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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationFri, 27 Nov 2009 12:35:53 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Nov/27/t1259350784txsoheqdi1y263d.htm/, Retrieved Sun, 28 Apr 2024 23:07:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=61181, Retrieved Sun, 28 Apr 2024 23:07:03 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact153

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [(Partial) Autocorrelation Function] [Identifying Integ...] [2009-11-22 12:16:10] [b98453cac15ba1066b407e146608df68]
-    D          [(Partial) Autocorrelation Function] [WS 8.1] [2009-11-27 19:35:53] [71c065898bd1c08eef04509b4bcee039] [Current]
-    D            [(Partial) Autocorrelation Function] [PAPER 5] [2009-12-20 01:17:09] [4a2be4899cba879e4eea9daa25281df8]
-    D              [(Partial) Autocorrelation Function] [PAPER 7] [2009-12-20 01:19:31] [4a2be4899cba879e4eea9daa25281df8]
-    D                [(Partial) Autocorrelation Function] [paper 4] [2009-12-20 16:12:22] [4a2be4899cba879e4eea9daa25281df8]
-    D              [(Partial) Autocorrelation Function] [PAPER 12] [2009-12-20 01:36:32] [4a2be4899cba879e4eea9daa25281df8]
-    D                [(Partial) Autocorrelation Function] [PAPER 13] [2009-12-20 01:39:09] [4a2be4899cba879e4eea9daa25281df8]
-                       [(Partial) Autocorrelation Function] [PAPER 14] [2009-12-20 01:40:45] [4a2be4899cba879e4eea9daa25281df8]
-    D                  [(Partial) Autocorrelation Function] [paper 3] [2009-12-20 16:09:30] [4a2be4899cba879e4eea9daa25281df8]
-    D                [(Partial) Autocorrelation Function] [paper 2] [2009-12-20 16:07:26] [4a2be4899cba879e4eea9daa25281df8]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
100,00
94,97
107,50
124,27
107,06
79,71
163,41
144,83
166,82
154,26
132,60
157,51
104,02
106,03
113,23
117,64
113,34
66,62
185,99
174,57
208,19
163,81
162,46
148,16
113,41
105,63
111,79
132,36
110,75
67,37
178,29
156,38
189,71
152,80
150,80
160,40
127,25
108,47
117,09
147,25
116,19
75,83
181,94
179,12
183,15
197,90
155,42
162,54
125,90
105,50
121,11
137,51
97,20
69,74
152,58
146,59
161,16
152,84
121,95
140,12

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61181&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61181&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61181&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.3712622.87580.002786
20.1728421.33880.092838
30.003510.02720.4892
4-0.144125-1.11640.134353
5-0.259602-2.01090.02442
6-0.540785-4.18894.7e-05
7-0.324671-2.51490.007302
8-0.206419-1.59890.057546
9-0.06975-0.54030.295501
100.0710040.550.292181
110.2493431.93140.029081
120.7451495.77190
130.2759612.13760.018317
140.1202660.93160.177645
15-0.003271-0.02530.489935
16-0.109712-0.84980.199399
17-0.207962-1.61090.056229
18-0.445061-3.44740.00052
19-0.274795-2.12860.018703
20-0.179854-1.39310.084358
21-0.079076-0.61250.271253
220.0235270.18220.428004
230.1714651.32820.094578
240.5361244.15285.3e-05
250.2406961.86440.033578
260.1059210.82050.207601
270.0326840.25320.400502
28-0.068795-0.53290.298042
29-0.113166-0.87660.192105
30-0.309786-2.39960.009768
31-0.206965-1.60310.057078
32-0.151961-1.17710.121904
33-0.094926-0.73530.232512
34-0.01637-0.12680.449761
350.0655540.50780.306736
360.3046952.36020.010768

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.371262 & 2.8758 & 0.002786 \tabularnewline
2 & 0.172842 & 1.3388 & 0.092838 \tabularnewline
3 & 0.00351 & 0.0272 & 0.4892 \tabularnewline
4 & -0.144125 & -1.1164 & 0.134353 \tabularnewline
5 & -0.259602 & -2.0109 & 0.02442 \tabularnewline
6 & -0.540785 & -4.1889 & 4.7e-05 \tabularnewline
7 & -0.324671 & -2.5149 & 0.007302 \tabularnewline
8 & -0.206419 & -1.5989 & 0.057546 \tabularnewline
9 & -0.06975 & -0.5403 & 0.295501 \tabularnewline
10 & 0.071004 & 0.55 & 0.292181 \tabularnewline
11 & 0.249343 & 1.9314 & 0.029081 \tabularnewline
12 & 0.745149 & 5.7719 & 0 \tabularnewline
13 & 0.275961 & 2.1376 & 0.018317 \tabularnewline
14 & 0.120266 & 0.9316 & 0.177645 \tabularnewline
15 & -0.003271 & -0.0253 & 0.489935 \tabularnewline
16 & -0.109712 & -0.8498 & 0.199399 \tabularnewline
17 & -0.207962 & -1.6109 & 0.056229 \tabularnewline
18 & -0.445061 & -3.4474 & 0.00052 \tabularnewline
19 & -0.274795 & -2.1286 & 0.018703 \tabularnewline
20 & -0.179854 & -1.3931 & 0.084358 \tabularnewline
21 & -0.079076 & -0.6125 & 0.271253 \tabularnewline
22 & 0.023527 & 0.1822 & 0.428004 \tabularnewline
23 & 0.171465 & 1.3282 & 0.094578 \tabularnewline
24 & 0.536124 & 4.1528 & 5.3e-05 \tabularnewline
25 & 0.240696 & 1.8644 & 0.033578 \tabularnewline
26 & 0.105921 & 0.8205 & 0.207601 \tabularnewline
27 & 0.032684 & 0.2532 & 0.400502 \tabularnewline
28 & -0.068795 & -0.5329 & 0.298042 \tabularnewline
29 & -0.113166 & -0.8766 & 0.192105 \tabularnewline
30 & -0.309786 & -2.3996 & 0.009768 \tabularnewline
31 & -0.206965 & -1.6031 & 0.057078 \tabularnewline
32 & -0.151961 & -1.1771 & 0.121904 \tabularnewline
33 & -0.094926 & -0.7353 & 0.232512 \tabularnewline
34 & -0.01637 & -0.1268 & 0.449761 \tabularnewline
35 & 0.065554 & 0.5078 & 0.306736 \tabularnewline
36 & 0.304695 & 2.3602 & 0.010768 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61181&T=1

[TABLE]
[ROW][C]Autocorrelation Function[/C][/ROW]
[ROW][C]Time lag k[/C][C]ACF(k)[/C][C]T-STAT[/C][C]P-value[/C][/ROW]
[ROW][C]1[/C][C]0.371262[/C][C]2.8758[/C][C]0.002786[/C][/ROW]
[ROW][C]2[/C][C]0.172842[/C][C]1.3388[/C][C]0.092838[/C][/ROW]
[ROW][C]3[/C][C]0.00351[/C][C]0.0272[/C][C]0.4892[/C][/ROW]
[ROW][C]4[/C][C]-0.144125[/C][C]-1.1164[/C][C]0.134353[/C][/ROW]
[ROW][C]5[/C][C]-0.259602[/C][C]-2.0109[/C][C]0.02442[/C][/ROW]
[ROW][C]6[/C][C]-0.540785[/C][C]-4.1889[/C][C]4.7e-05[/C][/ROW]
[ROW][C]7[/C][C]-0.324671[/C][C]-2.5149[/C][C]0.007302[/C][/ROW]
[ROW][C]8[/C][C]-0.206419[/C][C]-1.5989[/C][C]0.057546[/C][/ROW]
[ROW][C]9[/C][C]-0.06975[/C][C]-0.5403[/C][C]0.295501[/C][/ROW]
[ROW][C]10[/C][C]0.071004[/C][C]0.55[/C][C]0.292181[/C][/ROW]
[ROW][C]11[/C][C]0.249343[/C][C]1.9314[/C][C]0.029081[/C][/ROW]
[ROW][C]12[/C][C]0.745149[/C][C]5.7719[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.275961[/C][C]2.1376[/C][C]0.018317[/C][/ROW]
[ROW][C]14[/C][C]0.120266[/C][C]0.9316[/C][C]0.177645[/C][/ROW]
[ROW][C]15[/C][C]-0.003271[/C][C]-0.0253[/C][C]0.489935[/C][/ROW]
[ROW][C]16[/C][C]-0.109712[/C][C]-0.8498[/C][C]0.199399[/C][/ROW]
[ROW][C]17[/C][C]-0.207962[/C][C]-1.6109[/C][C]0.056229[/C][/ROW]
[ROW][C]18[/C][C]-0.445061[/C][C]-3.4474[/C][C]0.00052[/C][/ROW]
[ROW][C]19[/C][C]-0.274795[/C][C]-2.1286[/C][C]0.018703[/C][/ROW]
[ROW][C]20[/C][C]-0.179854[/C][C]-1.3931[/C][C]0.084358[/C][/ROW]
[ROW][C]21[/C][C]-0.079076[/C][C]-0.6125[/C][C]0.271253[/C][/ROW]
[ROW][C]22[/C][C]0.023527[/C][C]0.1822[/C][C]0.428004[/C][/ROW]
[ROW][C]23[/C][C]0.171465[/C][C]1.3282[/C][C]0.094578[/C][/ROW]
[ROW][C]24[/C][C]0.536124[/C][C]4.1528[/C][C]5.3e-05[/C][/ROW]
[ROW][C]25[/C][C]0.240696[/C][C]1.8644[/C][C]0.033578[/C][/ROW]
[ROW][C]26[/C][C]0.105921[/C][C]0.8205[/C][C]0.207601[/C][/ROW]
[ROW][C]27[/C][C]0.032684[/C][C]0.2532[/C][C]0.400502[/C][/ROW]
[ROW][C]28[/C][C]-0.068795[/C][C]-0.5329[/C][C]0.298042[/C][/ROW]
[ROW][C]29[/C][C]-0.113166[/C][C]-0.8766[/C][C]0.192105[/C][/ROW]
[ROW][C]30[/C][C]-0.309786[/C][C]-2.3996[/C][C]0.009768[/C][/ROW]
[ROW][C]31[/C][C]-0.206965[/C][C]-1.6031[/C][C]0.057078[/C][/ROW]
[ROW][C]32[/C][C]-0.151961[/C][C]-1.1771[/C][C]0.121904[/C][/ROW]
[ROW][C]33[/C][C]-0.094926[/C][C]-0.7353[/C][C]0.232512[/C][/ROW]
[ROW][C]34[/C][C]-0.01637[/C][C]-0.1268[/C][C]0.449761[/C][/ROW]
[ROW][C]35[/C][C]0.065554[/C][C]0.5078[/C][C]0.306736[/C][/ROW]
[ROW][C]36[/C][C]0.304695[/C][C]2.3602[/C][C]0.010768[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61181&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61181&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.3712622.87580.002786
20.1728421.33880.092838
30.003510.02720.4892
4-0.144125-1.11640.134353
5-0.259602-2.01090.02442
6-0.540785-4.18894.7e-05
7-0.324671-2.51490.007302
8-0.206419-1.59890.057546
9-0.06975-0.54030.295501
100.0710040.550.292181
110.2493431.93140.029081
120.7451495.77190
130.2759612.13760.018317
140.1202660.93160.177645
15-0.003271-0.02530.489935
16-0.109712-0.84980.199399
17-0.207962-1.61090.056229
18-0.445061-3.44740.00052
19-0.274795-2.12860.018703
20-0.179854-1.39310.084358
21-0.079076-0.61250.271253
220.0235270.18220.428004
230.1714651.32820.094578
240.5361244.15285.3e-05
250.2406961.86440.033578
260.1059210.82050.207601
270.0326840.25320.400502
28-0.068795-0.53290.298042
29-0.113166-0.87660.192105
30-0.309786-2.39960.009768
31-0.206965-1.60310.057078
32-0.151961-1.17710.121904
33-0.094926-0.73530.232512
34-0.01637-0.12680.449761
350.0655540.50780.306736
360.3046952.36020.010768






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3712622.87580.002786
20.0406030.31450.377112
3-0.08496-0.65810.256497
4-0.147559-1.1430.128792
5-0.178923-1.38590.085449
6-0.451546-3.49770.000445
7-0.023642-0.18310.427657
8-0.063336-0.49060.31275
9-0.044084-0.34150.36697
10-0.009714-0.07520.470137
110.1216170.9420.174974
120.6246164.83835e-06
13-0.352364-2.72940.004157
14-0.155168-1.20190.117057
15-0.018512-0.14340.443231
160.004020.03110.487631
17-0.035742-0.27690.391422
180.1328131.02880.153859
190.0290690.22520.411307
20-0.064475-0.49940.309655
21-0.066776-0.51720.303444
22-0.028544-0.22110.412883
23-0.040937-0.31710.376136
24-0.076384-0.59170.278149
250.1617281.25270.10758
260.0032870.02550.489886
270.0128640.09960.460478
28-0.078651-0.60920.272338
290.1132870.87750.191854
30-0.017693-0.13710.445725
31-0.033884-0.26250.396933
32-0.024536-0.19010.424953
330.0042250.03270.487001
34-0.036313-0.28130.389731
35-0.102167-0.79140.21592
36-0.100616-0.77940.219412

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.371262 & 2.8758 & 0.002786 \tabularnewline
2 & 0.040603 & 0.3145 & 0.377112 \tabularnewline
3 & -0.08496 & -0.6581 & 0.256497 \tabularnewline
4 & -0.147559 & -1.143 & 0.128792 \tabularnewline
5 & -0.178923 & -1.3859 & 0.085449 \tabularnewline
6 & -0.451546 & -3.4977 & 0.000445 \tabularnewline
7 & -0.023642 & -0.1831 & 0.427657 \tabularnewline
8 & -0.063336 & -0.4906 & 0.31275 \tabularnewline
9 & -0.044084 & -0.3415 & 0.36697 \tabularnewline
10 & -0.009714 & -0.0752 & 0.470137 \tabularnewline
11 & 0.121617 & 0.942 & 0.174974 \tabularnewline
12 & 0.624616 & 4.8383 & 5e-06 \tabularnewline
13 & -0.352364 & -2.7294 & 0.004157 \tabularnewline
14 & -0.155168 & -1.2019 & 0.117057 \tabularnewline
15 & -0.018512 & -0.1434 & 0.443231 \tabularnewline
16 & 0.00402 & 0.0311 & 0.487631 \tabularnewline
17 & -0.035742 & -0.2769 & 0.391422 \tabularnewline
18 & 0.132813 & 1.0288 & 0.153859 \tabularnewline
19 & 0.029069 & 0.2252 & 0.411307 \tabularnewline
20 & -0.064475 & -0.4994 & 0.309655 \tabularnewline
21 & -0.066776 & -0.5172 & 0.303444 \tabularnewline
22 & -0.028544 & -0.2211 & 0.412883 \tabularnewline
23 & -0.040937 & -0.3171 & 0.376136 \tabularnewline
24 & -0.076384 & -0.5917 & 0.278149 \tabularnewline
25 & 0.161728 & 1.2527 & 0.10758 \tabularnewline
26 & 0.003287 & 0.0255 & 0.489886 \tabularnewline
27 & 0.012864 & 0.0996 & 0.460478 \tabularnewline
28 & -0.078651 & -0.6092 & 0.272338 \tabularnewline
29 & 0.113287 & 0.8775 & 0.191854 \tabularnewline
30 & -0.017693 & -0.1371 & 0.445725 \tabularnewline
31 & -0.033884 & -0.2625 & 0.396933 \tabularnewline
32 & -0.024536 & -0.1901 & 0.424953 \tabularnewline
33 & 0.004225 & 0.0327 & 0.487001 \tabularnewline
34 & -0.036313 & -0.2813 & 0.389731 \tabularnewline
35 & -0.102167 & -0.7914 & 0.21592 \tabularnewline
36 & -0.100616 & -0.7794 & 0.219412 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61181&T=2

[TABLE]
[ROW][C]Partial Autocorrelation Function[/C][/ROW]
[ROW][C]Time lag k[/C][C]PACF(k)[/C][C]T-STAT[/C][C]P-value[/C][/ROW]
[ROW][C]1[/C][C]0.371262[/C][C]2.8758[/C][C]0.002786[/C][/ROW]
[ROW][C]2[/C][C]0.040603[/C][C]0.3145[/C][C]0.377112[/C][/ROW]
[ROW][C]3[/C][C]-0.08496[/C][C]-0.6581[/C][C]0.256497[/C][/ROW]
[ROW][C]4[/C][C]-0.147559[/C][C]-1.143[/C][C]0.128792[/C][/ROW]
[ROW][C]5[/C][C]-0.178923[/C][C]-1.3859[/C][C]0.085449[/C][/ROW]
[ROW][C]6[/C][C]-0.451546[/C][C]-3.4977[/C][C]0.000445[/C][/ROW]
[ROW][C]7[/C][C]-0.023642[/C][C]-0.1831[/C][C]0.427657[/C][/ROW]
[ROW][C]8[/C][C]-0.063336[/C][C]-0.4906[/C][C]0.31275[/C][/ROW]
[ROW][C]9[/C][C]-0.044084[/C][C]-0.3415[/C][C]0.36697[/C][/ROW]
[ROW][C]10[/C][C]-0.009714[/C][C]-0.0752[/C][C]0.470137[/C][/ROW]
[ROW][C]11[/C][C]0.121617[/C][C]0.942[/C][C]0.174974[/C][/ROW]
[ROW][C]12[/C][C]0.624616[/C][C]4.8383[/C][C]5e-06[/C][/ROW]
[ROW][C]13[/C][C]-0.352364[/C][C]-2.7294[/C][C]0.004157[/C][/ROW]
[ROW][C]14[/C][C]-0.155168[/C][C]-1.2019[/C][C]0.117057[/C][/ROW]
[ROW][C]15[/C][C]-0.018512[/C][C]-0.1434[/C][C]0.443231[/C][/ROW]
[ROW][C]16[/C][C]0.00402[/C][C]0.0311[/C][C]0.487631[/C][/ROW]
[ROW][C]17[/C][C]-0.035742[/C][C]-0.2769[/C][C]0.391422[/C][/ROW]
[ROW][C]18[/C][C]0.132813[/C][C]1.0288[/C][C]0.153859[/C][/ROW]
[ROW][C]19[/C][C]0.029069[/C][C]0.2252[/C][C]0.411307[/C][/ROW]
[ROW][C]20[/C][C]-0.064475[/C][C]-0.4994[/C][C]0.309655[/C][/ROW]
[ROW][C]21[/C][C]-0.066776[/C][C]-0.5172[/C][C]0.303444[/C][/ROW]
[ROW][C]22[/C][C]-0.028544[/C][C]-0.2211[/C][C]0.412883[/C][/ROW]
[ROW][C]23[/C][C]-0.040937[/C][C]-0.3171[/C][C]0.376136[/C][/ROW]
[ROW][C]24[/C][C]-0.076384[/C][C]-0.5917[/C][C]0.278149[/C][/ROW]
[ROW][C]25[/C][C]0.161728[/C][C]1.2527[/C][C]0.10758[/C][/ROW]
[ROW][C]26[/C][C]0.003287[/C][C]0.0255[/C][C]0.489886[/C][/ROW]
[ROW][C]27[/C][C]0.012864[/C][C]0.0996[/C][C]0.460478[/C][/ROW]
[ROW][C]28[/C][C]-0.078651[/C][C]-0.6092[/C][C]0.272338[/C][/ROW]
[ROW][C]29[/C][C]0.113287[/C][C]0.8775[/C][C]0.191854[/C][/ROW]
[ROW][C]30[/C][C]-0.017693[/C][C]-0.1371[/C][C]0.445725[/C][/ROW]
[ROW][C]31[/C][C]-0.033884[/C][C]-0.2625[/C][C]0.396933[/C][/ROW]
[ROW][C]32[/C][C]-0.024536[/C][C]-0.1901[/C][C]0.424953[/C][/ROW]
[ROW][C]33[/C][C]0.004225[/C][C]0.0327[/C][C]0.487001[/C][/ROW]
[ROW][C]34[/C][C]-0.036313[/C][C]-0.2813[/C][C]0.389731[/C][/ROW]
[ROW][C]35[/C][C]-0.102167[/C][C]-0.7914[/C][C]0.21592[/C][/ROW]
[ROW][C]36[/C][C]-0.100616[/C][C]-0.7794[/C][C]0.219412[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61181&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61181&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3712622.87580.002786
20.0406030.31450.377112
3-0.08496-0.65810.256497
4-0.147559-1.1430.128792
5-0.178923-1.38590.085449
6-0.451546-3.49770.000445
7-0.023642-0.18310.427657
8-0.063336-0.49060.31275
9-0.044084-0.34150.36697
10-0.009714-0.07520.470137
110.1216170.9420.174974
120.6246164.83835e-06
13-0.352364-2.72940.004157
14-0.155168-1.20190.117057
15-0.018512-0.14340.443231
160.004020.03110.487631
17-0.035742-0.27690.391422
180.1328131.02880.153859
190.0290690.22520.411307
20-0.064475-0.49940.309655
21-0.066776-0.51720.303444
22-0.028544-0.22110.412883
23-0.040937-0.31710.376136
24-0.076384-0.59170.278149
250.1617281.25270.10758
260.0032870.02550.489886
270.0128640.09960.460478
28-0.078651-0.60920.272338
290.1132870.87750.191854
30-0.017693-0.13710.445725
31-0.033884-0.26250.396933
32-0.024536-0.19010.424953
330.0042250.03270.487001
34-0.036313-0.28130.389731
35-0.102167-0.79140.21592
36-0.100616-0.77940.219412


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
R code (references can be found in the software module):
if (par1 == 'Default') {
par1 = 10*log10(length(x))
} else {
par1 <- as.numeric(par1)
}
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
par5 <- as.numeric(par5)
if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
par7 <- as.numeric(par7)
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
dev.off()
(myacf <- c(racf$acf))
(mypacf <- c(rpacf$acf))
lengthx <- length(x)
sqrtn <- sqrt(lengthx)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','ACF(k)','click here for more information about the Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 2:(par1+1)) {
a<-table.row.start(a)
a<-table.element(a,i-1,header=TRUE)
a<-table.element(a,round(myacf[i],6))
mytstat <- myacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Partial Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','PACF(k)','click here for more information about the Partial Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:par1) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,round(mypacf[i],6))
mytstat <- mypacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')