R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
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Type 'license()' or 'licence()' for distribution details.
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Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
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> x <- array(list(1579,0,2146,0,2462,0,3695,0,4831,0,5134,0,6250,0,5760,0,6249,0,2917,0,1741,0,2359,0,1511,1,2059,0,2635,0,2867,0,4403,0,5720,0,4502,0,5749,0,5627,0,2846,0,1762,0,2429,0,1169,0,2154,1,2249,0,2687,0,4359,0,5382,0,4459,0,6398,0,4596,0,3024,0,1887,0,2070,0,1351,0,2218,0,2461,1,3028,0,4784,0,4975,0,4607,0,6249,0,4809,0,3157,0,1910,0,2228,0,1594,0,2467,0,2222,0,3607,1,4685,0,4962,0,5770,0,5480,0,5000,0,3228,0,1993,0,2288,0,1580,0,2111,0,2192,0,3601,0,4665,1,4876,0,5813,0,5589,0,5331,0,3075,0,2002,0,2306,0,1507,0,1992,0,2487,0,3490,0,4647,0,5594,1,5611,0,5788,0,6204,0,3013,0,1931,0,2549,0,1504,0,2090,0,2702,0,2939,0,4500,0,6208,0,6415,1,5657,0,5964,0,3163,0,1997,0,2422,0,1376,0,2202,0,2683,0,3303,0,5202,0,5231,0,4880,0,7998,1,4977,0,3531,0,2025,0,2205,0,1442,0,2238,0,2179,0,3218,0,5139,0,4990,0,4914,0,6084,0,5672,1,3548,0,1793,0,2086,0),dim=c(2,120),dimnames=list(c('Y','X'),1:120))
> y <- array(NA,dim=c(2,120),dimnames=list(c('Y','X'),1:120))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from package:base :
as.Date.numeric
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
Y X
1 1579 0
2 2146 0
3 2462 0
4 3695 0
5 4831 0
6 5134 0
7 6250 0
8 5760 0
9 6249 0
10 2917 0
11 1741 0
12 2359 0
13 1511 1
14 2059 0
15 2635 0
16 2867 0
17 4403 0
18 5720 0
19 4502 0
20 5749 0
21 5627 0
22 2846 0
23 1762 0
24 2429 0
25 1169 0
26 2154 1
27 2249 0
28 2687 0
29 4359 0
30 5382 0
31 4459 0
32 6398 0
33 4596 0
34 3024 0
35 1887 0
36 2070 0
37 1351 0
38 2218 0
39 2461 1
40 3028 0
41 4784 0
42 4975 0
43 4607 0
44 6249 0
45 4809 0
46 3157 0
47 1910 0
48 2228 0
49 1594 0
50 2467 0
51 2222 0
52 3607 1
53 4685 0
54 4962 0
55 5770 0
56 5480 0
57 5000 0
58 3228 0
59 1993 0
60 2288 0
61 1580 0
62 2111 0
63 2192 0
64 3601 0
65 4665 1
66 4876 0
67 5813 0
68 5589 0
69 5331 0
70 3075 0
71 2002 0
72 2306 0
73 1507 0
74 1992 0
75 2487 0
76 3490 0
77 4647 0
78 5594 1
79 5611 0
80 5788 0
81 6204 0
82 3013 0
83 1931 0
84 2549 0
85 1504 0
86 2090 0
87 2702 0
88 2939 0
89 4500 0
90 6208 0
91 6415 1
92 5657 0
93 5964 0
94 3163 0
95 1997 0
96 2422 0
97 1376 0
98 2202 0
99 2683 0
100 3303 0
101 5202 0
102 5231 0
103 4880 0
104 7998 1
105 4977 0
106 3531 0
107 2025 0
108 2205 0
109 1442 0
110 2238 0
111 2179 0
112 3218 0
113 5139 0
114 4990 0
115 4914 0
116 6084 0
117 5672 1
118 3548 0
119 1793 0
120 2086 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X
3559.4 893.6
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-2942.0 -1370.7 -443.4 1416.1 3545.0
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 3559.4 153.1 23.256 <2e-16 ***
X 893.6 558.9 1.599 0.113
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1613 on 118 degrees of freedom
Multiple R-squared: 0.02121, Adjusted R-squared: 0.01291
F-statistic: 2.557 on 1 and 118 DF, p-value: 0.1125
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 0.5393774 0.9212453 0.4606226
[2,] 0.6042868 0.7914263 0.3957132
[3,] 0.7728707 0.4542586 0.2271293
[4,] 0.7852053 0.4295894 0.2147947
[5,] 0.8228507 0.3542986 0.1771493
[6,] 0.7833802 0.4332397 0.2166198
[7,] 0.8213717 0.3572567 0.1786283
[8,] 0.7994928 0.4010144 0.2005072
[9,] 0.7578599 0.4842801 0.2421401
[10,] 0.7511083 0.4977834 0.2488917
[11,] 0.7034644 0.5930712 0.2965356
[12,] 0.6414744 0.7170512 0.3585256
[13,] 0.5857619 0.8284762 0.4142381
[14,] 0.6334934 0.7330131 0.3665066
[15,] 0.5786723 0.8426554 0.4213277
[16,] 0.6150754 0.7698492 0.3849246
[17,] 0.6309274 0.7381452 0.3690726
[18,] 0.5887004 0.8225992 0.4112996
[19,] 0.6239289 0.7521423 0.3760711
[20,] 0.5990956 0.8018087 0.4009044
[21,] 0.6791165 0.6417671 0.3208835
[22,] 0.6638568 0.6722864 0.3361432
[23,] 0.6449326 0.7101348 0.3550674
[24,] 0.6019685 0.7960630 0.3980315
[25,] 0.5560805 0.8878391 0.4439195
[26,] 0.5724098 0.8551803 0.4275902
[27,] 0.5286918 0.9426164 0.4713082
[28,] 0.6439407 0.7121186 0.3560593
[29,] 0.6059896 0.7880207 0.3940104
[30,] 0.5583216 0.8833569 0.4416784
[31,] 0.5721427 0.8557145 0.4278573
[32,] 0.5693327 0.8613346 0.4306673
[33,] 0.6230772 0.7538456 0.3769228
[34,] 0.6069130 0.7861741 0.3930870
[35,] 0.6187764 0.7624473 0.3812236
[36,] 0.5700883 0.8598233 0.4299117
[37,] 0.5487735 0.9024530 0.4512265
[38,] 0.5378990 0.9242019 0.4621010
[39,] 0.5062921 0.9874157 0.4937079
[40,] 0.6072469 0.7855062 0.3927531
[41,] 0.5852446 0.8295108 0.4147554
[42,] 0.5363963 0.9272073 0.4636037
[43,] 0.5459107 0.9081785 0.4540893
[44,] 0.5328715 0.9342569 0.4671285
[45,] 0.5648427 0.8703146 0.4351573
[46,] 0.5377121 0.9245758 0.4622879
[47,] 0.5231179 0.9537641 0.4768821
[48,] 0.5402513 0.9194974 0.4597487
[49,] 0.5151040 0.9697920 0.4848960
[50,] 0.5050348 0.9899304 0.4949652
[51,] 0.5581762 0.8836477 0.4418238
[52,] 0.5848686 0.8302628 0.4151314
[53,] 0.5773410 0.8453181 0.4226590
[54,] 0.5278471 0.9443057 0.4721529
[55,] 0.5292950 0.9414100 0.4707050
[56,] 0.5120356 0.9759289 0.4879644
[57,] 0.5446351 0.9107298 0.4553649
[58,] 0.5376110 0.9247780 0.4623890
[59,] 0.5257269 0.9485461 0.4742731
[60,] 0.4729462 0.9458924 0.5270538
[61,] 0.4891066 0.9782132 0.5108934
[62,] 0.4737957 0.9475914 0.5262043
[63,] 0.5321354 0.9357291 0.4678646
[64,] 0.5707753 0.8584493 0.4292247
[65,] 0.5892117 0.8215765 0.4107883
[66,] 0.5409990 0.9180021 0.4590010
[67,] 0.5389521 0.9220957 0.4610479
[68,] 0.5186192 0.9627616 0.4813808
[69,] 0.5568746 0.8862509 0.4431254
[70,] 0.5575721 0.8848557 0.4424279
[71,] 0.5296314 0.9407372 0.4703686
[72,] 0.4750564 0.9501129 0.5249436
[73,] 0.4461937 0.8923875 0.5538063
[74,] 0.4528615 0.9057230 0.5471385
[75,] 0.4917888 0.9835776 0.5082112
[76,] 0.5519723 0.8960554 0.4480277
[77,] 0.6632536 0.6734928 0.3367464
[78,] 0.6142905 0.7714189 0.3857095
[79,] 0.6136309 0.7727383 0.3863691
[80,] 0.5780631 0.8438737 0.4219369
[81,] 0.6162124 0.7675753 0.3837876
[82,] 0.6095121 0.7809758 0.3904879
[83,] 0.5695834 0.8608331 0.4304166
[84,] 0.5202148 0.9595704 0.4797852
[85,] 0.4796024 0.9592047 0.5203976
[86,] 0.5942482 0.8115037 0.4057518
[87,] 0.5801998 0.8396004 0.4198002
[88,] 0.6354868 0.7290264 0.3645132
[89,] 0.7333799 0.5332402 0.2666201
[90,] 0.6776321 0.6447358 0.3223679
[91,] 0.6662555 0.6674890 0.3337445
[92,] 0.6296013 0.7407973 0.3703987
[93,] 0.6830921 0.6338158 0.3169079
[94,] 0.6674714 0.6650572 0.3325286
[95,] 0.6232807 0.7534386 0.3767193
[96,] 0.5546725 0.8906550 0.4453275
[97,] 0.5570151 0.8859699 0.4429849
[98,] 0.5710504 0.8578991 0.4289496
[99,] 0.5593702 0.8812597 0.4406298
[100,] 0.6116985 0.7766030 0.3883015
[101,] 0.6180744 0.7638512 0.3819256
[102,] 0.5346925 0.9306149 0.4653075
[103,] 0.5004003 0.9991994 0.4995997
[104,] 0.4555282 0.9110564 0.5444718
[105,] 0.5163778 0.9672444 0.4836222
[106,] 0.4942856 0.9885711 0.5057144
[107,] 0.5002797 0.9994406 0.4997203
[108,] 0.4087047 0.8174094 0.5912953
[109,] 0.3447712 0.6895424 0.6552288
[110,] 0.2788510 0.5577021 0.7211490
[111,] 0.2237614 0.4475228 0.7762386
> postscript(file="/var/www/html/rcomp/tmp/16xg01290865899.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2hpx21290865899.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3hpx21290865899.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4hpx21290865899.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5rye51290865899.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> qqline(mysum$resid)
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 120
Frequency = 1
1 2 3 4 5 6
-1980.40541 -1413.40541 -1097.40541 135.59459 1271.59459 1574.59459
7 8 9 10 11 12
2690.59459 2200.59459 2689.59459 -642.40541 -1818.40541 -1200.40541
13 14 15 16 17 18
-2942.00000 -1500.40541 -924.40541 -692.40541 843.59459 2160.59459
19 20 21 22 23 24
942.59459 2189.59459 2067.59459 -713.40541 -1797.40541 -1130.40541
25 26 27 28 29 30
-2390.40541 -2299.00000 -1310.40541 -872.40541 799.59459 1822.59459
31 32 33 34 35 36
899.59459 2838.59459 1036.59459 -535.40541 -1672.40541 -1489.40541
37 38 39 40 41 42
-2208.40541 -1341.40541 -1992.00000 -531.40541 1224.59459 1415.59459
43 44 45 46 47 48
1047.59459 2689.59459 1249.59459 -402.40541 -1649.40541 -1331.40541
49 50 51 52 53 54
-1965.40541 -1092.40541 -1337.40541 -846.00000 1125.59459 1402.59459
55 56 57 58 59 60
2210.59459 1920.59459 1440.59459 -331.40541 -1566.40541 -1271.40541
61 62 63 64 65 66
-1979.40541 -1448.40541 -1367.40541 41.59459 212.00000 1316.59459
67 68 69 70 71 72
2253.59459 2029.59459 1771.59459 -484.40541 -1557.40541 -1253.40541
73 74 75 76 77 78
-2052.40541 -1567.40541 -1072.40541 -69.40541 1087.59459 1141.00000
79 80 81 82 83 84
2051.59459 2228.59459 2644.59459 -546.40541 -1628.40541 -1010.40541
85 86 87 88 89 90
-2055.40541 -1469.40541 -857.40541 -620.40541 940.59459 2648.59459
91 92 93 94 95 96
1962.00000 2097.59459 2404.59459 -396.40541 -1562.40541 -1137.40541
97 98 99 100 101 102
-2183.40541 -1357.40541 -876.40541 -256.40541 1642.59459 1671.59459
103 104 105 106 107 108
1320.59459 3545.00000 1417.59459 -28.40541 -1534.40541 -1354.40541
109 110 111 112 113 114
-2117.40541 -1321.40541 -1380.40541 -341.40541 1579.59459 1430.59459
115 116 117 118 119 120
1354.59459 2524.59459 1219.00000 -11.40541 -1766.40541 -1473.40541
> postscript(file="/var/www/html/rcomp/tmp/6rye51290865899.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 120
Frequency = 1
lag(myerror, k = 1) myerror
0 -1980.40541 NA
1 -1413.40541 -1980.40541
2 -1097.40541 -1413.40541
3 135.59459 -1097.40541
4 1271.59459 135.59459
5 1574.59459 1271.59459
6 2690.59459 1574.59459
7 2200.59459 2690.59459
8 2689.59459 2200.59459
9 -642.40541 2689.59459
10 -1818.40541 -642.40541
11 -1200.40541 -1818.40541
12 -2942.00000 -1200.40541
13 -1500.40541 -2942.00000
14 -924.40541 -1500.40541
15 -692.40541 -924.40541
16 843.59459 -692.40541
17 2160.59459 843.59459
18 942.59459 2160.59459
19 2189.59459 942.59459
20 2067.59459 2189.59459
21 -713.40541 2067.59459
22 -1797.40541 -713.40541
23 -1130.40541 -1797.40541
24 -2390.40541 -1130.40541
25 -2299.00000 -2390.40541
26 -1310.40541 -2299.00000
27 -872.40541 -1310.40541
28 799.59459 -872.40541
29 1822.59459 799.59459
30 899.59459 1822.59459
31 2838.59459 899.59459
32 1036.59459 2838.59459
33 -535.40541 1036.59459
34 -1672.40541 -535.40541
35 -1489.40541 -1672.40541
36 -2208.40541 -1489.40541
37 -1341.40541 -2208.40541
38 -1992.00000 -1341.40541
39 -531.40541 -1992.00000
40 1224.59459 -531.40541
41 1415.59459 1224.59459
42 1047.59459 1415.59459
43 2689.59459 1047.59459
44 1249.59459 2689.59459
45 -402.40541 1249.59459
46 -1649.40541 -402.40541
47 -1331.40541 -1649.40541
48 -1965.40541 -1331.40541
49 -1092.40541 -1965.40541
50 -1337.40541 -1092.40541
51 -846.00000 -1337.40541
52 1125.59459 -846.00000
53 1402.59459 1125.59459
54 2210.59459 1402.59459
55 1920.59459 2210.59459
56 1440.59459 1920.59459
57 -331.40541 1440.59459
58 -1566.40541 -331.40541
59 -1271.40541 -1566.40541
60 -1979.40541 -1271.40541
61 -1448.40541 -1979.40541
62 -1367.40541 -1448.40541
63 41.59459 -1367.40541
64 212.00000 41.59459
65 1316.59459 212.00000
66 2253.59459 1316.59459
67 2029.59459 2253.59459
68 1771.59459 2029.59459
69 -484.40541 1771.59459
70 -1557.40541 -484.40541
71 -1253.40541 -1557.40541
72 -2052.40541 -1253.40541
73 -1567.40541 -2052.40541
74 -1072.40541 -1567.40541
75 -69.40541 -1072.40541
76 1087.59459 -69.40541
77 1141.00000 1087.59459
78 2051.59459 1141.00000
79 2228.59459 2051.59459
80 2644.59459 2228.59459
81 -546.40541 2644.59459
82 -1628.40541 -546.40541
83 -1010.40541 -1628.40541
84 -2055.40541 -1010.40541
85 -1469.40541 -2055.40541
86 -857.40541 -1469.40541
87 -620.40541 -857.40541
88 940.59459 -620.40541
89 2648.59459 940.59459
90 1962.00000 2648.59459
91 2097.59459 1962.00000
92 2404.59459 2097.59459
93 -396.40541 2404.59459
94 -1562.40541 -396.40541
95 -1137.40541 -1562.40541
96 -2183.40541 -1137.40541
97 -1357.40541 -2183.40541
98 -876.40541 -1357.40541
99 -256.40541 -876.40541
100 1642.59459 -256.40541
101 1671.59459 1642.59459
102 1320.59459 1671.59459
103 3545.00000 1320.59459
104 1417.59459 3545.00000
105 -28.40541 1417.59459
106 -1534.40541 -28.40541
107 -1354.40541 -1534.40541
108 -2117.40541 -1354.40541
109 -1321.40541 -2117.40541
110 -1380.40541 -1321.40541
111 -341.40541 -1380.40541
112 1579.59459 -341.40541
113 1430.59459 1579.59459
114 1354.59459 1430.59459
115 2524.59459 1354.59459
116 1219.00000 2524.59459
117 -11.40541 1219.00000
118 -1766.40541 -11.40541
119 -1473.40541 -1766.40541
120 NA -1473.40541
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -1413.40541 -1980.40541
[2,] -1097.40541 -1413.40541
[3,] 135.59459 -1097.40541
[4,] 1271.59459 135.59459
[5,] 1574.59459 1271.59459
[6,] 2690.59459 1574.59459
[7,] 2200.59459 2690.59459
[8,] 2689.59459 2200.59459
[9,] -642.40541 2689.59459
[10,] -1818.40541 -642.40541
[11,] -1200.40541 -1818.40541
[12,] -2942.00000 -1200.40541
[13,] -1500.40541 -2942.00000
[14,] -924.40541 -1500.40541
[15,] -692.40541 -924.40541
[16,] 843.59459 -692.40541
[17,] 2160.59459 843.59459
[18,] 942.59459 2160.59459
[19,] 2189.59459 942.59459
[20,] 2067.59459 2189.59459
[21,] -713.40541 2067.59459
[22,] -1797.40541 -713.40541
[23,] -1130.40541 -1797.40541
[24,] -2390.40541 -1130.40541
[25,] -2299.00000 -2390.40541
[26,] -1310.40541 -2299.00000
[27,] -872.40541 -1310.40541
[28,] 799.59459 -872.40541
[29,] 1822.59459 799.59459
[30,] 899.59459 1822.59459
[31,] 2838.59459 899.59459
[32,] 1036.59459 2838.59459
[33,] -535.40541 1036.59459
[34,] -1672.40541 -535.40541
[35,] -1489.40541 -1672.40541
[36,] -2208.40541 -1489.40541
[37,] -1341.40541 -2208.40541
[38,] -1992.00000 -1341.40541
[39,] -531.40541 -1992.00000
[40,] 1224.59459 -531.40541
[41,] 1415.59459 1224.59459
[42,] 1047.59459 1415.59459
[43,] 2689.59459 1047.59459
[44,] 1249.59459 2689.59459
[45,] -402.40541 1249.59459
[46,] -1649.40541 -402.40541
[47,] -1331.40541 -1649.40541
[48,] -1965.40541 -1331.40541
[49,] -1092.40541 -1965.40541
[50,] -1337.40541 -1092.40541
[51,] -846.00000 -1337.40541
[52,] 1125.59459 -846.00000
[53,] 1402.59459 1125.59459
[54,] 2210.59459 1402.59459
[55,] 1920.59459 2210.59459
[56,] 1440.59459 1920.59459
[57,] -331.40541 1440.59459
[58,] -1566.40541 -331.40541
[59,] -1271.40541 -1566.40541
[60,] -1979.40541 -1271.40541
[61,] -1448.40541 -1979.40541
[62,] -1367.40541 -1448.40541
[63,] 41.59459 -1367.40541
[64,] 212.00000 41.59459
[65,] 1316.59459 212.00000
[66,] 2253.59459 1316.59459
[67,] 2029.59459 2253.59459
[68,] 1771.59459 2029.59459
[69,] -484.40541 1771.59459
[70,] -1557.40541 -484.40541
[71,] -1253.40541 -1557.40541
[72,] -2052.40541 -1253.40541
[73,] -1567.40541 -2052.40541
[74,] -1072.40541 -1567.40541
[75,] -69.40541 -1072.40541
[76,] 1087.59459 -69.40541
[77,] 1141.00000 1087.59459
[78,] 2051.59459 1141.00000
[79,] 2228.59459 2051.59459
[80,] 2644.59459 2228.59459
[81,] -546.40541 2644.59459
[82,] -1628.40541 -546.40541
[83,] -1010.40541 -1628.40541
[84,] -2055.40541 -1010.40541
[85,] -1469.40541 -2055.40541
[86,] -857.40541 -1469.40541
[87,] -620.40541 -857.40541
[88,] 940.59459 -620.40541
[89,] 2648.59459 940.59459
[90,] 1962.00000 2648.59459
[91,] 2097.59459 1962.00000
[92,] 2404.59459 2097.59459
[93,] -396.40541 2404.59459
[94,] -1562.40541 -396.40541
[95,] -1137.40541 -1562.40541
[96,] -2183.40541 -1137.40541
[97,] -1357.40541 -2183.40541
[98,] -876.40541 -1357.40541
[99,] -256.40541 -876.40541
[100,] 1642.59459 -256.40541
[101,] 1671.59459 1642.59459
[102,] 1320.59459 1671.59459
[103,] 3545.00000 1320.59459
[104,] 1417.59459 3545.00000
[105,] -28.40541 1417.59459
[106,] -1534.40541 -28.40541
[107,] -1354.40541 -1534.40541
[108,] -2117.40541 -1354.40541
[109,] -1321.40541 -2117.40541
[110,] -1380.40541 -1321.40541
[111,] -341.40541 -1380.40541
[112,] 1579.59459 -341.40541
[113,] 1430.59459 1579.59459
[114,] 1354.59459 1430.59459
[115,] 2524.59459 1354.59459
[116,] 1219.00000 2524.59459
[117,] -11.40541 1219.00000
[118,] -1766.40541 -11.40541
[119,] -1473.40541 -1766.40541
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -1413.40541 -1980.40541
2 -1097.40541 -1413.40541
3 135.59459 -1097.40541
4 1271.59459 135.59459
5 1574.59459 1271.59459
6 2690.59459 1574.59459
7 2200.59459 2690.59459
8 2689.59459 2200.59459
9 -642.40541 2689.59459
10 -1818.40541 -642.40541
11 -1200.40541 -1818.40541
12 -2942.00000 -1200.40541
13 -1500.40541 -2942.00000
14 -924.40541 -1500.40541
15 -692.40541 -924.40541
16 843.59459 -692.40541
17 2160.59459 843.59459
18 942.59459 2160.59459
19 2189.59459 942.59459
20 2067.59459 2189.59459
21 -713.40541 2067.59459
22 -1797.40541 -713.40541
23 -1130.40541 -1797.40541
24 -2390.40541 -1130.40541
25 -2299.00000 -2390.40541
26 -1310.40541 -2299.00000
27 -872.40541 -1310.40541
28 799.59459 -872.40541
29 1822.59459 799.59459
30 899.59459 1822.59459
31 2838.59459 899.59459
32 1036.59459 2838.59459
33 -535.40541 1036.59459
34 -1672.40541 -535.40541
35 -1489.40541 -1672.40541
36 -2208.40541 -1489.40541
37 -1341.40541 -2208.40541
38 -1992.00000 -1341.40541
39 -531.40541 -1992.00000
40 1224.59459 -531.40541
41 1415.59459 1224.59459
42 1047.59459 1415.59459
43 2689.59459 1047.59459
44 1249.59459 2689.59459
45 -402.40541 1249.59459
46 -1649.40541 -402.40541
47 -1331.40541 -1649.40541
48 -1965.40541 -1331.40541
49 -1092.40541 -1965.40541
50 -1337.40541 -1092.40541
51 -846.00000 -1337.40541
52 1125.59459 -846.00000
53 1402.59459 1125.59459
54 2210.59459 1402.59459
55 1920.59459 2210.59459
56 1440.59459 1920.59459
57 -331.40541 1440.59459
58 -1566.40541 -331.40541
59 -1271.40541 -1566.40541
60 -1979.40541 -1271.40541
61 -1448.40541 -1979.40541
62 -1367.40541 -1448.40541
63 41.59459 -1367.40541
64 212.00000 41.59459
65 1316.59459 212.00000
66 2253.59459 1316.59459
67 2029.59459 2253.59459
68 1771.59459 2029.59459
69 -484.40541 1771.59459
70 -1557.40541 -484.40541
71 -1253.40541 -1557.40541
72 -2052.40541 -1253.40541
73 -1567.40541 -2052.40541
74 -1072.40541 -1567.40541
75 -69.40541 -1072.40541
76 1087.59459 -69.40541
77 1141.00000 1087.59459
78 2051.59459 1141.00000
79 2228.59459 2051.59459
80 2644.59459 2228.59459
81 -546.40541 2644.59459
82 -1628.40541 -546.40541
83 -1010.40541 -1628.40541
84 -2055.40541 -1010.40541
85 -1469.40541 -2055.40541
86 -857.40541 -1469.40541
87 -620.40541 -857.40541
88 940.59459 -620.40541
89 2648.59459 940.59459
90 1962.00000 2648.59459
91 2097.59459 1962.00000
92 2404.59459 2097.59459
93 -396.40541 2404.59459
94 -1562.40541 -396.40541
95 -1137.40541 -1562.40541
96 -2183.40541 -1137.40541
97 -1357.40541 -2183.40541
98 -876.40541 -1357.40541
99 -256.40541 -876.40541
100 1642.59459 -256.40541
101 1671.59459 1642.59459
102 1320.59459 1671.59459
103 3545.00000 1320.59459
104 1417.59459 3545.00000
105 -28.40541 1417.59459
106 -1534.40541 -28.40541
107 -1354.40541 -1534.40541
108 -2117.40541 -1354.40541
109 -1321.40541 -2117.40541
110 -1380.40541 -1321.40541
111 -341.40541 -1380.40541
112 1579.59459 -341.40541
113 1430.59459 1579.59459
114 1354.59459 1430.59459
115 2524.59459 1354.59459
116 1219.00000 2524.59459
117 -11.40541 1219.00000
118 -1766.40541 -11.40541
119 -1473.40541 -1766.40541
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/727eq1290865899.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/827eq1290865899.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9vgdt1290865899.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10vgdt1290865899.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/11yzuh1290865899.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
+ a<-table.element(a,mysum$coefficients[i,1])
+ a<-table.element(a, round(mysum$coefficients[i,2],6))
+ a<-table.element(a, round(mysum$coefficients[i,3],4))
+ a<-table.element(a, round(mysum$coefficients[i,4],6))
+ a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/12kzan1290865899.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$r.squared))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a, mysum$r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a, mysum$adj.r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[1])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a, mysum$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/13yr8w1290865899.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/14jsok1290865899.tab")
> if (n > n25) {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'p-values',header=TRUE)
+ a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'breakpoint index',header=TRUE)
+ a<-table.element(a,'greater',header=TRUE)
+ a<-table.element(a,'2-sided',header=TRUE)
+ a<-table.element(a,'less',header=TRUE)
+ a<-table.row.end(a)
+ for (mypoint in kp3:nmkm3) {
+ a<-table.row.start(a)
+ a<-table.element(a,mypoint,header=TRUE)
+ a<-table.element(a,gqarr[mypoint-kp3+1,1])
+ a<-table.element(a,gqarr[mypoint-kp3+1,2])
+ a<-table.element(a,gqarr[mypoint-kp3+1,3])
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/rcomp/tmp/154anp1290865899.tab")
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Description',header=TRUE)
+ a<-table.element(a,'# significant tests',header=TRUE)
+ a<-table.element(a,'% significant tests',header=TRUE)
+ a<-table.element(a,'OK/NOK',header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'1% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant1)
+ a<-table.element(a,numsignificant1/numgqtests)
+ if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'5% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant5)
+ a<-table.element(a,numsignificant5/numgqtests)
+ if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'10% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant10)
+ a<-table.element(a,numsignificant10/numgqtests)
+ if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/rcomp/tmp/16qtlv1290865899.tab")
+ }
>
> try(system("convert tmp/16xg01290865899.ps tmp/16xg01290865899.png",intern=TRUE))
character(0)
> try(system("convert tmp/2hpx21290865899.ps tmp/2hpx21290865899.png",intern=TRUE))
character(0)
> try(system("convert tmp/3hpx21290865899.ps tmp/3hpx21290865899.png",intern=TRUE))
character(0)
> try(system("convert tmp/4hpx21290865899.ps tmp/4hpx21290865899.png",intern=TRUE))
character(0)
> try(system("convert tmp/5rye51290865899.ps tmp/5rye51290865899.png",intern=TRUE))
character(0)
> try(system("convert tmp/6rye51290865899.ps tmp/6rye51290865899.png",intern=TRUE))
character(0)
> try(system("convert tmp/727eq1290865899.ps tmp/727eq1290865899.png",intern=TRUE))
character(0)
> try(system("convert tmp/827eq1290865899.ps tmp/827eq1290865899.png",intern=TRUE))
character(0)
> try(system("convert tmp/9vgdt1290865899.ps tmp/9vgdt1290865899.png",intern=TRUE))
character(0)
> try(system("convert tmp/10vgdt1290865899.ps tmp/10vgdt1290865899.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.371 1.791 8.893