R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
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'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(170588
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+ ,71
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+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,203
+ ,4
+ ,0
+ ,0
+ ,0
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+ ,7
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+ ,54)
+ ,dim=c(5
+ ,164)
+ ,dimnames=list(c('Total_Time_spent_in_RFC_in_seconds'
+ ,'Number_of_Logins'
+ ,'Total_Number_of_Blogged_Computations'
+ ,'Total_Number_of_Reviewed_Compendiums'
+ ,'Total_Number_of_submitted_Feedback_Messages_in_Peer_Reviews')
+ ,1:164))
> y <- array(NA,dim=c(5,164),dimnames=list(c('Total_Time_spent_in_RFC_in_seconds','Number_of_Logins','Total_Number_of_Blogged_Computations','Total_Number_of_Reviewed_Compendiums','Total_Number_of_submitted_Feedback_Messages_in_Peer_Reviews'),1:164))
> 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 = '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
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
Total_Time_spent_in_RFC_in_seconds Number_of_Logins
1 170588 46
2 86621 48
3 113337 37
4 144530 72
5 81530 31
6 35523 17
7 305115 78
8 32750 16
9 115885 37
10 130539 24
11 156990 63
12 128274 74
13 102350 43
14 192887 42
15 129796 55
16 245478 120
17 169569 42
18 185279 100
19 109598 36
20 155012 49
21 154730 46
22 280379 56
23 90938 17
24 101324 31
25 139502 77
26 145120 90
27 161729 80
28 160905 54
29 106888 34
30 187289 38
31 181853 53
32 129340 47
33 196862 63
34 62731 25
35 234863 55
36 167255 37
37 264528 83
38 121976 49
39 80964 26
40 209631 107
41 213310 55
42 115911 40
43 131337 46
44 81106 31
45 93125 49
46 305708 95
47 78800 42
48 157566 54
49 213487 68
50 131108 39
51 128734 53
52 24188 24
53 257662 200
54 65029 17
55 98066 58
56 173587 27
57 179571 58
58 197067 113
59 208823 74
60 134088 50
61 245107 86
62 201409 76
63 141760 61
64 170635 59
65 129100 38
66 108811 34
67 113450 85
68 142286 100
69 143937 49
70 89882 35
71 118807 33
72 69471 28
73 126630 44
74 145908 37
75 96981 33
76 189066 44
77 191467 55
78 106193 58
79 89318 36
80 120362 42
81 98791 30
82 274949 66
83 132798 53
84 128075 57
85 80953 25
86 109237 39
87 96634 35
88 226183 114
89 167226 53
90 117805 70
91 121630 48
92 152193 49
93 112004 42
94 169613 51
95 176577 51
96 130533 27
97 142339 29
98 189764 54
99 201603 92
100 243180 72
101 155931 63
102 182557 40
103 106351 108
104 43287 14
105 127394 44
106 127930 91
107 135306 29
108 175663 63
109 74112 32
110 89059 65
111 166142 41
112 141933 55
113 22938 10
114 125927 53
115 61857 25
116 91185 31
117 236316 64
118 21054 16
119 169093 35
120 31414 19
121 183059 74
122 137544 35
123 75032 45
124 71908 28
125 38214 34
126 90961 25
127 193662 48
128 127185 38
129 242153 49
130 201748 65
131 254599 71
132 139144 23
133 76470 29
134 183260 190
135 280039 113
136 50999 15
137 253056 85
138 98466 48
139 168059 33
140 128768 50
141 75746 72
142 244909 79
143 152366 54
144 173260 63
145 197033 68
146 67507 39
147 139409 49
148 185366 67
149 0 0
150 14688 10
151 98 1
152 455 2
153 0 0
154 0 0
155 128873 57
156 185288 71
157 0 0
158 203 4
159 7199 5
160 46660 20
161 17547 5
162 73567 27
163 969 2
164 105477 33
Total_Number_of_Blogged_Computations Total_Number_of_Reviewed_Compendiums
1 65 26
2 54 20
3 58 24
4 77 25
5 41 15
6 0 16
7 111 20
8 1 18
9 37 19
10 60 20
11 64 26
12 71 37
13 38 23
14 76 36
15 61 28
16 125 35
17 85 20
18 69 22
19 77 19
20 100 28
21 78 27
22 76 25
23 40 15
24 81 26
25 102 27
26 70 24
27 75 21
28 93 27
29 42 21
30 95 30
31 87 25
32 44 33
33 87 30
34 28 20
35 87 27
36 71 25
37 70 30
38 50 20
39 30 8
40 87 24
41 78 22
42 48 25
43 52 20
44 31 21
45 30 21
46 70 26
47 20 26
48 84 30
49 81 26
50 79 30
51 72 18
52 8 4
53 67 31
54 21 18
55 30 14
56 70 20
57 87 35
58 87 24
59 116 26
60 54 20
61 96 31
62 93 21
63 49 31
64 49 26
65 38 19
66 64 15
67 64 19
68 66 28
69 98 20
70 99 17
71 56 25
72 22 20
73 51 25
74 61 24
75 94 22
76 98 25
77 76 20
78 57 23
79 75 22
80 48 25
81 48 18
82 109 30
83 27 22
84 83 25
85 49 8
86 24 21
87 46 22
88 44 24
89 49 30
90 108 27
91 42 21
92 110 25
93 28 21
94 79 24
95 49 20
96 64 20
97 75 20
98 118 24
99 95 40
100 106 22
101 73 31
102 108 26
103 30 20
104 13 19
105 69 15
106 75 21
107 80 22
108 106 24
109 28 19
110 70 20
111 51 23
112 90 27
113 12 1
114 87 24
115 23 11
116 57 27
117 85 22
118 4 0
119 56 17
120 18 8
121 86 23
122 40 31
123 16 23
124 18 17
125 16 8
126 42 22
127 78 33
128 30 33
129 104 31
130 121 33
131 111 35
132 57 21
133 28 20
134 56 24
135 82 29
136 2 20
137 91 27
138 41 24
139 84 26
140 55 26
141 3 12
142 54 21
143 93 24
144 41 21
145 94 30
146 101 32
147 70 24
148 114 29
149 0 0
150 4 0
151 0 0
152 0 0
153 0 0
154 0 0
155 42 20
156 97 27
157 0 0
158 0 0
159 7 0
160 12 5
161 0 1
162 37 23
163 0 0
164 39 16
Total_Number_of_submitted_Feedback_Messages_in_Peer_Reviews t
1 99 1
2 77 2
3 90 3
4 96 4
5 41 5
6 64 6
7 76 7
8 67 8
9 72 9
10 75 10
11 97 11
12 139 12
13 76 13
14 123 14
15 106 15
16 133 16
17 76 17
18 83 18
19 72 19
20 107 20
21 99 21
22 88 22
23 56 23
24 104 24
25 103 25
26 90 26
27 78 27
28 103 28
29 81 29
30 114 30
31 95 31
32 118 32
33 113 33
34 75 34
35 103 35
36 93 36
37 114 37
38 76 38
39 27 39
40 92 40
41 84 41
42 92 42
43 72 43
44 79 44
45 57 45
46 99 46
47 82 47
48 113 48
49 97 49
50 110 50
51 78 51
52 12 52
53 114 53
54 67 54
55 52 55
56 76 56
57 134 57
58 92 58
59 93 59
60 75 60
61 118 61
62 77 62
63 122 63
64 99 64
65 72 65
66 58 66
67 73 67
68 103 68
69 76 69
70 65 70
71 95 71
72 76 72
73 95 73
74 92 74
75 84 75
76 95 76
77 76 77
78 87 78
79 84 79
80 95 80
81 69 81
82 115 82
83 83 83
84 47 84
85 28 85
86 79 86
87 83 87
88 92 88
89 98 89
90 103 90
91 77 91
92 95 92
93 78 93
94 92 94
95 76 95
96 76 96
97 67 97
98 92 98
99 151 99
100 83 100
101 118 101
102 98 102
103 76 103
104 71 104
105 57 105
106 79 106
107 83 107
108 92 108
109 75 109
110 79 110
111 88 111
112 99 112
113 0 113
114 91 114
115 32 115
116 101 116
117 84 117
118 0 118
119 60 119
120 25 120
121 86 121
122 115 122
123 88 123
124 59 124
125 27 125
126 83 126
127 126 127
128 125 128
129 119 129
130 127 130
131 133 131
132 79 132
133 76 133
134 92 134
135 109 135
136 76 136
137 100 137
138 87 138
139 97 139
140 95 140
141 48 141
142 80 142
143 91 143
144 79 144
145 114 145
146 120 146
147 89 147
148 111 148
149 0 149
150 0 150
151 0 151
152 0 152
153 0 153
154 0 154
155 74 155
156 107 156
157 0 157
158 0 158
159 0 159
160 15 160
161 4 161
162 82 162
163 0 163
164 54 164
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept)
6297.40
Number_of_Logins
795.47
Total_Number_of_Blogged_Computations
922.70
Total_Number_of_Reviewed_Compendiums
886.94
Total_Number_of_submitted_Feedback_Messages_in_Peer_Reviews
204.46
t
-22.65
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-112617 -17895 -3324 14841 119742
Coefficients:
Estimate Std. Error
(Intercept) 6297.40 10688.93
Number_of_Logins 795.47 113.91
Total_Number_of_Blogged_Computations 922.70 122.88
Total_Number_of_Reviewed_Compendiums 886.94 2033.11
Total_Number_of_submitted_Feedback_Messages_in_Peer_Reviews 204.46 535.38
t -22.65 61.94
t value Pr(>|t|)
(Intercept) 0.589 0.557
Number_of_Logins 6.984 7.54e-11
Total_Number_of_Blogged_Computations 7.509 4.12e-12
Total_Number_of_Reviewed_Compendiums 0.436 0.663
Total_Number_of_submitted_Feedback_Messages_in_Peer_Reviews 0.382 0.703
t -0.366 0.715
(Intercept)
Number_of_Logins ***
Total_Number_of_Blogged_Computations ***
Total_Number_of_Reviewed_Compendiums
Total_Number_of_submitted_Feedback_Messages_in_Peer_Reviews
t
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 35310 on 158 degrees of freedom
Multiple R-squared: 0.7414, Adjusted R-squared: 0.7332
F-statistic: 90.58 on 5 and 158 DF, p-value: < 2.2e-16
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 0.5438550 9.122899e-01 4.561450e-01
[2,] 0.7110073 5.779854e-01 2.889927e-01
[3,] 0.5804622 8.390757e-01 4.195378e-01
[4,] 0.4759024 9.518047e-01 5.240976e-01
[5,] 0.3783444 7.566887e-01 6.216556e-01
[6,] 0.3887331 7.774661e-01 6.112669e-01
[7,] 0.3559602 7.119204e-01 6.440398e-01
[8,] 0.3040798 6.081595e-01 6.959202e-01
[9,] 0.3613789 7.227578e-01 6.386211e-01
[10,] 0.3150894 6.301787e-01 6.849106e-01
[11,] 0.4578614 9.157228e-01 5.421386e-01
[12,] 0.4369253 8.738506e-01 5.630747e-01
[13,] 0.3622877 7.245755e-01 6.377123e-01
[14,] 0.8969274 2.061452e-01 1.030726e-01
[15,] 0.8627960 2.744079e-01 1.372040e-01
[16,] 0.8643200 2.713601e-01 1.356800e-01
[17,] 0.9262993 1.474014e-01 7.370072e-02
[18,] 0.9110231 1.779538e-01 8.897689e-02
[19,] 0.8830531 2.338939e-01 1.169469e-01
[20,] 0.8513947 2.972106e-01 1.486053e-01
[21,] 0.8329784 3.340432e-01 1.670216e-01
[22,] 0.8101146 3.797708e-01 1.898854e-01
[23,] 0.7743462 4.513075e-01 2.256538e-01
[24,] 0.7398203 5.203594e-01 2.601797e-01
[25,] 0.7075437 5.849126e-01 2.924563e-01
[26,] 0.6644101 6.711799e-01 3.355899e-01
[27,] 0.7613923 4.772153e-01 2.386077e-01
[28,] 0.7270636 5.458728e-01 2.729364e-01
[29,] 0.8970483 2.059034e-01 1.029517e-01
[30,] 0.8726846 2.546309e-01 1.273154e-01
[31,] 0.8488332 3.023336e-01 1.511668e-01
[32,] 0.8164690 3.670619e-01 1.835310e-01
[33,] 0.8333108 3.333784e-01 1.666892e-01
[34,] 0.8035143 3.929715e-01 1.964857e-01
[35,] 0.7688758 4.622484e-01 2.311242e-01
[36,] 0.7335221 5.329558e-01 2.664779e-01
[37,] 0.7370572 5.258856e-01 2.629428e-01
[38,] 0.9580278 8.394435e-02 4.197217e-02
[39,] 0.9510646 9.787079e-02 4.893539e-02
[40,] 0.9448766 1.102469e-01 5.512345e-02
[41,] 0.9391869 1.216262e-01 6.081310e-02
[42,] 0.9367596 1.264809e-01 6.324043e-02
[43,] 0.9302587 1.394826e-01 6.974131e-02
[44,] 0.9218386 1.563228e-01 7.816142e-02
[45,] 0.9110301 1.779398e-01 8.896990e-02
[46,] 0.8898128 2.203743e-01 1.101872e-01
[47,] 0.8664445 2.671110e-01 1.335555e-01
[48,] 0.8747186 2.505628e-01 1.252814e-01
[49,] 0.8510384 2.979232e-01 1.489616e-01
[50,] 0.8384875 3.230250e-01 1.615125e-01
[51,] 0.8267772 3.464457e-01 1.732228e-01
[52,] 0.7956167 4.087665e-01 2.043833e-01
[53,] 0.7849772 4.300457e-01 2.150228e-01
[54,] 0.7596652 4.806697e-01 2.403348e-01
[55,] 0.7229693 5.540614e-01 2.770307e-01
[56,] 0.7145317 5.709366e-01 2.854683e-01
[57,] 0.6962061 6.075877e-01 3.037939e-01
[58,] 0.6697807 6.604386e-01 3.302193e-01
[59,] 0.7162805 5.674390e-01 2.837195e-01
[60,] 0.7457135 5.085730e-01 2.542865e-01
[61,] 0.7392608 5.214785e-01 2.607392e-01
[62,] 0.8211326 3.577349e-01 1.788674e-01
[63,] 0.7895288 4.209423e-01 2.104712e-01
[64,] 0.7570129 4.859743e-01 2.429871e-01
[65,] 0.7196504 5.606991e-01 2.803496e-01
[66,] 0.6883029 6.233942e-01 3.116971e-01
[67,] 0.7478345 5.043310e-01 2.521655e-01
[68,] 0.7194377 5.611246e-01 2.805623e-01
[69,] 0.7305642 5.388716e-01 2.694358e-01
[70,] 0.7255186 5.489629e-01 2.744814e-01
[71,] 0.7566812 4.866375e-01 2.433188e-01
[72,] 0.7208754 5.582492e-01 2.791246e-01
[73,] 0.6820793 6.358414e-01 3.179207e-01
[74,] 0.7786679 4.426643e-01 2.213321e-01
[75,] 0.7632329 4.735341e-01 2.367671e-01
[76,] 0.7670946 4.658108e-01 2.329054e-01
[77,] 0.7303151 5.393698e-01 2.696849e-01
[78,] 0.7023867 5.952265e-01 2.976133e-01
[79,] 0.6662433 6.675135e-01 3.337567e-01
[80,] 0.7176671 5.646658e-01 2.823329e-01
[81,] 0.6939713 6.120574e-01 3.060287e-01
[82,] 0.8514558 2.970883e-01 1.485442e-01
[83,] 0.8239320 3.521361e-01 1.760680e-01
[84,] 0.8204524 3.590952e-01 1.795476e-01
[85,] 0.7944942 4.110116e-01 2.055058e-01
[86,] 0.7648197 4.703607e-01 2.351803e-01
[87,] 0.8163107 3.673785e-01 1.836893e-01
[88,] 0.7900193 4.199614e-01 2.099807e-01
[89,] 0.7588123 4.823754e-01 2.411877e-01
[90,] 0.7210295 5.579411e-01 2.789705e-01
[91,] 0.7029926 5.940148e-01 2.970074e-01
[92,] 0.7430067 5.139866e-01 2.569933e-01
[93,] 0.7087178 5.825645e-01 2.912822e-01
[94,] 0.6680090 6.639820e-01 3.319910e-01
[95,] 0.6793049 6.413902e-01 3.206951e-01
[96,] 0.6410772 7.178456e-01 3.589228e-01
[97,] 0.5960350 8.079300e-01 4.039650e-01
[98,] 0.6399722 7.200556e-01 3.600278e-01
[99,] 0.5932523 8.134954e-01 4.067477e-01
[100,] 0.5530583 8.938834e-01 4.469417e-01
[101,] 0.5088712 9.822575e-01 4.911288e-01
[102,] 0.6317372 7.365256e-01 3.682628e-01
[103,] 0.6483871 7.032259e-01 3.516129e-01
[104,] 0.6529979 6.940041e-01 3.470021e-01
[105,] 0.6072554 7.854891e-01 3.927446e-01
[106,] 0.6509455 6.981089e-01 3.490545e-01
[107,] 0.6077758 7.844483e-01 3.922242e-01
[108,] 0.6304216 7.391568e-01 3.695784e-01
[109,] 0.7038912 5.922175e-01 2.961088e-01
[110,] 0.6600847 6.798307e-01 3.399153e-01
[111,] 0.7127774 5.744451e-01 2.872226e-01
[112,] 0.6839299 6.321402e-01 3.160701e-01
[113,] 0.6370896 7.258209e-01 3.629104e-01
[114,] 0.5940446 8.119108e-01 4.059554e-01
[115,] 0.5622386 8.755228e-01 4.377614e-01
[116,] 0.5106947 9.786106e-01 4.893053e-01
[117,] 0.5201577 9.596847e-01 4.798423e-01
[118,] 0.4907119 9.814238e-01 5.092881e-01
[119,] 0.4480981 8.961962e-01 5.519019e-01
[120,] 0.3952210 7.904420e-01 6.047790e-01
[121,] 0.4296002 8.592004e-01 5.703998e-01
[122,] 0.3984996 7.969992e-01 6.015004e-01
[123,] 0.3797541 7.595082e-01 6.202459e-01
[124,] 0.3479330 6.958659e-01 6.520670e-01
[125,] 0.2980232 5.960464e-01 7.019768e-01
[126,] 0.9386941 1.226118e-01 6.130588e-02
[127,] 0.9268738 1.462525e-01 7.312624e-02
[128,] 0.9496898 1.006205e-01 5.031023e-02
[129,] 0.9341005 1.317990e-01 6.589949e-02
[130,] 0.9210626 1.578747e-01 7.893736e-02
[131,] 0.9740835 5.183307e-02 2.591653e-02
[132,] 0.9614481 7.710378e-02 3.855189e-02
[133,] 0.9999871 2.580013e-05 1.290006e-05
[134,] 0.9999899 2.028277e-05 1.014138e-05
[135,] 0.9999738 5.247002e-05 2.623501e-05
[136,] 0.9999352 1.296354e-04 6.481769e-05
[137,] 0.9999519 9.610221e-05 4.805110e-05
[138,] 1.0000000 3.067975e-08 1.533987e-08
[139,] 0.9999999 1.023768e-07 5.118838e-08
[140,] 0.9999998 3.546880e-07 1.773440e-07
[141,] 0.9999990 1.997149e-06 9.985747e-07
[142,] 0.9999944 1.129063e-05 5.645317e-06
[143,] 0.9999651 6.975403e-05 3.487702e-05
[144,] 0.9997936 4.127817e-04 2.063909e-04
[145,] 0.9989824 2.035227e-03 1.017613e-03
[146,] 0.9962456 7.508715e-03 3.754358e-03
[147,] 0.9809053 3.818939e-02 1.909469e-02
> postscript(file="/var/wessaorg/rcomp/tmp/1hb1z1321982611.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/2ecvd1321982611.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/3xfzw1321982611.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4u2bi1321982611.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5kbcc1321982611.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 = 164
Frequency = 1
1 2 3 4 5 6
24444.1363 -41121.7586 -15529.3898 -31800.3870 -8831.4854 -11437.7870
7 8 9 10 11 12
101231.6115 -16679.9640 14646.1781 16941.5074 -1118.8269 -63364.8050
13 14 15 16 17 18
-8859.3551 26293.3949 -22704.3101 -29487.4058 18539.4654 -307.2166
19 20 21 22 23 24
-27527.0001 -28792.1119 -3842.9755 119742.2315 9976.6889 -48152.3677
25 26 27 28 29 30
-66602.7960 -36458.0579 -11370.8926 -18531.6080 261.0721 13870.0390
31 32 33 34 35 36
12225.5595 -7613.6968 11210.2085 -21591.8911 60325.6782 25640.5606
37 38 39 40 41 42
78538.8170 -1851.6149 14570.6303 -1247.9143 55532.2610 -6527.3355
43 44 45 46 47 48
8981.4694 -12236.1257 -9092.2740 116991.5582 -18122.7198 -17818.6832
49 50 51 52 53 54
36575.4874 -27072.3838 -16915.5938 -13405.9167 -19154.1391 -2608.6740
55 56 57 58 59 60
-3853.2101 49213.4269 -10288.1271 -18177.0868 -4111.6690 6476.8214
61 62 63 64 65 66
31579.9060 15879.4986 -9285.6997 30340.0832 27411.3193 -7253.2836
67 68 69 70 71 72
-49775.4267 -48810.4332 -23478.2755 -62386.8550 -5401.2032 -11045.9049
73 74 75 76 77 78
-1669.6073 15472.6346 -57289.5065 17467.2761 39759.5425 -35256.7002
79 80 81 82 83 84
-49716.9699 -3420.0082 -3898.2361 67312.1759 24824.7815 -30029.2477
85 86 87 88 89 90
-1338.8837 16941.2425 -14461.4506 50499.1439 28926.8476 -86795.5398
91 92 93 94 95 96
6088.4661 -34093.1605 13994.0017 11885.3019 53372.1073 12601.5898
97 98 99 100 101 102
14529.6584 -6244.9618 -29643.0929 47584.2205 -17172.0611 4001.6946
103 104 105 106 107 108
-44483.3796 -15154.9588 -150.7950 -52335.3315 -1935.5505 -16206.3044
109 110 111 112 113 114
-13193.6323 -64932.9475 44294.5314 -32810.6681 -714.2370 -40115.8471
115 116 117 118 119 120
756.2233 -34336.3869 66641.3573 1010.7250 58632.4542 -16095.1619
121 122 123 124 125 126
3301.6533 18252.4248 -17430.9627 2396.2054 -19677.5409 -7605.5991
127 128 129 130 131 132
25056.8735 11051.4882 52012.4768 -20192.9505 34134.2721 30168.4525
133 134 135 136 137 138
-8997.0382 -62910.5187 63241.9215 726.8389 53887.1538 -19793.7257
139 140 141 142 143 144
18259.3511 -7364.7524 -7857.3814 94177.0255 -19351.7342 47500.5143
145 146 147 148 149 150
3277.0941 -112617.0378 -6609.6759 -24480.2478 -2922.7655 142.3252
151 152 153 154 155 156
-3574.9428 -3990.7687 -2832.1713 -2809.5228 9122.0110 -9281.2969
157 158 159 160 161 162
-2741.5771 -5697.8262 -5933.5762 9502.9040 9213.8818 -21844.1644
163 164
-3227.6346 15426.2227
> postscript(file="/var/wessaorg/rcomp/tmp/6q4zt1321982611.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 = 164
Frequency = 1
lag(myerror, k = 1) myerror
0 24444.1363 NA
1 -41121.7586 24444.1363
2 -15529.3898 -41121.7586
3 -31800.3870 -15529.3898
4 -8831.4854 -31800.3870
5 -11437.7870 -8831.4854
6 101231.6115 -11437.7870
7 -16679.9640 101231.6115
8 14646.1781 -16679.9640
9 16941.5074 14646.1781
10 -1118.8269 16941.5074
11 -63364.8050 -1118.8269
12 -8859.3551 -63364.8050
13 26293.3949 -8859.3551
14 -22704.3101 26293.3949
15 -29487.4058 -22704.3101
16 18539.4654 -29487.4058
17 -307.2166 18539.4654
18 -27527.0001 -307.2166
19 -28792.1119 -27527.0001
20 -3842.9755 -28792.1119
21 119742.2315 -3842.9755
22 9976.6889 119742.2315
23 -48152.3677 9976.6889
24 -66602.7960 -48152.3677
25 -36458.0579 -66602.7960
26 -11370.8926 -36458.0579
27 -18531.6080 -11370.8926
28 261.0721 -18531.6080
29 13870.0390 261.0721
30 12225.5595 13870.0390
31 -7613.6968 12225.5595
32 11210.2085 -7613.6968
33 -21591.8911 11210.2085
34 60325.6782 -21591.8911
35 25640.5606 60325.6782
36 78538.8170 25640.5606
37 -1851.6149 78538.8170
38 14570.6303 -1851.6149
39 -1247.9143 14570.6303
40 55532.2610 -1247.9143
41 -6527.3355 55532.2610
42 8981.4694 -6527.3355
43 -12236.1257 8981.4694
44 -9092.2740 -12236.1257
45 116991.5582 -9092.2740
46 -18122.7198 116991.5582
47 -17818.6832 -18122.7198
48 36575.4874 -17818.6832
49 -27072.3838 36575.4874
50 -16915.5938 -27072.3838
51 -13405.9167 -16915.5938
52 -19154.1391 -13405.9167
53 -2608.6740 -19154.1391
54 -3853.2101 -2608.6740
55 49213.4269 -3853.2101
56 -10288.1271 49213.4269
57 -18177.0868 -10288.1271
58 -4111.6690 -18177.0868
59 6476.8214 -4111.6690
60 31579.9060 6476.8214
61 15879.4986 31579.9060
62 -9285.6997 15879.4986
63 30340.0832 -9285.6997
64 27411.3193 30340.0832
65 -7253.2836 27411.3193
66 -49775.4267 -7253.2836
67 -48810.4332 -49775.4267
68 -23478.2755 -48810.4332
69 -62386.8550 -23478.2755
70 -5401.2032 -62386.8550
71 -11045.9049 -5401.2032
72 -1669.6073 -11045.9049
73 15472.6346 -1669.6073
74 -57289.5065 15472.6346
75 17467.2761 -57289.5065
76 39759.5425 17467.2761
77 -35256.7002 39759.5425
78 -49716.9699 -35256.7002
79 -3420.0082 -49716.9699
80 -3898.2361 -3420.0082
81 67312.1759 -3898.2361
82 24824.7815 67312.1759
83 -30029.2477 24824.7815
84 -1338.8837 -30029.2477
85 16941.2425 -1338.8837
86 -14461.4506 16941.2425
87 50499.1439 -14461.4506
88 28926.8476 50499.1439
89 -86795.5398 28926.8476
90 6088.4661 -86795.5398
91 -34093.1605 6088.4661
92 13994.0017 -34093.1605
93 11885.3019 13994.0017
94 53372.1073 11885.3019
95 12601.5898 53372.1073
96 14529.6584 12601.5898
97 -6244.9618 14529.6584
98 -29643.0929 -6244.9618
99 47584.2205 -29643.0929
100 -17172.0611 47584.2205
101 4001.6946 -17172.0611
102 -44483.3796 4001.6946
103 -15154.9588 -44483.3796
104 -150.7950 -15154.9588
105 -52335.3315 -150.7950
106 -1935.5505 -52335.3315
107 -16206.3044 -1935.5505
108 -13193.6323 -16206.3044
109 -64932.9475 -13193.6323
110 44294.5314 -64932.9475
111 -32810.6681 44294.5314
112 -714.2370 -32810.6681
113 -40115.8471 -714.2370
114 756.2233 -40115.8471
115 -34336.3869 756.2233
116 66641.3573 -34336.3869
117 1010.7250 66641.3573
118 58632.4542 1010.7250
119 -16095.1619 58632.4542
120 3301.6533 -16095.1619
121 18252.4248 3301.6533
122 -17430.9627 18252.4248
123 2396.2054 -17430.9627
124 -19677.5409 2396.2054
125 -7605.5991 -19677.5409
126 25056.8735 -7605.5991
127 11051.4882 25056.8735
128 52012.4768 11051.4882
129 -20192.9505 52012.4768
130 34134.2721 -20192.9505
131 30168.4525 34134.2721
132 -8997.0382 30168.4525
133 -62910.5187 -8997.0382
134 63241.9215 -62910.5187
135 726.8389 63241.9215
136 53887.1538 726.8389
137 -19793.7257 53887.1538
138 18259.3511 -19793.7257
139 -7364.7524 18259.3511
140 -7857.3814 -7364.7524
141 94177.0255 -7857.3814
142 -19351.7342 94177.0255
143 47500.5143 -19351.7342
144 3277.0941 47500.5143
145 -112617.0378 3277.0941
146 -6609.6759 -112617.0378
147 -24480.2478 -6609.6759
148 -2922.7655 -24480.2478
149 142.3252 -2922.7655
150 -3574.9428 142.3252
151 -3990.7687 -3574.9428
152 -2832.1713 -3990.7687
153 -2809.5228 -2832.1713
154 9122.0110 -2809.5228
155 -9281.2969 9122.0110
156 -2741.5771 -9281.2969
157 -5697.8262 -2741.5771
158 -5933.5762 -5697.8262
159 9502.9040 -5933.5762
160 9213.8818 9502.9040
161 -21844.1644 9213.8818
162 -3227.6346 -21844.1644
163 15426.2227 -3227.6346
164 NA 15426.2227
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -41121.7586 24444.1363
[2,] -15529.3898 -41121.7586
[3,] -31800.3870 -15529.3898
[4,] -8831.4854 -31800.3870
[5,] -11437.7870 -8831.4854
[6,] 101231.6115 -11437.7870
[7,] -16679.9640 101231.6115
[8,] 14646.1781 -16679.9640
[9,] 16941.5074 14646.1781
[10,] -1118.8269 16941.5074
[11,] -63364.8050 -1118.8269
[12,] -8859.3551 -63364.8050
[13,] 26293.3949 -8859.3551
[14,] -22704.3101 26293.3949
[15,] -29487.4058 -22704.3101
[16,] 18539.4654 -29487.4058
[17,] -307.2166 18539.4654
[18,] -27527.0001 -307.2166
[19,] -28792.1119 -27527.0001
[20,] -3842.9755 -28792.1119
[21,] 119742.2315 -3842.9755
[22,] 9976.6889 119742.2315
[23,] -48152.3677 9976.6889
[24,] -66602.7960 -48152.3677
[25,] -36458.0579 -66602.7960
[26,] -11370.8926 -36458.0579
[27,] -18531.6080 -11370.8926
[28,] 261.0721 -18531.6080
[29,] 13870.0390 261.0721
[30,] 12225.5595 13870.0390
[31,] -7613.6968 12225.5595
[32,] 11210.2085 -7613.6968
[33,] -21591.8911 11210.2085
[34,] 60325.6782 -21591.8911
[35,] 25640.5606 60325.6782
[36,] 78538.8170 25640.5606
[37,] -1851.6149 78538.8170
[38,] 14570.6303 -1851.6149
[39,] -1247.9143 14570.6303
[40,] 55532.2610 -1247.9143
[41,] -6527.3355 55532.2610
[42,] 8981.4694 -6527.3355
[43,] -12236.1257 8981.4694
[44,] -9092.2740 -12236.1257
[45,] 116991.5582 -9092.2740
[46,] -18122.7198 116991.5582
[47,] -17818.6832 -18122.7198
[48,] 36575.4874 -17818.6832
[49,] -27072.3838 36575.4874
[50,] -16915.5938 -27072.3838
[51,] -13405.9167 -16915.5938
[52,] -19154.1391 -13405.9167
[53,] -2608.6740 -19154.1391
[54,] -3853.2101 -2608.6740
[55,] 49213.4269 -3853.2101
[56,] -10288.1271 49213.4269
[57,] -18177.0868 -10288.1271
[58,] -4111.6690 -18177.0868
[59,] 6476.8214 -4111.6690
[60,] 31579.9060 6476.8214
[61,] 15879.4986 31579.9060
[62,] -9285.6997 15879.4986
[63,] 30340.0832 -9285.6997
[64,] 27411.3193 30340.0832
[65,] -7253.2836 27411.3193
[66,] -49775.4267 -7253.2836
[67,] -48810.4332 -49775.4267
[68,] -23478.2755 -48810.4332
[69,] -62386.8550 -23478.2755
[70,] -5401.2032 -62386.8550
[71,] -11045.9049 -5401.2032
[72,] -1669.6073 -11045.9049
[73,] 15472.6346 -1669.6073
[74,] -57289.5065 15472.6346
[75,] 17467.2761 -57289.5065
[76,] 39759.5425 17467.2761
[77,] -35256.7002 39759.5425
[78,] -49716.9699 -35256.7002
[79,] -3420.0082 -49716.9699
[80,] -3898.2361 -3420.0082
[81,] 67312.1759 -3898.2361
[82,] 24824.7815 67312.1759
[83,] -30029.2477 24824.7815
[84,] -1338.8837 -30029.2477
[85,] 16941.2425 -1338.8837
[86,] -14461.4506 16941.2425
[87,] 50499.1439 -14461.4506
[88,] 28926.8476 50499.1439
[89,] -86795.5398 28926.8476
[90,] 6088.4661 -86795.5398
[91,] -34093.1605 6088.4661
[92,] 13994.0017 -34093.1605
[93,] 11885.3019 13994.0017
[94,] 53372.1073 11885.3019
[95,] 12601.5898 53372.1073
[96,] 14529.6584 12601.5898
[97,] -6244.9618 14529.6584
[98,] -29643.0929 -6244.9618
[99,] 47584.2205 -29643.0929
[100,] -17172.0611 47584.2205
[101,] 4001.6946 -17172.0611
[102,] -44483.3796 4001.6946
[103,] -15154.9588 -44483.3796
[104,] -150.7950 -15154.9588
[105,] -52335.3315 -150.7950
[106,] -1935.5505 -52335.3315
[107,] -16206.3044 -1935.5505
[108,] -13193.6323 -16206.3044
[109,] -64932.9475 -13193.6323
[110,] 44294.5314 -64932.9475
[111,] -32810.6681 44294.5314
[112,] -714.2370 -32810.6681
[113,] -40115.8471 -714.2370
[114,] 756.2233 -40115.8471
[115,] -34336.3869 756.2233
[116,] 66641.3573 -34336.3869
[117,] 1010.7250 66641.3573
[118,] 58632.4542 1010.7250
[119,] -16095.1619 58632.4542
[120,] 3301.6533 -16095.1619
[121,] 18252.4248 3301.6533
[122,] -17430.9627 18252.4248
[123,] 2396.2054 -17430.9627
[124,] -19677.5409 2396.2054
[125,] -7605.5991 -19677.5409
[126,] 25056.8735 -7605.5991
[127,] 11051.4882 25056.8735
[128,] 52012.4768 11051.4882
[129,] -20192.9505 52012.4768
[130,] 34134.2721 -20192.9505
[131,] 30168.4525 34134.2721
[132,] -8997.0382 30168.4525
[133,] -62910.5187 -8997.0382
[134,] 63241.9215 -62910.5187
[135,] 726.8389 63241.9215
[136,] 53887.1538 726.8389
[137,] -19793.7257 53887.1538
[138,] 18259.3511 -19793.7257
[139,] -7364.7524 18259.3511
[140,] -7857.3814 -7364.7524
[141,] 94177.0255 -7857.3814
[142,] -19351.7342 94177.0255
[143,] 47500.5143 -19351.7342
[144,] 3277.0941 47500.5143
[145,] -112617.0378 3277.0941
[146,] -6609.6759 -112617.0378
[147,] -24480.2478 -6609.6759
[148,] -2922.7655 -24480.2478
[149,] 142.3252 -2922.7655
[150,] -3574.9428 142.3252
[151,] -3990.7687 -3574.9428
[152,] -2832.1713 -3990.7687
[153,] -2809.5228 -2832.1713
[154,] 9122.0110 -2809.5228
[155,] -9281.2969 9122.0110
[156,] -2741.5771 -9281.2969
[157,] -5697.8262 -2741.5771
[158,] -5933.5762 -5697.8262
[159,] 9502.9040 -5933.5762
[160,] 9213.8818 9502.9040
[161,] -21844.1644 9213.8818
[162,] -3227.6346 -21844.1644
[163,] 15426.2227 -3227.6346
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -41121.7586 24444.1363
2 -15529.3898 -41121.7586
3 -31800.3870 -15529.3898
4 -8831.4854 -31800.3870
5 -11437.7870 -8831.4854
6 101231.6115 -11437.7870
7 -16679.9640 101231.6115
8 14646.1781 -16679.9640
9 16941.5074 14646.1781
10 -1118.8269 16941.5074
11 -63364.8050 -1118.8269
12 -8859.3551 -63364.8050
13 26293.3949 -8859.3551
14 -22704.3101 26293.3949
15 -29487.4058 -22704.3101
16 18539.4654 -29487.4058
17 -307.2166 18539.4654
18 -27527.0001 -307.2166
19 -28792.1119 -27527.0001
20 -3842.9755 -28792.1119
21 119742.2315 -3842.9755
22 9976.6889 119742.2315
23 -48152.3677 9976.6889
24 -66602.7960 -48152.3677
25 -36458.0579 -66602.7960
26 -11370.8926 -36458.0579
27 -18531.6080 -11370.8926
28 261.0721 -18531.6080
29 13870.0390 261.0721
30 12225.5595 13870.0390
31 -7613.6968 12225.5595
32 11210.2085 -7613.6968
33 -21591.8911 11210.2085
34 60325.6782 -21591.8911
35 25640.5606 60325.6782
36 78538.8170 25640.5606
37 -1851.6149 78538.8170
38 14570.6303 -1851.6149
39 -1247.9143 14570.6303
40 55532.2610 -1247.9143
41 -6527.3355 55532.2610
42 8981.4694 -6527.3355
43 -12236.1257 8981.4694
44 -9092.2740 -12236.1257
45 116991.5582 -9092.2740
46 -18122.7198 116991.5582
47 -17818.6832 -18122.7198
48 36575.4874 -17818.6832
49 -27072.3838 36575.4874
50 -16915.5938 -27072.3838
51 -13405.9167 -16915.5938
52 -19154.1391 -13405.9167
53 -2608.6740 -19154.1391
54 -3853.2101 -2608.6740
55 49213.4269 -3853.2101
56 -10288.1271 49213.4269
57 -18177.0868 -10288.1271
58 -4111.6690 -18177.0868
59 6476.8214 -4111.6690
60 31579.9060 6476.8214
61 15879.4986 31579.9060
62 -9285.6997 15879.4986
63 30340.0832 -9285.6997
64 27411.3193 30340.0832
65 -7253.2836 27411.3193
66 -49775.4267 -7253.2836
67 -48810.4332 -49775.4267
68 -23478.2755 -48810.4332
69 -62386.8550 -23478.2755
70 -5401.2032 -62386.8550
71 -11045.9049 -5401.2032
72 -1669.6073 -11045.9049
73 15472.6346 -1669.6073
74 -57289.5065 15472.6346
75 17467.2761 -57289.5065
76 39759.5425 17467.2761
77 -35256.7002 39759.5425
78 -49716.9699 -35256.7002
79 -3420.0082 -49716.9699
80 -3898.2361 -3420.0082
81 67312.1759 -3898.2361
82 24824.7815 67312.1759
83 -30029.2477 24824.7815
84 -1338.8837 -30029.2477
85 16941.2425 -1338.8837
86 -14461.4506 16941.2425
87 50499.1439 -14461.4506
88 28926.8476 50499.1439
89 -86795.5398 28926.8476
90 6088.4661 -86795.5398
91 -34093.1605 6088.4661
92 13994.0017 -34093.1605
93 11885.3019 13994.0017
94 53372.1073 11885.3019
95 12601.5898 53372.1073
96 14529.6584 12601.5898
97 -6244.9618 14529.6584
98 -29643.0929 -6244.9618
99 47584.2205 -29643.0929
100 -17172.0611 47584.2205
101 4001.6946 -17172.0611
102 -44483.3796 4001.6946
103 -15154.9588 -44483.3796
104 -150.7950 -15154.9588
105 -52335.3315 -150.7950
106 -1935.5505 -52335.3315
107 -16206.3044 -1935.5505
108 -13193.6323 -16206.3044
109 -64932.9475 -13193.6323
110 44294.5314 -64932.9475
111 -32810.6681 44294.5314
112 -714.2370 -32810.6681
113 -40115.8471 -714.2370
114 756.2233 -40115.8471
115 -34336.3869 756.2233
116 66641.3573 -34336.3869
117 1010.7250 66641.3573
118 58632.4542 1010.7250
119 -16095.1619 58632.4542
120 3301.6533 -16095.1619
121 18252.4248 3301.6533
122 -17430.9627 18252.4248
123 2396.2054 -17430.9627
124 -19677.5409 2396.2054
125 -7605.5991 -19677.5409
126 25056.8735 -7605.5991
127 11051.4882 25056.8735
128 52012.4768 11051.4882
129 -20192.9505 52012.4768
130 34134.2721 -20192.9505
131 30168.4525 34134.2721
132 -8997.0382 30168.4525
133 -62910.5187 -8997.0382
134 63241.9215 -62910.5187
135 726.8389 63241.9215
136 53887.1538 726.8389
137 -19793.7257 53887.1538
138 18259.3511 -19793.7257
139 -7364.7524 18259.3511
140 -7857.3814 -7364.7524
141 94177.0255 -7857.3814
142 -19351.7342 94177.0255
143 47500.5143 -19351.7342
144 3277.0941 47500.5143
145 -112617.0378 3277.0941
146 -6609.6759 -112617.0378
147 -24480.2478 -6609.6759
148 -2922.7655 -24480.2478
149 142.3252 -2922.7655
150 -3574.9428 142.3252
151 -3990.7687 -3574.9428
152 -2832.1713 -3990.7687
153 -2809.5228 -2832.1713
154 9122.0110 -2809.5228
155 -9281.2969 9122.0110
156 -2741.5771 -9281.2969
157 -5697.8262 -2741.5771
158 -5933.5762 -5697.8262
159 9502.9040 -5933.5762
160 9213.8818 9502.9040
161 -21844.1644 9213.8818
162 -3227.6346 -21844.1644
163 15426.2227 -3227.6346
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/7mfa01321982611.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/8rgi81321982611.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9rk851321982611.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10w4ju1321982611.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/11kire1321982611.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
+ a<-table.element(a,mysum$coefficients[i,1])
+ a<-table.element(a, round(mysum$coefficients[i,2],6))
+ a<-table.element(a, round(mysum$coefficients[i,3],4))
+ a<-table.element(a, round(mysum$coefficients[i,4],6))
+ a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/12l2x51321982611.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$r.squared))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a, mysum$r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a, mysum$adj.r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[1])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a, mysum$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/13e9i51321982611.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/14dhy01321982611.tab")
> if (n > n25) {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'p-values',header=TRUE)
+ a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'breakpoint index',header=TRUE)
+ a<-table.element(a,'greater',header=TRUE)
+ a<-table.element(a,'2-sided',header=TRUE)
+ a<-table.element(a,'less',header=TRUE)
+ a<-table.row.end(a)
+ for (mypoint in kp3:nmkm3) {
+ a<-table.row.start(a)
+ a<-table.element(a,mypoint,header=TRUE)
+ a<-table.element(a,gqarr[mypoint-kp3+1,1])
+ a<-table.element(a,gqarr[mypoint-kp3+1,2])
+ a<-table.element(a,gqarr[mypoint-kp3+1,3])
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/wessaorg/rcomp/tmp/15x80o1321982611.tab")
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Description',header=TRUE)
+ a<-table.element(a,'# significant tests',header=TRUE)
+ a<-table.element(a,'% significant tests',header=TRUE)
+ a<-table.element(a,'OK/NOK',header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'1% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant1)
+ a<-table.element(a,numsignificant1/numgqtests)
+ if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'5% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant5)
+ a<-table.element(a,numsignificant5/numgqtests)
+ if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'10% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant10)
+ a<-table.element(a,numsignificant10/numgqtests)
+ if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/wessaorg/rcomp/tmp/16piwg1321982611.tab")
+ }
>
> try(system("convert tmp/1hb1z1321982611.ps tmp/1hb1z1321982611.png",intern=TRUE))
character(0)
> try(system("convert tmp/2ecvd1321982611.ps tmp/2ecvd1321982611.png",intern=TRUE))
character(0)
> try(system("convert tmp/3xfzw1321982611.ps tmp/3xfzw1321982611.png",intern=TRUE))
character(0)
> try(system("convert tmp/4u2bi1321982611.ps tmp/4u2bi1321982611.png",intern=TRUE))
character(0)
> try(system("convert tmp/5kbcc1321982611.ps tmp/5kbcc1321982611.png",intern=TRUE))
character(0)
> try(system("convert tmp/6q4zt1321982611.ps tmp/6q4zt1321982611.png",intern=TRUE))
character(0)
> try(system("convert tmp/7mfa01321982611.ps tmp/7mfa01321982611.png",intern=TRUE))
character(0)
> try(system("convert tmp/8rgi81321982611.ps tmp/8rgi81321982611.png",intern=TRUE))
character(0)
> try(system("convert tmp/9rk851321982611.ps tmp/9rk851321982611.png",intern=TRUE))
character(0)
> try(system("convert tmp/10w4ju1321982611.ps tmp/10w4ju1321982611.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
4.934 0.545 5.666