R version 2.6.0 (2007-10-03)
Copyright (C) 2007 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(1687
+ ,0
+ ,-183.9235445
+ ,1508
+ ,0
+ ,-177.0726091
+ ,1507
+ ,0
+ ,-228.6351091
+ ,1385
+ ,0
+ ,-237.4476091
+ ,1632
+ ,0
+ ,-127.7601091
+ ,1511
+ ,0
+ ,-193.0101091
+ ,1559
+ ,0
+ ,-220.6351091
+ ,1630
+ ,0
+ ,-164.5101091
+ ,1579
+ ,0
+ ,-268.3226091
+ ,1653
+ ,0
+ ,-333.6976091
+ ,2152
+ ,0
+ ,-34.26010911
+ ,2148
+ ,0
+ ,-154.8851091
+ ,1752
+ ,0
+ ,-97.74528053
+ ,1765
+ ,0
+ ,101.1056549
+ ,1717
+ ,0
+ ,2.543154874
+ ,1558
+ ,0
+ ,-43.26934513
+ ,1575
+ ,0
+ ,-163.5818451
+ ,1520
+ ,0
+ ,-162.8318451
+ ,1805
+ ,0
+ ,46.54315487
+ ,1800
+ ,0
+ ,26.66815487
+ ,1719
+ ,0
+ ,-107.1443451
+ ,2008
+ ,0
+ ,42.48065487
+ ,2242
+ ,0
+ ,76.91815487
+ ,2478
+ ,0
+ ,196.2931549
+ ,2030
+ ,0
+ ,201.4329835
+ ,1655
+ ,0
+ ,12.28391886
+ ,1693
+ ,0
+ ,-0.278581137
+ ,1623
+ ,0
+ ,42.90891886
+ ,1805
+ ,0
+ ,87.59641886
+ ,1746
+ ,0
+ ,84.34641886
+ ,1795
+ ,0
+ ,57.72141886
+ ,1926
+ ,0
+ ,173.8464189
+ ,1619
+ ,0
+ ,-185.9660811
+ ,1992
+ ,0
+ ,47.65891886
+ ,2233
+ ,0
+ ,89.09641886
+ ,2192
+ ,0
+ ,-68.52858114
+ ,2080
+ ,0
+ ,272.6112475
+ ,1768
+ ,0
+ ,146.4621829
+ ,1835
+ ,0
+ ,162.8996829
+ ,1569
+ ,0
+ ,10.08718285
+ ,1976
+ ,0
+ ,279.7746829
+ ,1853
+ ,0
+ ,212.5246829
+ ,1965
+ ,0
+ ,248.8996829
+ ,1689
+ ,0
+ ,-41.97531715
+ ,1778
+ ,0
+ ,-5.787817149
+ ,1976
+ ,0
+ ,52.83718285
+ ,2397
+ ,0
+ ,274.2746829
+ ,2654
+ ,0
+ ,414.6496829
+ ,2097
+ ,0
+ ,310.7895114
+ ,1963
+ ,0
+ ,362.6404468
+ ,1677
+ ,0
+ ,26.07794684
+ ,1941
+ ,0
+ ,403.2654468
+ ,2003
+ ,0
+ ,327.9529468
+ ,1813
+ ,0
+ ,193.7029468
+ ,2012
+ ,0
+ ,317.0779468
+ ,1912
+ ,0
+ ,202.2029468
+ ,2084
+ ,0
+ ,321.3904468
+ ,2080
+ ,0
+ ,178.0154468
+ ,2118
+ ,0
+ ,16.45294684
+ ,2150
+ ,0
+ ,-68.17205316
+ ,1608
+ ,0
+ ,-157.0322246
+ ,1503
+ ,0
+ ,-76.18128917
+ ,1548
+ ,0
+ ,-81.74378917
+ ,1382
+ ,0
+ ,-134.5562892
+ ,1731
+ ,0
+ ,77.13121083
+ ,1798
+ ,0
+ ,199.8812108
+ ,1779
+ ,0
+ ,105.2562108
+ ,1887
+ ,0
+ ,198.3812108
+ ,2004
+ ,0
+ ,262.5687108
+ ,2077
+ ,0
+ ,196.1937108
+ ,2092
+ ,0
+ ,11.63121083
+ ,2051
+ ,0
+ ,-145.9937892
+ ,1577
+ ,0
+ ,-166.8539606
+ ,1356
+ ,0
+ ,-202.0030252
+ ,1652
+ ,0
+ ,43.43447482
+ ,1382
+ ,0
+ ,-113.3780252
+ ,1519
+ ,0
+ ,-113.6905252
+ ,1421
+ ,0
+ ,-155.9405252
+ ,1442
+ ,0
+ ,-210.5655252
+ ,1543
+ ,0
+ ,-124.4405252
+ ,1656
+ ,0
+ ,-64.25302518
+ ,1561
+ ,0
+ ,-298.6280252
+ ,1905
+ ,0
+ ,-154.1905252
+ ,2199
+ ,0
+ ,23.18447482
+ ,1473
+ ,0
+ ,-249.6756966
+ ,1655
+ ,0
+ ,118.1752388
+ ,1407
+ ,0
+ ,-180.3872612
+ ,1395
+ ,0
+ ,-79.19976119
+ ,1530
+ ,0
+ ,-81.51226119
+ ,1309
+ ,0
+ ,-246.7622612
+ ,1526
+ ,0
+ ,-105.3872612
+ ,1327
+ ,0
+ ,-319.2622612
+ ,1627
+ ,0
+ ,-72.07476119
+ ,1748
+ ,0
+ ,-90.44976119
+ ,1958
+ ,0
+ ,-80.01226119
+ ,2274
+ ,0
+ ,119.3627388
+ ,1648
+ ,0
+ ,-53.49743261
+ ,1401
+ ,0
+ ,-114.6464972
+ ,1411
+ ,0
+ ,-155.2089972
+ ,1403
+ ,0
+ ,-50.02149721
+ ,1394
+ ,0
+ ,-196.3339972
+ ,1520
+ ,0
+ ,-14.58399721
+ ,1528
+ ,0
+ ,-82.20899721
+ ,1643
+ ,0
+ ,17.91600279
+ ,1515
+ ,0
+ ,-162.8964972
+ ,1685
+ ,0
+ ,-132.2714972
+ ,2000
+ ,0
+ ,-16.83399721
+ ,2215
+ ,0
+ ,81.54100279
+ ,1956
+ ,0
+ ,275.6808314
+ ,1462
+ ,0
+ ,-32.46823322
+ ,1563
+ ,0
+ ,17.96926678
+ ,1459
+ ,0
+ ,27.15676678
+ ,1446
+ ,0
+ ,-123.1557332
+ ,1622
+ ,0
+ ,108.5942668
+ ,1657
+ ,0
+ ,67.96926678
+ ,1638
+ ,0
+ ,34.09426678
+ ,1643
+ ,0
+ ,-13.71823322
+ ,1683
+ ,0
+ ,-113.0932332
+ ,2050
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+ ,54.34426678
+ ,2262
+ ,0
+ ,149.7192668
+ ,1813
+ ,0
+ ,153.8590954
+ ,1445
+ ,0
+ ,-28.28996923
+ ,1762
+ ,0
+ ,238.1475308
+ ,1461
+ ,0
+ ,50.33503077
+ ,1556
+ ,0
+ ,8.022530771
+ ,1431
+ ,0
+ ,-61.22746923
+ ,1427
+ ,0
+ ,-140.8524692
+ ,1554
+ ,0
+ ,-28.72746923
+ ,1645
+ ,0
+ ,9.460030771
+ ,1653
+ ,0
+ ,-121.9149692
+ ,2016
+ ,0
+ ,41.52253077
+ ,2207
+ ,0
+ ,115.8975308
+ ,1665
+ ,0
+ ,27.03735936
+ ,1361
+ ,0
+ ,-91.11170524
+ ,1506
+ ,0
+ ,3.325794759
+ ,1360
+ ,0
+ ,-29.48670524
+ ,1453
+ ,0
+ ,-73.79920524
+ ,1522
+ ,0
+ ,50.95079476
+ ,1460
+ ,0
+ ,-86.67420524
+ ,1552
+ ,0
+ ,-9.54920524
+ ,1548
+ ,0
+ ,-66.36170524
+ ,1827
+ ,0
+ ,73.26329476
+ ,1737
+ ,0
+ ,-216.2992052
+ ,1941
+ ,0
+ ,-128.9242052
+ ,1474
+ ,0
+ ,-142.7843767
+ ,1458
+ ,0
+ ,27.06655875
+ ,1542
+ ,0
+ ,60.50405875
+ ,1404
+ ,0
+ ,35.69155875
+ ,1522
+ ,0
+ ,16.37905875
+ ,1385
+ ,0
+ ,-64.87094125
+ ,1641
+ ,0
+ ,115.5040587
+ ,1510
+ ,0
+ ,-30.37094125
+ ,1681
+ ,0
+ ,87.81655875
+ ,1938
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+ ,205.4415587
+ ,1868
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+ ,-64.12094125
+ ,1726
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+ ,-322.7459413
+ ,1456
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+ ,-139.6061127
+ ,1445
+ ,0
+ ,35.24482274
+ ,1456
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+ ,-4.317677263
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+ ,17.86982274
+ ,1487
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+ ,2.557322737
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+ ,-16.31767726
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+ ,21.99482274
+ ,1850
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+ ,138.6198227
+ ,1998
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+ ,87.05732274
+ ,2079
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+ ,51.43232274
+ ,1494
+ ,0
+ ,-80.42784867
+ ,1057
+ ,1
+ ,-105.1918797
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+ ,5.245620328
+ ,1168
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+ ,68.43312033
+ ,1236
+ ,1
+ ,-0.879379672
+ ,1076
+ ,1
+ ,-105.1293797
+ ,1174
+ ,1
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+ ,1139
+ ,1
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+ ,1427
+ ,1
+ ,102.5581203
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+ ,1
+ ,23.18312033
+ ,1483
+ ,1
+ ,-180.3793797
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+ ,1357
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+ ,30.13544892
+ ,1165
+ ,1
+ ,23.98638432
+ ,1282
+ ,1
+ ,90.42388432
+ ,1110
+ ,1
+ ,31.61138432
+ ,1297
+ ,1
+ ,81.29888432
+ ,1185
+ ,1
+ ,25.04888432
+ ,1222
+ ,1
+ ,-13.57611568
+ ,1284
+ ,1
+ ,33.54888432
+ ,1444
+ ,1
+ ,140.7363843
+ ,1575
+ ,1
+ ,132.3613843
+ ,1737
+ ,1
+ ,94.79888432
+ ,1763
+ ,1
+ ,4.173884316)
+ ,dim=c(3
+ ,192)
+ ,dimnames=list(c('Slacht'
+ ,'wet'
+ ,'')
+ ,1:192))
> y <- array(NA,dim=c(3,192),dimnames=list(c('Slacht','wet',''),1:192))
> 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)
> 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
Slacht wet
1 1687 0 -183.9235445
2 1508 0 -177.0726091
3 1507 0 -228.6351091
4 1385 0 -237.4476091
5 1632 0 -127.7601091
6 1511 0 -193.0101091
7 1559 0 -220.6351091
8 1630 0 -164.5101091
9 1579 0 -268.3226091
10 1653 0 -333.6976091
11 2152 0 -34.2601091
12 2148 0 -154.8851091
13 1752 0 -97.7452805
14 1765 0 101.1056549
15 1717 0 2.5431549
16 1558 0 -43.2693451
17 1575 0 -163.5818451
18 1520 0 -162.8318451
19 1805 0 46.5431549
20 1800 0 26.6681549
21 1719 0 -107.1443451
22 2008 0 42.4806549
23 2242 0 76.9181549
24 2478 0 196.2931549
25 2030 0 201.4329835
26 1655 0 12.2839189
27 1693 0 -0.2785811
28 1623 0 42.9089189
29 1805 0 87.5964189
30 1746 0 84.3464189
31 1795 0 57.7214189
32 1926 0 173.8464189
33 1619 0 -185.9660811
34 1992 0 47.6589189
35 2233 0 89.0964189
36 2192 0 -68.5285811
37 2080 0 272.6112475
38 1768 0 146.4621829
39 1835 0 162.8996829
40 1569 0 10.0871828
41 1976 0 279.7746829
42 1853 0 212.5246829
43 1965 0 248.8996829
44 1689 0 -41.9753172
45 1778 0 -5.7878171
46 1976 0 52.8371828
47 2397 0 274.2746829
48 2654 0 414.6496829
49 2097 0 310.7895114
50 1963 0 362.6404468
51 1677 0 26.0779468
52 1941 0 403.2654468
53 2003 0 327.9529468
54 1813 0 193.7029468
55 2012 0 317.0779468
56 1912 0 202.2029468
57 2084 0 321.3904468
58 2080 0 178.0154468
59 2118 0 16.4529468
60 2150 0 -68.1720532
61 1608 0 -157.0322246
62 1503 0 -76.1812892
63 1548 0 -81.7437892
64 1382 0 -134.5562892
65 1731 0 77.1312108
66 1798 0 199.8812108
67 1779 0 105.2562108
68 1887 0 198.3812108
69 2004 0 262.5687108
70 2077 0 196.1937108
71 2092 0 11.6312108
72 2051 0 -145.9937892
73 1577 0 -166.8539606
74 1356 0 -202.0030252
75 1652 0 43.4344748
76 1382 0 -113.3780252
77 1519 0 -113.6905252
78 1421 0 -155.9405252
79 1442 0 -210.5655252
80 1543 0 -124.4405252
81 1656 0 -64.2530252
82 1561 0 -298.6280252
83 1905 0 -154.1905252
84 2199 0 23.1844748
85 1473 0 -249.6756966
86 1655 0 118.1752388
87 1407 0 -180.3872612
88 1395 0 -79.1997612
89 1530 0 -81.5122612
90 1309 0 -246.7622612
91 1526 0 -105.3872612
92 1327 0 -319.2622612
93 1627 0 -72.0747612
94 1748 0 -90.4497612
95 1958 0 -80.0122612
96 2274 0 119.3627388
97 1648 0 -53.4974326
98 1401 0 -114.6464972
99 1411 0 -155.2089972
100 1403 0 -50.0214972
101 1394 0 -196.3339972
102 1520 0 -14.5839972
103 1528 0 -82.2089972
104 1643 0 17.9160028
105 1515 0 -162.8964972
106 1685 0 -132.2714972
107 2000 0 -16.8339972
108 2215 0 81.5410028
109 1956 0 275.6808314
110 1462 0 -32.4682332
111 1563 0 17.9692668
112 1459 0 27.1567668
113 1446 0 -123.1557332
114 1622 0 108.5942668
115 1657 0 67.9692668
116 1638 0 34.0942668
117 1643 0 -13.7182332
118 1683 0 -113.0932332
119 2050 0 54.3442668
120 2262 0 149.7192668
121 1813 0 153.8590954
122 1445 0 -28.2899692
123 1762 0 238.1475308
124 1461 0 50.3350308
125 1556 0 8.0225308
126 1431 0 -61.2274692
127 1427 0 -140.8524692
128 1554 0 -28.7274692
129 1645 0 9.4600308
130 1653 0 -121.9149692
131 2016 0 41.5225308
132 2207 0 115.8975308
133 1665 0 27.0373594
134 1361 0 -91.1117052
135 1506 0 3.3257948
136 1360 0 -29.4867052
137 1453 0 -73.7992052
138 1522 0 50.9507948
139 1460 0 -86.6742052
140 1552 0 -9.5492052
141 1548 0 -66.3617052
142 1827 0 73.2632948
143 1737 0 -216.2992052
144 1941 0 -128.9242052
145 1474 0 -142.7843767
146 1458 0 27.0665587
147 1542 0 60.5040587
148 1404 0 35.6915587
149 1522 0 16.3790587
150 1385 0 -64.8709413
151 1641 0 115.5040587
152 1510 0 -30.3709413
153 1681 0 87.8165587
154 1938 0 205.4415587
155 1868 0 -64.1209413
156 1726 0 -322.7459413
157 1456 0 -139.6061127
158 1445 0 35.2448227
159 1456 0 -4.3176773
160 1365 0 17.8698227
161 1487 0 2.5573227
162 1558 0 129.3073227
163 1488 0 -16.3176773
164 1684 0 164.8073227
165 1594 0 21.9948227
166 1850 0 138.6198227
167 1998 0 87.0573227
168 2079 0 51.4323227
169 1494 0 -80.4278487
170 1057 1 -105.1918797
171 1218 1 5.2456203
172 1168 1 68.4331203
173 1236 1 -0.8793797
174 1076 1 -105.1293797
175 1174 1 -82.7543797
176 1139 1 -132.6293797
177 1427 1 102.5581203
178 1487 1 23.1831203
179 1483 1 -180.3793797
180 1513 1 -267.0043797
181 1357 1 30.1354489
182 1165 1 23.9863843
183 1282 1 90.4238843
184 1110 1 31.6113843
185 1297 1 81.2988843
186 1185 1 25.0488843
187 1222 1 -13.5761157
188 1284 1 33.5488843
189 1444 1 140.7363843
190 1575 1 132.3613843
191 1737 1 94.7988843
192 1763 1 4.1738843
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) wet V3
1717.8 -396.1 1.0
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-370.62 -148.92 -52.08 92.11 585.13
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1717.7515 16.5127 104.026 < 2e-16 ***
wet -396.0558 47.7094 -8.301 1.93e-14 ***
V3 1.0000 0.1056 9.473 < 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 214.7 on 189 degrees of freedom
Multiple R-Squared: 0.4564, Adjusted R-squared: 0.4506
F-statistic: 79.33 on 2 and 189 DF, p-value: < 2.2e-16
> postscript(file="/var/www/html/rcomp/tmp/19ebb1195122538.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/2pzym1195122538.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/329xs1195122538.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4iif81195122538.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5jqea1195122538.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 192
Frequency = 1
1 2 3 4 5 6
153.1720652 -32.6788702 17.8836298 -95.3038702 42.0086298 -13.7413702
7 8 9 10 11 12
61.8836298 76.7586298 129.5711298 268.9461298 468.5086298 585.1336298
13 14 15 16 17 18
131.9938012 -53.8571342 -3.2946342 -116.4821342 20.8303658 -34.9196342
19 20 21 22 23 24
40.7053658 55.5803658 108.3928658 247.7678658 447.3303658 563.9553658
25 26 27 28 29 30
110.8155372 -75.0353982 -24.4728982 -137.6603982 -0.3478982 -56.0978982
31 32 33 34 35 36
19.5271018 34.4021018 87.2146018 226.5896018 426.1521018 542.7771019
37 38 39 40 41 42
89.6372732 -96.2136622 -45.6511622 -158.8386621 -21.5261622 -77.2761622
43 44 45 46 47 48
-1.6511622 13.2238379 66.0363379 205.4113379 404.9738378 521.5988378
49 50 51 52 53 54
68.4590093 -117.3919261 -66.8294261 -180.0169261 -42.7044261 -98.4544261
55 56 57 58 59 60
-22.8294261 -7.9544261 44.8580739 184.2330739 383.7955739 500.4205739
61 62 63 64 65 66
47.2807453 -138.5701901 -88.0076901 -201.1951901 -63.8826901 -119.6326901
67 68 69 70 71 72
-44.0076901 -29.1326901 23.6798099 163.0548099 362.6173099 479.2423099
73 74 75 76 77 78
26.1024813 -159.7484541 -109.1859541 -222.3734541 -85.0609541 -140.8109541
79 80 81 82 83 84
-65.1859541 -50.3109541 2.5015459 141.8765459 341.4390459 458.0640459
85 86 87 88 89 90
4.9242173 -180.9267181 -130.3642181 -243.5517181 -106.2392181 -161.9892181
91 92 93 94 95 96
-86.3642181 -71.4892181 -18.6767181 120.6982819 320.2607819 436.8857819
97 98 99 100 101 102
-16.2540467 -202.1049821 -151.5424821 -264.7299821 -127.4174821 -183.1674821
103 104 105 106 107 108
-107.5424821 -92.6674821 -39.8549821 99.5200179 299.0825179 415.7075179
109 110 111 112 113 114
-37.4323107 -223.2832461 -172.7207461 -285.9082461 -148.5957461 -204.3457461
115 116 117 118 119 120
-128.7207461 -113.8457461 -61.0332461 78.3417539 277.9042539 394.5292539
121 122 123 124 125 126
-58.6105747 -244.4615101 -193.8990101 -307.0865101 -169.7740101 -225.5240101
127 128 129 130 131 132
-149.8990101 -135.0240101 -82.2115101 57.1634899 256.7259899 373.3509899
133 134 135 136 137 138
-79.7888387 -265.6397740 -215.0772740 -328.2647740 -190.9522740 -246.7022741
139 140 141 142 143 144
-171.0772740 -156.2022740 -103.3897740 35.9852259 235.5477259 352.1727259
145 146 147 148 149 150
-100.9671026 -286.8180380 -236.2555380 -349.4430380 -212.1305380 -267.8805380
151 152 153 154 155 156
-192.2555380 -177.3805380 -124.5680380 14.8069620 214.3694620 330.9944620
157 158 159 160 161 162
-122.1453666 -307.9963020 -257.4338020 -370.6213020 -233.3088020 -289.0588020
163 164 165 166 167 168
-213.4338020 -198.5588020 -145.7463020 -6.3713020 193.1911980 309.8161980
169 170 171 172 173 174
-143.3236306 -159.5037725 -108.9412725 -222.1287725 -84.8162725 -140.5662725
175 176 177 178 179 180
-64.9412725 -50.0662725 2.7462275 142.1212275 341.6837275 458.3087275
181 182 183 184 185 186
5.1688989 -180.6820365 -130.1195365 -243.3070365 -105.9945365 -161.7445365
187 188 189 190 191 192
-86.1195365 -71.2445365 -18.4320365 120.9429635 320.5054635 437.1304635
> postscript(file="/var/www/html/rcomp/tmp/6edl21195122538.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 = 192
Frequency = 1
lag(myerror, k = 1) myerror
0 153.1720652 NA
1 -32.6788702 153.1720652
2 17.8836298 -32.6788702
3 -95.3038702 17.8836298
4 42.0086298 -95.3038702
5 -13.7413702 42.0086298
6 61.8836298 -13.7413702
7 76.7586298 61.8836298
8 129.5711298 76.7586298
9 268.9461298 129.5711298
10 468.5086298 268.9461298
11 585.1336298 468.5086298
12 131.9938012 585.1336298
13 -53.8571342 131.9938012
14 -3.2946342 -53.8571342
15 -116.4821342 -3.2946342
16 20.8303658 -116.4821342
17 -34.9196342 20.8303658
18 40.7053658 -34.9196342
19 55.5803658 40.7053658
20 108.3928658 55.5803658
21 247.7678658 108.3928658
22 447.3303658 247.7678658
23 563.9553658 447.3303658
24 110.8155372 563.9553658
25 -75.0353982 110.8155372
26 -24.4728982 -75.0353982
27 -137.6603982 -24.4728982
28 -0.3478982 -137.6603982
29 -56.0978982 -0.3478982
30 19.5271018 -56.0978982
31 34.4021018 19.5271018
32 87.2146018 34.4021018
33 226.5896018 87.2146018
34 426.1521018 226.5896018
35 542.7771019 426.1521018
36 89.6372732 542.7771019
37 -96.2136622 89.6372732
38 -45.6511622 -96.2136622
39 -158.8386621 -45.6511622
40 -21.5261622 -158.8386621
41 -77.2761622 -21.5261622
42 -1.6511622 -77.2761622
43 13.2238379 -1.6511622
44 66.0363379 13.2238379
45 205.4113379 66.0363379
46 404.9738378 205.4113379
47 521.5988378 404.9738378
48 68.4590093 521.5988378
49 -117.3919261 68.4590093
50 -66.8294261 -117.3919261
51 -180.0169261 -66.8294261
52 -42.7044261 -180.0169261
53 -98.4544261 -42.7044261
54 -22.8294261 -98.4544261
55 -7.9544261 -22.8294261
56 44.8580739 -7.9544261
57 184.2330739 44.8580739
58 383.7955739 184.2330739
59 500.4205739 383.7955739
60 47.2807453 500.4205739
61 -138.5701901 47.2807453
62 -88.0076901 -138.5701901
63 -201.1951901 -88.0076901
64 -63.8826901 -201.1951901
65 -119.6326901 -63.8826901
66 -44.0076901 -119.6326901
67 -29.1326901 -44.0076901
68 23.6798099 -29.1326901
69 163.0548099 23.6798099
70 362.6173099 163.0548099
71 479.2423099 362.6173099
72 26.1024813 479.2423099
73 -159.7484541 26.1024813
74 -109.1859541 -159.7484541
75 -222.3734541 -109.1859541
76 -85.0609541 -222.3734541
77 -140.8109541 -85.0609541
78 -65.1859541 -140.8109541
79 -50.3109541 -65.1859541
80 2.5015459 -50.3109541
81 141.8765459 2.5015459
82 341.4390459 141.8765459
83 458.0640459 341.4390459
84 4.9242173 458.0640459
85 -180.9267181 4.9242173
86 -130.3642181 -180.9267181
87 -243.5517181 -130.3642181
88 -106.2392181 -243.5517181
89 -161.9892181 -106.2392181
90 -86.3642181 -161.9892181
91 -71.4892181 -86.3642181
92 -18.6767181 -71.4892181
93 120.6982819 -18.6767181
94 320.2607819 120.6982819
95 436.8857819 320.2607819
96 -16.2540467 436.8857819
97 -202.1049821 -16.2540467
98 -151.5424821 -202.1049821
99 -264.7299821 -151.5424821
100 -127.4174821 -264.7299821
101 -183.1674821 -127.4174821
102 -107.5424821 -183.1674821
103 -92.6674821 -107.5424821
104 -39.8549821 -92.6674821
105 99.5200179 -39.8549821
106 299.0825179 99.5200179
107 415.7075179 299.0825179
108 -37.4323107 415.7075179
109 -223.2832461 -37.4323107
110 -172.7207461 -223.2832461
111 -285.9082461 -172.7207461
112 -148.5957461 -285.9082461
113 -204.3457461 -148.5957461
114 -128.7207461 -204.3457461
115 -113.8457461 -128.7207461
116 -61.0332461 -113.8457461
117 78.3417539 -61.0332461
118 277.9042539 78.3417539
119 394.5292539 277.9042539
120 -58.6105747 394.5292539
121 -244.4615101 -58.6105747
122 -193.8990101 -244.4615101
123 -307.0865101 -193.8990101
124 -169.7740101 -307.0865101
125 -225.5240101 -169.7740101
126 -149.8990101 -225.5240101
127 -135.0240101 -149.8990101
128 -82.2115101 -135.0240101
129 57.1634899 -82.2115101
130 256.7259899 57.1634899
131 373.3509899 256.7259899
132 -79.7888387 373.3509899
133 -265.6397740 -79.7888387
134 -215.0772740 -265.6397740
135 -328.2647740 -215.0772740
136 -190.9522740 -328.2647740
137 -246.7022741 -190.9522740
138 -171.0772740 -246.7022741
139 -156.2022740 -171.0772740
140 -103.3897740 -156.2022740
141 35.9852259 -103.3897740
142 235.5477259 35.9852259
143 352.1727259 235.5477259
144 -100.9671026 352.1727259
145 -286.8180380 -100.9671026
146 -236.2555380 -286.8180380
147 -349.4430380 -236.2555380
148 -212.1305380 -349.4430380
149 -267.8805380 -212.1305380
150 -192.2555380 -267.8805380
151 -177.3805380 -192.2555380
152 -124.5680380 -177.3805380
153 14.8069620 -124.5680380
154 214.3694620 14.8069620
155 330.9944620 214.3694620
156 -122.1453666 330.9944620
157 -307.9963020 -122.1453666
158 -257.4338020 -307.9963020
159 -370.6213020 -257.4338020
160 -233.3088020 -370.6213020
161 -289.0588020 -233.3088020
162 -213.4338020 -289.0588020
163 -198.5588020 -213.4338020
164 -145.7463020 -198.5588020
165 -6.3713020 -145.7463020
166 193.1911980 -6.3713020
167 309.8161980 193.1911980
168 -143.3236306 309.8161980
169 -159.5037725 -143.3236306
170 -108.9412725 -159.5037725
171 -222.1287725 -108.9412725
172 -84.8162725 -222.1287725
173 -140.5662725 -84.8162725
174 -64.9412725 -140.5662725
175 -50.0662725 -64.9412725
176 2.7462275 -50.0662725
177 142.1212275 2.7462275
178 341.6837275 142.1212275
179 458.3087275 341.6837275
180 5.1688989 458.3087275
181 -180.6820365 5.1688989
182 -130.1195365 -180.6820365
183 -243.3070365 -130.1195365
184 -105.9945365 -243.3070365
185 -161.7445365 -105.9945365
186 -86.1195365 -161.7445365
187 -71.2445365 -86.1195365
188 -18.4320365 -71.2445365
189 120.9429635 -18.4320365
190 320.5054635 120.9429635
191 437.1304635 320.5054635
192 NA 437.1304635
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -32.6788702 153.1720652
[2,] 17.8836298 -32.6788702
[3,] -95.3038702 17.8836298
[4,] 42.0086298 -95.3038702
[5,] -13.7413702 42.0086298
[6,] 61.8836298 -13.7413702
[7,] 76.7586298 61.8836298
[8,] 129.5711298 76.7586298
[9,] 268.9461298 129.5711298
[10,] 468.5086298 268.9461298
[11,] 585.1336298 468.5086298
[12,] 131.9938012 585.1336298
[13,] -53.8571342 131.9938012
[14,] -3.2946342 -53.8571342
[15,] -116.4821342 -3.2946342
[16,] 20.8303658 -116.4821342
[17,] -34.9196342 20.8303658
[18,] 40.7053658 -34.9196342
[19,] 55.5803658 40.7053658
[20,] 108.3928658 55.5803658
[21,] 247.7678658 108.3928658
[22,] 447.3303658 247.7678658
[23,] 563.9553658 447.3303658
[24,] 110.8155372 563.9553658
[25,] -75.0353982 110.8155372
[26,] -24.4728982 -75.0353982
[27,] -137.6603982 -24.4728982
[28,] -0.3478982 -137.6603982
[29,] -56.0978982 -0.3478982
[30,] 19.5271018 -56.0978982
[31,] 34.4021018 19.5271018
[32,] 87.2146018 34.4021018
[33,] 226.5896018 87.2146018
[34,] 426.1521018 226.5896018
[35,] 542.7771019 426.1521018
[36,] 89.6372732 542.7771019
[37,] -96.2136622 89.6372732
[38,] -45.6511622 -96.2136622
[39,] -158.8386621 -45.6511622
[40,] -21.5261622 -158.8386621
[41,] -77.2761622 -21.5261622
[42,] -1.6511622 -77.2761622
[43,] 13.2238379 -1.6511622
[44,] 66.0363379 13.2238379
[45,] 205.4113379 66.0363379
[46,] 404.9738378 205.4113379
[47,] 521.5988378 404.9738378
[48,] 68.4590093 521.5988378
[49,] -117.3919261 68.4590093
[50,] -66.8294261 -117.3919261
[51,] -180.0169261 -66.8294261
[52,] -42.7044261 -180.0169261
[53,] -98.4544261 -42.7044261
[54,] -22.8294261 -98.4544261
[55,] -7.9544261 -22.8294261
[56,] 44.8580739 -7.9544261
[57,] 184.2330739 44.8580739
[58,] 383.7955739 184.2330739
[59,] 500.4205739 383.7955739
[60,] 47.2807453 500.4205739
[61,] -138.5701901 47.2807453
[62,] -88.0076901 -138.5701901
[63,] -201.1951901 -88.0076901
[64,] -63.8826901 -201.1951901
[65,] -119.6326901 -63.8826901
[66,] -44.0076901 -119.6326901
[67,] -29.1326901 -44.0076901
[68,] 23.6798099 -29.1326901
[69,] 163.0548099 23.6798099
[70,] 362.6173099 163.0548099
[71,] 479.2423099 362.6173099
[72,] 26.1024813 479.2423099
[73,] -159.7484541 26.1024813
[74,] -109.1859541 -159.7484541
[75,] -222.3734541 -109.1859541
[76,] -85.0609541 -222.3734541
[77,] -140.8109541 -85.0609541
[78,] -65.1859541 -140.8109541
[79,] -50.3109541 -65.1859541
[80,] 2.5015459 -50.3109541
[81,] 141.8765459 2.5015459
[82,] 341.4390459 141.8765459
[83,] 458.0640459 341.4390459
[84,] 4.9242173 458.0640459
[85,] -180.9267181 4.9242173
[86,] -130.3642181 -180.9267181
[87,] -243.5517181 -130.3642181
[88,] -106.2392181 -243.5517181
[89,] -161.9892181 -106.2392181
[90,] -86.3642181 -161.9892181
[91,] -71.4892181 -86.3642181
[92,] -18.6767181 -71.4892181
[93,] 120.6982819 -18.6767181
[94,] 320.2607819 120.6982819
[95,] 436.8857819 320.2607819
[96,] -16.2540467 436.8857819
[97,] -202.1049821 -16.2540467
[98,] -151.5424821 -202.1049821
[99,] -264.7299821 -151.5424821
[100,] -127.4174821 -264.7299821
[101,] -183.1674821 -127.4174821
[102,] -107.5424821 -183.1674821
[103,] -92.6674821 -107.5424821
[104,] -39.8549821 -92.6674821
[105,] 99.5200179 -39.8549821
[106,] 299.0825179 99.5200179
[107,] 415.7075179 299.0825179
[108,] -37.4323107 415.7075179
[109,] -223.2832461 -37.4323107
[110,] -172.7207461 -223.2832461
[111,] -285.9082461 -172.7207461
[112,] -148.5957461 -285.9082461
[113,] -204.3457461 -148.5957461
[114,] -128.7207461 -204.3457461
[115,] -113.8457461 -128.7207461
[116,] -61.0332461 -113.8457461
[117,] 78.3417539 -61.0332461
[118,] 277.9042539 78.3417539
[119,] 394.5292539 277.9042539
[120,] -58.6105747 394.5292539
[121,] -244.4615101 -58.6105747
[122,] -193.8990101 -244.4615101
[123,] -307.0865101 -193.8990101
[124,] -169.7740101 -307.0865101
[125,] -225.5240101 -169.7740101
[126,] -149.8990101 -225.5240101
[127,] -135.0240101 -149.8990101
[128,] -82.2115101 -135.0240101
[129,] 57.1634899 -82.2115101
[130,] 256.7259899 57.1634899
[131,] 373.3509899 256.7259899
[132,] -79.7888387 373.3509899
[133,] -265.6397740 -79.7888387
[134,] -215.0772740 -265.6397740
[135,] -328.2647740 -215.0772740
[136,] -190.9522740 -328.2647740
[137,] -246.7022741 -190.9522740
[138,] -171.0772740 -246.7022741
[139,] -156.2022740 -171.0772740
[140,] -103.3897740 -156.2022740
[141,] 35.9852259 -103.3897740
[142,] 235.5477259 35.9852259
[143,] 352.1727259 235.5477259
[144,] -100.9671026 352.1727259
[145,] -286.8180380 -100.9671026
[146,] -236.2555380 -286.8180380
[147,] -349.4430380 -236.2555380
[148,] -212.1305380 -349.4430380
[149,] -267.8805380 -212.1305380
[150,] -192.2555380 -267.8805380
[151,] -177.3805380 -192.2555380
[152,] -124.5680380 -177.3805380
[153,] 14.8069620 -124.5680380
[154,] 214.3694620 14.8069620
[155,] 330.9944620 214.3694620
[156,] -122.1453666 330.9944620
[157,] -307.9963020 -122.1453666
[158,] -257.4338020 -307.9963020
[159,] -370.6213020 -257.4338020
[160,] -233.3088020 -370.6213020
[161,] -289.0588020 -233.3088020
[162,] -213.4338020 -289.0588020
[163,] -198.5588020 -213.4338020
[164,] -145.7463020 -198.5588020
[165,] -6.3713020 -145.7463020
[166,] 193.1911980 -6.3713020
[167,] 309.8161980 193.1911980
[168,] -143.3236306 309.8161980
[169,] -159.5037725 -143.3236306
[170,] -108.9412725 -159.5037725
[171,] -222.1287725 -108.9412725
[172,] -84.8162725 -222.1287725
[173,] -140.5662725 -84.8162725
[174,] -64.9412725 -140.5662725
[175,] -50.0662725 -64.9412725
[176,] 2.7462275 -50.0662725
[177,] 142.1212275 2.7462275
[178,] 341.6837275 142.1212275
[179,] 458.3087275 341.6837275
[180,] 5.1688989 458.3087275
[181,] -180.6820365 5.1688989
[182,] -130.1195365 -180.6820365
[183,] -243.3070365 -130.1195365
[184,] -105.9945365 -243.3070365
[185,] -161.7445365 -105.9945365
[186,] -86.1195365 -161.7445365
[187,] -71.2445365 -86.1195365
[188,] -18.4320365 -71.2445365
[189,] 120.9429635 -18.4320365
[190,] 320.5054635 120.9429635
[191,] 437.1304635 320.5054635
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -32.6788702 153.1720652
2 17.8836298 -32.6788702
3 -95.3038702 17.8836298
4 42.0086298 -95.3038702
5 -13.7413702 42.0086298
6 61.8836298 -13.7413702
7 76.7586298 61.8836298
8 129.5711298 76.7586298
9 268.9461298 129.5711298
10 468.5086298 268.9461298
11 585.1336298 468.5086298
12 131.9938012 585.1336298
13 -53.8571342 131.9938012
14 -3.2946342 -53.8571342
15 -116.4821342 -3.2946342
16 20.8303658 -116.4821342
17 -34.9196342 20.8303658
18 40.7053658 -34.9196342
19 55.5803658 40.7053658
20 108.3928658 55.5803658
21 247.7678658 108.3928658
22 447.3303658 247.7678658
23 563.9553658 447.3303658
24 110.8155372 563.9553658
25 -75.0353982 110.8155372
26 -24.4728982 -75.0353982
27 -137.6603982 -24.4728982
28 -0.3478982 -137.6603982
29 -56.0978982 -0.3478982
30 19.5271018 -56.0978982
31 34.4021018 19.5271018
32 87.2146018 34.4021018
33 226.5896018 87.2146018
34 426.1521018 226.5896018
35 542.7771019 426.1521018
36 89.6372732 542.7771019
37 -96.2136622 89.6372732
38 -45.6511622 -96.2136622
39 -158.8386621 -45.6511622
40 -21.5261622 -158.8386621
41 -77.2761622 -21.5261622
42 -1.6511622 -77.2761622
43 13.2238379 -1.6511622
44 66.0363379 13.2238379
45 205.4113379 66.0363379
46 404.9738378 205.4113379
47 521.5988378 404.9738378
48 68.4590093 521.5988378
49 -117.3919261 68.4590093
50 -66.8294261 -117.3919261
51 -180.0169261 -66.8294261
52 -42.7044261 -180.0169261
53 -98.4544261 -42.7044261
54 -22.8294261 -98.4544261
55 -7.9544261 -22.8294261
56 44.8580739 -7.9544261
57 184.2330739 44.8580739
58 383.7955739 184.2330739
59 500.4205739 383.7955739
60 47.2807453 500.4205739
61 -138.5701901 47.2807453
62 -88.0076901 -138.5701901
63 -201.1951901 -88.0076901
64 -63.8826901 -201.1951901
65 -119.6326901 -63.8826901
66 -44.0076901 -119.6326901
67 -29.1326901 -44.0076901
68 23.6798099 -29.1326901
69 163.0548099 23.6798099
70 362.6173099 163.0548099
71 479.2423099 362.6173099
72 26.1024813 479.2423099
73 -159.7484541 26.1024813
74 -109.1859541 -159.7484541
75 -222.3734541 -109.1859541
76 -85.0609541 -222.3734541
77 -140.8109541 -85.0609541
78 -65.1859541 -140.8109541
79 -50.3109541 -65.1859541
80 2.5015459 -50.3109541
81 141.8765459 2.5015459
82 341.4390459 141.8765459
83 458.0640459 341.4390459
84 4.9242173 458.0640459
85 -180.9267181 4.9242173
86 -130.3642181 -180.9267181
87 -243.5517181 -130.3642181
88 -106.2392181 -243.5517181
89 -161.9892181 -106.2392181
90 -86.3642181 -161.9892181
91 -71.4892181 -86.3642181
92 -18.6767181 -71.4892181
93 120.6982819 -18.6767181
94 320.2607819 120.6982819
95 436.8857819 320.2607819
96 -16.2540467 436.8857819
97 -202.1049821 -16.2540467
98 -151.5424821 -202.1049821
99 -264.7299821 -151.5424821
100 -127.4174821 -264.7299821
101 -183.1674821 -127.4174821
102 -107.5424821 -183.1674821
103 -92.6674821 -107.5424821
104 -39.8549821 -92.6674821
105 99.5200179 -39.8549821
106 299.0825179 99.5200179
107 415.7075179 299.0825179
108 -37.4323107 415.7075179
109 -223.2832461 -37.4323107
110 -172.7207461 -223.2832461
111 -285.9082461 -172.7207461
112 -148.5957461 -285.9082461
113 -204.3457461 -148.5957461
114 -128.7207461 -204.3457461
115 -113.8457461 -128.7207461
116 -61.0332461 -113.8457461
117 78.3417539 -61.0332461
118 277.9042539 78.3417539
119 394.5292539 277.9042539
120 -58.6105747 394.5292539
121 -244.4615101 -58.6105747
122 -193.8990101 -244.4615101
123 -307.0865101 -193.8990101
124 -169.7740101 -307.0865101
125 -225.5240101 -169.7740101
126 -149.8990101 -225.5240101
127 -135.0240101 -149.8990101
128 -82.2115101 -135.0240101
129 57.1634899 -82.2115101
130 256.7259899 57.1634899
131 373.3509899 256.7259899
132 -79.7888387 373.3509899
133 -265.6397740 -79.7888387
134 -215.0772740 -265.6397740
135 -328.2647740 -215.0772740
136 -190.9522740 -328.2647740
137 -246.7022741 -190.9522740
138 -171.0772740 -246.7022741
139 -156.2022740 -171.0772740
140 -103.3897740 -156.2022740
141 35.9852259 -103.3897740
142 235.5477259 35.9852259
143 352.1727259 235.5477259
144 -100.9671026 352.1727259
145 -286.8180380 -100.9671026
146 -236.2555380 -286.8180380
147 -349.4430380 -236.2555380
148 -212.1305380 -349.4430380
149 -267.8805380 -212.1305380
150 -192.2555380 -267.8805380
151 -177.3805380 -192.2555380
152 -124.5680380 -177.3805380
153 14.8069620 -124.5680380
154 214.3694620 14.8069620
155 330.9944620 214.3694620
156 -122.1453666 330.9944620
157 -307.9963020 -122.1453666
158 -257.4338020 -307.9963020
159 -370.6213020 -257.4338020
160 -233.3088020 -370.6213020
161 -289.0588020 -233.3088020
162 -213.4338020 -289.0588020
163 -198.5588020 -213.4338020
164 -145.7463020 -198.5588020
165 -6.3713020 -145.7463020
166 193.1911980 -6.3713020
167 309.8161980 193.1911980
168 -143.3236306 309.8161980
169 -159.5037725 -143.3236306
170 -108.9412725 -159.5037725
171 -222.1287725 -108.9412725
172 -84.8162725 -222.1287725
173 -140.5662725 -84.8162725
174 -64.9412725 -140.5662725
175 -50.0662725 -64.9412725
176 2.7462275 -50.0662725
177 142.1212275 2.7462275
178 341.6837275 142.1212275
179 458.3087275 341.6837275
180 5.1688989 458.3087275
181 -180.6820365 5.1688989
182 -130.1195365 -180.6820365
183 -243.3070365 -130.1195365
184 -105.9945365 -243.3070365
185 -161.7445365 -105.9945365
186 -86.1195365 -161.7445365
187 -71.2445365 -86.1195365
188 -18.4320365 -71.2445365
189 120.9429635 -18.4320365
190 320.5054635 120.9429635
191 437.1304635 320.5054635
> 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/7fd0g1195122538.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/80moz1195122538.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9t4al1195122538.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> load(file='/var/www/html/rcomp/createtable')
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/10l8fy1195122538.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/11jn1l1195122539.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/12wmxj1195122539.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/13nnau1195122539.tab")
>
> system("convert tmp/19ebb1195122538.ps tmp/19ebb1195122538.png")
> system("convert tmp/2pzym1195122538.ps tmp/2pzym1195122538.png")
> system("convert tmp/329xs1195122538.ps tmp/329xs1195122538.png")
> system("convert tmp/4iif81195122538.ps tmp/4iif81195122538.png")
> system("convert tmp/5jqea1195122538.ps tmp/5jqea1195122538.png")
> system("convert tmp/6edl21195122538.ps tmp/6edl21195122538.png")
> system("convert tmp/7fd0g1195122538.ps tmp/7fd0g1195122538.png")
> system("convert tmp/80moz1195122538.ps tmp/80moz1195122538.png")
> system("convert tmp/9t4al1195122538.ps tmp/9t4al1195122538.png")
>
>
> proc.time()
user system elapsed
3.178 1.611 3.624