R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)
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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(110.92
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+ ,3566.59
+ ,38.58
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+ ,88.96
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+ ,3389.08
+ ,38.13
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+ ,89.91
+ ,3413.72
+ ,38.75
+ ,110.14
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+ ,3365.87
+ ,38.2
+ ,112.47
+ ,92.48
+ ,3382.78
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+ ,113.17
+ ,92.42
+ ,3406.53
+ ,38.29
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+ ,92.92
+ ,3457.04
+ ,38.73
+ ,114.47
+ ,92.19
+ ,3401.2
+ ,38.33
+ ,113.05
+ ,91.53
+ ,3406.02
+ ,38.73
+ ,114.56
+ ,91.62
+ ,3414.23
+ ,39.06
+ ,115.72
+ ,92.47
+ ,3434.98
+ ,39.28
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+ ,91.27
+ ,3354.82
+ ,38.6
+ ,114.42
+ ,91.88
+ ,3439.32
+ ,39.68
+ ,112.06
+ ,89.99
+ ,3414.84
+ ,39.61
+ ,111.59
+ ,89.68
+ ,3513.81
+ ,40.74
+ ,111.9
+ ,89.92
+ ,3497.22
+ ,40.55
+ ,112.25
+ ,91.48
+ ,3530.72
+ ,40.8
+ ,108.07
+ ,88.34
+ ,3509.92
+ ,40.81
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+ ,91.66
+ ,3531.82
+ ,41.47
+ ,112.23
+ ,92.43
+ ,3512.69
+ ,41
+ ,111.88
+ ,91.5
+ ,3553.69
+ ,41.42
+ ,112.14
+ ,92.03
+ ,3581.58
+ ,41.84
+ ,112.47
+ ,92.22
+ ,3502.09
+ ,40.89
+ ,110.11
+ ,90.31
+ ,3543.79
+ ,41.05
+ ,109.96
+ ,90.86
+ ,3537.3
+ ,41.2
+ ,109.86
+ ,92.1
+ ,3506.05
+ ,40.45
+ ,111.41
+ ,92.9
+ ,3519.05
+ ,40.55
+ ,111.56
+ ,93.06
+ ,3509.88
+ ,40.5
+ ,110.56
+ ,92.82
+ ,3405.79
+ ,39.23
+ ,108.36
+ ,92.19
+ ,3399.04
+ ,39.42
+ ,111.67
+ ,95.78
+ ,3453.71
+ ,40.05
+ ,113.6
+ ,97.3
+ ,3413.07
+ ,39.7
+ ,116.85
+ ,99.3
+ ,3379.11
+ ,39.17
+ ,116.7
+ ,98.99
+ ,3413.89
+ ,39.42
+ ,115.64
+ ,98.14
+ ,3431.55
+ ,39.24
+ ,115.27
+ ,96.96
+ ,3462.83
+ ,39.6
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+ ,3433.21
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+ ,114.26
+ ,96.25
+ ,3432.56
+ ,39.38
+ ,113.91
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+ ,3461.65
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+ ,114.54
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+ ,3513.28
+ ,40.45
+ ,112.6
+ ,94.83
+ ,3480.58
+ ,40.45
+ ,113.78
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+ ,95.36
+ ,3480.49
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+ ,3450.27
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+ ,3435.62
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+ ,112.73
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+ ,3456.71
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+ ,112.38
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+ ,3232.46
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+ ,3280.19
+ ,37.35
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+ ,3207.12
+ ,36.12
+ ,114.4
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+ ,3081.74
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+ ,94.36
+ ,3074.68
+ ,34.83
+ ,112.08
+ ,93.14
+ ,3101.53
+ ,35.39
+ ,111.58
+ ,92.58
+ ,3193.89
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+ ,36.66
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+ ,3235.4
+ ,36.54
+ ,113.3
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+ ,3176.97
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+ ,3179.9
+ ,36.01
+ ,111.69
+ ,93.29
+ ,3180.81
+ ,36.03
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+ ,91.88
+ ,3135.18
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+ ,3157.25
+ ,36.04
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+ ,91.36
+ ,3175.41
+ ,35.96
+ ,105.87
+ ,87.44
+ ,3156.8
+ ,35.94
+ ,105.81
+ ,88.73
+ ,3168.79
+ ,36.06
+ ,104.62
+ ,87.75
+ ,3229.36
+ ,36.52
+ ,106.05
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+ ,3267.75
+ ,36.91
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+ ,90.02
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+ ,90.13
+ ,3240.2
+ ,35.98
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+ ,3196.65
+ ,35.5
+ ,104.61
+ ,88.77
+ ,3051.68
+ ,34.04
+ ,103.05
+ ,88.21
+ ,3063.12
+ ,34.2
+ ,103.27
+ ,87.98
+ ,3012.71
+ ,33.63
+ ,106.32
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+ ,3021.64
+ ,33.84
+ ,106.71
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+ ,3090.9
+ ,34.41
+ ,107.55
+ ,92.44
+ ,3114.22
+ ,34.84
+ ,105.54
+ ,90.19
+ ,3126.52
+ ,35.2
+ ,103.58
+ ,89.34
+ ,3117.92
+ ,35.3
+ ,103.13
+ ,88.52
+ ,3066.19
+ ,34.8
+ ,101.66
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+ ,3087.62
+ ,35.43
+ ,102.69
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+ ,34.88
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+ ,3030.04
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+ ,100.68
+ ,86
+ ,3046.91
+ ,34.83
+ ,97.92
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+ ,3042.76
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+ ,3051.69
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+ ,3071.16
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+ ,3058.44
+ ,34.8
+ ,100.03
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+ ,2986.1
+ ,34.32
+ ,99.72
+ ,86.88
+ ,2954.49
+ ,33.96
+ ,100.65
+ ,87.68
+ ,2950.47
+ ,34
+ ,97.35
+ ,83.35
+ ,3017.01
+ ,34.77
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+ ,84.56
+ ,3015.58
+ ,34.53
+ ,97.62
+ ,85.02
+ ,3084.7
+ ,35.2
+ ,92
+ ,78.39
+ ,3042.97
+ ,35.06
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+ ,80.41
+ ,3047.94
+ ,35.18
+ ,93.19
+ ,79.43
+ ,3038.25
+ ,35
+ ,91.36
+ ,79.3
+ ,3003.27
+ ,34.49
+ ,91.34
+ ,80.05
+ ,3084.09
+ ,35.15
+ ,91.39
+ ,80.11
+ ,3027.15
+ ,34.59
+ ,89.23
+ ,78.43
+ ,3008
+ ,34.65
+ ,92.66
+ ,80.75
+ ,3011.99
+ ,34.59
+ ,95.76
+ ,84.31
+ ,3048.67
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+ ,83.45
+ ,3039.27
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+ ,3057.99
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+ ,97.81
+ ,84.3
+ ,3130.17
+ ,35.15
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+ ,82.59
+ ,3118.65
+ ,34.48
+ ,97.16
+ ,83.08
+ ,3124.8
+ ,34.91
+ ,96.25
+ ,81.5
+ ,3214.22
+ ,35.95
+ ,101.86
+ ,86.44
+ ,3161.97
+ ,35.52
+ ,99.95
+ ,84.46
+ ,3223.36
+ ,36.16
+ ,99.17
+ ,83.92
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+ ,100.92
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+ ,3266.27
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+ ,3229.32
+ ,36.51
+ ,97.83
+ ,82.46
+ ,3233.46
+ ,36.23
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+ ,83.28
+ ,3169.32
+ ,35.91
+ ,101.63
+ ,86.57
+ ,3098.37
+ ,35.56
+ ,103.15
+ ,87.7
+ ,3188.58
+ ,36.45
+ ,106.88
+ ,90.72
+ ,3174.02
+ ,36.34
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+ ,91.06
+ ,3240.29
+ ,37.32
+ ,106.98
+ ,91.32
+ ,3292.51
+ ,37.47
+ ,106.75
+ ,90.75
+ ,3205.28
+ ,36.98
+ ,106.84
+ ,90.83
+ ,3189.09
+ ,36.42
+ ,106.16
+ ,90.28
+ ,3269.79
+ ,37.04
+ ,108.22
+ ,91.52
+ ,3237.69
+ ,37.15
+ ,109.28
+ ,93.22
+ ,3217.6
+ ,37.13
+ ,106.92
+ ,91.56
+ ,3319.81
+ ,38.21
+ ,107.14
+ ,91.32
+ ,3313.47
+ ,37.91
+ ,106.86
+ ,92.61
+ ,3406.78
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+ ,109.34
+ ,92.94
+ ,3462.91
+ ,39.12
+ ,111.03
+ ,93.32
+ ,3423.81
+ ,38.05
+ ,110.33
+ ,94.28
+ ,3381.12
+ ,37.83
+ ,111.43
+ ,95.5
+ ,3430.15
+ ,38.02
+ ,112.06
+ ,95.65
+ ,3469.59
+ ,38.43
+ ,112.24
+ ,96.19
+ ,3501.98
+ ,40.94
+ ,112.7
+ ,96.43
+ ,3476.18
+ ,40.75
+ ,113.23
+ ,97.11
+ ,3472.46
+ ,41.06
+ ,113.44
+ ,98.08
+ ,3530
+ ,41.69
+ ,111.25
+ ,96.27
+ ,3530.83
+ ,41.73
+ ,113.47
+ ,98.55
+ ,3577.88
+ ,42.34
+ ,115.98
+ ,102.56
+ ,3594.83
+ ,42.54
+ ,118.33
+ ,105.28
+ ,3580.21
+ ,42.5
+ ,119.72
+ ,105.84
+ ,3564.51
+ ,42.78
+ ,119.42
+ ,104.84
+ ,3550.16
+ ,42.65
+ ,119.53
+ ,104.8
+ ,3490.06
+ ,42
+ ,119.64
+ ,104.78
+ ,3487.48
+ ,42.3
+ ,119.17
+ ,104.02
+ ,3478.36
+ ,42.02
+ ,118.45
+ ,103.75
+ ,3392.33
+ ,41.52
+ ,118.71
+ ,103.1
+ ,3362
+ ,41.77
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+ ,3487.54
+ ,42.43
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+ ,104.08
+ ,3501.17
+ ,42.43
+ ,118.12
+ ,103
+ ,3499.73
+ ,42.48
+ ,118.14
+ ,103.22
+ ,3452.45
+ ,42.01
+ ,118.71
+ ,104.77
+ ,3453.99
+ ,41.99
+ ,118.44
+ ,103.61
+ ,3441.45
+ ,42.01
+ ,120.48
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+ ,3467.03
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+ ,3447.31
+ ,41.84
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+ ,103.83
+ ,3447.37
+ ,41.79
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+ ,102.62
+ ,3465.24
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+ ,100.95
+ ,3472.54
+ ,41.87
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+ ,3439.62
+ ,41.66
+ ,121.72
+ ,102.19
+ ,3393.25
+ ,41.19
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+ ,3390.35
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+ ,102.08
+ ,3375.64
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+ ,3384.55
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+ ,3373.14
+ ,40.67
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+ ,3424.71
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+ ,3405.27
+ ,40.89
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+ ,3427.92
+ ,40.97
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+ ,3376.66
+ ,40.87
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+ ,106.74
+ ,3367.46
+ ,40.56
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+ ,3298.55
+ ,40.47
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+ ,3265.64
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+ ,106.93
+ ,3318.76
+ ,40.23
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+ ,106.39
+ ,3360.7
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+ ,3312.48
+ ,40.3
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+ ,107.86
+ ,3322.65
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+ ,107.22
+ ,3338.42
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+ ,3328.94
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+ ,106.85
+ ,3264.93
+ ,40.05
+ ,125.05
+ ,106.62
+ ,3269.99
+ ,40.14
+ ,125.05
+ ,107.13
+ ,3225
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+ ,3204.83
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+ ,104.94
+ ,3210.79
+ ,40.49
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+ ,107.17
+ ,3144.64
+ ,39.99
+ ,123.59
+ ,106.85
+ ,3137.36
+ ,39.94
+ ,123.63
+ ,106.58
+ ,3144.91
+ ,39.97
+ ,125.96
+ ,108.94
+ ,3193.65
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+ ,3159.81
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+ ,3127.56
+ ,39.07
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+ ,3071.08
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+ ,3103.11
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+ ,3102.09
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+ ,106
+ ,3069.3
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+ ,3030.47
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+ ,105.14
+ ,3055.39
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+ ,2974.2
+ ,36.45
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+ ,2972.3
+ ,37.02
+ ,119.04
+ ,102.2
+ ,2998.73
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+ ,101.25
+ ,2976.17
+ ,37.67
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+ ,100.92
+ ,3078.72
+ ,38.55
+ ,117.41
+ ,99.64
+ ,3089.59
+ ,38.16
+ ,117.66
+ ,99.02
+ ,3172.35
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+ ,99.72
+ ,3095.49
+ ,38.05
+ ,117.83
+ ,98.97
+ ,3175.98
+ ,38.77
+ ,116.05
+ ,98.72
+ ,3179.63
+ ,38.76
+ ,116.46
+ ,97.19
+ ,3201.28
+ ,38.86
+ ,114.94
+ ,97.69
+ ,3164.95
+ ,38.49
+ ,114.66
+ ,97.83
+ ,3129.95
+ ,38.29)
+ ,dim=c(4
+ ,259)
+ ,dimnames=list(c('Brent'
+ ,'WTI'
+ ,'Cac40'
+ ,'Total')
+ ,1:259))
> y <- array(NA,dim=c(4,259),dimnames=list(c('Brent','WTI','Cac40','Total'),1:259))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '4'
> par3 <- 'Linear Trend'
> par2 <- 'Do not include Seasonal Dummies'
> par1 <- '4'
> #'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, 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
Total Brent WTI Cac40 t
1 38.58 110.92 89.06 3566.59 1
2 38.48 111.19 88.96 3557.28 2
3 38.56 111.19 88.95 3568.88 3
4 38.25 110.42 87.66 3515.19 4
5 37.97 109.69 86.62 3502.13 5
6 38.42 110.03 87.03 3500.94 6
7 38.60 110.77 87.83 3528.80 7
8 38.30 111.34 88.14 3498.22 8
9 38.22 111.34 88.28 3477.36 9
10 38.22 110.41 87.06 3462.06 10
11 38.22 111.05 87.69 3439.58 11
12 36.98 110.44 87.34 3341.52 12
13 37.43 111.56 88.94 3382.40 13
14 37.52 109.48 87.59 3400.02 14
15 37.98 109.18 87.12 3430.60 15
16 37.83 107.69 85.78 3411.65 16
17 38.00 108.70 86.70 3423.57 17
18 37.70 107.19 85.69 3407.68 18
19 37.88 107.84 85.92 3409.59 19
20 39.02 108.33 86.59 3478.66 20
21 38.84 109.40 86.06 3448.50 21
22 39.44 107.08 85.03 3492.46 22
23 39.12 106.75 84.69 3475.40 23
24 38.82 111.02 88.25 3429.27 24
25 38.99 107.81 85.79 3459.44 25
26 38.39 105.44 84.78 3408.89 26
27 38.71 105.75 84.83 3435.09 27
28 38.43 108.15 86.89 3411.53 28
29 38.67 108.47 86.12 3426.49 29
30 38.45 108.96 85.71 3406.50 30
31 39.34 109.29 85.28 3483.25 31
32 39.60 109.23 85.95 3504.56 32
33 39.84 109.61 86.17 3535.18 33
34 40.00 108.56 86.19 3527.50 34
35 39.55 107.77 85.77 3500.94 35
36 38.50 108.25 86.69 3420.28 36
37 38.13 109.72 89.23 3389.08 37
38 38.75 109.57 89.91 3413.72 38
39 38.20 110.14 90.51 3365.87 39
40 38.39 112.47 92.48 3382.78 40
41 38.29 113.17 92.42 3406.53 41
42 38.73 113.70 92.92 3457.04 42
43 38.33 114.47 92.19 3401.20 43
44 38.73 113.05 91.53 3406.02 44
45 39.06 114.56 91.62 3414.23 45
46 39.28 115.72 92.47 3434.98 46
47 38.60 114.51 91.27 3354.82 47
48 39.68 114.42 91.88 3439.32 48
49 39.61 112.06 89.99 3414.84 49
50 40.74 111.59 89.68 3513.81 50
51 40.55 111.90 89.92 3497.22 51
52 40.80 112.25 91.48 3530.72 52
53 40.81 108.07 88.34 3509.92 53
54 41.47 111.30 91.66 3531.82 54
55 41.00 112.23 92.43 3512.69 55
56 41.42 111.88 91.50 3553.69 56
57 41.84 112.14 92.03 3581.58 57
58 40.89 112.47 92.22 3502.09 58
59 41.05 110.11 90.31 3543.79 59
60 41.20 109.96 90.86 3537.30 60
61 40.45 109.86 92.10 3506.05 61
62 40.55 111.41 92.90 3519.05 62
63 40.50 111.56 93.06 3509.88 63
64 39.23 110.56 92.82 3405.79 64
65 39.42 108.36 92.19 3399.04 65
66 40.05 111.67 95.78 3453.71 66
67 39.70 113.60 97.30 3413.07 67
68 39.17 116.85 99.30 3379.11 68
69 39.42 116.70 98.99 3413.89 69
70 39.24 115.64 98.14 3431.55 70
71 39.60 115.27 96.96 3462.83 71
72 39.38 114.41 96.88 3433.21 72
73 39.38 114.26 96.25 3432.56 73
74 39.80 113.91 96.31 3461.65 74
75 40.45 114.54 96.34 3513.28 75
76 40.45 112.60 94.83 3480.58 76
77 40.38 113.78 95.78 3488.38 77
78 40.25 114.17 95.36 3480.49 78
79 40.03 115.78 96.86 3449.20 79
80 40.00 114.59 96.19 3450.27 80
81 39.76 114.88 96.44 3426.41 81
82 39.96 112.79 94.57 3435.62 82
83 40.00 112.73 95.15 3456.71 83
84 39.90 112.38 96.17 3438.26 84
85 39.76 112.59 95.67 3453.28 85
86 38.90 114.21 96.76 3401.56 86
87 38.92 113.47 96.09 3374.19 87
88 37.34 114.44 95.92 3232.46 88
89 37.99 115.03 97.36 3321.56 89
90 37.60 114.86 96.84 3291.66 90
91 37.45 113.61 96.17 3320.71 91
92 37.35 114.08 96.19 3280.19 92
93 36.12 113.73 96.17 3207.12 93
94 34.83 114.40 95.30 3081.74 94
95 34.83 114.48 94.36 3074.68 95
96 35.39 112.08 93.14 3101.53 96
97 36.05 111.58 92.58 3193.89 97
98 36.66 111.44 93.23 3263.64 98
99 36.54 113.38 93.35 3235.40 99
100 35.87 113.30 93.53 3176.97 100
101 36.01 112.03 93.32 3179.90 101
102 36.03 111.69 93.29 3180.81 102
103 35.63 109.56 91.88 3135.18 103
104 36.04 108.50 91.25 3157.25 104
105 35.96 109.01 91.36 3175.41 105
106 35.94 105.87 87.44 3156.80 106
107 36.06 105.81 88.73 3168.79 107
108 36.52 104.62 87.75 3229.36 108
109 36.91 106.05 89.61 3267.75 109
110 37.05 106.44 90.02 3271.20 110
111 35.98 106.55 90.13 3240.20 111
112 35.50 105.33 89.16 3196.65 112
113 34.04 104.61 88.77 3051.68 113
114 34.20 103.05 88.21 3063.12 114
115 33.63 103.27 87.98 3012.71 115
116 33.84 106.32 91.25 3021.64 116
117 34.41 106.71 91.59 3090.90 117
118 34.84 107.55 92.44 3114.22 118
119 35.20 105.54 90.19 3126.52 119
120 35.30 103.58 89.34 3117.92 120
121 34.80 103.13 88.52 3066.19 121
122 35.43 101.66 87.50 3087.62 122
123 34.88 102.69 87.07 3032.45 123
124 34.81 100.66 85.66 3030.04 124
125 34.83 100.68 86.00 3046.91 125
126 34.70 97.92 84.33 3042.76 126
127 34.59 100.28 85.17 3051.69 127
128 34.77 98.30 84.36 3071.16 128
129 34.80 97.83 84.06 3058.44 129
130 34.32 100.03 86.92 2986.10 130
131 33.96 99.72 86.88 2954.49 131
132 34.00 100.65 87.68 2950.47 132
133 34.77 97.35 83.35 3017.01 133
134 34.53 97.38 84.56 3015.58 134
135 35.20 97.62 85.02 3084.70 135
136 35.06 92.00 78.39 3042.97 136
137 35.18 93.78 80.41 3047.94 137
138 35.00 93.19 79.43 3038.25 138
139 34.49 91.36 79.30 3003.27 139
140 35.15 91.34 80.05 3084.09 140
141 34.59 91.39 80.11 3027.15 141
142 34.65 89.23 78.43 3008.00 142
143 34.59 92.66 80.75 3011.99 143
144 34.92 95.76 84.31 3048.67 144
145 34.37 95.73 83.45 3039.27 145
146 34.47 98.66 85.11 3057.99 146
147 35.13 97.53 84.05 3129.77 147
148 35.15 97.81 84.30 3130.17 148
149 34.48 96.56 82.59 3118.65 149
150 34.91 97.16 83.08 3124.80 150
151 35.95 96.25 81.50 3214.22 151
152 35.52 101.86 86.44 3161.97 152
153 36.16 99.95 84.46 3223.36 153
154 36.15 99.17 83.92 3226.33 154
155 36.07 100.92 85.39 3212.80 155
156 36.50 98.65 84.40 3266.27 156
157 36.51 98.97 84.42 3229.32 157
158 36.23 97.83 82.46 3233.46 158
159 35.91 98.75 83.28 3169.32 159
160 35.56 101.63 86.57 3098.37 160
161 36.45 103.15 87.70 3188.58 161
162 36.34 106.88 90.72 3174.02 162
163 37.32 107.28 91.06 3240.29 163
164 37.47 106.98 91.32 3292.51 164
165 36.98 106.75 90.75 3205.28 165
166 36.42 106.84 90.83 3189.09 166
167 37.04 106.16 90.28 3269.79 167
168 37.15 108.22 91.52 3237.69 168
169 37.13 109.28 93.22 3217.60 169
170 38.21 106.92 91.56 3319.81 170
171 37.91 107.14 91.32 3313.47 171
172 38.40 106.86 92.61 3406.78 172
173 39.12 109.34 92.94 3462.91 173
174 38.05 111.03 93.32 3423.81 174
175 37.83 110.33 94.28 3381.12 175
176 38.02 111.43 95.50 3430.15 176
177 38.43 112.06 95.65 3469.59 177
178 40.94 112.24 96.19 3501.98 178
179 40.75 112.70 96.43 3476.18 179
180 41.06 113.23 97.11 3472.46 180
181 41.69 113.44 98.08 3530.00 181
182 41.73 111.25 96.27 3530.83 182
183 42.34 113.47 98.55 3577.88 183
184 42.54 115.98 102.56 3594.83 184
185 42.50 118.33 105.28 3580.21 185
186 42.78 119.72 105.84 3564.51 186
187 42.65 119.42 104.84 3550.16 187
188 42.00 119.53 104.80 3490.06 188
189 42.30 119.64 104.78 3487.48 189
190 42.02 119.17 104.02 3478.36 190
191 41.52 118.45 103.75 3392.33 191
192 41.77 118.71 103.10 3362.00 192
193 42.43 118.81 103.86 3487.54 193
194 42.43 118.85 104.08 3501.17 194
195 42.48 118.12 103.00 3499.73 195
196 42.01 118.14 103.22 3452.45 196
197 41.99 118.71 104.77 3453.99 197
198 42.01 118.44 103.61 3441.45 198
199 42.05 120.48 102.83 3467.03 199
200 41.84 121.39 102.86 3447.31 200
201 41.79 121.52 103.83 3447.37 201
202 41.82 119.79 102.62 3465.24 202
203 41.87 119.39 100.95 3472.54 203
204 41.66 121.97 102.34 3439.62 204
205 41.19 121.72 102.19 3393.25 205
206 40.99 123.30 103.25 3390.35 206
207 41.15 122.69 102.08 3375.64 207
208 40.95 124.98 103.98 3384.55 208
209 40.67 125.37 104.92 3373.14 209
210 41.10 123.42 103.44 3424.71 210
211 40.88 122.92 102.97 3410.00 211
212 40.93 122.56 103.30 3411.54 212
213 40.89 124.31 105.56 3405.27 213
214 40.97 125.20 106.89 3427.92 214
215 40.87 125.73 107.05 3376.66 215
216 40.56 124.94 106.74 3367.46 216
217 40.47 125.11 106.80 3298.55 217
218 40.01 123.32 105.66 3265.64 218
219 40.23 124.07 106.93 3318.76 219
220 40.45 124.05 106.39 3360.70 220
221 40.30 125.28 108.19 3312.48 221
222 40.38 125.95 107.86 3322.65 222
223 39.95 126.06 107.22 3338.42 223
224 39.74 122.73 105.50 3321.50 224
225 40.37 124.47 105.66 3328.94 225
226 40.05 125.61 106.85 3264.93 226
227 40.14 125.05 106.62 3269.99 227
228 39.42 125.05 107.13 3225.00 228
229 38.97 125.94 107.42 3196.49 229
230 39.06 125.57 106.89 3199.98 230
231 39.86 124.25 106.14 3204.83 231
232 40.49 122.19 104.94 3210.79 232
233 39.99 124.20 107.17 3144.64 233
234 39.94 123.59 106.85 3137.36 234
235 39.97 123.63 106.58 3144.91 235
236 40.21 125.96 108.94 3193.65 236
237 40.39 122.95 107.03 3245.40 237
238 39.95 121.77 106.61 3222.30 238
239 39.46 123.38 107.97 3159.81 239
240 39.07 125.28 109.59 3127.56 240
241 38.64 125.31 109.70 3071.08 241
242 38.96 124.12 108.58 3103.11 242
243 38.57 122.64 105.96 3102.09 243
244 37.84 121.50 106.00 3069.30 244
245 37.36 120.03 105.03 3030.47 245
246 37.08 120.73 105.14 3055.39 246
247 36.45 119.76 104.28 2974.20 247
248 37.02 120.06 102.58 2972.30 248
249 37.68 119.04 102.20 2998.73 249
250 37.67 117.49 101.25 2976.17 250
251 38.55 117.23 100.92 3078.72 251
252 38.16 117.41 99.64 3089.59 252
253 38.96 117.66 99.02 3172.35 253
254 38.05 118.66 99.72 3095.49 254
255 38.77 117.83 98.97 3175.98 255
256 38.76 116.05 98.72 3179.63 256
257 38.86 116.46 97.19 3201.28 257
258 38.49 114.94 97.69 3164.95 258
259 38.29 114.66 97.83 3129.95 259
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Brent WTI Cac40 t
-9.548606 0.027639 0.069267 0.011236 0.009171
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-2.35113 -0.40125 0.01992 0.42903 1.41508
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -9.5486062 0.8916728 -10.709 < 2e-16 ***
Brent 0.0276389 0.0197875 1.397 0.16370
WTI 0.0692672 0.0246720 2.808 0.00538 **
Cac40 0.0112359 0.0003284 34.213 < 2e-16 ***
t 0.0091711 0.0011498 7.977 5.16e-14 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.6513 on 254 degrees of freedom
Multiple R-squared: 0.9229, Adjusted R-squared: 0.9217
F-statistic: 759.9 on 4 and 254 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,] 9.684965e-03 1.936993e-02 0.9903150353
[2,] 4.375646e-03 8.751292e-03 0.9956243538
[3,] 8.266839e-04 1.653368e-03 0.9991733161
[4,] 1.717665e-04 3.435331e-04 0.9998282335
[5,] 1.967199e-04 3.934399e-04 0.9998032801
[6,] 6.138337e-05 1.227667e-04 0.9999386166
[7,] 1.399048e-05 2.798095e-05 0.9999860095
[8,] 2.831025e-06 5.662050e-06 0.9999971690
[9,] 5.679423e-07 1.135885e-06 0.9999994321
[10,] 1.065106e-07 2.130213e-07 0.9999998935
[11,] 2.534617e-08 5.069234e-08 0.9999999747
[12,] 4.948903e-09 9.897805e-09 0.9999999951
[13,] 4.664183e-09 9.328366e-09 0.9999999953
[14,] 9.122041e-10 1.824408e-09 0.9999999991
[15,] 8.456274e-10 1.691255e-09 0.9999999992
[16,] 1.643975e-10 3.287950e-10 0.9999999998
[17,] 3.823093e-11 7.646187e-11 1.0000000000
[18,] 1.102199e-11 2.204398e-11 1.0000000000
[19,] 2.367494e-12 4.734987e-12 1.0000000000
[20,] 4.781785e-13 9.563570e-13 1.0000000000
[21,] 3.300680e-13 6.601359e-13 1.0000000000
[22,] 1.860884e-12 3.721768e-12 1.0000000000
[23,] 2.636368e-11 5.272736e-11 1.0000000000
[24,] 6.754349e-11 1.350870e-10 0.9999999999
[25,] 3.829715e-11 7.659429e-11 1.0000000000
[26,] 2.920045e-11 5.840090e-11 1.0000000000
[27,] 8.267412e-12 1.653482e-11 1.0000000000
[28,] 4.524005e-12 9.048010e-12 1.0000000000
[29,] 1.247118e-11 2.494236e-11 1.0000000000
[30,] 5.841049e-12 1.168210e-11 1.0000000000
[31,] 3.225741e-12 6.451483e-12 1.0000000000
[32,] 9.939927e-13 1.987985e-12 1.0000000000
[33,] 3.177386e-13 6.354772e-13 1.0000000000
[34,] 2.713153e-13 5.426306e-13 1.0000000000
[35,] 2.049774e-13 4.099547e-13 1.0000000000
[36,] 1.106889e-13 2.213777e-13 1.0000000000
[37,] 3.450834e-14 6.901667e-14 1.0000000000
[38,] 1.678926e-14 3.357851e-14 1.0000000000
[39,] 7.149391e-15 1.429878e-14 1.0000000000
[40,] 2.507619e-15 5.015238e-15 1.0000000000
[41,] 4.175007e-15 8.350014e-15 1.0000000000
[42,] 6.851028e-15 1.370206e-14 1.0000000000
[43,] 1.661512e-14 3.323025e-14 1.0000000000
[44,] 1.720088e-14 3.440175e-14 1.0000000000
[45,] 1.497456e-14 2.994913e-14 1.0000000000
[46,] 1.701617e-14 3.403234e-14 1.0000000000
[47,] 1.151683e-12 2.303366e-12 1.0000000000
[48,] 1.923140e-12 3.846280e-12 1.0000000000
[49,] 1.556411e-12 3.112823e-12 1.0000000000
[50,] 1.597997e-12 3.195993e-12 1.0000000000
[51,] 1.355563e-12 2.711125e-12 1.0000000000
[52,] 2.261920e-12 4.523840e-12 1.0000000000
[53,] 2.260361e-12 4.520723e-12 1.0000000000
[54,] 3.706406e-12 7.412812e-12 1.0000000000
[55,] 6.529574e-12 1.305915e-11 1.0000000000
[56,] 8.867217e-12 1.773443e-11 1.0000000000
[57,] 1.285968e-11 2.571936e-11 1.0000000000
[58,] 8.695485e-12 1.739097e-11 1.0000000000
[59,] 4.643047e-12 9.286095e-12 1.0000000000
[60,] 2.881435e-12 5.762869e-12 1.0000000000
[61,] 1.265125e-12 2.530250e-12 1.0000000000
[62,] 6.954306e-13 1.390861e-12 1.0000000000
[63,] 3.044221e-12 6.088442e-12 1.0000000000
[64,] 2.717268e-11 5.434536e-11 1.0000000000
[65,] 6.478485e-11 1.295697e-10 0.9999999999
[66,] 2.245085e-10 4.490170e-10 0.9999999998
[67,] 4.428866e-10 8.857731e-10 0.9999999996
[68,] 9.128479e-10 1.825696e-09 0.9999999991
[69,] 1.062439e-09 2.124878e-09 0.9999999989
[70,] 1.506437e-09 3.012874e-09 0.9999999985
[71,] 3.853665e-09 7.707329e-09 0.9999999961
[72,] 4.364414e-09 8.728828e-09 0.9999999956
[73,] 6.555162e-09 1.311032e-08 0.9999999934
[74,] 9.116282e-09 1.823256e-08 0.9999999909
[75,] 2.214541e-08 4.429081e-08 0.9999999779
[76,] 6.582815e-08 1.316563e-07 0.9999999342
[77,] 8.262143e-08 1.652429e-07 0.9999999174
[78,] 3.344086e-07 6.688172e-07 0.9999996656
[79,] 2.164999e-06 4.329998e-06 0.9999978350
[80,] 4.575088e-06 9.150176e-06 0.9999954249
[81,] 7.107014e-06 1.421403e-05 0.9999928930
[82,] 1.752334e-05 3.504668e-05 0.9999824767
[83,] 4.169963e-05 8.339926e-05 0.9999583004
[84,] 3.993548e-04 7.987096e-04 0.9996006452
[85,] 7.053635e-04 1.410727e-03 0.9992946365
[86,] 1.507371e-03 3.014743e-03 0.9984926287
[87,] 1.403348e-03 2.806695e-03 0.9985966525
[88,] 1.194600e-03 2.389200e-03 0.9988054000
[89,] 9.488593e-04 1.897719e-03 0.9990511407
[90,] 1.768773e-03 3.537546e-03 0.9982312269
[91,] 5.577305e-03 1.115461e-02 0.9944226948
[92,] 8.598003e-03 1.719601e-02 0.9914019971
[93,] 9.055388e-03 1.811078e-02 0.9909446123
[94,] 8.567730e-03 1.713546e-02 0.9914322701
[95,] 7.954095e-03 1.590819e-02 0.9920459051
[96,] 6.412404e-03 1.282481e-02 0.9935875956
[97,] 5.291738e-03 1.058348e-02 0.9947082618
[98,] 5.038049e-03 1.007610e-02 0.9949619513
[99,] 5.207616e-03 1.041523e-02 0.9947923841
[100,] 4.855015e-03 9.710030e-03 0.9951449851
[101,] 6.290717e-03 1.258143e-02 0.9937092835
[102,] 8.603249e-03 1.720650e-02 0.9913967510
[103,] 1.010898e-02 2.021796e-02 0.9898910204
[104,] 2.084103e-02 4.168206e-02 0.9791589677
[105,] 2.744367e-02 5.488734e-02 0.9725563302
[106,] 2.309554e-02 4.619109e-02 0.9769044565
[107,] 1.948647e-02 3.897294e-02 0.9805135312
[108,] 1.672051e-02 3.344103e-02 0.9832794862
[109,] 1.587647e-02 3.175293e-02 0.9841235348
[110,] 1.903866e-02 3.807733e-02 0.9809613350
[111,] 2.250623e-02 4.501247e-02 0.9774937662
[112,] 2.031240e-02 4.062479e-02 0.9796876048
[113,] 1.728488e-02 3.456977e-02 0.9827151169
[114,] 1.545017e-02 3.090033e-02 0.9845498330
[115,] 1.577027e-02 3.154054e-02 0.9842297286
[116,] 1.821711e-02 3.643422e-02 0.9817828876
[117,] 2.057250e-02 4.114500e-02 0.9794274993
[118,] 1.856784e-02 3.713569e-02 0.9814321572
[119,] 1.650757e-02 3.301513e-02 0.9834924328
[120,] 1.315571e-02 2.631142e-02 0.9868442916
[121,] 1.040367e-02 2.080733e-02 0.9895963330
[122,] 8.406014e-03 1.681203e-02 0.9915939862
[123,] 8.883280e-03 1.776656e-02 0.9911167198
[124,] 9.802923e-03 1.960585e-02 0.9901970774
[125,] 1.074904e-02 2.149808e-02 0.9892509622
[126,] 1.103550e-02 2.207100e-02 0.9889645012
[127,] 9.092645e-03 1.818529e-02 0.9909073550
[128,] 7.227830e-03 1.445566e-02 0.9927721703
[129,] 1.038993e-02 2.077985e-02 0.9896100747
[130,] 1.330026e-02 2.660053e-02 0.9866997351
[131,] 1.851079e-02 3.702159e-02 0.9814892064
[132,] 2.151853e-02 4.303706e-02 0.9784814690
[133,] 2.165708e-02 4.331417e-02 0.9783429158
[134,] 2.142946e-02 4.285892e-02 0.9785705416
[135,] 3.144193e-02 6.288387e-02 0.9685580671
[136,] 3.806672e-02 7.613344e-02 0.9619332814
[137,] 3.581708e-02 7.163417e-02 0.9641829157
[138,] 3.477324e-02 6.954648e-02 0.9652267591
[139,] 3.667990e-02 7.335979e-02 0.9633201036
[140,] 5.180685e-02 1.036137e-01 0.9481931505
[141,] 6.709389e-02 1.341878e-01 0.9329061076
[142,] 1.147897e-01 2.295794e-01 0.8852103221
[143,] 1.373595e-01 2.747191e-01 0.8626404617
[144,] 1.776506e-01 3.553012e-01 0.8223493879
[145,] 1.903802e-01 3.807605e-01 0.8096197713
[146,] 2.103228e-01 4.206457e-01 0.7896771681
[147,] 2.256474e-01 4.512948e-01 0.7743525895
[148,] 2.288180e-01 4.576360e-01 0.7711820134
[149,] 2.521391e-01 5.042783e-01 0.7478608720
[150,] 2.417646e-01 4.835293e-01 0.7582353678
[151,] 2.369378e-01 4.738757e-01 0.7630621544
[152,] 2.293764e-01 4.587528e-01 0.7706236178
[153,] 2.258965e-01 4.517930e-01 0.7741034817
[154,] 2.124615e-01 4.249230e-01 0.7875385063
[155,] 1.902184e-01 3.804368e-01 0.8097816152
[156,] 1.761069e-01 3.522138e-01 0.8238931070
[157,] 1.640608e-01 3.281216e-01 0.8359392128
[158,] 1.560477e-01 3.120954e-01 0.8439522859
[159,] 1.386792e-01 2.773584e-01 0.8613207839
[160,] 1.288690e-01 2.577380e-01 0.8711309774
[161,] 1.154491e-01 2.308983e-01 0.8845508619
[162,] 1.034221e-01 2.068441e-01 0.8965779367
[163,] 9.583692e-02 1.916738e-01 0.9041630842
[164,] 8.778002e-02 1.755600e-01 0.9122199800
[165,] 1.103698e-01 2.207397e-01 0.8896301711
[166,] 1.199448e-01 2.398896e-01 0.8800552170
[167,] 2.026507e-01 4.053014e-01 0.7973493040
[168,] 3.370156e-01 6.740313e-01 0.6629843577
[169,] 7.811635e-01 4.376730e-01 0.2188364932
[170,] 9.966310e-01 6.738087e-03 0.0033690435
[171,] 9.974729e-01 5.054207e-03 0.0025271035
[172,] 9.984616e-01 3.076818e-03 0.0015384090
[173,] 9.989091e-01 2.181870e-03 0.0010909348
[174,] 9.990794e-01 1.841197e-03 0.0009205987
[175,] 9.992190e-01 1.561943e-03 0.0007809717
[176,] 9.991881e-01 1.623710e-03 0.0008118548
[177,] 9.992165e-01 1.566903e-03 0.0007834513
[178,] 9.993271e-01 1.345804e-03 0.0006729019
[179,] 9.991838e-01 1.632418e-03 0.0008162091
[180,] 9.990364e-01 1.927210e-03 0.0009636049
[181,] 9.990553e-01 1.889429e-03 0.0009447144
[182,] 9.989899e-01 2.020104e-03 0.0010100520
[183,] 9.989313e-01 2.137356e-03 0.0010686778
[184,] 9.990585e-01 1.882916e-03 0.0009414579
[185,] 9.996006e-01 7.987694e-04 0.0003993847
[186,] 9.995281e-01 9.438593e-04 0.0004719296
[187,] 9.993777e-01 1.244513e-03 0.0006222565
[188,] 9.992377e-01 1.524630e-03 0.0007623150
[189,] 9.990624e-01 1.875277e-03 0.0009376387
[190,] 9.987422e-01 2.515697e-03 0.0012578483
[191,] 9.985155e-01 2.969072e-03 0.0014845360
[192,] 9.983196e-01 3.360848e-03 0.0016804239
[193,] 9.981599e-01 3.680155e-03 0.0018400776
[194,] 9.977176e-01 4.564899e-03 0.0022824494
[195,] 9.970198e-01 5.960361e-03 0.0029801803
[196,] 9.966131e-01 6.773705e-03 0.0033868525
[197,] 9.964449e-01 7.110287e-03 0.0035551437
[198,] 9.962359e-01 7.528236e-03 0.0037641182
[199,] 9.951056e-01 9.788898e-03 0.0048944488
[200,] 9.959711e-01 8.057841e-03 0.0040289204
[201,] 9.947540e-01 1.049200e-02 0.0052460010
[202,] 9.925774e-01 1.484514e-02 0.0074225696
[203,] 9.898210e-01 2.035804e-02 0.0101790175
[204,] 9.860528e-01 2.789432e-02 0.0139471581
[205,] 9.812935e-01 3.741302e-02 0.0187065101
[206,] 9.746271e-01 5.074587e-02 0.0253729344
[207,] 9.690502e-01 6.189959e-02 0.0309497933
[208,] 9.588066e-01 8.238680e-02 0.0411934005
[209,] 9.480174e-01 1.039652e-01 0.0519826220
[210,] 9.378339e-01 1.243322e-01 0.0621660800
[211,] 9.258011e-01 1.483978e-01 0.0741988753
[212,] 9.057126e-01 1.885748e-01 0.0942873985
[213,] 8.867228e-01 2.265543e-01 0.1132771544
[214,] 8.624501e-01 2.750997e-01 0.1375498574
[215,] 8.357542e-01 3.284915e-01 0.1642457604
[216,] 8.702946e-01 2.594107e-01 0.1297053501
[217,] 9.184451e-01 1.631098e-01 0.0815549077
[218,] 9.191972e-01 1.616056e-01 0.0808028046
[219,] 9.072374e-01 1.855253e-01 0.0927626307
[220,] 8.966345e-01 2.067310e-01 0.1033654951
[221,] 9.217771e-01 1.564458e-01 0.0782228800
[222,] 9.676636e-01 6.467286e-02 0.0323364308
[223,] 9.968868e-01 6.226488e-03 0.0031132442
[224,] 9.989267e-01 2.146618e-03 0.0010733090
[225,] 9.987289e-01 2.542226e-03 0.0012711129
[226,] 9.981284e-01 3.743192e-03 0.0018715958
[227,] 9.974015e-01 5.196945e-03 0.0025984726
[228,] 9.966072e-01 6.785623e-03 0.0033928113
[229,] 9.948992e-01 1.020163e-02 0.0051008172
[230,] 9.912381e-01 1.752385e-02 0.0087619259
[231,] 9.851445e-01 2.971098e-02 0.0148554899
[232,] 9.765812e-01 4.683770e-02 0.0234188500
[233,] 9.640895e-01 7.182100e-02 0.0359104986
[234,] 9.639843e-01 7.203146e-02 0.0360157293
[235,] 9.963095e-01 7.380986e-03 0.0036904932
[236,] 9.981304e-01 3.739237e-03 0.0018696183
[237,] 9.986015e-01 2.796919e-03 0.0013984596
[238,] 9.964209e-01 7.158233e-03 0.0035791163
[239,] 9.911378e-01 1.772437e-02 0.0088621859
[240,] 9.991347e-01 1.730691e-03 0.0008653456
[241,] 9.998198e-01 3.603723e-04 0.0001801862
[242,] 9.993825e-01 1.235091e-03 0.0006175457
[243,] 9.971012e-01 5.797548e-03 0.0028987740
[244,] 9.957955e-01 8.409030e-03 0.0042045151
> postscript(file="/var/wessaorg/rcomp/tmp/1cvt51355780000.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/27woe1355780000.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/36dg81355780000.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/43oyu1355780000.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5bwl41355780000.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 = 259
Frequency = 1
1 2 3 4 5 6
-1.188923231 -1.194024225 -1.252838613 -0.858119610 -0.908336001 -0.491933203
7 8 9 10 11 12
-0.710001954 -0.712807433 -0.577295865 -0.304348040 -0.122264233 -0.228543519
13 14 15 16 17 18
-0.388819761 -0.354966978 -0.206883399 -0.019134819 -0.083878525 -0.102817091
19 20 21 22 23 24
0.012654578 0.307470472 0.464310956 0.696678987 0.591863403 0.436393027
25 26 27 28 29 30
0.517354372 0.611620213 0.616038157 0.382560042 0.489791811 0.500082094
31 32 33 34 35 36
0.539222770 0.505864783 0.366910066 0.631665921 0.521846297 0.291967215
37 38 39 40 41 42
0.046786993 0.337808419 0.258958757 0.048934129 -0.342279849 -0.528256504
43 44 45 46 47 48
-0.280733989 0.140901730 0.321515420 0.208261931 0.536321243 0.617954411
49 50 51 52 53 54
1.009980144 1.053259057 1.015298710 0.761995777 1.329560425 1.415083048
55 56 57 58 59 60
1.071814021 1.096064808 1.149627816 1.061313701 0.941135508 1.120934024
61 62 63 64 65 66
0.629756111 0.476264729 0.504897901 0.439530638 0.800645605 0.467055799
67 68 69 70 71 72
0.405880789 0.019918581 -0.104417052 -0.403839021 -0.312506078 -0.179560106
73 74 75 76 77 78
-0.133643671 -0.044148352 -0.002917458 0.513537153 0.248308560 0.216101491
79 80 81 82 83 84
0.190100980 0.218206899 0.211791367 0.486433095 0.241781049 0.278932640
85 86 87 88 89 90
-0.010171617 -0.418500310 -0.033284022 -0.045030858 -0.521368925 -0.543870179
91 92 93 94 95 96
-0.948485312 -0.616754942 -1.023862699 -0.872537115 -0.739482918 -0.339497418
97 98 99 100 101 102
-0.673803487 -0.897830115 -0.771632050 -0.804548766 -0.656993367 -0.644913826
103 104 105 106 107 108
-0.384854864 -0.159065772 -0.473995325 0.064246762 -0.047338692 -0.176293649
109 110 111 112 113 114
-0.395170146 -0.342283688 -1.083802755 -0.982743385 -0.776137467 -0.671940423
115 116 117 118 119 120
-0.674860849 -0.885170744 -1.136867582 -1.060152779 -0.636119422 -0.335612659
121 122 123 124 125 126
-0.194316001 0.297010223 0.359038419 0.460719584 0.257895895 0.357313351
127 128 129 130 131 132
0.014393708 0.077291946 0.274811485 0.339532651 0.336865892 0.331744990
133 134 135 136 137 138
0.736075322 0.418328997 0.264038948 1.198312882 1.064182475 1.068075750
139 140 141 142 143 144
1.001519049 0.692868046 0.757928907 1.199993597 0.830489947 0.406915467
145 146 147 148 149 150
0.013760480 -0.301711562 -0.352737474 -0.371458602 -0.768196928 -0.466992847
151 152 153 154 155 156
-0.306280941 -0.655612793 -0.524613893 -0.518192808 -0.605533638 -0.654171280
157 158 159 160 161 162
-0.248407095 -0.416822473 -0.107552376 0.022971565 -0.230069656 -0.497926833
163 164 165 166 167 168
-0.306304836 -0.761930372 -0.235158026 -0.630449396 -0.869462995 -0.550790488
169 170 171 172 173 174
-0.501284684 -0.398661628 -0.626053769 -1.275258866 -1.286501516 -1.999381756
175 176 177 178 179 180
-1.796043241 -2.281017419 -2.351133451 -0.256613375 -0.195237281 0.085638695
181 182 183 184 185 186
-0.013037211 0.194368888 0.047262850 -0.299491393 -0.437752538 -0.067728350
187 188 189 190 191 192
0.031894096 0.047728667 0.365891176 0.244824548 0.740876758 1.360326931
193 194 195 196 197 198
0.545198889 0.366538680 0.518532277 0.554801131 0.385208421 0.624747550
199 200 201 202 203 204
0.365808211 0.340978879 0.210351368 0.162024150 0.247563153 0.230686742
205 206 207 208 209 210
0.289822350 -0.003857495 0.410153356 -0.094030122 -0.330890410 -0.333083421
211 212 213 214 215 216
-0.350599920 -0.339982401 -0.523616702 -0.824004095 -0.382956328 -0.555449893
217 218 219 220 221 222
0.110787552 0.139826977 -0.354891613 -0.577337603 -0.353392373 -0.392492038
223 224 225 226 227 228
-0.967561885 -0.785444941 -0.307385297 -0.031285304 0.024099425 -0.234896564
229 230 231 232 233 234
-0.418419384 -0.329865575 0.494903228 1.188823284 1.212884228 1.274535478
235 236 237 238 239 240
1.228130252 0.683453948 0.488320650 0.360404125 0.424659887 0.223118448
241 242 243 244 245 246
0.410100229 0.471514155 0.306189431 -0.035820090 0.019115746 -0.577019621
247 248 249 250 251 252
-0.217571575 0.474068122 0.882446493 1.225400641 0.974036345 0.536418527
253 254 255 256 257 258
0.433403569 0.301694771 0.183039990 0.189372107 0.131591569 0.167996852
259
0.350122390
> postscript(file="/var/wessaorg/rcomp/tmp/6fmug1355780000.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 = 259
Frequency = 1
lag(myerror, k = 1) myerror
0 -1.188923231 NA
1 -1.194024225 -1.188923231
2 -1.252838613 -1.194024225
3 -0.858119610 -1.252838613
4 -0.908336001 -0.858119610
5 -0.491933203 -0.908336001
6 -0.710001954 -0.491933203
7 -0.712807433 -0.710001954
8 -0.577295865 -0.712807433
9 -0.304348040 -0.577295865
10 -0.122264233 -0.304348040
11 -0.228543519 -0.122264233
12 -0.388819761 -0.228543519
13 -0.354966978 -0.388819761
14 -0.206883399 -0.354966978
15 -0.019134819 -0.206883399
16 -0.083878525 -0.019134819
17 -0.102817091 -0.083878525
18 0.012654578 -0.102817091
19 0.307470472 0.012654578
20 0.464310956 0.307470472
21 0.696678987 0.464310956
22 0.591863403 0.696678987
23 0.436393027 0.591863403
24 0.517354372 0.436393027
25 0.611620213 0.517354372
26 0.616038157 0.611620213
27 0.382560042 0.616038157
28 0.489791811 0.382560042
29 0.500082094 0.489791811
30 0.539222770 0.500082094
31 0.505864783 0.539222770
32 0.366910066 0.505864783
33 0.631665921 0.366910066
34 0.521846297 0.631665921
35 0.291967215 0.521846297
36 0.046786993 0.291967215
37 0.337808419 0.046786993
38 0.258958757 0.337808419
39 0.048934129 0.258958757
40 -0.342279849 0.048934129
41 -0.528256504 -0.342279849
42 -0.280733989 -0.528256504
43 0.140901730 -0.280733989
44 0.321515420 0.140901730
45 0.208261931 0.321515420
46 0.536321243 0.208261931
47 0.617954411 0.536321243
48 1.009980144 0.617954411
49 1.053259057 1.009980144
50 1.015298710 1.053259057
51 0.761995777 1.015298710
52 1.329560425 0.761995777
53 1.415083048 1.329560425
54 1.071814021 1.415083048
55 1.096064808 1.071814021
56 1.149627816 1.096064808
57 1.061313701 1.149627816
58 0.941135508 1.061313701
59 1.120934024 0.941135508
60 0.629756111 1.120934024
61 0.476264729 0.629756111
62 0.504897901 0.476264729
63 0.439530638 0.504897901
64 0.800645605 0.439530638
65 0.467055799 0.800645605
66 0.405880789 0.467055799
67 0.019918581 0.405880789
68 -0.104417052 0.019918581
69 -0.403839021 -0.104417052
70 -0.312506078 -0.403839021
71 -0.179560106 -0.312506078
72 -0.133643671 -0.179560106
73 -0.044148352 -0.133643671
74 -0.002917458 -0.044148352
75 0.513537153 -0.002917458
76 0.248308560 0.513537153
77 0.216101491 0.248308560
78 0.190100980 0.216101491
79 0.218206899 0.190100980
80 0.211791367 0.218206899
81 0.486433095 0.211791367
82 0.241781049 0.486433095
83 0.278932640 0.241781049
84 -0.010171617 0.278932640
85 -0.418500310 -0.010171617
86 -0.033284022 -0.418500310
87 -0.045030858 -0.033284022
88 -0.521368925 -0.045030858
89 -0.543870179 -0.521368925
90 -0.948485312 -0.543870179
91 -0.616754942 -0.948485312
92 -1.023862699 -0.616754942
93 -0.872537115 -1.023862699
94 -0.739482918 -0.872537115
95 -0.339497418 -0.739482918
96 -0.673803487 -0.339497418
97 -0.897830115 -0.673803487
98 -0.771632050 -0.897830115
99 -0.804548766 -0.771632050
100 -0.656993367 -0.804548766
101 -0.644913826 -0.656993367
102 -0.384854864 -0.644913826
103 -0.159065772 -0.384854864
104 -0.473995325 -0.159065772
105 0.064246762 -0.473995325
106 -0.047338692 0.064246762
107 -0.176293649 -0.047338692
108 -0.395170146 -0.176293649
109 -0.342283688 -0.395170146
110 -1.083802755 -0.342283688
111 -0.982743385 -1.083802755
112 -0.776137467 -0.982743385
113 -0.671940423 -0.776137467
114 -0.674860849 -0.671940423
115 -0.885170744 -0.674860849
116 -1.136867582 -0.885170744
117 -1.060152779 -1.136867582
118 -0.636119422 -1.060152779
119 -0.335612659 -0.636119422
120 -0.194316001 -0.335612659
121 0.297010223 -0.194316001
122 0.359038419 0.297010223
123 0.460719584 0.359038419
124 0.257895895 0.460719584
125 0.357313351 0.257895895
126 0.014393708 0.357313351
127 0.077291946 0.014393708
128 0.274811485 0.077291946
129 0.339532651 0.274811485
130 0.336865892 0.339532651
131 0.331744990 0.336865892
132 0.736075322 0.331744990
133 0.418328997 0.736075322
134 0.264038948 0.418328997
135 1.198312882 0.264038948
136 1.064182475 1.198312882
137 1.068075750 1.064182475
138 1.001519049 1.068075750
139 0.692868046 1.001519049
140 0.757928907 0.692868046
141 1.199993597 0.757928907
142 0.830489947 1.199993597
143 0.406915467 0.830489947
144 0.013760480 0.406915467
145 -0.301711562 0.013760480
146 -0.352737474 -0.301711562
147 -0.371458602 -0.352737474
148 -0.768196928 -0.371458602
149 -0.466992847 -0.768196928
150 -0.306280941 -0.466992847
151 -0.655612793 -0.306280941
152 -0.524613893 -0.655612793
153 -0.518192808 -0.524613893
154 -0.605533638 -0.518192808
155 -0.654171280 -0.605533638
156 -0.248407095 -0.654171280
157 -0.416822473 -0.248407095
158 -0.107552376 -0.416822473
159 0.022971565 -0.107552376
160 -0.230069656 0.022971565
161 -0.497926833 -0.230069656
162 -0.306304836 -0.497926833
163 -0.761930372 -0.306304836
164 -0.235158026 -0.761930372
165 -0.630449396 -0.235158026
166 -0.869462995 -0.630449396
167 -0.550790488 -0.869462995
168 -0.501284684 -0.550790488
169 -0.398661628 -0.501284684
170 -0.626053769 -0.398661628
171 -1.275258866 -0.626053769
172 -1.286501516 -1.275258866
173 -1.999381756 -1.286501516
174 -1.796043241 -1.999381756
175 -2.281017419 -1.796043241
176 -2.351133451 -2.281017419
177 -0.256613375 -2.351133451
178 -0.195237281 -0.256613375
179 0.085638695 -0.195237281
180 -0.013037211 0.085638695
181 0.194368888 -0.013037211
182 0.047262850 0.194368888
183 -0.299491393 0.047262850
184 -0.437752538 -0.299491393
185 -0.067728350 -0.437752538
186 0.031894096 -0.067728350
187 0.047728667 0.031894096
188 0.365891176 0.047728667
189 0.244824548 0.365891176
190 0.740876758 0.244824548
191 1.360326931 0.740876758
192 0.545198889 1.360326931
193 0.366538680 0.545198889
194 0.518532277 0.366538680
195 0.554801131 0.518532277
196 0.385208421 0.554801131
197 0.624747550 0.385208421
198 0.365808211 0.624747550
199 0.340978879 0.365808211
200 0.210351368 0.340978879
201 0.162024150 0.210351368
202 0.247563153 0.162024150
203 0.230686742 0.247563153
204 0.289822350 0.230686742
205 -0.003857495 0.289822350
206 0.410153356 -0.003857495
207 -0.094030122 0.410153356
208 -0.330890410 -0.094030122
209 -0.333083421 -0.330890410
210 -0.350599920 -0.333083421
211 -0.339982401 -0.350599920
212 -0.523616702 -0.339982401
213 -0.824004095 -0.523616702
214 -0.382956328 -0.824004095
215 -0.555449893 -0.382956328
216 0.110787552 -0.555449893
217 0.139826977 0.110787552
218 -0.354891613 0.139826977
219 -0.577337603 -0.354891613
220 -0.353392373 -0.577337603
221 -0.392492038 -0.353392373
222 -0.967561885 -0.392492038
223 -0.785444941 -0.967561885
224 -0.307385297 -0.785444941
225 -0.031285304 -0.307385297
226 0.024099425 -0.031285304
227 -0.234896564 0.024099425
228 -0.418419384 -0.234896564
229 -0.329865575 -0.418419384
230 0.494903228 -0.329865575
231 1.188823284 0.494903228
232 1.212884228 1.188823284
233 1.274535478 1.212884228
234 1.228130252 1.274535478
235 0.683453948 1.228130252
236 0.488320650 0.683453948
237 0.360404125 0.488320650
238 0.424659887 0.360404125
239 0.223118448 0.424659887
240 0.410100229 0.223118448
241 0.471514155 0.410100229
242 0.306189431 0.471514155
243 -0.035820090 0.306189431
244 0.019115746 -0.035820090
245 -0.577019621 0.019115746
246 -0.217571575 -0.577019621
247 0.474068122 -0.217571575
248 0.882446493 0.474068122
249 1.225400641 0.882446493
250 0.974036345 1.225400641
251 0.536418527 0.974036345
252 0.433403569 0.536418527
253 0.301694771 0.433403569
254 0.183039990 0.301694771
255 0.189372107 0.183039990
256 0.131591569 0.189372107
257 0.167996852 0.131591569
258 0.350122390 0.167996852
259 NA 0.350122390
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -1.194024225 -1.188923231
[2,] -1.252838613 -1.194024225
[3,] -0.858119610 -1.252838613
[4,] -0.908336001 -0.858119610
[5,] -0.491933203 -0.908336001
[6,] -0.710001954 -0.491933203
[7,] -0.712807433 -0.710001954
[8,] -0.577295865 -0.712807433
[9,] -0.304348040 -0.577295865
[10,] -0.122264233 -0.304348040
[11,] -0.228543519 -0.122264233
[12,] -0.388819761 -0.228543519
[13,] -0.354966978 -0.388819761
[14,] -0.206883399 -0.354966978
[15,] -0.019134819 -0.206883399
[16,] -0.083878525 -0.019134819
[17,] -0.102817091 -0.083878525
[18,] 0.012654578 -0.102817091
[19,] 0.307470472 0.012654578
[20,] 0.464310956 0.307470472
[21,] 0.696678987 0.464310956
[22,] 0.591863403 0.696678987
[23,] 0.436393027 0.591863403
[24,] 0.517354372 0.436393027
[25,] 0.611620213 0.517354372
[26,] 0.616038157 0.611620213
[27,] 0.382560042 0.616038157
[28,] 0.489791811 0.382560042
[29,] 0.500082094 0.489791811
[30,] 0.539222770 0.500082094
[31,] 0.505864783 0.539222770
[32,] 0.366910066 0.505864783
[33,] 0.631665921 0.366910066
[34,] 0.521846297 0.631665921
[35,] 0.291967215 0.521846297
[36,] 0.046786993 0.291967215
[37,] 0.337808419 0.046786993
[38,] 0.258958757 0.337808419
[39,] 0.048934129 0.258958757
[40,] -0.342279849 0.048934129
[41,] -0.528256504 -0.342279849
[42,] -0.280733989 -0.528256504
[43,] 0.140901730 -0.280733989
[44,] 0.321515420 0.140901730
[45,] 0.208261931 0.321515420
[46,] 0.536321243 0.208261931
[47,] 0.617954411 0.536321243
[48,] 1.009980144 0.617954411
[49,] 1.053259057 1.009980144
[50,] 1.015298710 1.053259057
[51,] 0.761995777 1.015298710
[52,] 1.329560425 0.761995777
[53,] 1.415083048 1.329560425
[54,] 1.071814021 1.415083048
[55,] 1.096064808 1.071814021
[56,] 1.149627816 1.096064808
[57,] 1.061313701 1.149627816
[58,] 0.941135508 1.061313701
[59,] 1.120934024 0.941135508
[60,] 0.629756111 1.120934024
[61,] 0.476264729 0.629756111
[62,] 0.504897901 0.476264729
[63,] 0.439530638 0.504897901
[64,] 0.800645605 0.439530638
[65,] 0.467055799 0.800645605
[66,] 0.405880789 0.467055799
[67,] 0.019918581 0.405880789
[68,] -0.104417052 0.019918581
[69,] -0.403839021 -0.104417052
[70,] -0.312506078 -0.403839021
[71,] -0.179560106 -0.312506078
[72,] -0.133643671 -0.179560106
[73,] -0.044148352 -0.133643671
[74,] -0.002917458 -0.044148352
[75,] 0.513537153 -0.002917458
[76,] 0.248308560 0.513537153
[77,] 0.216101491 0.248308560
[78,] 0.190100980 0.216101491
[79,] 0.218206899 0.190100980
[80,] 0.211791367 0.218206899
[81,] 0.486433095 0.211791367
[82,] 0.241781049 0.486433095
[83,] 0.278932640 0.241781049
[84,] -0.010171617 0.278932640
[85,] -0.418500310 -0.010171617
[86,] -0.033284022 -0.418500310
[87,] -0.045030858 -0.033284022
[88,] -0.521368925 -0.045030858
[89,] -0.543870179 -0.521368925
[90,] -0.948485312 -0.543870179
[91,] -0.616754942 -0.948485312
[92,] -1.023862699 -0.616754942
[93,] -0.872537115 -1.023862699
[94,] -0.739482918 -0.872537115
[95,] -0.339497418 -0.739482918
[96,] -0.673803487 -0.339497418
[97,] -0.897830115 -0.673803487
[98,] -0.771632050 -0.897830115
[99,] -0.804548766 -0.771632050
[100,] -0.656993367 -0.804548766
[101,] -0.644913826 -0.656993367
[102,] -0.384854864 -0.644913826
[103,] -0.159065772 -0.384854864
[104,] -0.473995325 -0.159065772
[105,] 0.064246762 -0.473995325
[106,] -0.047338692 0.064246762
[107,] -0.176293649 -0.047338692
[108,] -0.395170146 -0.176293649
[109,] -0.342283688 -0.395170146
[110,] -1.083802755 -0.342283688
[111,] -0.982743385 -1.083802755
[112,] -0.776137467 -0.982743385
[113,] -0.671940423 -0.776137467
[114,] -0.674860849 -0.671940423
[115,] -0.885170744 -0.674860849
[116,] -1.136867582 -0.885170744
[117,] -1.060152779 -1.136867582
[118,] -0.636119422 -1.060152779
[119,] -0.335612659 -0.636119422
[120,] -0.194316001 -0.335612659
[121,] 0.297010223 -0.194316001
[122,] 0.359038419 0.297010223
[123,] 0.460719584 0.359038419
[124,] 0.257895895 0.460719584
[125,] 0.357313351 0.257895895
[126,] 0.014393708 0.357313351
[127,] 0.077291946 0.014393708
[128,] 0.274811485 0.077291946
[129,] 0.339532651 0.274811485
[130,] 0.336865892 0.339532651
[131,] 0.331744990 0.336865892
[132,] 0.736075322 0.331744990
[133,] 0.418328997 0.736075322
[134,] 0.264038948 0.418328997
[135,] 1.198312882 0.264038948
[136,] 1.064182475 1.198312882
[137,] 1.068075750 1.064182475
[138,] 1.001519049 1.068075750
[139,] 0.692868046 1.001519049
[140,] 0.757928907 0.692868046
[141,] 1.199993597 0.757928907
[142,] 0.830489947 1.199993597
[143,] 0.406915467 0.830489947
[144,] 0.013760480 0.406915467
[145,] -0.301711562 0.013760480
[146,] -0.352737474 -0.301711562
[147,] -0.371458602 -0.352737474
[148,] -0.768196928 -0.371458602
[149,] -0.466992847 -0.768196928
[150,] -0.306280941 -0.466992847
[151,] -0.655612793 -0.306280941
[152,] -0.524613893 -0.655612793
[153,] -0.518192808 -0.524613893
[154,] -0.605533638 -0.518192808
[155,] -0.654171280 -0.605533638
[156,] -0.248407095 -0.654171280
[157,] -0.416822473 -0.248407095
[158,] -0.107552376 -0.416822473
[159,] 0.022971565 -0.107552376
[160,] -0.230069656 0.022971565
[161,] -0.497926833 -0.230069656
[162,] -0.306304836 -0.497926833
[163,] -0.761930372 -0.306304836
[164,] -0.235158026 -0.761930372
[165,] -0.630449396 -0.235158026
[166,] -0.869462995 -0.630449396
[167,] -0.550790488 -0.869462995
[168,] -0.501284684 -0.550790488
[169,] -0.398661628 -0.501284684
[170,] -0.626053769 -0.398661628
[171,] -1.275258866 -0.626053769
[172,] -1.286501516 -1.275258866
[173,] -1.999381756 -1.286501516
[174,] -1.796043241 -1.999381756
[175,] -2.281017419 -1.796043241
[176,] -2.351133451 -2.281017419
[177,] -0.256613375 -2.351133451
[178,] -0.195237281 -0.256613375
[179,] 0.085638695 -0.195237281
[180,] -0.013037211 0.085638695
[181,] 0.194368888 -0.013037211
[182,] 0.047262850 0.194368888
[183,] -0.299491393 0.047262850
[184,] -0.437752538 -0.299491393
[185,] -0.067728350 -0.437752538
[186,] 0.031894096 -0.067728350
[187,] 0.047728667 0.031894096
[188,] 0.365891176 0.047728667
[189,] 0.244824548 0.365891176
[190,] 0.740876758 0.244824548
[191,] 1.360326931 0.740876758
[192,] 0.545198889 1.360326931
[193,] 0.366538680 0.545198889
[194,] 0.518532277 0.366538680
[195,] 0.554801131 0.518532277
[196,] 0.385208421 0.554801131
[197,] 0.624747550 0.385208421
[198,] 0.365808211 0.624747550
[199,] 0.340978879 0.365808211
[200,] 0.210351368 0.340978879
[201,] 0.162024150 0.210351368
[202,] 0.247563153 0.162024150
[203,] 0.230686742 0.247563153
[204,] 0.289822350 0.230686742
[205,] -0.003857495 0.289822350
[206,] 0.410153356 -0.003857495
[207,] -0.094030122 0.410153356
[208,] -0.330890410 -0.094030122
[209,] -0.333083421 -0.330890410
[210,] -0.350599920 -0.333083421
[211,] -0.339982401 -0.350599920
[212,] -0.523616702 -0.339982401
[213,] -0.824004095 -0.523616702
[214,] -0.382956328 -0.824004095
[215,] -0.555449893 -0.382956328
[216,] 0.110787552 -0.555449893
[217,] 0.139826977 0.110787552
[218,] -0.354891613 0.139826977
[219,] -0.577337603 -0.354891613
[220,] -0.353392373 -0.577337603
[221,] -0.392492038 -0.353392373
[222,] -0.967561885 -0.392492038
[223,] -0.785444941 -0.967561885
[224,] -0.307385297 -0.785444941
[225,] -0.031285304 -0.307385297
[226,] 0.024099425 -0.031285304
[227,] -0.234896564 0.024099425
[228,] -0.418419384 -0.234896564
[229,] -0.329865575 -0.418419384
[230,] 0.494903228 -0.329865575
[231,] 1.188823284 0.494903228
[232,] 1.212884228 1.188823284
[233,] 1.274535478 1.212884228
[234,] 1.228130252 1.274535478
[235,] 0.683453948 1.228130252
[236,] 0.488320650 0.683453948
[237,] 0.360404125 0.488320650
[238,] 0.424659887 0.360404125
[239,] 0.223118448 0.424659887
[240,] 0.410100229 0.223118448
[241,] 0.471514155 0.410100229
[242,] 0.306189431 0.471514155
[243,] -0.035820090 0.306189431
[244,] 0.019115746 -0.035820090
[245,] -0.577019621 0.019115746
[246,] -0.217571575 -0.577019621
[247,] 0.474068122 -0.217571575
[248,] 0.882446493 0.474068122
[249,] 1.225400641 0.882446493
[250,] 0.974036345 1.225400641
[251,] 0.536418527 0.974036345
[252,] 0.433403569 0.536418527
[253,] 0.301694771 0.433403569
[254,] 0.183039990 0.301694771
[255,] 0.189372107 0.183039990
[256,] 0.131591569 0.189372107
[257,] 0.167996852 0.131591569
[258,] 0.350122390 0.167996852
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -1.194024225 -1.188923231
2 -1.252838613 -1.194024225
3 -0.858119610 -1.252838613
4 -0.908336001 -0.858119610
5 -0.491933203 -0.908336001
6 -0.710001954 -0.491933203
7 -0.712807433 -0.710001954
8 -0.577295865 -0.712807433
9 -0.304348040 -0.577295865
10 -0.122264233 -0.304348040
11 -0.228543519 -0.122264233
12 -0.388819761 -0.228543519
13 -0.354966978 -0.388819761
14 -0.206883399 -0.354966978
15 -0.019134819 -0.206883399
16 -0.083878525 -0.019134819
17 -0.102817091 -0.083878525
18 0.012654578 -0.102817091
19 0.307470472 0.012654578
20 0.464310956 0.307470472
21 0.696678987 0.464310956
22 0.591863403 0.696678987
23 0.436393027 0.591863403
24 0.517354372 0.436393027
25 0.611620213 0.517354372
26 0.616038157 0.611620213
27 0.382560042 0.616038157
28 0.489791811 0.382560042
29 0.500082094 0.489791811
30 0.539222770 0.500082094
31 0.505864783 0.539222770
32 0.366910066 0.505864783
33 0.631665921 0.366910066
34 0.521846297 0.631665921
35 0.291967215 0.521846297
36 0.046786993 0.291967215
37 0.337808419 0.046786993
38 0.258958757 0.337808419
39 0.048934129 0.258958757
40 -0.342279849 0.048934129
41 -0.528256504 -0.342279849
42 -0.280733989 -0.528256504
43 0.140901730 -0.280733989
44 0.321515420 0.140901730
45 0.208261931 0.321515420
46 0.536321243 0.208261931
47 0.617954411 0.536321243
48 1.009980144 0.617954411
49 1.053259057 1.009980144
50 1.015298710 1.053259057
51 0.761995777 1.015298710
52 1.329560425 0.761995777
53 1.415083048 1.329560425
54 1.071814021 1.415083048
55 1.096064808 1.071814021
56 1.149627816 1.096064808
57 1.061313701 1.149627816
58 0.941135508 1.061313701
59 1.120934024 0.941135508
60 0.629756111 1.120934024
61 0.476264729 0.629756111
62 0.504897901 0.476264729
63 0.439530638 0.504897901
64 0.800645605 0.439530638
65 0.467055799 0.800645605
66 0.405880789 0.467055799
67 0.019918581 0.405880789
68 -0.104417052 0.019918581
69 -0.403839021 -0.104417052
70 -0.312506078 -0.403839021
71 -0.179560106 -0.312506078
72 -0.133643671 -0.179560106
73 -0.044148352 -0.133643671
74 -0.002917458 -0.044148352
75 0.513537153 -0.002917458
76 0.248308560 0.513537153
77 0.216101491 0.248308560
78 0.190100980 0.216101491
79 0.218206899 0.190100980
80 0.211791367 0.218206899
81 0.486433095 0.211791367
82 0.241781049 0.486433095
83 0.278932640 0.241781049
84 -0.010171617 0.278932640
85 -0.418500310 -0.010171617
86 -0.033284022 -0.418500310
87 -0.045030858 -0.033284022
88 -0.521368925 -0.045030858
89 -0.543870179 -0.521368925
90 -0.948485312 -0.543870179
91 -0.616754942 -0.948485312
92 -1.023862699 -0.616754942
93 -0.872537115 -1.023862699
94 -0.739482918 -0.872537115
95 -0.339497418 -0.739482918
96 -0.673803487 -0.339497418
97 -0.897830115 -0.673803487
98 -0.771632050 -0.897830115
99 -0.804548766 -0.771632050
100 -0.656993367 -0.804548766
101 -0.644913826 -0.656993367
102 -0.384854864 -0.644913826
103 -0.159065772 -0.384854864
104 -0.473995325 -0.159065772
105 0.064246762 -0.473995325
106 -0.047338692 0.064246762
107 -0.176293649 -0.047338692
108 -0.395170146 -0.176293649
109 -0.342283688 -0.395170146
110 -1.083802755 -0.342283688
111 -0.982743385 -1.083802755
112 -0.776137467 -0.982743385
113 -0.671940423 -0.776137467
114 -0.674860849 -0.671940423
115 -0.885170744 -0.674860849
116 -1.136867582 -0.885170744
117 -1.060152779 -1.136867582
118 -0.636119422 -1.060152779
119 -0.335612659 -0.636119422
120 -0.194316001 -0.335612659
121 0.297010223 -0.194316001
122 0.359038419 0.297010223
123 0.460719584 0.359038419
124 0.257895895 0.460719584
125 0.357313351 0.257895895
126 0.014393708 0.357313351
127 0.077291946 0.014393708
128 0.274811485 0.077291946
129 0.339532651 0.274811485
130 0.336865892 0.339532651
131 0.331744990 0.336865892
132 0.736075322 0.331744990
133 0.418328997 0.736075322
134 0.264038948 0.418328997
135 1.198312882 0.264038948
136 1.064182475 1.198312882
137 1.068075750 1.064182475
138 1.001519049 1.068075750
139 0.692868046 1.001519049
140 0.757928907 0.692868046
141 1.199993597 0.757928907
142 0.830489947 1.199993597
143 0.406915467 0.830489947
144 0.013760480 0.406915467
145 -0.301711562 0.013760480
146 -0.352737474 -0.301711562
147 -0.371458602 -0.352737474
148 -0.768196928 -0.371458602
149 -0.466992847 -0.768196928
150 -0.306280941 -0.466992847
151 -0.655612793 -0.306280941
152 -0.524613893 -0.655612793
153 -0.518192808 -0.524613893
154 -0.605533638 -0.518192808
155 -0.654171280 -0.605533638
156 -0.248407095 -0.654171280
157 -0.416822473 -0.248407095
158 -0.107552376 -0.416822473
159 0.022971565 -0.107552376
160 -0.230069656 0.022971565
161 -0.497926833 -0.230069656
162 -0.306304836 -0.497926833
163 -0.761930372 -0.306304836
164 -0.235158026 -0.761930372
165 -0.630449396 -0.235158026
166 -0.869462995 -0.630449396
167 -0.550790488 -0.869462995
168 -0.501284684 -0.550790488
169 -0.398661628 -0.501284684
170 -0.626053769 -0.398661628
171 -1.275258866 -0.626053769
172 -1.286501516 -1.275258866
173 -1.999381756 -1.286501516
174 -1.796043241 -1.999381756
175 -2.281017419 -1.796043241
176 -2.351133451 -2.281017419
177 -0.256613375 -2.351133451
178 -0.195237281 -0.256613375
179 0.085638695 -0.195237281
180 -0.013037211 0.085638695
181 0.194368888 -0.013037211
182 0.047262850 0.194368888
183 -0.299491393 0.047262850
184 -0.437752538 -0.299491393
185 -0.067728350 -0.437752538
186 0.031894096 -0.067728350
187 0.047728667 0.031894096
188 0.365891176 0.047728667
189 0.244824548 0.365891176
190 0.740876758 0.244824548
191 1.360326931 0.740876758
192 0.545198889 1.360326931
193 0.366538680 0.545198889
194 0.518532277 0.366538680
195 0.554801131 0.518532277
196 0.385208421 0.554801131
197 0.624747550 0.385208421
198 0.365808211 0.624747550
199 0.340978879 0.365808211
200 0.210351368 0.340978879
201 0.162024150 0.210351368
202 0.247563153 0.162024150
203 0.230686742 0.247563153
204 0.289822350 0.230686742
205 -0.003857495 0.289822350
206 0.410153356 -0.003857495
207 -0.094030122 0.410153356
208 -0.330890410 -0.094030122
209 -0.333083421 -0.330890410
210 -0.350599920 -0.333083421
211 -0.339982401 -0.350599920
212 -0.523616702 -0.339982401
213 -0.824004095 -0.523616702
214 -0.382956328 -0.824004095
215 -0.555449893 -0.382956328
216 0.110787552 -0.555449893
217 0.139826977 0.110787552
218 -0.354891613 0.139826977
219 -0.577337603 -0.354891613
220 -0.353392373 -0.577337603
221 -0.392492038 -0.353392373
222 -0.967561885 -0.392492038
223 -0.785444941 -0.967561885
224 -0.307385297 -0.785444941
225 -0.031285304 -0.307385297
226 0.024099425 -0.031285304
227 -0.234896564 0.024099425
228 -0.418419384 -0.234896564
229 -0.329865575 -0.418419384
230 0.494903228 -0.329865575
231 1.188823284 0.494903228
232 1.212884228 1.188823284
233 1.274535478 1.212884228
234 1.228130252 1.274535478
235 0.683453948 1.228130252
236 0.488320650 0.683453948
237 0.360404125 0.488320650
238 0.424659887 0.360404125
239 0.223118448 0.424659887
240 0.410100229 0.223118448
241 0.471514155 0.410100229
242 0.306189431 0.471514155
243 -0.035820090 0.306189431
244 0.019115746 -0.035820090
245 -0.577019621 0.019115746
246 -0.217571575 -0.577019621
247 0.474068122 -0.217571575
248 0.882446493 0.474068122
249 1.225400641 0.882446493
250 0.974036345 1.225400641
251 0.536418527 0.974036345
252 0.433403569 0.536418527
253 0.301694771 0.433403569
254 0.183039990 0.301694771
255 0.189372107 0.183039990
256 0.131591569 0.189372107
257 0.167996852 0.131591569
258 0.350122390 0.167996852
> 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/wessaorg/rcomp/tmp/7cht81355780000.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/8vjec1355780000.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9wcaj1355780000.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/107gzs1355780000.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/wessaorg/rcomp/tmp/11mz5m1355780000.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/wessaorg/rcomp/tmp/12dx401355780000.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/wessaorg/rcomp/tmp/13iptp1355780000.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/wessaorg/rcomp/tmp/14oibl1355780000.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/wessaorg/rcomp/tmp/15zkom1355780000.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/wessaorg/rcomp/tmp/16fjog1355780000.tab")
+ }
>
> try(system("convert tmp/1cvt51355780000.ps tmp/1cvt51355780000.png",intern=TRUE))
character(0)
> try(system("convert tmp/27woe1355780000.ps tmp/27woe1355780000.png",intern=TRUE))
character(0)
> try(system("convert tmp/36dg81355780000.ps tmp/36dg81355780000.png",intern=TRUE))
character(0)
> try(system("convert tmp/43oyu1355780000.ps tmp/43oyu1355780000.png",intern=TRUE))
character(0)
> try(system("convert tmp/5bwl41355780000.ps tmp/5bwl41355780000.png",intern=TRUE))
character(0)
> try(system("convert tmp/6fmug1355780000.ps tmp/6fmug1355780000.png",intern=TRUE))
character(0)
> try(system("convert tmp/7cht81355780000.ps tmp/7cht81355780000.png",intern=TRUE))
character(0)
> try(system("convert tmp/8vjec1355780000.ps tmp/8vjec1355780000.png",intern=TRUE))
character(0)
> try(system("convert tmp/9wcaj1355780000.ps tmp/9wcaj1355780000.png",intern=TRUE))
character(0)
> try(system("convert tmp/107gzs1355780000.ps tmp/107gzs1355780000.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
14.010 1.460 15.468