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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 computationSat, 19 Dec 2009 18:17:09 -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/Dec/20/t1261271890scvu98w6m4uheo3.htm/, Retrieved Sat, 27 Apr 2024 06:58:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=69772, Retrieved Sat, 27 Apr 2024 06:58:16 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact179

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] [4a2be4899cba879e4eea9daa25281df8]
-    D            [(Partial) Autocorrelation Function] [PAPER 5] [2009-12-20 01:17:09] [71c065898bd1c08eef04509b4bcee039] [Current]
-    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 
144,63
124,24
135,21
119,80
102,79
109,42
99,61
83,02
95,29
116,18
81,25
71,35
128,63
134,85
167,22
147,01
104,08
111,61
82,63
80,48
93,46
104,55
87,97
63,36
136,50
117,44
133,53
121,53
102,82
124,11
82,47
85,96
90,34
90,80
84,80
49,10
146,65
135,41
158,36
124,67
122,70
108,72
83,33
79,52
83,55
96,35
79,77
42,99
142,84
121,85
140,67
118,67
115,19
118,30
93,70
85,76
93,73
113,70
90,93
58,46
144,86
138,19
137,77
146,55
118,52
123,15
92,73
81,64
94,17
103,34
71,46
52,82
116,78
110,56
127,52
120,22
94,15
104,45
87,32
77,88
91,95
103,19
85,96

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=69772&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=69772&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69772&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
10.3755623.42150.000484
20.1520871.38560.084793
3-0.030007-0.27340.392622
4-0.212152-1.93280.028336
5-0.282185-2.57080.005965
6-0.481417-4.38591.7e-05
7-0.296714-2.70320.004164
8-0.212804-1.93870.027966
9-0.078918-0.7190.237087
100.047560.43330.332964
110.2604652.37290.009979
120.7737447.04910
130.2845112.5920.005636
140.1333951.21530.113851
15-0.002179-0.01990.492103
16-0.179115-1.63180.053254
17-0.256295-2.3350.01098
18-0.459641-4.18753.5e-05
19-0.281467-2.56430.00607
20-0.209089-1.90490.030129
21-0.112628-1.02610.153916
220.0371250.33820.368024
230.2397582.18430.015881
240.6430615.85860
250.2727262.48470.007489
260.1211431.10370.136464
270.0160270.1460.442134
28-0.125565-1.14390.127967
29-0.193108-1.75930.041106
30-0.365606-3.33080.000647
31-0.214645-1.95550.026944
32-0.197969-1.80360.037463
33-0.120503-1.09780.137725
340.014350.13070.44815
350.166541.51720.066502
360.482174.39281.6e-05

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.375562 & 3.4215 & 0.000484 \tabularnewline
2 & 0.152087 & 1.3856 & 0.084793 \tabularnewline
3 & -0.030007 & -0.2734 & 0.392622 \tabularnewline
4 & -0.212152 & -1.9328 & 0.028336 \tabularnewline
5 & -0.282185 & -2.5708 & 0.005965 \tabularnewline
6 & -0.481417 & -4.3859 & 1.7e-05 \tabularnewline
7 & -0.296714 & -2.7032 & 0.004164 \tabularnewline
8 & -0.212804 & -1.9387 & 0.027966 \tabularnewline
9 & -0.078918 & -0.719 & 0.237087 \tabularnewline
10 & 0.04756 & 0.4333 & 0.332964 \tabularnewline
11 & 0.260465 & 2.3729 & 0.009979 \tabularnewline
12 & 0.773744 & 7.0491 & 0 \tabularnewline
13 & 0.284511 & 2.592 & 0.005636 \tabularnewline
14 & 0.133395 & 1.2153 & 0.113851 \tabularnewline
15 & -0.002179 & -0.0199 & 0.492103 \tabularnewline
16 & -0.179115 & -1.6318 & 0.053254 \tabularnewline
17 & -0.256295 & -2.335 & 0.01098 \tabularnewline
18 & -0.459641 & -4.1875 & 3.5e-05 \tabularnewline
19 & -0.281467 & -2.5643 & 0.00607 \tabularnewline
20 & -0.209089 & -1.9049 & 0.030129 \tabularnewline
21 & -0.112628 & -1.0261 & 0.153916 \tabularnewline
22 & 0.037125 & 0.3382 & 0.368024 \tabularnewline
23 & 0.239758 & 2.1843 & 0.015881 \tabularnewline
24 & 0.643061 & 5.8586 & 0 \tabularnewline
25 & 0.272726 & 2.4847 & 0.007489 \tabularnewline
26 & 0.121143 & 1.1037 & 0.136464 \tabularnewline
27 & 0.016027 & 0.146 & 0.442134 \tabularnewline
28 & -0.125565 & -1.1439 & 0.127967 \tabularnewline
29 & -0.193108 & -1.7593 & 0.041106 \tabularnewline
30 & -0.365606 & -3.3308 & 0.000647 \tabularnewline
31 & -0.214645 & -1.9555 & 0.026944 \tabularnewline
32 & -0.197969 & -1.8036 & 0.037463 \tabularnewline
33 & -0.120503 & -1.0978 & 0.137725 \tabularnewline
34 & 0.01435 & 0.1307 & 0.44815 \tabularnewline
35 & 0.16654 & 1.5172 & 0.066502 \tabularnewline
36 & 0.48217 & 4.3928 & 1.6e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69772&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]0.375562[/C][C]3.4215[/C][C]0.000484[/C][/ROW]
[ROW][C]2[/C][C]0.152087[/C][C]1.3856[/C][C]0.084793[/C][/ROW]
[ROW][C]3[/C][C]-0.030007[/C][C]-0.2734[/C][C]0.392622[/C][/ROW]
[ROW][C]4[/C][C]-0.212152[/C][C]-1.9328[/C][C]0.028336[/C][/ROW]
[ROW][C]5[/C][C]-0.282185[/C][C]-2.5708[/C][C]0.005965[/C][/ROW]
[ROW][C]6[/C][C]-0.481417[/C][C]-4.3859[/C][C]1.7e-05[/C][/ROW]
[ROW][C]7[/C][C]-0.296714[/C][C]-2.7032[/C][C]0.004164[/C][/ROW]
[ROW][C]8[/C][C]-0.212804[/C][C]-1.9387[/C][C]0.027966[/C][/ROW]
[ROW][C]9[/C][C]-0.078918[/C][C]-0.719[/C][C]0.237087[/C][/ROW]
[ROW][C]10[/C][C]0.04756[/C][C]0.4333[/C][C]0.332964[/C][/ROW]
[ROW][C]11[/C][C]0.260465[/C][C]2.3729[/C][C]0.009979[/C][/ROW]
[ROW][C]12[/C][C]0.773744[/C][C]7.0491[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.284511[/C][C]2.592[/C][C]0.005636[/C][/ROW]
[ROW][C]14[/C][C]0.133395[/C][C]1.2153[/C][C]0.113851[/C][/ROW]
[ROW][C]15[/C][C]-0.002179[/C][C]-0.0199[/C][C]0.492103[/C][/ROW]
[ROW][C]16[/C][C]-0.179115[/C][C]-1.6318[/C][C]0.053254[/C][/ROW]
[ROW][C]17[/C][C]-0.256295[/C][C]-2.335[/C][C]0.01098[/C][/ROW]
[ROW][C]18[/C][C]-0.459641[/C][C]-4.1875[/C][C]3.5e-05[/C][/ROW]
[ROW][C]19[/C][C]-0.281467[/C][C]-2.5643[/C][C]0.00607[/C][/ROW]
[ROW][C]20[/C][C]-0.209089[/C][C]-1.9049[/C][C]0.030129[/C][/ROW]
[ROW][C]21[/C][C]-0.112628[/C][C]-1.0261[/C][C]0.153916[/C][/ROW]
[ROW][C]22[/C][C]0.037125[/C][C]0.3382[/C][C]0.368024[/C][/ROW]
[ROW][C]23[/C][C]0.239758[/C][C]2.1843[/C][C]0.015881[/C][/ROW]
[ROW][C]24[/C][C]0.643061[/C][C]5.8586[/C][C]0[/C][/ROW]
[ROW][C]25[/C][C]0.272726[/C][C]2.4847[/C][C]0.007489[/C][/ROW]
[ROW][C]26[/C][C]0.121143[/C][C]1.1037[/C][C]0.136464[/C][/ROW]
[ROW][C]27[/C][C]0.016027[/C][C]0.146[/C][C]0.442134[/C][/ROW]
[ROW][C]28[/C][C]-0.125565[/C][C]-1.1439[/C][C]0.127967[/C][/ROW]
[ROW][C]29[/C][C]-0.193108[/C][C]-1.7593[/C][C]0.041106[/C][/ROW]
[ROW][C]30[/C][C]-0.365606[/C][C]-3.3308[/C][C]0.000647[/C][/ROW]
[ROW][C]31[/C][C]-0.214645[/C][C]-1.9555[/C][C]0.026944[/C][/ROW]
[ROW][C]32[/C][C]-0.197969[/C][C]-1.8036[/C][C]0.037463[/C][/ROW]
[ROW][C]33[/C][C]-0.120503[/C][C]-1.0978[/C][C]0.137725[/C][/ROW]
[ROW][C]34[/C][C]0.01435[/C][C]0.1307[/C][C]0.44815[/C][/ROW]
[ROW][C]35[/C][C]0.16654[/C][C]1.5172[/C][C]0.066502[/C][/ROW]
[ROW][C]36[/C][C]0.48217[/C][C]4.3928[/C][C]1.6e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69772&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69772&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
10.3755623.42150.000484
20.1520871.38560.084793
3-0.030007-0.27340.392622
4-0.212152-1.93280.028336
5-0.282185-2.57080.005965
6-0.481417-4.38591.7e-05
7-0.296714-2.70320.004164
8-0.212804-1.93870.027966
9-0.078918-0.7190.237087
100.047560.43330.332964
110.2604652.37290.009979
120.7737447.04910
130.2845112.5920.005636
140.1333951.21530.113851
15-0.002179-0.01990.492103
16-0.179115-1.63180.053254
17-0.256295-2.3350.01098
18-0.459641-4.18753.5e-05
19-0.281467-2.56430.00607
20-0.209089-1.90490.030129
21-0.112628-1.02610.153916
220.0371250.33820.368024
230.2397582.18430.015881
240.6430615.85860
250.2727262.48470.007489
260.1211431.10370.136464
270.0160270.1460.442134
28-0.125565-1.14390.127967
29-0.193108-1.75930.041106
30-0.365606-3.33080.000647
31-0.214645-1.95550.026944
32-0.197969-1.80360.037463
33-0.120503-1.09780.137725
340.014350.13070.44815
350.166541.51720.066502
360.482174.39281.6e-05






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3755623.42150.000484
20.0128540.11710.453531
3-0.106215-0.96770.168012
4-0.199076-1.81370.036672
5-0.154754-1.40990.081156
6-0.376135-3.42680.000476
7-0.04898-0.44620.328295
8-0.152624-1.39050.084052
9-0.098707-0.89930.185556
10-0.118007-1.07510.142725
110.1221321.11270.134531
120.6781316.17810
13-0.386993-3.52570.000345
14-0.089537-0.81570.208498
150.069740.63540.263469
16-0.024033-0.2190.413612
17-0.117164-1.06740.144439
18-0.035637-0.32470.373123
190.0107660.09810.461051
20-0.105237-0.95880.170234
21-0.064198-0.58490.28011
220.1691031.54060.063609
230.0069930.06370.474677
24-0.11939-1.08770.13994
250.0950680.86610.194464
26-0.093001-0.84730.199639
27-0.094068-0.8570.196957
280.1017520.9270.178306
290.1038610.94620.173392
30-0.00522-0.04760.481091
31-0.043434-0.39570.346669
32-0.033163-0.30210.381656
330.072310.65880.255932
34-0.085163-0.77590.220016
35-0.100865-0.91890.1804
36-0.036128-0.32910.371439

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.375562 & 3.4215 & 0.000484 \tabularnewline
2 & 0.012854 & 0.1171 & 0.453531 \tabularnewline
3 & -0.106215 & -0.9677 & 0.168012 \tabularnewline
4 & -0.199076 & -1.8137 & 0.036672 \tabularnewline
5 & -0.154754 & -1.4099 & 0.081156 \tabularnewline
6 & -0.376135 & -3.4268 & 0.000476 \tabularnewline
7 & -0.04898 & -0.4462 & 0.328295 \tabularnewline
8 & -0.152624 & -1.3905 & 0.084052 \tabularnewline
9 & -0.098707 & -0.8993 & 0.185556 \tabularnewline
10 & -0.118007 & -1.0751 & 0.142725 \tabularnewline
11 & 0.122132 & 1.1127 & 0.134531 \tabularnewline
12 & 0.678131 & 6.1781 & 0 \tabularnewline
13 & -0.386993 & -3.5257 & 0.000345 \tabularnewline
14 & -0.089537 & -0.8157 & 0.208498 \tabularnewline
15 & 0.06974 & 0.6354 & 0.263469 \tabularnewline
16 & -0.024033 & -0.219 & 0.413612 \tabularnewline
17 & -0.117164 & -1.0674 & 0.144439 \tabularnewline
18 & -0.035637 & -0.3247 & 0.373123 \tabularnewline
19 & 0.010766 & 0.0981 & 0.461051 \tabularnewline
20 & -0.105237 & -0.9588 & 0.170234 \tabularnewline
21 & -0.064198 & -0.5849 & 0.28011 \tabularnewline
22 & 0.169103 & 1.5406 & 0.063609 \tabularnewline
23 & 0.006993 & 0.0637 & 0.474677 \tabularnewline
24 & -0.11939 & -1.0877 & 0.13994 \tabularnewline
25 & 0.095068 & 0.8661 & 0.194464 \tabularnewline
26 & -0.093001 & -0.8473 & 0.199639 \tabularnewline
27 & -0.094068 & -0.857 & 0.196957 \tabularnewline
28 & 0.101752 & 0.927 & 0.178306 \tabularnewline
29 & 0.103861 & 0.9462 & 0.173392 \tabularnewline
30 & -0.00522 & -0.0476 & 0.481091 \tabularnewline
31 & -0.043434 & -0.3957 & 0.346669 \tabularnewline
32 & -0.033163 & -0.3021 & 0.381656 \tabularnewline
33 & 0.07231 & 0.6588 & 0.255932 \tabularnewline
34 & -0.085163 & -0.7759 & 0.220016 \tabularnewline
35 & -0.100865 & -0.9189 & 0.1804 \tabularnewline
36 & -0.036128 & -0.3291 & 0.371439 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69772&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]0.375562[/C][C]3.4215[/C][C]0.000484[/C][/ROW]
[ROW][C]2[/C][C]0.012854[/C][C]0.1171[/C][C]0.453531[/C][/ROW]
[ROW][C]3[/C][C]-0.106215[/C][C]-0.9677[/C][C]0.168012[/C][/ROW]
[ROW][C]4[/C][C]-0.199076[/C][C]-1.8137[/C][C]0.036672[/C][/ROW]
[ROW][C]5[/C][C]-0.154754[/C][C]-1.4099[/C][C]0.081156[/C][/ROW]
[ROW][C]6[/C][C]-0.376135[/C][C]-3.4268[/C][C]0.000476[/C][/ROW]
[ROW][C]7[/C][C]-0.04898[/C][C]-0.4462[/C][C]0.328295[/C][/ROW]
[ROW][C]8[/C][C]-0.152624[/C][C]-1.3905[/C][C]0.084052[/C][/ROW]
[ROW][C]9[/C][C]-0.098707[/C][C]-0.8993[/C][C]0.185556[/C][/ROW]
[ROW][C]10[/C][C]-0.118007[/C][C]-1.0751[/C][C]0.142725[/C][/ROW]
[ROW][C]11[/C][C]0.122132[/C][C]1.1127[/C][C]0.134531[/C][/ROW]
[ROW][C]12[/C][C]0.678131[/C][C]6.1781[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.386993[/C][C]-3.5257[/C][C]0.000345[/C][/ROW]
[ROW][C]14[/C][C]-0.089537[/C][C]-0.8157[/C][C]0.208498[/C][/ROW]
[ROW][C]15[/C][C]0.06974[/C][C]0.6354[/C][C]0.263469[/C][/ROW]
[ROW][C]16[/C][C]-0.024033[/C][C]-0.219[/C][C]0.413612[/C][/ROW]
[ROW][C]17[/C][C]-0.117164[/C][C]-1.0674[/C][C]0.144439[/C][/ROW]
[ROW][C]18[/C][C]-0.035637[/C][C]-0.3247[/C][C]0.373123[/C][/ROW]
[ROW][C]19[/C][C]0.010766[/C][C]0.0981[/C][C]0.461051[/C][/ROW]
[ROW][C]20[/C][C]-0.105237[/C][C]-0.9588[/C][C]0.170234[/C][/ROW]
[ROW][C]21[/C][C]-0.064198[/C][C]-0.5849[/C][C]0.28011[/C][/ROW]
[ROW][C]22[/C][C]0.169103[/C][C]1.5406[/C][C]0.063609[/C][/ROW]
[ROW][C]23[/C][C]0.006993[/C][C]0.0637[/C][C]0.474677[/C][/ROW]
[ROW][C]24[/C][C]-0.11939[/C][C]-1.0877[/C][C]0.13994[/C][/ROW]
[ROW][C]25[/C][C]0.095068[/C][C]0.8661[/C][C]0.194464[/C][/ROW]
[ROW][C]26[/C][C]-0.093001[/C][C]-0.8473[/C][C]0.199639[/C][/ROW]
[ROW][C]27[/C][C]-0.094068[/C][C]-0.857[/C][C]0.196957[/C][/ROW]
[ROW][C]28[/C][C]0.101752[/C][C]0.927[/C][C]0.178306[/C][/ROW]
[ROW][C]29[/C][C]0.103861[/C][C]0.9462[/C][C]0.173392[/C][/ROW]
[ROW][C]30[/C][C]-0.00522[/C][C]-0.0476[/C][C]0.481091[/C][/ROW]
[ROW][C]31[/C][C]-0.043434[/C][C]-0.3957[/C][C]0.346669[/C][/ROW]
[ROW][C]32[/C][C]-0.033163[/C][C]-0.3021[/C][C]0.381656[/C][/ROW]
[ROW][C]33[/C][C]0.07231[/C][C]0.6588[/C][C]0.255932[/C][/ROW]
[ROW][C]34[/C][C]-0.085163[/C][C]-0.7759[/C][C]0.220016[/C][/ROW]
[ROW][C]35[/C][C]-0.100865[/C][C]-0.9189[/C][C]0.1804[/C][/ROW]
[ROW][C]36[/C][C]-0.036128[/C][C]-0.3291[/C][C]0.371439[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69772&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69772&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
10.3755623.42150.000484
20.0128540.11710.453531
3-0.106215-0.96770.168012
4-0.199076-1.81370.036672
5-0.154754-1.40990.081156
6-0.376135-3.42680.000476
7-0.04898-0.44620.328295
8-0.152624-1.39050.084052
9-0.098707-0.89930.185556
10-0.118007-1.07510.142725
110.1221321.11270.134531
120.6781316.17810
13-0.386993-3.52570.000345
14-0.089537-0.81570.208498
150.069740.63540.263469
16-0.024033-0.2190.413612
17-0.117164-1.06740.144439
18-0.035637-0.32470.373123
190.0107660.09810.461051
20-0.105237-0.95880.170234
21-0.064198-0.58490.28011
220.1691031.54060.063609
230.0069930.06370.474677
24-0.11939-1.08770.13994
250.0950680.86610.194464
26-0.093001-0.84730.199639
27-0.094068-0.8570.196957
280.1017520.9270.178306
290.1038610.94620.173392
30-0.00522-0.04760.481091
31-0.043434-0.39570.346669
32-0.033163-0.30210.381656
330.072310.65880.255932
34-0.085163-0.77590.220016
35-0.100865-0.91890.1804
36-0.036128-0.32910.371439


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')