.png")
> system("convert tmp/7kpki1258766393.ps tmp/7kpki1258766393.png")
> system("convert tmp/8qksk1258766393.ps tmp/8qksk1258766393.png")
> system("convert tmp/9r8dv1258766393.ps tmp/9r8dv1258766393.png")
> system("convert tmp/1041d71258766393.ps tmp/1041d71258766393.png")
>
>
> proc.time()
user system elapsed
3.206 1.622 4.282