R version 2.8.0 (2008-10-20)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
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Natural language support but running in an English locale
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Type 'contributors()' for more information and
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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(12
+ ,1221.53
+ ,2617.2
+ ,10168.52
+ ,6957.61
+ ,23448.78
+ ,11
+ ,1180.55
+ ,2506.13
+ ,9937.04
+ ,6688.49
+ ,23007.99
+ ,10
+ ,1183.26
+ ,2679.07
+ ,9202.45
+ ,6601.37
+ ,23096.32
+ ,9
+ ,1141.2
+ ,2589.73
+ ,9369.35
+ ,6229.02
+ ,22358.17
+ ,8
+ ,1049.33
+ ,2457.46
+ ,8824.06
+ ,5925.22
+ ,20536.49
+ ,7
+ ,1101.6
+ ,2517.3
+ ,9537.3
+ ,6147.97
+ ,21029.81
+ ,6
+ ,1030.71
+ ,2386.53
+ ,9382.64
+ ,5965.52
+ ,20128.99
+ ,5
+ ,1089.41
+ ,2453.37
+ ,9768.7
+ ,5964.33
+ ,19765.19
+ ,4
+ ,1186.69
+ ,2529.66
+ ,11057.4
+ ,6135.7
+ ,21108.59
+ ,3
+ ,1169.43
+ ,2475.14
+ ,11089.94
+ ,6153.55
+ ,21239.35
+ ,2
+ ,1104.49
+ ,2525.93
+ ,10126.03
+ ,5598.46
+ ,20608.7
+ ,1
+ ,1073.87
+ ,2480.93
+ ,10198.04
+ ,5608.79
+ ,20121.99
+ ,12
+ ,1115.1
+ ,2229.85
+ ,10546.44
+ ,5957.43
+ ,21872.5
+ ,11
+ ,1095.63
+ ,2169.14
+ ,9345.55
+ ,5625.95
+ ,21821.5
+ ,10
+ ,1036.19
+ ,2030.98
+ ,10034.74
+ ,5414.96
+ ,21752.87
+ ,9
+ ,1057.08
+ ,2071.37
+ ,10133.23
+ ,5675.16
+ ,20955.25
+ ,8
+ ,1020.62
+ ,1953.35
+ ,10492.53
+ ,5458.04
+ ,19724.19
+ ,7
+ ,987.48
+ ,1748.74
+ ,10356.83
+ ,5332.14
+ ,20573.33
+ ,6
+ ,919.32
+ ,1696.58
+ ,9958.44
+ ,4808.64
+ ,18378.73
+ ,5
+ ,919.14
+ ,1900.09
+ ,9522.5
+ ,4940.82
+ ,18171
+ ,4
+ ,872.81
+ ,1908.64
+ ,8828.26
+ ,4769.45
+ ,15520.99
+ ,3
+ ,797.87
+ ,1881.46
+ ,8109.53
+ ,4084.76
+ ,13576.02
+ ,2
+ ,735.09
+ ,2100.18
+ ,7568.42
+ ,3843.74
+ ,12811.57
+ ,1
+ ,825.88
+ ,2672.2
+ ,7994.05
+ ,4338.35
+ ,13278.21
+ ,12
+ ,903.25
+ ,3136
+ ,8859.56
+ ,4810.2
+ ,14387.48
+ ,11
+ ,896.24
+ ,2994.38
+ ,8512.27
+ ,4669.44
+ ,13888.24
+ ,10
+ ,968.75
+ ,3168.22
+ ,8576.98
+ ,4987.97
+ ,13968.67
+ ,9
+ ,1166.36
+ ,3751.41
+ ,11259.86
+ ,5831.02
+ ,18016.21
+ ,8
+ ,1282.83
+ ,3925.43
+ ,13072.87
+ ,6422.3
+ ,21261.89
+ ,7
+ ,1267.38
+ ,3719.52
+ ,13376.81
+ ,6479.56
+ ,22731.1
+ ,6
+ ,1280
+ ,3757.12
+ ,13481.38
+ ,6418.32
+ ,22102.01
+ ,5
+ ,1400.38
+ ,3722.23
+ ,14338.54
+ ,7096.79
+ ,24533.12
+ ,4
+ ,1385.59
+ ,4127.47
+ ,13849.99
+ ,6948.82
+ ,25755.35
+ ,3
+ ,1322.7
+ ,4162.5
+ ,12525.54
+ ,6534.97
+ ,22849.2
+ ,2
+ ,1330.63
+ ,4441.82
+ ,13603.02
+ ,6748.13
+ ,24331.67
+ ,1
+ ,1378.55
+ ,4325.29
+ ,13592.47
+ ,6851.75
+ ,23455.74
+ ,12
+ ,1468.36
+ ,4350.83
+ ,15307.78
+ ,8067.32
+ ,27812.65
+ ,11
+ ,1481.14
+ ,4384.47
+ ,15680.67
+ ,7870.52
+ ,28643.61
+ ,10
+ ,1549.38
+ ,4639.4
+ ,16737.63
+ ,8019.22
+ ,31352.58
+ ,9
+ ,1526.75
+ ,4697.86
+ ,16785.69
+ ,7861.51
+ ,27142.47
+ ,8
+ ,1473.99
+ ,4614.76
+ ,16569.09
+ ,7638.17
+ ,23984.14
+ ,7
+ ,1455.27
+ ,4471.65
+ ,17248.89
+ ,7584.14
+ ,23184.94
+ ,6
+ ,1503.35
+ ,4305.23
+ ,18138.36
+ ,8007.32
+ ,21772.73
+ ,5
+ ,1530.62
+ ,4433.57
+ ,17875.75
+ ,7883.04
+ ,20634.47
+ ,4
+ ,1482.37
+ ,4388.53
+ ,17400.41
+ ,7408.87
+ ,20318.98
+ ,3
+ ,1420.86
+ ,4140.3
+ ,17287.65
+ ,6917.03
+ ,19800.93
+ ,2
+ ,1406.82
+ ,4144.38
+ ,17604.12
+ ,6715.44
+ ,19651.51
+ ,1
+ ,1438.24
+ ,4070.78
+ ,17383.42
+ ,6789.11
+ ,20106.42
+ ,12
+ ,1418.3
+ ,3906.01
+ ,17225.83
+ ,6596.92
+ ,19964.72
+ ,11
+ ,1400.63
+ ,3795.91
+ ,16274.33
+ ,6309.19
+ ,18960.48
+ ,10
+ ,1377.94
+ ,3703.32
+ ,16399.39
+ ,6268.92
+ ,18324.35
+ ,9
+ ,1335.85
+ ,3675.8
+ ,16127.58
+ ,6004.33
+ ,17543.05
+ ,8
+ ,1303.82
+ ,3911.06
+ ,16140.76
+ ,5859.57
+ ,17392.27
+ ,7
+ ,1276.66
+ ,3912.28
+ ,15456.81
+ ,5681.97
+ ,16971.34
+ ,6
+ ,1270.2
+ ,3839.25
+ ,15505.18
+ ,5683.31
+ ,16267.62
+ ,5
+ ,1270.09
+ ,3744.63
+ ,15467.33
+ ,5692.86
+ ,15857.89
+ ,4
+ ,1310.61
+ ,3549.25
+ ,16906.23
+ ,6009.89
+ ,16661.3
+ ,3
+ ,1294.87
+ ,3394.14
+ ,17059.66
+ ,5970.08
+ ,15805.04
+ ,2
+ ,1280.66
+ ,3264.26
+ ,16205.43
+ ,5796.04
+ ,15918.48
+ ,1
+ ,1280.08
+ ,3328.8
+ ,16649.82
+ ,5674.15
+ ,15753.14
+ ,12
+ ,1248.29
+ ,3223.98
+ ,16111.43
+ ,5408.26
+ ,14876.43
+ ,11
+ ,1249.48
+ ,3228.01
+ ,14872.15
+ ,5193.4
+ ,14937.14
+ ,10
+ ,1207.01
+ ,3112.83
+ ,13606.5
+ ,4929.07
+ ,14386.37
+ ,9
+ ,1228.81
+ ,3051.67
+ ,13574.3
+ ,5044.12
+ ,15428.52
+ ,8
+ ,1220.33
+ ,3039.71
+ ,12413.6
+ ,4829.69
+ ,14903.55
+ ,7
+ ,1234.18
+ ,3125.67
+ ,11899.6
+ ,4886.5
+ ,14880.98
+ ,6
+ ,1191.33
+ ,3106.54
+ ,11584.01
+ ,4586.28
+ ,14201.06
+ ,5
+ ,1191.5
+ ,11276.59
+ ,4460.63
+ ,13867.07
+ ,4
+ ,1156.85
+ ,11008.9
+ ,4184.84
+ ,13908.97
+ ,3
+ ,1180.59
+ ,11668.95
+ ,4348.77
+ ,13516.88
+ ,2
+ ,1203.6
+ ,11740.6
+ ,4350.49
+ ,14195.35
+ ,1
+ ,1181.27
+ ,11387.59
+ ,4254.85
+ ,13721.69)
+ ,dim=c(6
+ ,72)
+ ,dimnames=list(c('month'
+ ,'S&P'
+ ,'Bel20'
+ ,'Nikkei225'
+ ,'DAX'
+ ,'HangSeng')
+ ,1:72))
> y <- array(NA,dim=c(6,72),dimnames=list(c('month','S&P','Bel20','Nikkei225','DAX','HangSeng'),1:72))
> 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'
> #'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
Nikkei225 month S&P Bel20 DAX HangSeng t
1 10168.52 12.00 1221.53 2617.20 6957.61 23448.78 1
2 9937.04 11.00 1180.55 2506.13 6688.49 23007.99 2
3 9202.45 10.00 1183.26 2679.07 6601.37 23096.32 3
4 9369.35 9.00 1141.20 2589.73 6229.02 22358.17 4
5 8824.06 8.00 1049.33 2457.46 5925.22 20536.49 5
6 9537.30 7.00 1101.60 2517.30 6147.97 21029.81 6
7 9382.64 6.00 1030.71 2386.53 5965.52 20128.99 7
8 9768.70 5.00 1089.41 2453.37 5964.33 19765.19 8
9 11057.40 4.00 1186.69 2529.66 6135.70 21108.59 9
10 11089.94 3.00 1169.43 2475.14 6153.55 21239.35 10
11 10126.03 2.00 1104.49 2525.93 5598.46 20608.70 11
12 10198.04 1.00 1073.87 2480.93 5608.79 20121.99 12
13 10546.44 12.00 1115.10 2229.85 5957.43 21872.50 13
14 9345.55 11.00 1095.63 2169.14 5625.95 21821.50 14
15 10034.74 10.00 1036.19 2030.98 5414.96 21752.87 15
16 10133.23 9.00 1057.08 2071.37 5675.16 20955.25 16
17 10492.53 8.00 1020.62 1953.35 5458.04 19724.19 17
18 10356.83 7.00 987.48 1748.74 5332.14 20573.33 18
19 9958.44 6.00 919.32 1696.58 4808.64 18378.73 19
20 9522.50 5.00 919.14 1900.09 4940.82 18171.00 20
21 8828.26 4.00 872.81 1908.64 4769.45 15520.99 21
22 8109.53 3.00 797.87 1881.46 4084.76 13576.02 22
23 7568.42 2.00 735.09 2100.18 3843.74 12811.57 23
24 7994.05 1.00 825.88 2672.20 4338.35 13278.21 24
25 8859.56 12.00 903.25 3136.00 4810.20 14387.48 25
26 8512.27 11.00 896.24 2994.38 4669.44 13888.24 26
27 8576.98 10.00 968.75 3168.22 4987.97 13968.67 27
28 11259.86 9.00 1166.36 3751.41 5831.02 18016.21 28
29 13072.87 8.00 1282.83 3925.43 6422.30 21261.89 29
30 13376.81 7.00 1267.38 3719.52 6479.56 22731.10 30
31 13481.38 6.00 1280.00 3757.12 6418.32 22102.01 31
32 14338.54 5.00 1400.38 3722.23 7096.79 24533.12 32
33 13849.99 4.00 1385.59 4127.47 6948.82 25755.35 33
34 12525.54 3.00 1322.70 4162.50 6534.97 22849.20 34
35 13603.02 2.00 1330.63 4441.82 6748.13 24331.67 35
36 13592.47 1.00 1378.55 4325.29 6851.75 23455.74 36
37 15307.78 12.00 1468.36 4350.83 8067.32 27812.65 37
38 15680.67 11.00 1481.14 4384.47 7870.52 28643.61 38
39 16737.63 10.00 1549.38 4639.40 8019.22 31352.58 39
40 16785.69 9.00 1526.75 4697.86 7861.51 27142.47 40
41 16569.09 8.00 1473.99 4614.76 7638.17 23984.14 41
42 17248.89 7.00 1455.27 4471.65 7584.14 23184.94 42
43 18138.36 6.00 1503.35 4305.23 8007.32 21772.73 43
44 17875.75 5.00 1530.62 4433.57 7883.04 20634.47 44
45 17400.41 4.00 1482.37 4388.53 7408.87 20318.98 45
46 17287.65 3.00 1420.86 4140.30 6917.03 19800.93 46
47 17604.12 2.00 1406.82 4144.38 6715.44 19651.51 47
48 17383.42 1.00 1438.24 4070.78 6789.11 20106.42 48
49 17225.83 12.00 1418.30 3906.01 6596.92 19964.72 49
50 16274.33 11.00 1400.63 3795.91 6309.19 18960.48 50
51 16399.39 10.00 1377.94 3703.32 6268.92 18324.35 51
52 16127.58 9.00 1335.85 3675.80 6004.33 17543.05 52
53 16140.76 8.00 1303.82 3911.06 5859.57 17392.27 53
54 15456.81 7.00 1276.66 3912.28 5681.97 16971.34 54
55 15505.18 6.00 1270.20 3839.25 5683.31 16267.62 55
56 15467.33 5.00 1270.09 3744.63 5692.86 15857.89 56
57 16906.23 4.00 1310.61 3549.25 6009.89 16661.30 57
58 17059.66 3.00 1294.87 3394.14 5970.08 15805.04 58
59 16205.43 2.00 1280.66 3264.26 5796.04 15918.48 59
60 16649.82 1.00 1280.08 3328.80 5674.15 15753.14 60
61 16111.43 12.00 1248.29 3223.98 5408.26 14876.43 61
62 14872.15 11.00 1249.48 3228.01 5193.40 14937.14 62
63 13606.50 10.00 1207.01 3112.83 4929.07 14386.37 63
64 13574.30 9.00 1228.81 3051.67 5044.12 15428.52 64
65 12413.60 8.00 1220.33 3039.71 4829.69 14903.55 65
66 11899.60 7.00 1234.18 3125.67 4886.50 14880.98 66
67 11584.01 6.00 1191.33 3106.54 4586.28 14201.06 67
68 4460.63 5.00 1191.50 11276.59 13867.07 4.00 68
69 13908.97 1156.85 11008.90 4184.84 3.00 1180.59 69
70 2.00 11668.95 4348.77 13516.88 1203.60 11740.60 70
71 1181.27 4350.49 14195.35 1.00 11387.59 4254.85 71
72 2617.20 13721.69 12.00 1221.53 10168.52 6957.61 72
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) month `S&P` Bel20 DAX HangSeng
1.7614 -0.9603 -0.1553 -0.1953 -0.1864 0.4772
t
164.1086
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-4537.52 -1014.54 -73.81 1136.01 5658.13
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.76137 1398.86140 0.001 0.999
month -0.96026 0.11796 -8.141 1.64e-11 ***
`S&P` -0.15526 0.13169 -1.179 0.243
Bel20 -0.19526 0.14125 -1.382 0.172
DAX -0.18641 0.12839 -1.452 0.151
HangSeng 0.47720 0.05324 8.963 5.74e-13 ***
t 164.10859 14.16248 11.588 < 2e-16 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 1906 on 65 degrees of freedom
Multiple R-squared: 0.7975, Adjusted R-squared: 0.7789
F-statistic: 42.68 on 6 and 65 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,] 1.398492e-03 2.796983e-03 0.9986015
[2,] 1.276666e-04 2.553332e-04 0.9998723
[3,] 1.151137e-05 2.302274e-05 0.9999885
[4,] 8.125220e-07 1.625044e-06 0.9999992
[5,] 1.256267e-05 2.512535e-05 0.9999874
[6,] 2.763499e-06 5.526999e-06 0.9999972
[7,] 6.647030e-07 1.329406e-06 0.9999993
[8,] 8.942687e-08 1.788537e-07 0.9999999
[9,] 1.949130e-08 3.898260e-08 1.0000000
[10,] 2.502494e-09 5.004988e-09 1.0000000
[11,] 4.036579e-10 8.073158e-10 1.0000000
[12,] 1.259379e-10 2.518757e-10 1.0000000
[13,] 1.598399e-11 3.196797e-11 1.0000000
[14,] 9.417316e-12 1.883463e-11 1.0000000
[15,] 1.990987e-12 3.981974e-12 1.0000000
[16,] 9.920055e-12 1.984011e-11 1.0000000
[17,] 1.918182e-12 3.836365e-12 1.0000000
[18,] 3.501249e-12 7.002497e-12 1.0000000
[19,] 8.666880e-13 1.733376e-12 1.0000000
[20,] 1.937829e-13 3.875658e-13 1.0000000
[21,] 5.033432e-14 1.006686e-13 1.0000000
[22,] 1.690204e-14 3.380407e-14 1.0000000
[23,] 5.952244e-14 1.190449e-13 1.0000000
[24,] 1.677484e-13 3.354968e-13 1.0000000
[25,] 2.203521e-11 4.407043e-11 1.0000000
[26,] 2.691365e-10 5.382730e-10 1.0000000
[27,] 1.289855e-06 2.579711e-06 0.9999987
[28,] 3.046183e-06 6.092365e-06 0.9999970
[29,] 3.865893e-06 7.731785e-06 0.9999961
[30,] 4.323810e-06 8.647621e-06 0.9999957
[31,] 5.336750e-06 1.067350e-05 0.9999947
[32,] 9.417636e-06 1.883527e-05 0.9999906
[33,] 1.764513e-05 3.529026e-05 0.9999824
[34,] 8.997253e-06 1.799451e-05 0.9999910
[35,] 4.678705e-06 9.357410e-06 0.9999953
[36,] 1.894093e-06 3.788186e-06 0.9999981
[37,] 1.191046e-06 2.382091e-06 0.9999988
[38,] 1.188800e-06 2.377600e-06 0.9999988
[39,] 4.926738e-07 9.853476e-07 0.9999995
[40,] 2.068428e-07 4.136855e-07 0.9999998
[41,] 1.968641e-07 3.937283e-07 0.9999998
[42,] 1.300657e-07 2.601314e-07 0.9999999
[43,] 1.439172e-07 2.878345e-07 0.9999999
[44,] 1.344073e-07 2.688147e-07 0.9999999
[45,] 1.006935e-06 2.013871e-06 0.9999990
[46,] 6.409372e-05 1.281874e-04 0.9999359
[47,] 2.102965e-01 4.205930e-01 0.7897035
[48,] 2.180342e-01 4.360683e-01 0.7819658
[49,] 1.679831e-01 3.359663e-01 0.8320169
[50,] 2.235374e-01 4.470747e-01 0.7764626
[51,] 2.770577e-01 5.541154e-01 0.7229423
[52,] 3.526935e-01 7.053870e-01 0.6473065
[53,] 3.802987e-01 7.605973e-01 0.6197013
> postscript(file="/var/www/html/freestat/rcomp/tmp/1qac61291415244.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/2qac61291415244.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/freestat/rcomp/tmp/31jc81291415244.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/41jc81291415244.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/51jc81291415244.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 = 72
Frequency = 1
1 2 3 4 5 6
822.08270 557.66125 -366.19948 -105.50854 -43.28355 330.79836
7 8 9 10 11 12
370.38964 786.92965 1331.43494 1126.50928 194.83590 322.42030
13 14 15 16 17 18
-295.70468 -1713.99594 -1232.66198 -858.98107 -146.46680 -921.01356
19 20 21 22 23 24
-555.56214 -993.09179 -625.28283 -725.51802 -1078.86907 -822.99649
25 26 27 28 29 30
-449.84219 -778.94441 -813.10391 74.92970 336.31471 -257.85382
31 32 33 34 35 36
-20.26509 -349.94862 -1537.56796 -1720.34079 -1419.85751 -1173.47976
37 38 39 40 41 42
-1445.30742 -1662.15442 -1974.89311 -104.33147 955.10612 1810.29370
43 44 45 46 47 48
3262.45816 3384.08449 2789.55022 2609.22951 2792.97178 2194.35936
49 50 51 52 53 54
1879.74672 1164.52340 1398.96723 1273.69383 1207.73691 522.50062
55 56 57 58 59 60
726.60429 702.49629 1620.17861 1976.99557 843.55262 1191.56448
61 62 63 64 65 66
843.02682 -629.37403 -1875.62387 -2557.31843 -3676.19573 -4314.96883
67 68 69 70 71 72
-4537.52250 -1725.71839 5658.12756 -2345.91702 -3998.10966 2791.70016
> postscript(file="/var/www/html/freestat/rcomp/tmp/6uttb1291415244.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 = 72
Frequency = 1
lag(myerror, k = 1) myerror
0 822.08270 NA
1 557.66125 822.08270
2 -366.19948 557.66125
3 -105.50854 -366.19948
4 -43.28355 -105.50854
5 330.79836 -43.28355
6 370.38964 330.79836
7 786.92965 370.38964
8 1331.43494 786.92965
9 1126.50928 1331.43494
10 194.83590 1126.50928
11 322.42030 194.83590
12 -295.70468 322.42030
13 -1713.99594 -295.70468
14 -1232.66198 -1713.99594
15 -858.98107 -1232.66198
16 -146.46680 -858.98107
17 -921.01356 -146.46680
18 -555.56214 -921.01356
19 -993.09179 -555.56214
20 -625.28283 -993.09179
21 -725.51802 -625.28283
22 -1078.86907 -725.51802
23 -822.99649 -1078.86907
24 -449.84219 -822.99649
25 -778.94441 -449.84219
26 -813.10391 -778.94441
27 74.92970 -813.10391
28 336.31471 74.92970
29 -257.85382 336.31471
30 -20.26509 -257.85382
31 -349.94862 -20.26509
32 -1537.56796 -349.94862
33 -1720.34079 -1537.56796
34 -1419.85751 -1720.34079
35 -1173.47976 -1419.85751
36 -1445.30742 -1173.47976
37 -1662.15442 -1445.30742
38 -1974.89311 -1662.15442
39 -104.33147 -1974.89311
40 955.10612 -104.33147
41 1810.29370 955.10612
42 3262.45816 1810.29370
43 3384.08449 3262.45816
44 2789.55022 3384.08449
45 2609.22951 2789.55022
46 2792.97178 2609.22951
47 2194.35936 2792.97178
48 1879.74672 2194.35936
49 1164.52340 1879.74672
50 1398.96723 1164.52340
51 1273.69383 1398.96723
52 1207.73691 1273.69383
53 522.50062 1207.73691
54 726.60429 522.50062
55 702.49629 726.60429
56 1620.17861 702.49629
57 1976.99557 1620.17861
58 843.55262 1976.99557
59 1191.56448 843.55262
60 843.02682 1191.56448
61 -629.37403 843.02682
62 -1875.62387 -629.37403
63 -2557.31843 -1875.62387
64 -3676.19573 -2557.31843
65 -4314.96883 -3676.19573
66 -4537.52250 -4314.96883
67 -1725.71839 -4537.52250
68 5658.12756 -1725.71839
69 -2345.91702 5658.12756
70 -3998.10966 -2345.91702
71 2791.70016 -3998.10966
72 NA 2791.70016
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 557.66125 822.08270
[2,] -366.19948 557.66125
[3,] -105.50854 -366.19948
[4,] -43.28355 -105.50854
[5,] 330.79836 -43.28355
[6,] 370.38964 330.79836
[7,] 786.92965 370.38964
[8,] 1331.43494 786.92965
[9,] 1126.50928 1331.43494
[10,] 194.83590 1126.50928
[11,] 322.42030 194.83590
[12,] -295.70468 322.42030
[13,] -1713.99594 -295.70468
[14,] -1232.66198 -1713.99594
[15,] -858.98107 -1232.66198
[16,] -146.46680 -858.98107
[17,] -921.01356 -146.46680
[18,] -555.56214 -921.01356
[19,] -993.09179 -555.56214
[20,] -625.28283 -993.09179
[21,] -725.51802 -625.28283
[22,] -1078.86907 -725.51802
[23,] -822.99649 -1078.86907
[24,] -449.84219 -822.99649
[25,] -778.94441 -449.84219
[26,] -813.10391 -778.94441
[27,] 74.92970 -813.10391
[28,] 336.31471 74.92970
[29,] -257.85382 336.31471
[30,] -20.26509 -257.85382
[31,] -349.94862 -20.26509
[32,] -1537.56796 -349.94862
[33,] -1720.34079 -1537.56796
[34,] -1419.85751 -1720.34079
[35,] -1173.47976 -1419.85751
[36,] -1445.30742 -1173.47976
[37,] -1662.15442 -1445.30742
[38,] -1974.89311 -1662.15442
[39,] -104.33147 -1974.89311
[40,] 955.10612 -104.33147
[41,] 1810.29370 955.10612
[42,] 3262.45816 1810.29370
[43,] 3384.08449 3262.45816
[44,] 2789.55022 3384.08449
[45,] 2609.22951 2789.55022
[46,] 2792.97178 2609.22951
[47,] 2194.35936 2792.97178
[48,] 1879.74672 2194.35936
[49,] 1164.52340 1879.74672
[50,] 1398.96723 1164.52340
[51,] 1273.69383 1398.96723
[52,] 1207.73691 1273.69383
[53,] 522.50062 1207.73691
[54,] 726.60429 522.50062
[55,] 702.49629 726.60429
[56,] 1620.17861 702.49629
[57,] 1976.99557 1620.17861
[58,] 843.55262 1976.99557
[59,] 1191.56448 843.55262
[60,] 843.02682 1191.56448
[61,] -629.37403 843.02682
[62,] -1875.62387 -629.37403
[63,] -2557.31843 -1875.62387
[64,] -3676.19573 -2557.31843
[65,] -4314.96883 -3676.19573
[66,] -4537.52250 -4314.96883
[67,] -1725.71839 -4537.52250
[68,] 5658.12756 -1725.71839
[69,] -2345.91702 5658.12756
[70,] -3998.10966 -2345.91702
[71,] 2791.70016 -3998.10966
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 557.66125 822.08270
2 -366.19948 557.66125
3 -105.50854 -366.19948
4 -43.28355 -105.50854
5 330.79836 -43.28355
6 370.38964 330.79836
7 786.92965 370.38964
8 1331.43494 786.92965
9 1126.50928 1331.43494
10 194.83590 1126.50928
11 322.42030 194.83590
12 -295.70468 322.42030
13 -1713.99594 -295.70468
14 -1232.66198 -1713.99594
15 -858.98107 -1232.66198
16 -146.46680 -858.98107
17 -921.01356 -146.46680
18 -555.56214 -921.01356
19 -993.09179 -555.56214
20 -625.28283 -993.09179
21 -725.51802 -625.28283
22 -1078.86907 -725.51802
23 -822.99649 -1078.86907
24 -449.84219 -822.99649
25 -778.94441 -449.84219
26 -813.10391 -778.94441
27 74.92970 -813.10391
28 336.31471 74.92970
29 -257.85382 336.31471
30 -20.26509 -257.85382
31 -349.94862 -20.26509
32 -1537.56796 -349.94862
33 -1720.34079 -1537.56796
34 -1419.85751 -1720.34079
35 -1173.47976 -1419.85751
36 -1445.30742 -1173.47976
37 -1662.15442 -1445.30742
38 -1974.89311 -1662.15442
39 -104.33147 -1974.89311
40 955.10612 -104.33147
41 1810.29370 955.10612
42 3262.45816 1810.29370
43 3384.08449 3262.45816
44 2789.55022 3384.08449
45 2609.22951 2789.55022
46 2792.97178 2609.22951
47 2194.35936 2792.97178
48 1879.74672 2194.35936
49 1164.52340 1879.74672
50 1398.96723 1164.52340
51 1273.69383 1398.96723
52 1207.73691 1273.69383
53 522.50062 1207.73691
54 726.60429 522.50062
55 702.49629 726.60429
56 1620.17861 702.49629
57 1976.99557 1620.17861
58 843.55262 1976.99557
59 1191.56448 843.55262
60 843.02682 1191.56448
61 -629.37403 843.02682
62 -1875.62387 -629.37403
63 -2557.31843 -1875.62387
64 -3676.19573 -2557.31843
65 -4314.96883 -3676.19573
66 -4537.52250 -4314.96883
67 -1725.71839 -4537.52250
68 5658.12756 -1725.71839
69 -2345.91702 5658.12756
70 -3998.10966 -2345.91702
71 2791.70016 -3998.10966
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/7m2ae1291415244.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/8m2ae1291415244.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/9m2ae1291415244.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/10ftaz1291415244.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/freestat/rcomp/tmp/11juq51291415244.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
+ a<-table.element(a,mysum$coefficients[i,1])
+ a<-table.element(a, round(mysum$coefficients[i,2],6))
+ a<-table.element(a, round(mysum$coefficients[i,3],4))
+ a<-table.element(a, round(mysum$coefficients[i,4],6))
+ a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/freestat/rcomp/tmp/124cot1291415244.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$r.squared))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a, mysum$r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a, mysum$adj.r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[1])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a, mysum$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/freestat/rcomp/tmp/1304m21291415244.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/freestat/rcomp/tmp/143m3q1291415244.tab")
> if (n > n25) {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'p-values',header=TRUE)
+ a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'breakpoint index',header=TRUE)
+ a<-table.element(a,'greater',header=TRUE)
+ a<-table.element(a,'2-sided',header=TRUE)
+ a<-table.element(a,'less',header=TRUE)
+ a<-table.row.end(a)
+ for (mypoint in kp3:nmkm3) {
+ a<-table.row.start(a)
+ a<-table.element(a,mypoint,header=TRUE)
+ a<-table.element(a,gqarr[mypoint-kp3+1,1])
+ a<-table.element(a,gqarr[mypoint-kp3+1,2])
+ a<-table.element(a,gqarr[mypoint-kp3+1,3])
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/freestat/rcomp/tmp/15pn1d1291415244.tab")
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Description',header=TRUE)
+ a<-table.element(a,'# significant tests',header=TRUE)
+ a<-table.element(a,'% significant tests',header=TRUE)
+ a<-table.element(a,'OK/NOK',header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'1% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant1)
+ a<-table.element(a,numsignificant1/numgqtests)
+ if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'5% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant5)
+ a<-table.element(a,numsignificant5/numgqtests)
+ if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'10% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant10)
+ a<-table.element(a,numsignificant10/numgqtests)
+ if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/freestat/rcomp/tmp/16s5011291415244.tab")
+ }
>
> try(system("convert tmp/1qac61291415244.ps tmp/1qac61291415244.png",intern=TRUE))
character(0)
> try(system("convert tmp/2qac61291415244.ps tmp/2qac61291415244.png",intern=TRUE))
character(0)
> try(system("convert tmp/31jc81291415244.ps tmp/31jc81291415244.png",intern=TRUE))
character(0)
> try(system("convert tmp/41jc81291415244.ps tmp/41jc81291415244.png",intern=TRUE))
character(0)
> try(system("convert tmp/51jc81291415244.ps tmp/51jc81291415244.png",intern=TRUE))
character(0)
> try(system("convert tmp/6uttb1291415244.ps tmp/6uttb1291415244.png",intern=TRUE))
character(0)
> try(system("convert tmp/7m2ae1291415244.ps tmp/7m2ae1291415244.png",intern=TRUE))
character(0)
> try(system("convert tmp/8m2ae1291415244.ps tmp/8m2ae1291415244.png",intern=TRUE))
character(0)
> try(system("convert tmp/9m2ae1291415244.ps tmp/9m2ae1291415244.png",intern=TRUE))
character(0)
> try(system("convert tmp/10ftaz1291415244.ps tmp/10ftaz1291415244.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
4.043 2.467 4.374