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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 computationTue, 24 Nov 2009 11:19:05 -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/24/t1259086806kmr1inhf1apyira.htm/, Retrieved Tue, 10 Jun 2025 03:12:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59203, Retrieved Tue, 10 Jun 2025 03:12:33 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsWorkshop 8 - methode 1 link 1
Estimated Impact282

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] [Workshop 8] [2009-11-24 18:19:05] [100339cefec36dfa6f2b82a1c918e250] [Current]
-    D            [(Partial) Autocorrelation Function] [Workshop 8: Metho...] [2009-11-26 15:48:49] [1433a524809eda02c3198b3ae6eebb69]
-    D              [(Partial) Autocorrelation Function] [Workshop 8: Metho...] [2009-11-26 16:45:29] [6f6b63f0ca778484da1b5c31f09bf8b6]
-   P                 [(Partial) Autocorrelation Function] [Workshop 8: Metho...] [2009-11-26 16:52:54] [6f6b63f0ca778484da1b5c31f09bf8b6]
-   P                 [(Partial) Autocorrelation Function] [Method1: d= 1, D=...] [2009-12-11 12:34:39] [1433a524809eda02c3198b3ae6eebb69]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
162
161
149
139
135
130
127
122
117
112
113
149
157
157
147
137
132
125
123
117
114
111
112
144
150
149
134
123
116
117
111
105
102
95
93
124
130
124
115
106
105
105
101
95
93
84
87
116
120
117
109
105
107
109
109
108
107
99
103
131
137

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=59203&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=59203&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59203&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
10.7961056.21780
20.5006743.91040.000117
30.2869522.24120.014333
40.17481.36520.088597
50.13341.04190.150788
60.1137720.88860.188859
70.0888430.69390.245194
80.0874210.68280.248665
90.1766641.37980.086344
100.3681422.87530.002776
110.5951634.64849e-06
120.6635575.18251e-06
130.471893.68560.000243
140.2131911.66510.050513
150.028680.2240.411754
16-0.070506-0.55070.291936
17-0.112669-0.880.191163
18-0.136698-1.06760.144943
19-0.173361-1.3540.090367
20-0.182034-1.42170.080098
21-0.116442-0.90940.183348
220.0311850.24360.404194
230.2053581.60390.056951
240.2461751.92270.029596
250.0914550.71430.238887
26-0.102592-0.80130.213042
27-0.21802-1.70280.046849
28-0.273109-2.1330.018476
29-0.290408-2.26820.013436
30-0.314784-2.45850.008402
31-0.337141-2.63320.005352
32-0.339018-2.64780.005149
33-0.280966-2.19440.016012
34-0.155232-1.21240.115017
35-0.0104-0.08120.467764
360.0180220.14080.444262

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.796105 & 6.2178 & 0 \tabularnewline
2 & 0.500674 & 3.9104 & 0.000117 \tabularnewline
3 & 0.286952 & 2.2412 & 0.014333 \tabularnewline
4 & 0.1748 & 1.3652 & 0.088597 \tabularnewline
5 & 0.1334 & 1.0419 & 0.150788 \tabularnewline
6 & 0.113772 & 0.8886 & 0.188859 \tabularnewline
7 & 0.088843 & 0.6939 & 0.245194 \tabularnewline
8 & 0.087421 & 0.6828 & 0.248665 \tabularnewline
9 & 0.176664 & 1.3798 & 0.086344 \tabularnewline
10 & 0.368142 & 2.8753 & 0.002776 \tabularnewline
11 & 0.595163 & 4.6484 & 9e-06 \tabularnewline
12 & 0.663557 & 5.1825 & 1e-06 \tabularnewline
13 & 0.47189 & 3.6856 & 0.000243 \tabularnewline
14 & 0.213191 & 1.6651 & 0.050513 \tabularnewline
15 & 0.02868 & 0.224 & 0.411754 \tabularnewline
16 & -0.070506 & -0.5507 & 0.291936 \tabularnewline
17 & -0.112669 & -0.88 & 0.191163 \tabularnewline
18 & -0.136698 & -1.0676 & 0.144943 \tabularnewline
19 & -0.173361 & -1.354 & 0.090367 \tabularnewline
20 & -0.182034 & -1.4217 & 0.080098 \tabularnewline
21 & -0.116442 & -0.9094 & 0.183348 \tabularnewline
22 & 0.031185 & 0.2436 & 0.404194 \tabularnewline
23 & 0.205358 & 1.6039 & 0.056951 \tabularnewline
24 & 0.246175 & 1.9227 & 0.029596 \tabularnewline
25 & 0.091455 & 0.7143 & 0.238887 \tabularnewline
26 & -0.102592 & -0.8013 & 0.213042 \tabularnewline
27 & -0.21802 & -1.7028 & 0.046849 \tabularnewline
28 & -0.273109 & -2.133 & 0.018476 \tabularnewline
29 & -0.290408 & -2.2682 & 0.013436 \tabularnewline
30 & -0.314784 & -2.4585 & 0.008402 \tabularnewline
31 & -0.337141 & -2.6332 & 0.005352 \tabularnewline
32 & -0.339018 & -2.6478 & 0.005149 \tabularnewline
33 & -0.280966 & -2.1944 & 0.016012 \tabularnewline
34 & -0.155232 & -1.2124 & 0.115017 \tabularnewline
35 & -0.0104 & -0.0812 & 0.467764 \tabularnewline
36 & 0.018022 & 0.1408 & 0.444262 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59203&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]0.796105[/C][C]6.2178[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.500674[/C][C]3.9104[/C][C]0.000117[/C][/ROW]
[ROW][C]3[/C][C]0.286952[/C][C]2.2412[/C][C]0.014333[/C][/ROW]
[ROW][C]4[/C][C]0.1748[/C][C]1.3652[/C][C]0.088597[/C][/ROW]
[ROW][C]5[/C][C]0.1334[/C][C]1.0419[/C][C]0.150788[/C][/ROW]
[ROW][C]6[/C][C]0.113772[/C][C]0.8886[/C][C]0.188859[/C][/ROW]
[ROW][C]7[/C][C]0.088843[/C][C]0.6939[/C][C]0.245194[/C][/ROW]
[ROW][C]8[/C][C]0.087421[/C][C]0.6828[/C][C]0.248665[/C][/ROW]
[ROW][C]9[/C][C]0.176664[/C][C]1.3798[/C][C]0.086344[/C][/ROW]
[ROW][C]10[/C][C]0.368142[/C][C]2.8753[/C][C]0.002776[/C][/ROW]
[ROW][C]11[/C][C]0.595163[/C][C]4.6484[/C][C]9e-06[/C][/ROW]
[ROW][C]12[/C][C]0.663557[/C][C]5.1825[/C][C]1e-06[/C][/ROW]
[ROW][C]13[/C][C]0.47189[/C][C]3.6856[/C][C]0.000243[/C][/ROW]
[ROW][C]14[/C][C]0.213191[/C][C]1.6651[/C][C]0.050513[/C][/ROW]
[ROW][C]15[/C][C]0.02868[/C][C]0.224[/C][C]0.411754[/C][/ROW]
[ROW][C]16[/C][C]-0.070506[/C][C]-0.5507[/C][C]0.291936[/C][/ROW]
[ROW][C]17[/C][C]-0.112669[/C][C]-0.88[/C][C]0.191163[/C][/ROW]
[ROW][C]18[/C][C]-0.136698[/C][C]-1.0676[/C][C]0.144943[/C][/ROW]
[ROW][C]19[/C][C]-0.173361[/C][C]-1.354[/C][C]0.090367[/C][/ROW]
[ROW][C]20[/C][C]-0.182034[/C][C]-1.4217[/C][C]0.080098[/C][/ROW]
[ROW][C]21[/C][C]-0.116442[/C][C]-0.9094[/C][C]0.183348[/C][/ROW]
[ROW][C]22[/C][C]0.031185[/C][C]0.2436[/C][C]0.404194[/C][/ROW]
[ROW][C]23[/C][C]0.205358[/C][C]1.6039[/C][C]0.056951[/C][/ROW]
[ROW][C]24[/C][C]0.246175[/C][C]1.9227[/C][C]0.029596[/C][/ROW]
[ROW][C]25[/C][C]0.091455[/C][C]0.7143[/C][C]0.238887[/C][/ROW]
[ROW][C]26[/C][C]-0.102592[/C][C]-0.8013[/C][C]0.213042[/C][/ROW]
[ROW][C]27[/C][C]-0.21802[/C][C]-1.7028[/C][C]0.046849[/C][/ROW]
[ROW][C]28[/C][C]-0.273109[/C][C]-2.133[/C][C]0.018476[/C][/ROW]
[ROW][C]29[/C][C]-0.290408[/C][C]-2.2682[/C][C]0.013436[/C][/ROW]
[ROW][C]30[/C][C]-0.314784[/C][C]-2.4585[/C][C]0.008402[/C][/ROW]
[ROW][C]31[/C][C]-0.337141[/C][C]-2.6332[/C][C]0.005352[/C][/ROW]
[ROW][C]32[/C][C]-0.339018[/C][C]-2.6478[/C][C]0.005149[/C][/ROW]
[ROW][C]33[/C][C]-0.280966[/C][C]-2.1944[/C][C]0.016012[/C][/ROW]
[ROW][C]34[/C][C]-0.155232[/C][C]-1.2124[/C][C]0.115017[/C][/ROW]
[ROW][C]35[/C][C]-0.0104[/C][C]-0.0812[/C][C]0.467764[/C][/ROW]
[ROW][C]36[/C][C]0.018022[/C][C]0.1408[/C][C]0.444262[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59203&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59203&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
10.7961056.21780
20.5006743.91040.000117
30.2869522.24120.014333
40.17481.36520.088597
50.13341.04190.150788
60.1137720.88860.188859
70.0888430.69390.245194
80.0874210.68280.248665
90.1766641.37980.086344
100.3681422.87530.002776
110.5951634.64849e-06
120.6635575.18251e-06
130.471893.68560.000243
140.2131911.66510.050513
150.028680.2240.411754
16-0.070506-0.55070.291936
17-0.112669-0.880.191163
18-0.136698-1.06760.144943
19-0.173361-1.3540.090367
20-0.182034-1.42170.080098
21-0.116442-0.90940.183348
220.0311850.24360.404194
230.2053581.60390.056951
240.2461751.92270.029596
250.0914550.71430.238887
26-0.102592-0.80130.213042
27-0.21802-1.70280.046849
28-0.273109-2.1330.018476
29-0.290408-2.26820.013436
30-0.314784-2.45850.008402
31-0.337141-2.63320.005352
32-0.339018-2.64780.005149
33-0.280966-2.19440.016012
34-0.155232-1.21240.115017
35-0.0104-0.08120.467764
360.0180220.14080.444262






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.7961056.21780
2-0.363471-2.83880.003071
30.103350.80720.211347
40.0267590.2090.417574
50.0395060.30850.379358
6-0.009805-0.07660.469603
7-0.011712-0.09150.463707
80.0861670.6730.251749
90.2544421.98730.025695
100.3213932.51020.007368
110.3412552.66530.004915
12-0.091496-0.71460.23879
13-0.425352-3.32210.000757
14-0.129465-1.01120.157968
15-0.086574-0.67620.250746
16-0.082544-0.64470.260774
17-0.038257-0.29880.383055
18-0.012746-0.09960.460513
19-0.064199-0.50140.308944
20-0.072282-0.56450.287229
21-0.174215-1.36070.089314
22-0.14352-1.12090.133355
230.0567250.4430.329653
240.0691470.54010.295562
25-0.041591-0.32480.373209
260.0375040.29290.385289
270.0774390.60480.273773
28-0.033413-0.2610.3975
29-0.024692-0.19280.42386
30-0.099941-0.78060.219039
310.0724190.56560.286867
320.0068920.05380.478625
33-0.006526-0.0510.479759
34-0.063816-0.49840.30999
350.007760.06060.475933
36-0.043982-0.34350.366198

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.796105 & 6.2178 & 0 \tabularnewline
2 & -0.363471 & -2.8388 & 0.003071 \tabularnewline
3 & 0.10335 & 0.8072 & 0.211347 \tabularnewline
4 & 0.026759 & 0.209 & 0.417574 \tabularnewline
5 & 0.039506 & 0.3085 & 0.379358 \tabularnewline
6 & -0.009805 & -0.0766 & 0.469603 \tabularnewline
7 & -0.011712 & -0.0915 & 0.463707 \tabularnewline
8 & 0.086167 & 0.673 & 0.251749 \tabularnewline
9 & 0.254442 & 1.9873 & 0.025695 \tabularnewline
10 & 0.321393 & 2.5102 & 0.007368 \tabularnewline
11 & 0.341255 & 2.6653 & 0.004915 \tabularnewline
12 & -0.091496 & -0.7146 & 0.23879 \tabularnewline
13 & -0.425352 & -3.3221 & 0.000757 \tabularnewline
14 & -0.129465 & -1.0112 & 0.157968 \tabularnewline
15 & -0.086574 & -0.6762 & 0.250746 \tabularnewline
16 & -0.082544 & -0.6447 & 0.260774 \tabularnewline
17 & -0.038257 & -0.2988 & 0.383055 \tabularnewline
18 & -0.012746 & -0.0996 & 0.460513 \tabularnewline
19 & -0.064199 & -0.5014 & 0.308944 \tabularnewline
20 & -0.072282 & -0.5645 & 0.287229 \tabularnewline
21 & -0.174215 & -1.3607 & 0.089314 \tabularnewline
22 & -0.14352 & -1.1209 & 0.133355 \tabularnewline
23 & 0.056725 & 0.443 & 0.329653 \tabularnewline
24 & 0.069147 & 0.5401 & 0.295562 \tabularnewline
25 & -0.041591 & -0.3248 & 0.373209 \tabularnewline
26 & 0.037504 & 0.2929 & 0.385289 \tabularnewline
27 & 0.077439 & 0.6048 & 0.273773 \tabularnewline
28 & -0.033413 & -0.261 & 0.3975 \tabularnewline
29 & -0.024692 & -0.1928 & 0.42386 \tabularnewline
30 & -0.099941 & -0.7806 & 0.219039 \tabularnewline
31 & 0.072419 & 0.5656 & 0.286867 \tabularnewline
32 & 0.006892 & 0.0538 & 0.478625 \tabularnewline
33 & -0.006526 & -0.051 & 0.479759 \tabularnewline
34 & -0.063816 & -0.4984 & 0.30999 \tabularnewline
35 & 0.00776 & 0.0606 & 0.475933 \tabularnewline
36 & -0.043982 & -0.3435 & 0.366198 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59203&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]0.796105[/C][C]6.2178[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.363471[/C][C]-2.8388[/C][C]0.003071[/C][/ROW]
[ROW][C]3[/C][C]0.10335[/C][C]0.8072[/C][C]0.211347[/C][/ROW]
[ROW][C]4[/C][C]0.026759[/C][C]0.209[/C][C]0.417574[/C][/ROW]
[ROW][C]5[/C][C]0.039506[/C][C]0.3085[/C][C]0.379358[/C][/ROW]
[ROW][C]6[/C][C]-0.009805[/C][C]-0.0766[/C][C]0.469603[/C][/ROW]
[ROW][C]7[/C][C]-0.011712[/C][C]-0.0915[/C][C]0.463707[/C][/ROW]
[ROW][C]8[/C][C]0.086167[/C][C]0.673[/C][C]0.251749[/C][/ROW]
[ROW][C]9[/C][C]0.254442[/C][C]1.9873[/C][C]0.025695[/C][/ROW]
[ROW][C]10[/C][C]0.321393[/C][C]2.5102[/C][C]0.007368[/C][/ROW]
[ROW][C]11[/C][C]0.341255[/C][C]2.6653[/C][C]0.004915[/C][/ROW]
[ROW][C]12[/C][C]-0.091496[/C][C]-0.7146[/C][C]0.23879[/C][/ROW]
[ROW][C]13[/C][C]-0.425352[/C][C]-3.3221[/C][C]0.000757[/C][/ROW]
[ROW][C]14[/C][C]-0.129465[/C][C]-1.0112[/C][C]0.157968[/C][/ROW]
[ROW][C]15[/C][C]-0.086574[/C][C]-0.6762[/C][C]0.250746[/C][/ROW]
[ROW][C]16[/C][C]-0.082544[/C][C]-0.6447[/C][C]0.260774[/C][/ROW]
[ROW][C]17[/C][C]-0.038257[/C][C]-0.2988[/C][C]0.383055[/C][/ROW]
[ROW][C]18[/C][C]-0.012746[/C][C]-0.0996[/C][C]0.460513[/C][/ROW]
[ROW][C]19[/C][C]-0.064199[/C][C]-0.5014[/C][C]0.308944[/C][/ROW]
[ROW][C]20[/C][C]-0.072282[/C][C]-0.5645[/C][C]0.287229[/C][/ROW]
[ROW][C]21[/C][C]-0.174215[/C][C]-1.3607[/C][C]0.089314[/C][/ROW]
[ROW][C]22[/C][C]-0.14352[/C][C]-1.1209[/C][C]0.133355[/C][/ROW]
[ROW][C]23[/C][C]0.056725[/C][C]0.443[/C][C]0.329653[/C][/ROW]
[ROW][C]24[/C][C]0.069147[/C][C]0.5401[/C][C]0.295562[/C][/ROW]
[ROW][C]25[/C][C]-0.041591[/C][C]-0.3248[/C][C]0.373209[/C][/ROW]
[ROW][C]26[/C][C]0.037504[/C][C]0.2929[/C][C]0.385289[/C][/ROW]
[ROW][C]27[/C][C]0.077439[/C][C]0.6048[/C][C]0.273773[/C][/ROW]
[ROW][C]28[/C][C]-0.033413[/C][C]-0.261[/C][C]0.3975[/C][/ROW]
[ROW][C]29[/C][C]-0.024692[/C][C]-0.1928[/C][C]0.42386[/C][/ROW]
[ROW][C]30[/C][C]-0.099941[/C][C]-0.7806[/C][C]0.219039[/C][/ROW]
[ROW][C]31[/C][C]0.072419[/C][C]0.5656[/C][C]0.286867[/C][/ROW]
[ROW][C]32[/C][C]0.006892[/C][C]0.0538[/C][C]0.478625[/C][/ROW]
[ROW][C]33[/C][C]-0.006526[/C][C]-0.051[/C][C]0.479759[/C][/ROW]
[ROW][C]34[/C][C]-0.063816[/C][C]-0.4984[/C][C]0.30999[/C][/ROW]
[ROW][C]35[/C][C]0.00776[/C][C]0.0606[/C][C]0.475933[/C][/ROW]
[ROW][C]36[/C][C]-0.043982[/C][C]-0.3435[/C][C]0.366198[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59203&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59203&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
10.7961056.21780
2-0.363471-2.83880.003071
30.103350.80720.211347
40.0267590.2090.417574
50.0395060.30850.379358
6-0.009805-0.07660.469603
7-0.011712-0.09150.463707
80.0861670.6730.251749
90.2544421.98730.025695
100.3213932.51020.007368
110.3412552.66530.004915
12-0.091496-0.71460.23879
13-0.425352-3.32210.000757
14-0.129465-1.01120.157968
15-0.086574-0.67620.250746
16-0.082544-0.64470.260774
17-0.038257-0.29880.383055
18-0.012746-0.09960.460513
19-0.064199-0.50140.308944
20-0.072282-0.56450.287229
21-0.174215-1.36070.089314
22-0.14352-1.12090.133355
230.0567250.4430.329653
240.0691470.54010.295562
25-0.041591-0.32480.373209
260.0375040.29290.385289
270.0774390.60480.273773
28-0.033413-0.2610.3975
29-0.024692-0.19280.42386
30-0.099941-0.78060.219039
310.0724190.56560.286867
320.0068920.05380.478625
33-0.006526-0.0510.479759
34-0.063816-0.49840.30999
350.007760.06060.475933
36-0.043982-0.34350.366198


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')