R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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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(1579
+ ,0
+ ,4.0
+ ,45.7
+ ,17.0
+ ,2146
+ ,0
+ ,5.9
+ ,81.9
+ ,21.0
+ ,2462
+ ,0
+ ,7.1
+ ,56.8
+ ,21.0
+ ,3695
+ ,0
+ ,10.5
+ ,65.1
+ ,18.0
+ ,4831
+ ,0
+ ,15.1
+ ,86.2
+ ,20.0
+ ,5134
+ ,0
+ ,16.8
+ ,35.1
+ ,11.0
+ ,6250
+ ,0
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+ ,133.8
+ ,20.0
+ ,5760
+ ,0
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+ ,34.5
+ ,13.0
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+ ,0
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+ ,69.9
+ ,14.0
+ ,2917
+ ,0
+ ,11.3
+ ,98.3
+ ,23.0
+ ,1741
+ ,0
+ ,7.9
+ ,86.7
+ ,24.0
+ ,2359
+ ,0
+ ,5.6
+ ,58.2
+ ,22.0
+ ,1511
+ ,1
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+ ,0
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+ ,83.5
+ ,18.0
+ ,2635
+ ,0
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+ ,112.3
+ ,24.0
+ ,2867
+ ,0
+ ,8.5
+ ,134.3
+ ,23.0
+ ,4403
+ ,0
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+ ,0
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+ ,5749
+ ,0
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+ ,43.4
+ ,13.0
+ ,5627
+ ,0
+ ,12.9
+ ,199.4
+ ,23.0
+ ,2846
+ ,0
+ ,14.4
+ ,68.1
+ ,14.0
+ ,1762
+ ,0
+ ,6.2
+ ,99.8
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+ ,2249
+ ,0
+ ,7.8
+ ,66.3
+ ,14.0
+ ,2687
+ ,0
+ ,9.9
+ ,41.9
+ ,12.0
+ ,4359
+ ,0
+ ,13.6
+ ,57.2
+ ,20.0
+ ,5382
+ ,0
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+ ,17.8
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+ ,6398
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+ ,18.6
+ ,172.1
+ ,19.0
+ ,4596
+ ,0
+ ,14.7
+ ,25.8
+ ,12.0
+ ,3024
+ ,0
+ ,10.5
+ ,105.1
+ ,17.0
+ ,1887
+ ,0
+ ,8.6
+ ,92.2
+ ,16.0
+ ,2070
+ ,0
+ ,4.4
+ ,109.3
+ ,18.0
+ ,1351
+ ,0
+ ,2.3
+ ,101.7
+ ,19.0
+ ,2218
+ ,0
+ ,2.8
+ ,29.1
+ ,8.0
+ ,2461
+ ,1
+ ,8.8
+ ,34.6
+ ,10.0
+ ,3028
+ ,0
+ ,10.7
+ ,46.7
+ ,10.0
+ ,4784
+ ,0
+ ,13.9
+ ,82.0
+ ,19.0
+ ,4975
+ ,0
+ ,19.3
+ ,34.4
+ ,8.0
+ ,4607
+ ,0
+ ,19.5
+ ,72.7
+ ,13.0
+ ,6249
+ ,0
+ ,20.4
+ ,44.4
+ ,8.0
+ ,4809
+ ,0
+ ,15.3
+ ,31.0
+ ,12.0
+ ,3157
+ ,0
+ ,7.9
+ ,64.0
+ ,15.0
+ ,1910
+ ,0
+ ,8.3
+ ,65.4
+ ,18.0
+ ,2228
+ ,0
+ ,4.5
+ ,64.5
+ ,17.0
+ ,1594
+ ,0
+ ,3.2
+ ,153.8
+ ,24.0
+ ,2467
+ ,0
+ ,5.0
+ ,48.8
+ ,14.0
+ ,2222
+ ,0
+ ,6.6
+ ,25.0
+ ,15.0
+ ,3607
+ ,1
+ ,11.1
+ ,37.2
+ ,15.0
+ ,4685
+ ,0
+ ,12.8
+ ,40.8
+ ,11.0
+ ,4962
+ ,0
+ ,16.3
+ ,78.4
+ ,18.0
+ ,5770
+ ,0
+ ,17.4
+ ,112.4
+ ,18.0
+ ,5480
+ ,0
+ ,18.9
+ ,122.7
+ ,21.0
+ ,5000
+ ,0
+ ,15.8
+ ,82.9
+ ,13.0
+ ,3228
+ ,0
+ ,11.7
+ ,67.6
+ ,15.0
+ ,1993
+ ,0
+ ,6.4
+ ,78.4
+ ,17.0
+ ,2288
+ ,0
+ ,2.9
+ ,65.7
+ ,17.0
+ ,1580
+ ,0
+ ,4.7
+ ,44.9
+ ,22.0
+ ,2111
+ ,0
+ ,2.4
+ ,80.9
+ ,19.0
+ ,2192
+ ,0
+ ,7.2
+ ,38.8
+ ,17.0
+ ,3601
+ ,0
+ ,10.7
+ ,46.1
+ ,17.0
+ ,4665
+ ,1
+ ,13.4
+ ,60.0
+ ,19.0
+ ,4876
+ ,0
+ ,18.5
+ ,53.9
+ ,11.0
+ ,5813
+ ,0
+ ,18.3
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+ ,16.0
+ ,5589
+ ,0
+ ,16.8
+ ,69.5
+ ,15.0
+ ,5331
+ ,0
+ ,16.6
+ ,74.2
+ ,11.0
+ ,3075
+ ,0
+ ,14.1
+ ,47.0
+ ,13.0
+ ,2002
+ ,0
+ ,6.1
+ ,60.9
+ ,18.0
+ ,2306
+ ,0
+ ,3.5
+ ,51.4
+ ,22.0
+ ,1507
+ ,0
+ ,1.7
+ ,18.7
+ ,9.0
+ ,1992
+ ,0
+ ,2.3
+ ,88.1
+ ,19.0
+ ,2487
+ ,0
+ ,4.5
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+ ,16.0
+ ,3490
+ ,0
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+ ,4647
+ ,0
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+ ,20.0
+ ,5594
+ ,1
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+ ,25.8
+ ,7.0
+ ,5611
+ ,0
+ ,23.0
+ ,48.1
+ ,8.0
+ ,5788
+ ,0
+ ,16.3
+ ,202.3
+ ,21.0
+ ,6204
+ ,0
+ ,18.4
+ ,9.2
+ ,8.0
+ ,3013
+ ,0
+ ,14.2
+ ,56.3
+ ,17.0
+ ,1931
+ ,0
+ ,9.1
+ ,71.6
+ ,20.0
+ ,2549
+ ,0
+ ,5.9
+ ,93.0
+ ,18.0
+ ,1504
+ ,0
+ ,7.2
+ ,82.3
+ ,26.0
+ ,2090
+ ,0
+ ,6.8
+ ,95.4
+ ,18.0
+ ,2702
+ ,0
+ ,8.0
+ ,61.9
+ ,20.0
+ ,2939
+ ,0
+ ,14.3
+ ,0.0
+ ,0.0
+ ,4500
+ ,0
+ ,14.6
+ ,103.4
+ ,22.0
+ ,6208
+ ,0
+ ,17.5
+ ,99.2
+ ,19.0
+ ,6415
+ ,1
+ ,17.2
+ ,96.7
+ ,18.0
+ ,5657
+ ,0
+ ,17.2
+ ,56.9
+ ,13.0
+ ,5964
+ ,0
+ ,14.1
+ ,57.6
+ ,16.0
+ ,3163
+ ,0
+ ,10.5
+ ,65.2
+ ,11.0
+ ,1997
+ ,0
+ ,6.8
+ ,71.7
+ ,22.0
+ ,2422
+ ,0
+ ,4.1
+ ,89.2
+ ,19.0
+ ,1376
+ ,0
+ ,6.5
+ ,70.7
+ ,23.0
+ ,2202
+ ,0
+ ,6.1
+ ,35.4
+ ,11.0
+ ,2683
+ ,0
+ ,6.3
+ ,140.5
+ ,24.0
+ ,3303
+ ,0
+ ,9.3
+ ,45.4
+ ,14.0
+ ,5202
+ ,0
+ ,16.4
+ ,53.9
+ ,11.0
+ ,5231
+ ,0
+ ,16.1
+ ,69.9
+ ,17.0
+ ,4880
+ ,0
+ ,18.0
+ ,101.9
+ ,20.0
+ ,7998
+ ,1
+ ,17.6
+ ,89.3
+ ,19.0
+ ,4977
+ ,0
+ ,14.0
+ ,70.7
+ ,12.0
+ ,3531
+ ,0
+ ,10.5
+ ,72.4
+ ,19.0
+ ,2025
+ ,0
+ ,6.9
+ ,67.6
+ ,26.0
+ ,2205
+ ,0
+ ,2.8
+ ,43.3
+ ,13.0
+ ,1442
+ ,0
+ ,0.7
+ ,62.9
+ ,12.0
+ ,2238
+ ,0
+ ,3.6
+ ,57.1
+ ,20.0
+ ,2179
+ ,0
+ ,6.7
+ ,68.2
+ ,15.0
+ ,3218
+ ,0
+ ,12.5
+ ,47.1
+ ,15.0
+ ,5139
+ ,0
+ ,14.4
+ ,43.1
+ ,17.0
+ ,4990
+ ,0
+ ,16.5
+ ,64.5
+ ,11.0
+ ,4914
+ ,0
+ ,18.7
+ ,73.1
+ ,20.0
+ ,6084
+ ,0
+ ,19.4
+ ,37.7
+ ,9.0
+ ,5672
+ ,1
+ ,15.8
+ ,29.1
+ ,10.0
+ ,3548
+ ,0
+ ,11.3
+ ,105.0
+ ,17.0
+ ,1793
+ ,0
+ ,9.7
+ ,98.0
+ ,25.0
+ ,2086
+ ,0
+ ,2.9
+ ,80.8
+ ,19.0)
+ ,dim=c(5
+ ,120)
+ ,dimnames=list(c('Huwelijken'
+ ,'Specialedag'
+ ,'Temperatuur'
+ ,'Neerslag'
+ ,'Neerslagdagen
')
+ ,1:120))
> y <- array(NA,dim=c(5,120),dimnames=list(c('Huwelijken','Specialedag','Temperatuur','Neerslag','Neerslagdagen
'),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
Huwelijken Specialedag Temperatuur Neerslag Neerslagdagen\r
1 1579 0 4.0 45.7 17
2 2146 0 5.9 81.9 21
3 2462 0 7.1 56.8 21
4 3695 0 10.5 65.1 18
5 4831 0 15.1 86.2 20
6 5134 0 16.8 35.1 11
7 6250 0 15.3 133.8 20
8 5760 0 18.4 34.5 13
9 6249 0 16.1 69.9 14
10 2917 0 11.3 98.3 23
11 1741 0 7.9 86.7 24
12 2359 0 5.6 58.2 22
13 1511 1 3.4 83.6 17
14 2059 0 4.8 83.5 18
15 2635 0 6.5 112.3 24
16 2867 0 8.5 134.3 23
17 4403 0 15.1 30.0 8
18 5720 0 15.7 44.5 10
19 4502 0 18.7 120.1 18
20 5749 0 19.2 43.4 13
21 5627 0 12.9 199.4 23
22 2846 0 14.4 68.1 14
23 1762 0 6.2 99.8 15
24 2429 0 3.3 69.5 18
25 1169 0 4.6 71.3 18
26 2154 1 7.2 167.8 20
27 2249 0 7.8 66.3 14
28 2687 0 9.9 41.9 12
29 4359 0 13.6 57.2 20
30 5382 0 17.1 72.3 14
31 4459 0 17.8 96.5 16
32 6398 0 18.6 172.1 19
33 4596 0 14.7 25.8 12
34 3024 0 10.5 105.1 17
35 1887 0 8.6 92.2 16
36 2070 0 4.4 109.3 18
37 1351 0 2.3 101.7 19
38 2218 0 2.8 29.1 8
39 2461 1 8.8 34.6 10
40 3028 0 10.7 46.7 10
41 4784 0 13.9 82.0 19
42 4975 0 19.3 34.4 8
43 4607 0 19.5 72.7 13
44 6249 0 20.4 44.4 8
45 4809 0 15.3 31.0 12
46 3157 0 7.9 64.0 15
47 1910 0 8.3 65.4 18
48 2228 0 4.5 64.5 17
49 1594 0 3.2 153.8 24
50 2467 0 5.0 48.8 14
51 2222 0 6.6 25.0 15
52 3607 1 11.1 37.2 15
53 4685 0 12.8 40.8 11
54 4962 0 16.3 78.4 18
55 5770 0 17.4 112.4 18
56 5480 0 18.9 122.7 21
57 5000 0 15.8 82.9 13
58 3228 0 11.7 67.6 15
59 1993 0 6.4 78.4 17
60 2288 0 2.9 65.7 17
61 1580 0 4.7 44.9 22
62 2111 0 2.4 80.9 19
63 2192 0 7.2 38.8 17
64 3601 0 10.7 46.1 17
65 4665 1 13.4 60.0 19
66 4876 0 18.5 53.9 11
67 5813 0 18.3 123.5 16
68 5589 0 16.8 69.5 15
69 5331 0 16.6 74.2 11
70 3075 0 14.1 47.0 13
71 2002 0 6.1 60.9 18
72 2306 0 3.5 51.4 22
73 1507 0 1.7 18.7 9
74 1992 0 2.3 88.1 19
75 2487 0 4.5 65.3 16
76 3490 0 9.3 46.0 16
77 4647 0 14.2 115.6 20
78 5594 1 17.3 25.8 7
79 5611 0 23.0 48.1 8
80 5788 0 16.3 202.3 21
81 6204 0 18.4 9.2 8
82 3013 0 14.2 56.3 17
83 1931 0 9.1 71.6 20
84 2549 0 5.9 93.0 18
85 1504 0 7.2 82.3 26
86 2090 0 6.8 95.4 18
87 2702 0 8.0 61.9 20
88 2939 0 14.3 0.0 0
89 4500 0 14.6 103.4 22
90 6208 0 17.5 99.2 19
91 6415 1 17.2 96.7 18
92 5657 0 17.2 56.9 13
93 5964 0 14.1 57.6 16
94 3163 0 10.5 65.2 11
95 1997 0 6.8 71.7 22
96 2422 0 4.1 89.2 19
97 1376 0 6.5 70.7 23
98 2202 0 6.1 35.4 11
99 2683 0 6.3 140.5 24
100 3303 0 9.3 45.4 14
101 5202 0 16.4 53.9 11
102 5231 0 16.1 69.9 17
103 4880 0 18.0 101.9 20
104 7998 1 17.6 89.3 19
105 4977 0 14.0 70.7 12
106 3531 0 10.5 72.4 19
107 2025 0 6.9 67.6 26
108 2205 0 2.8 43.3 13
109 1442 0 0.7 62.9 12
110 2238 0 3.6 57.1 20
111 2179 0 6.7 68.2 15
112 3218 0 12.5 47.1 15
113 5139 0 14.4 43.1 17
114 4990 0 16.5 64.5 11
115 4914 0 18.7 73.1 20
116 6084 0 19.4 37.7 9
117 5672 1 15.8 29.1 10
118 3548 0 11.3 105.0 17
119 1793 0 9.7 98.0 25
120 2086 0 2.9 80.8 19
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Specialedag Temperatuur Neerslag
783.758 510.481 253.377 4.649
`Neerslagdagen\r`
-20.739
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1612.6 -496.0 93.9 439.7 2223.3
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 783.758 329.571 2.378 0.0191 *
Specialedag 510.481 245.913 2.076 0.0401 *
Temperatuur 253.377 12.923 19.606 <2e-16 ***
Neerslag 4.649 2.463 1.887 0.0617 .
`Neerslagdagen\r` -20.739 19.712 -1.052 0.2949
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 706.4 on 115 degrees of freedom
Multiple R-squared: 0.8169, Adjusted R-squared: 0.8106
F-statistic: 128.3 on 4 and 115 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,] 0.09815852 0.1963170 0.9018415
[2,] 0.13633150 0.2726630 0.8636685
[3,] 0.25157355 0.5031471 0.7484264
[4,] 0.20197447 0.4039489 0.7980255
[5,] 0.33024797 0.6604959 0.6697520
[6,] 0.23740711 0.4748142 0.7625929
[7,] 0.20255118 0.4051024 0.7974488
[8,] 0.13847034 0.2769407 0.8615297
[9,] 0.13546767 0.2709353 0.8645323
[10,] 0.19280529 0.3856106 0.8071947
[11,] 0.16229410 0.3245882 0.8377059
[12,] 0.52157105 0.9568579 0.4784289
[13,] 0.44285521 0.8857104 0.5571448
[14,] 0.44955053 0.8991011 0.5504495
[15,] 0.81840755 0.3631849 0.1815924
[16,] 0.84219843 0.3156031 0.1578016
[17,] 0.85999141 0.2800172 0.1400086
[18,] 0.85697287 0.2860543 0.1430271
[19,] 0.87995956 0.2400809 0.1200404
[20,] 0.86438229 0.2712354 0.1356177
[21,] 0.84551013 0.3089797 0.1544899
[22,] 0.81012284 0.3797543 0.1898772
[23,] 0.76615944 0.4676811 0.2338406
[24,] 0.81434689 0.3713062 0.1856531
[25,] 0.78036599 0.4392680 0.2196340
[26,] 0.73842394 0.5231521 0.2615761
[27,] 0.71950702 0.5609860 0.2804930
[28,] 0.78841073 0.4231785 0.2115893
[29,] 0.74842293 0.5031541 0.2515771
[30,] 0.70381046 0.5923791 0.2961895
[31,] 0.72608227 0.5478355 0.2739177
[32,] 0.75390849 0.4921830 0.2460915
[33,] 0.73056151 0.5388770 0.2694385
[34,] 0.70826127 0.5834775 0.2917387
[35,] 0.70407138 0.5918572 0.2959286
[36,] 0.78048558 0.4390288 0.2195144
[37,] 0.74732116 0.5053577 0.2526788
[38,] 0.71162153 0.5767569 0.2883785
[39,] 0.67829313 0.6434137 0.3217069
[40,] 0.70912501 0.5817500 0.2908750
[41,] 0.67340459 0.6531908 0.3265954
[42,] 0.63962649 0.7207470 0.3603735
[43,] 0.61102037 0.7779593 0.3889796
[44,] 0.55733109 0.8853378 0.4426689
[45,] 0.56761818 0.8647636 0.4323818
[46,] 0.57337769 0.8532446 0.4266223
[47,] 0.52097062 0.9580588 0.4790294
[48,] 0.48917211 0.9783442 0.5108279
[49,] 0.43929972 0.8785994 0.5607003
[50,] 0.38738325 0.7747665 0.6126168
[51,] 0.36571947 0.7314389 0.6342805
[52,] 0.34085649 0.6817130 0.6591435
[53,] 0.35148964 0.7029793 0.6485104
[54,] 0.30399108 0.6079822 0.6960089
[55,] 0.29918894 0.5983779 0.7008111
[56,] 0.25874744 0.5174949 0.7412526
[57,] 0.22401297 0.4480259 0.7759870
[58,] 0.22997136 0.4599427 0.7700286
[59,] 0.21504208 0.4300842 0.7849579
[60,] 0.17946953 0.3589391 0.8205305
[61,] 0.16966826 0.3393365 0.8303317
[62,] 0.14145722 0.2829144 0.8585428
[63,] 0.20890507 0.4178101 0.7910949
[64,] 0.17728471 0.3545694 0.8227153
[65,] 0.19216825 0.3843365 0.8078318
[66,] 0.16474584 0.3294917 0.8352542
[67,] 0.14944377 0.2988875 0.8505562
[68,] 0.13687010 0.2737402 0.8631299
[69,] 0.12263559 0.2452712 0.8773644
[70,] 0.09713451 0.1942690 0.9028655
[71,] 0.11119252 0.2223850 0.8888075
[72,] 0.14957463 0.2991493 0.8504254
[73,] 0.12405237 0.2481047 0.8759476
[74,] 0.15015573 0.3003115 0.8498443
[75,] 0.22810040 0.4562008 0.7718996
[76,] 0.28718841 0.5743768 0.7128116
[77,] 0.24062210 0.4812442 0.7593779
[78,] 0.27268268 0.5453654 0.7273173
[79,] 0.25742397 0.5148479 0.7425760
[80,] 0.21071002 0.4214200 0.7892900
[81,] 0.48221534 0.9644307 0.5177847
[82,] 0.41940696 0.8388139 0.5805930
[83,] 0.47657419 0.9531484 0.5234258
[84,] 0.47051263 0.9410253 0.5294874
[85,] 0.43035584 0.8607117 0.5696442
[86,] 0.76012532 0.4797494 0.2398747
[87,] 0.75243948 0.4951210 0.2475605
[88,] 0.70413964 0.5917207 0.2958604
[89,] 0.67065390 0.6586922 0.3293461
[90,] 0.70096657 0.5980669 0.2990334
[91,] 0.65937238 0.6812552 0.3406276
[92,] 0.59615411 0.8076918 0.4038459
[93,] 0.51921049 0.9615790 0.4807895
[94,] 0.44116327 0.8823265 0.5588367
[95,] 0.40164257 0.8032851 0.5983574
[96,] 0.33155675 0.6631135 0.6684433
[97,] 0.87505148 0.2498970 0.1249485
[98,] 0.86489192 0.2702162 0.1351081
[99,] 0.81701411 0.3659718 0.1829859
[100,] 0.73678110 0.5264378 0.2632189
[101,] 0.64250157 0.7149969 0.3574984
[102,] 0.54234851 0.9153030 0.4576515
[103,] 0.45610659 0.9122132 0.5438934
[104,] 0.40144514 0.8028903 0.5985549
[105,] 0.66732170 0.6653566 0.3326783
> postscript(file="/var/www/html/rcomp/tmp/1l94s1292285051.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2eild1292285051.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3eild1292285051.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4eild1292285051.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/56r2g1292285051.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> qqline(mysum$resid)
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 120
Frequency = 1
1 2 3 4 5 6
-78.133449 -77.868044 50.757212 321.475412 235.337130 158.481228
7 8 9 10 11 12
1382.392944 423.346020 1351.295010 -709.859827 -949.716596 342.053885
13 14 15 16 17 18
-680.766213 44.190922 180.009264 -217.750836 -180.288720 958.760493
19 20 21 22 23 24
-1204.882438 168.272856 1124.773414 -1612.597052 -745.525232 859.335248
25 26 27 28 29 30
-738.421954 -1329.784344 -528.942592 -551.089081 278.209025 219.761757
31 32 33 34 35 36
-951.617208 495.472325 216.543005 -556.204089 -1172.561699 36.610241
37 38 39 40 41 42
-94.230441 755.430081 -1016.399653 -476.582011 491.173742 -692.924874
43 44 45 46 47 48
-1185.941381 255.875555 253.344676 385.150602 -907.490089 356.786244
49 50 51 52 53 54
-217.760100 479.861394 -39.167826 -361.555913 696.492117 57.064622
55 56 57 58 59 60
428.300941 -227.425966 97.138185 -523.416011 -424.243968 816.610985
61 62 63 64 65 66
-147.081847 737.120770 -243.864659 244.382313 90.648718 -617.651288
67 68 69 70 71 72
150.184748 536.529940 224.400067 -1230.239870 -237.142768 852.755082
73 74 75 76 77 78
392.228371 609.989222 591.328123 467.835424 142.710253 -58.413915
79 80 81 82 83 84
-1058.103699 369.332856 881.256599 -1277.851378 -1076.533656 211.315603
85 86 87 88 89 90
-947.420752 -486.879965 18.271364 -1468.046649 -7.450093 923.062834
91 92 93 94 95 96
686.477285 520.271727 1671.703933 -356.164660 -386.753137 578.797552
97 98 99 100 101 102
-906.352262 -63.781122 147.596803 242.145892 240.440079 395.512962
103 104 105 106 107 108
-523.437231 2223.264800 566.188938 144.280646 -282.074683 780.117902
109 110 111 112 113 114
437.359262 691.442287 -308.320908 -640.823140 858.833515 -46.171754
115 116 117 118 119 120
-532.924088 396.136695 446.529234 -234.440711 -1385.583695 585.897200
> postscript(file="/var/www/html/rcomp/tmp/66r2g1292285051.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 120
Frequency = 1
lag(myerror, k = 1) myerror
0 -78.133449 NA
1 -77.868044 -78.133449
2 50.757212 -77.868044
3 321.475412 50.757212
4 235.337130 321.475412
5 158.481228 235.337130
6 1382.392944 158.481228
7 423.346020 1382.392944
8 1351.295010 423.346020
9 -709.859827 1351.295010
10 -949.716596 -709.859827
11 342.053885 -949.716596
12 -680.766213 342.053885
13 44.190922 -680.766213
14 180.009264 44.190922
15 -217.750836 180.009264
16 -180.288720 -217.750836
17 958.760493 -180.288720
18 -1204.882438 958.760493
19 168.272856 -1204.882438
20 1124.773414 168.272856
21 -1612.597052 1124.773414
22 -745.525232 -1612.597052
23 859.335248 -745.525232
24 -738.421954 859.335248
25 -1329.784344 -738.421954
26 -528.942592 -1329.784344
27 -551.089081 -528.942592
28 278.209025 -551.089081
29 219.761757 278.209025
30 -951.617208 219.761757
31 495.472325 -951.617208
32 216.543005 495.472325
33 -556.204089 216.543005
34 -1172.561699 -556.204089
35 36.610241 -1172.561699
36 -94.230441 36.610241
37 755.430081 -94.230441
38 -1016.399653 755.430081
39 -476.582011 -1016.399653
40 491.173742 -476.582011
41 -692.924874 491.173742
42 -1185.941381 -692.924874
43 255.875555 -1185.941381
44 253.344676 255.875555
45 385.150602 253.344676
46 -907.490089 385.150602
47 356.786244 -907.490089
48 -217.760100 356.786244
49 479.861394 -217.760100
50 -39.167826 479.861394
51 -361.555913 -39.167826
52 696.492117 -361.555913
53 57.064622 696.492117
54 428.300941 57.064622
55 -227.425966 428.300941
56 97.138185 -227.425966
57 -523.416011 97.138185
58 -424.243968 -523.416011
59 816.610985 -424.243968
60 -147.081847 816.610985
61 737.120770 -147.081847
62 -243.864659 737.120770
63 244.382313 -243.864659
64 90.648718 244.382313
65 -617.651288 90.648718
66 150.184748 -617.651288
67 536.529940 150.184748
68 224.400067 536.529940
69 -1230.239870 224.400067
70 -237.142768 -1230.239870
71 852.755082 -237.142768
72 392.228371 852.755082
73 609.989222 392.228371
74 591.328123 609.989222
75 467.835424 591.328123
76 142.710253 467.835424
77 -58.413915 142.710253
78 -1058.103699 -58.413915
79 369.332856 -1058.103699
80 881.256599 369.332856
81 -1277.851378 881.256599
82 -1076.533656 -1277.851378
83 211.315603 -1076.533656
84 -947.420752 211.315603
85 -486.879965 -947.420752
86 18.271364 -486.879965
87 -1468.046649 18.271364
88 -7.450093 -1468.046649
89 923.062834 -7.450093
90 686.477285 923.062834
91 520.271727 686.477285
92 1671.703933 520.271727
93 -356.164660 1671.703933
94 -386.753137 -356.164660
95 578.797552 -386.753137
96 -906.352262 578.797552
97 -63.781122 -906.352262
98 147.596803 -63.781122
99 242.145892 147.596803
100 240.440079 242.145892
101 395.512962 240.440079
102 -523.437231 395.512962
103 2223.264800 -523.437231
104 566.188938 2223.264800
105 144.280646 566.188938
106 -282.074683 144.280646
107 780.117902 -282.074683
108 437.359262 780.117902
109 691.442287 437.359262
110 -308.320908 691.442287
111 -640.823140 -308.320908
112 858.833515 -640.823140
113 -46.171754 858.833515
114 -532.924088 -46.171754
115 396.136695 -532.924088
116 446.529234 396.136695
117 -234.440711 446.529234
118 -1385.583695 -234.440711
119 585.897200 -1385.583695
120 NA 585.897200
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -77.868044 -78.133449
[2,] 50.757212 -77.868044
[3,] 321.475412 50.757212
[4,] 235.337130 321.475412
[5,] 158.481228 235.337130
[6,] 1382.392944 158.481228
[7,] 423.346020 1382.392944
[8,] 1351.295010 423.346020
[9,] -709.859827 1351.295010
[10,] -949.716596 -709.859827
[11,] 342.053885 -949.716596
[12,] -680.766213 342.053885
[13,] 44.190922 -680.766213
[14,] 180.009264 44.190922
[15,] -217.750836 180.009264
[16,] -180.288720 -217.750836
[17,] 958.760493 -180.288720
[18,] -1204.882438 958.760493
[19,] 168.272856 -1204.882438
[20,] 1124.773414 168.272856
[21,] -1612.597052 1124.773414
[22,] -745.525232 -1612.597052
[23,] 859.335248 -745.525232
[24,] -738.421954 859.335248
[25,] -1329.784344 -738.421954
[26,] -528.942592 -1329.784344
[27,] -551.089081 -528.942592
[28,] 278.209025 -551.089081
[29,] 219.761757 278.209025
[30,] -951.617208 219.761757
[31,] 495.472325 -951.617208
[32,] 216.543005 495.472325
[33,] -556.204089 216.543005
[34,] -1172.561699 -556.204089
[35,] 36.610241 -1172.561699
[36,] -94.230441 36.610241
[37,] 755.430081 -94.230441
[38,] -1016.399653 755.430081
[39,] -476.582011 -1016.399653
[40,] 491.173742 -476.582011
[41,] -692.924874 491.173742
[42,] -1185.941381 -692.924874
[43,] 255.875555 -1185.941381
[44,] 253.344676 255.875555
[45,] 385.150602 253.344676
[46,] -907.490089 385.150602
[47,] 356.786244 -907.490089
[48,] -217.760100 356.786244
[49,] 479.861394 -217.760100
[50,] -39.167826 479.861394
[51,] -361.555913 -39.167826
[52,] 696.492117 -361.555913
[53,] 57.064622 696.492117
[54,] 428.300941 57.064622
[55,] -227.425966 428.300941
[56,] 97.138185 -227.425966
[57,] -523.416011 97.138185
[58,] -424.243968 -523.416011
[59,] 816.610985 -424.243968
[60,] -147.081847 816.610985
[61,] 737.120770 -147.081847
[62,] -243.864659 737.120770
[63,] 244.382313 -243.864659
[64,] 90.648718 244.382313
[65,] -617.651288 90.648718
[66,] 150.184748 -617.651288
[67,] 536.529940 150.184748
[68,] 224.400067 536.529940
[69,] -1230.239870 224.400067
[70,] -237.142768 -1230.239870
[71,] 852.755082 -237.142768
[72,] 392.228371 852.755082
[73,] 609.989222 392.228371
[74,] 591.328123 609.989222
[75,] 467.835424 591.328123
[76,] 142.710253 467.835424
[77,] -58.413915 142.710253
[78,] -1058.103699 -58.413915
[79,] 369.332856 -1058.103699
[80,] 881.256599 369.332856
[81,] -1277.851378 881.256599
[82,] -1076.533656 -1277.851378
[83,] 211.315603 -1076.533656
[84,] -947.420752 211.315603
[85,] -486.879965 -947.420752
[86,] 18.271364 -486.879965
[87,] -1468.046649 18.271364
[88,] -7.450093 -1468.046649
[89,] 923.062834 -7.450093
[90,] 686.477285 923.062834
[91,] 520.271727 686.477285
[92,] 1671.703933 520.271727
[93,] -356.164660 1671.703933
[94,] -386.753137 -356.164660
[95,] 578.797552 -386.753137
[96,] -906.352262 578.797552
[97,] -63.781122 -906.352262
[98,] 147.596803 -63.781122
[99,] 242.145892 147.596803
[100,] 240.440079 242.145892
[101,] 395.512962 240.440079
[102,] -523.437231 395.512962
[103,] 2223.264800 -523.437231
[104,] 566.188938 2223.264800
[105,] 144.280646 566.188938
[106,] -282.074683 144.280646
[107,] 780.117902 -282.074683
[108,] 437.359262 780.117902
[109,] 691.442287 437.359262
[110,] -308.320908 691.442287
[111,] -640.823140 -308.320908
[112,] 858.833515 -640.823140
[113,] -46.171754 858.833515
[114,] -532.924088 -46.171754
[115,] 396.136695 -532.924088
[116,] 446.529234 396.136695
[117,] -234.440711 446.529234
[118,] -1385.583695 -234.440711
[119,] 585.897200 -1385.583695
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -77.868044 -78.133449
2 50.757212 -77.868044
3 321.475412 50.757212
4 235.337130 321.475412
5 158.481228 235.337130
6 1382.392944 158.481228
7 423.346020 1382.392944
8 1351.295010 423.346020
9 -709.859827 1351.295010
10 -949.716596 -709.859827
11 342.053885 -949.716596
12 -680.766213 342.053885
13 44.190922 -680.766213
14 180.009264 44.190922
15 -217.750836 180.009264
16 -180.288720 -217.750836
17 958.760493 -180.288720
18 -1204.882438 958.760493
19 168.272856 -1204.882438
20 1124.773414 168.272856
21 -1612.597052 1124.773414
22 -745.525232 -1612.597052
23 859.335248 -745.525232
24 -738.421954 859.335248
25 -1329.784344 -738.421954
26 -528.942592 -1329.784344
27 -551.089081 -528.942592
28 278.209025 -551.089081
29 219.761757 278.209025
30 -951.617208 219.761757
31 495.472325 -951.617208
32 216.543005 495.472325
33 -556.204089 216.543005
34 -1172.561699 -556.204089
35 36.610241 -1172.561699
36 -94.230441 36.610241
37 755.430081 -94.230441
38 -1016.399653 755.430081
39 -476.582011 -1016.399653
40 491.173742 -476.582011
41 -692.924874 491.173742
42 -1185.941381 -692.924874
43 255.875555 -1185.941381
44 253.344676 255.875555
45 385.150602 253.344676
46 -907.490089 385.150602
47 356.786244 -907.490089
48 -217.760100 356.786244
49 479.861394 -217.760100
50 -39.167826 479.861394
51 -361.555913 -39.167826
52 696.492117 -361.555913
53 57.064622 696.492117
54 428.300941 57.064622
55 -227.425966 428.300941
56 97.138185 -227.425966
57 -523.416011 97.138185
58 -424.243968 -523.416011
59 816.610985 -424.243968
60 -147.081847 816.610985
61 737.120770 -147.081847
62 -243.864659 737.120770
63 244.382313 -243.864659
64 90.648718 244.382313
65 -617.651288 90.648718
66 150.184748 -617.651288
67 536.529940 150.184748
68 224.400067 536.529940
69 -1230.239870 224.400067
70 -237.142768 -1230.239870
71 852.755082 -237.142768
72 392.228371 852.755082
73 609.989222 392.228371
74 591.328123 609.989222
75 467.835424 591.328123
76 142.710253 467.835424
77 -58.413915 142.710253
78 -1058.103699 -58.413915
79 369.332856 -1058.103699
80 881.256599 369.332856
81 -1277.851378 881.256599
82 -1076.533656 -1277.851378
83 211.315603 -1076.533656
84 -947.420752 211.315603
85 -486.879965 -947.420752
86 18.271364 -486.879965
87 -1468.046649 18.271364
88 -7.450093 -1468.046649
89 923.062834 -7.450093
90 686.477285 923.062834
91 520.271727 686.477285
92 1671.703933 520.271727
93 -356.164660 1671.703933
94 -386.753137 -356.164660
95 578.797552 -386.753137
96 -906.352262 578.797552
97 -63.781122 -906.352262
98 147.596803 -63.781122
99 242.145892 147.596803
100 240.440079 242.145892
101 395.512962 240.440079
102 -523.437231 395.512962
103 2223.264800 -523.437231
104 566.188938 2223.264800
105 144.280646 566.188938
106 -282.074683 144.280646
107 780.117902 -282.074683
108 437.359262 780.117902
109 691.442287 437.359262
110 -308.320908 691.442287
111 -640.823140 -308.320908
112 858.833515 -640.823140
113 -46.171754 858.833515
114 -532.924088 -46.171754
115 396.136695 -532.924088
116 446.529234 396.136695
117 -234.440711 446.529234
118 -1385.583695 -234.440711
119 585.897200 -1385.583695
> 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/7hiji1292285051.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8hiji1292285051.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9ss1l1292285051.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10ss1l1292285051.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11dah91292285051.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/12ztgx1292285051.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/13nud91292285051.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/14y3uc1292285051.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/15j3s01292285051.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/16gd891292285051.tab")
+ }
>
> try(system("convert tmp/1l94s1292285051.ps tmp/1l94s1292285051.png",intern=TRUE))
character(0)
> try(system("convert tmp/2eild1292285051.ps tmp/2eild1292285051.png",intern=TRUE))
character(0)
> try(system("convert tmp/3eild1292285051.ps tmp/3eild1292285051.png",intern=TRUE))
character(0)
> try(system("convert tmp/4eild1292285051.ps tmp/4eild1292285051.png",intern=TRUE))
character(0)
> try(system("convert tmp/56r2g1292285051.ps tmp/56r2g1292285051.png",intern=TRUE))
character(0)
> try(system("convert tmp/66r2g1292285051.ps tmp/66r2g1292285051.png",intern=TRUE))
character(0)
> try(system("convert tmp/7hiji1292285051.ps tmp/7hiji1292285051.png",intern=TRUE))
character(0)
> try(system("convert tmp/8hiji1292285051.ps tmp/8hiji1292285051.png",intern=TRUE))
character(0)
> try(system("convert tmp/9ss1l1292285051.ps tmp/9ss1l1292285051.png",intern=TRUE))
character(0)
> try(system("convert tmp/10ss1l1292285051.ps tmp/10ss1l1292285051.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.348 1.756 11.363