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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationFri, 19 Dec 2008 03:44:18 -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/2008/Dec/19/t1229683523yie5xze5armgx2a.htm/, Retrieved Wed, 15 May 2024 02:32:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=35033, Retrieved Wed, 15 May 2024 02:32:03 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact214
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
F RMP   [Standard Deviation-Mean Plot] [q1] [2008-12-08 12:37:39] [3ffd109c9e040b1ae7e5dbe576d4698c]
F    D    [Standard Deviation-Mean Plot] [SMP] [2008-12-08 12:41:29] [3ffd109c9e040b1ae7e5dbe576d4698c]
- RM        [Variance Reduction Matrix] [VRM] [2008-12-08 13:10:17] [3ffd109c9e040b1ae7e5dbe576d4698c]
- RM          [(Partial) Autocorrelation Function] [ACF] [2008-12-08 13:14:12] [3ffd109c9e040b1ae7e5dbe576d4698c]
F               [(Partial) Autocorrelation Function] [ACF] [2008-12-08 13:17:45] [3ffd109c9e040b1ae7e5dbe576d4698c]
- RM              [Spectral Analysis] [spectraal] [2008-12-08 13:23:27] [3ffd109c9e040b1ae7e5dbe576d4698c]
F RM                [(Partial) Autocorrelation Function] [ACF] [2008-12-08 13:40:41] [3ffd109c9e040b1ae7e5dbe576d4698c]
-   P                   [(Partial) Autocorrelation Function] [autocorrelatie en...] [2008-12-19 10:44:18] [e8ace8b3d80d7fc51f1760fb13a6fe6b] [Current]
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Dataseries X:
147768
137507
136919
136151
133001
125554
119647
114158
116193
152803
161761
160942
149470
139208
134588
130322
126611
122401
117352
112135
112879
148729
157230
157221
146681
136524
132111
125326
122716
116615
113719
110737
112093
143565
149946
149147
134339
122683
115614
116566
111272
104609
101802
94542
93051
124129
130374
123946
114971
105531
104919
104782
101281
94545
93248
84031
87486
115867
120327
117008
108811




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=35033&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=35033&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35033&T=0

As an alternative you can also use a 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
1-0.17288-1.19780.118448
2-0.039533-0.27390.392672
3-0.046214-0.32020.37511
40.0788750.54650.293639
5-0.1397-0.96790.16898
60.1521491.05410.148552
70.0287610.19930.421451
8-0.018547-0.12850.449146
90.0379960.26320.396743
10-0.107249-0.7430.230539
110.3284882.27580.013679
12-0.311691-2.15950.01792
13-0.092808-0.6430.261644
140.0548790.38020.352732
150.0254630.17640.430355
16-0.282905-1.960.027906
170.0830790.57560.283791
18-0.007568-0.05240.479199
19-0.081746-0.56640.286897
200.0621750.43080.334285
21-0.027854-0.1930.423896
220.139420.96590.16946
23-0.123996-0.85910.197287
24-0.009198-0.06370.474726
25-0.06156-0.42650.335826
260.0321620.22280.412308
27-0.029401-0.20370.419726
280.1298640.89970.18638
290.0502340.3480.36467
30-0.072721-0.50380.308344
310.0062770.04350.482747
320.0359750.24920.402117
330.0813070.56330.287923
34-0.065083-0.45090.327042
35-0.020711-0.14350.443251
36-0.06949-0.48140.316195

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.17288 & -1.1978 & 0.118448 \tabularnewline
2 & -0.039533 & -0.2739 & 0.392672 \tabularnewline
3 & -0.046214 & -0.3202 & 0.37511 \tabularnewline
4 & 0.078875 & 0.5465 & 0.293639 \tabularnewline
5 & -0.1397 & -0.9679 & 0.16898 \tabularnewline
6 & 0.152149 & 1.0541 & 0.148552 \tabularnewline
7 & 0.028761 & 0.1993 & 0.421451 \tabularnewline
8 & -0.018547 & -0.1285 & 0.449146 \tabularnewline
9 & 0.037996 & 0.2632 & 0.396743 \tabularnewline
10 & -0.107249 & -0.743 & 0.230539 \tabularnewline
11 & 0.328488 & 2.2758 & 0.013679 \tabularnewline
12 & -0.311691 & -2.1595 & 0.01792 \tabularnewline
13 & -0.092808 & -0.643 & 0.261644 \tabularnewline
14 & 0.054879 & 0.3802 & 0.352732 \tabularnewline
15 & 0.025463 & 0.1764 & 0.430355 \tabularnewline
16 & -0.282905 & -1.96 & 0.027906 \tabularnewline
17 & 0.083079 & 0.5756 & 0.283791 \tabularnewline
18 & -0.007568 & -0.0524 & 0.479199 \tabularnewline
19 & -0.081746 & -0.5664 & 0.286897 \tabularnewline
20 & 0.062175 & 0.4308 & 0.334285 \tabularnewline
21 & -0.027854 & -0.193 & 0.423896 \tabularnewline
22 & 0.13942 & 0.9659 & 0.16946 \tabularnewline
23 & -0.123996 & -0.8591 & 0.197287 \tabularnewline
24 & -0.009198 & -0.0637 & 0.474726 \tabularnewline
25 & -0.06156 & -0.4265 & 0.335826 \tabularnewline
26 & 0.032162 & 0.2228 & 0.412308 \tabularnewline
27 & -0.029401 & -0.2037 & 0.419726 \tabularnewline
28 & 0.129864 & 0.8997 & 0.18638 \tabularnewline
29 & 0.050234 & 0.348 & 0.36467 \tabularnewline
30 & -0.072721 & -0.5038 & 0.308344 \tabularnewline
31 & 0.006277 & 0.0435 & 0.482747 \tabularnewline
32 & 0.035975 & 0.2492 & 0.402117 \tabularnewline
33 & 0.081307 & 0.5633 & 0.287923 \tabularnewline
34 & -0.065083 & -0.4509 & 0.327042 \tabularnewline
35 & -0.020711 & -0.1435 & 0.443251 \tabularnewline
36 & -0.06949 & -0.4814 & 0.316195 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35033&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]-0.17288[/C][C]-1.1978[/C][C]0.118448[/C][/ROW]
[ROW][C]2[/C][C]-0.039533[/C][C]-0.2739[/C][C]0.392672[/C][/ROW]
[ROW][C]3[/C][C]-0.046214[/C][C]-0.3202[/C][C]0.37511[/C][/ROW]
[ROW][C]4[/C][C]0.078875[/C][C]0.5465[/C][C]0.293639[/C][/ROW]
[ROW][C]5[/C][C]-0.1397[/C][C]-0.9679[/C][C]0.16898[/C][/ROW]
[ROW][C]6[/C][C]0.152149[/C][C]1.0541[/C][C]0.148552[/C][/ROW]
[ROW][C]7[/C][C]0.028761[/C][C]0.1993[/C][C]0.421451[/C][/ROW]
[ROW][C]8[/C][C]-0.018547[/C][C]-0.1285[/C][C]0.449146[/C][/ROW]
[ROW][C]9[/C][C]0.037996[/C][C]0.2632[/C][C]0.396743[/C][/ROW]
[ROW][C]10[/C][C]-0.107249[/C][C]-0.743[/C][C]0.230539[/C][/ROW]
[ROW][C]11[/C][C]0.328488[/C][C]2.2758[/C][C]0.013679[/C][/ROW]
[ROW][C]12[/C][C]-0.311691[/C][C]-2.1595[/C][C]0.01792[/C][/ROW]
[ROW][C]13[/C][C]-0.092808[/C][C]-0.643[/C][C]0.261644[/C][/ROW]
[ROW][C]14[/C][C]0.054879[/C][C]0.3802[/C][C]0.352732[/C][/ROW]
[ROW][C]15[/C][C]0.025463[/C][C]0.1764[/C][C]0.430355[/C][/ROW]
[ROW][C]16[/C][C]-0.282905[/C][C]-1.96[/C][C]0.027906[/C][/ROW]
[ROW][C]17[/C][C]0.083079[/C][C]0.5756[/C][C]0.283791[/C][/ROW]
[ROW][C]18[/C][C]-0.007568[/C][C]-0.0524[/C][C]0.479199[/C][/ROW]
[ROW][C]19[/C][C]-0.081746[/C][C]-0.5664[/C][C]0.286897[/C][/ROW]
[ROW][C]20[/C][C]0.062175[/C][C]0.4308[/C][C]0.334285[/C][/ROW]
[ROW][C]21[/C][C]-0.027854[/C][C]-0.193[/C][C]0.423896[/C][/ROW]
[ROW][C]22[/C][C]0.13942[/C][C]0.9659[/C][C]0.16946[/C][/ROW]
[ROW][C]23[/C][C]-0.123996[/C][C]-0.8591[/C][C]0.197287[/C][/ROW]
[ROW][C]24[/C][C]-0.009198[/C][C]-0.0637[/C][C]0.474726[/C][/ROW]
[ROW][C]25[/C][C]-0.06156[/C][C]-0.4265[/C][C]0.335826[/C][/ROW]
[ROW][C]26[/C][C]0.032162[/C][C]0.2228[/C][C]0.412308[/C][/ROW]
[ROW][C]27[/C][C]-0.029401[/C][C]-0.2037[/C][C]0.419726[/C][/ROW]
[ROW][C]28[/C][C]0.129864[/C][C]0.8997[/C][C]0.18638[/C][/ROW]
[ROW][C]29[/C][C]0.050234[/C][C]0.348[/C][C]0.36467[/C][/ROW]
[ROW][C]30[/C][C]-0.072721[/C][C]-0.5038[/C][C]0.308344[/C][/ROW]
[ROW][C]31[/C][C]0.006277[/C][C]0.0435[/C][C]0.482747[/C][/ROW]
[ROW][C]32[/C][C]0.035975[/C][C]0.2492[/C][C]0.402117[/C][/ROW]
[ROW][C]33[/C][C]0.081307[/C][C]0.5633[/C][C]0.287923[/C][/ROW]
[ROW][C]34[/C][C]-0.065083[/C][C]-0.4509[/C][C]0.327042[/C][/ROW]
[ROW][C]35[/C][C]-0.020711[/C][C]-0.1435[/C][C]0.443251[/C][/ROW]
[ROW][C]36[/C][C]-0.06949[/C][C]-0.4814[/C][C]0.316195[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35033&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35033&T=1

As an alternative you can also use a QR Code:  

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

Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.17288-1.19780.118448
2-0.039533-0.27390.392672
3-0.046214-0.32020.37511
40.0788750.54650.293639
5-0.1397-0.96790.16898
60.1521491.05410.148552
70.0287610.19930.421451
8-0.018547-0.12850.449146
90.0379960.26320.396743
10-0.107249-0.7430.230539
110.3284882.27580.013679
12-0.311691-2.15950.01792
13-0.092808-0.6430.261644
140.0548790.38020.352732
150.0254630.17640.430355
16-0.282905-1.960.027906
170.0830790.57560.283791
18-0.007568-0.05240.479199
19-0.081746-0.56640.286897
200.0621750.43080.334285
21-0.027854-0.1930.423896
220.139420.96590.16946
23-0.123996-0.85910.197287
24-0.009198-0.06370.474726
25-0.06156-0.42650.335826
260.0321620.22280.412308
27-0.029401-0.20370.419726
280.1298640.89970.18638
290.0502340.3480.36467
30-0.072721-0.50380.308344
310.0062770.04350.482747
320.0359750.24920.402117
330.0813070.56330.287923
34-0.065083-0.45090.327042
35-0.020711-0.14350.443251
36-0.06949-0.48140.316195







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.17288-1.19780.118448
2-0.071559-0.49580.311158
3-0.068289-0.47310.319136
40.0572050.39630.346811
5-0.126434-0.8760.192708
60.1171030.81130.210596
70.0687460.47630.318017
8-0.001143-0.00790.496857
90.0753680.52220.301979
10-0.126812-0.87860.192003
110.3573782.4760.008433
12-0.30076-2.08370.021266
13-0.15643-1.08380.141938
140.0733160.5080.306907
15-0.157054-1.08810.140991
16-0.169926-1.17730.122444
17-0.183492-1.27130.104879
18-0.004977-0.03450.486318
19-0.031382-0.21740.4144
20-0.021665-0.15010.440657
210.0537330.37230.355663
220.124560.8630.196221
230.146171.01270.158141
240.0068660.04760.481129
25-0.140106-0.97070.168286
26-0.003948-0.02740.489147
270.1541.06690.145667
28-0.112485-0.77930.21981
29-0.057936-0.40140.344957
30-0.039872-0.27620.391773
31-0.079906-0.55360.291211
320.0345950.23970.405798
33-0.064861-0.44940.327594
340.0538950.37340.355249
35-0.028841-0.19980.421233
36-0.060729-0.42070.337911

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.17288 & -1.1978 & 0.118448 \tabularnewline
2 & -0.071559 & -0.4958 & 0.311158 \tabularnewline
3 & -0.068289 & -0.4731 & 0.319136 \tabularnewline
4 & 0.057205 & 0.3963 & 0.346811 \tabularnewline
5 & -0.126434 & -0.876 & 0.192708 \tabularnewline
6 & 0.117103 & 0.8113 & 0.210596 \tabularnewline
7 & 0.068746 & 0.4763 & 0.318017 \tabularnewline
8 & -0.001143 & -0.0079 & 0.496857 \tabularnewline
9 & 0.075368 & 0.5222 & 0.301979 \tabularnewline
10 & -0.126812 & -0.8786 & 0.192003 \tabularnewline
11 & 0.357378 & 2.476 & 0.008433 \tabularnewline
12 & -0.30076 & -2.0837 & 0.021266 \tabularnewline
13 & -0.15643 & -1.0838 & 0.141938 \tabularnewline
14 & 0.073316 & 0.508 & 0.306907 \tabularnewline
15 & -0.157054 & -1.0881 & 0.140991 \tabularnewline
16 & -0.169926 & -1.1773 & 0.122444 \tabularnewline
17 & -0.183492 & -1.2713 & 0.104879 \tabularnewline
18 & -0.004977 & -0.0345 & 0.486318 \tabularnewline
19 & -0.031382 & -0.2174 & 0.4144 \tabularnewline
20 & -0.021665 & -0.1501 & 0.440657 \tabularnewline
21 & 0.053733 & 0.3723 & 0.355663 \tabularnewline
22 & 0.12456 & 0.863 & 0.196221 \tabularnewline
23 & 0.14617 & 1.0127 & 0.158141 \tabularnewline
24 & 0.006866 & 0.0476 & 0.481129 \tabularnewline
25 & -0.140106 & -0.9707 & 0.168286 \tabularnewline
26 & -0.003948 & -0.0274 & 0.489147 \tabularnewline
27 & 0.154 & 1.0669 & 0.145667 \tabularnewline
28 & -0.112485 & -0.7793 & 0.21981 \tabularnewline
29 & -0.057936 & -0.4014 & 0.344957 \tabularnewline
30 & -0.039872 & -0.2762 & 0.391773 \tabularnewline
31 & -0.079906 & -0.5536 & 0.291211 \tabularnewline
32 & 0.034595 & 0.2397 & 0.405798 \tabularnewline
33 & -0.064861 & -0.4494 & 0.327594 \tabularnewline
34 & 0.053895 & 0.3734 & 0.355249 \tabularnewline
35 & -0.028841 & -0.1998 & 0.421233 \tabularnewline
36 & -0.060729 & -0.4207 & 0.337911 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35033&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]-0.17288[/C][C]-1.1978[/C][C]0.118448[/C][/ROW]
[ROW][C]2[/C][C]-0.071559[/C][C]-0.4958[/C][C]0.311158[/C][/ROW]
[ROW][C]3[/C][C]-0.068289[/C][C]-0.4731[/C][C]0.319136[/C][/ROW]
[ROW][C]4[/C][C]0.057205[/C][C]0.3963[/C][C]0.346811[/C][/ROW]
[ROW][C]5[/C][C]-0.126434[/C][C]-0.876[/C][C]0.192708[/C][/ROW]
[ROW][C]6[/C][C]0.117103[/C][C]0.8113[/C][C]0.210596[/C][/ROW]
[ROW][C]7[/C][C]0.068746[/C][C]0.4763[/C][C]0.318017[/C][/ROW]
[ROW][C]8[/C][C]-0.001143[/C][C]-0.0079[/C][C]0.496857[/C][/ROW]
[ROW][C]9[/C][C]0.075368[/C][C]0.5222[/C][C]0.301979[/C][/ROW]
[ROW][C]10[/C][C]-0.126812[/C][C]-0.8786[/C][C]0.192003[/C][/ROW]
[ROW][C]11[/C][C]0.357378[/C][C]2.476[/C][C]0.008433[/C][/ROW]
[ROW][C]12[/C][C]-0.30076[/C][C]-2.0837[/C][C]0.021266[/C][/ROW]
[ROW][C]13[/C][C]-0.15643[/C][C]-1.0838[/C][C]0.141938[/C][/ROW]
[ROW][C]14[/C][C]0.073316[/C][C]0.508[/C][C]0.306907[/C][/ROW]
[ROW][C]15[/C][C]-0.157054[/C][C]-1.0881[/C][C]0.140991[/C][/ROW]
[ROW][C]16[/C][C]-0.169926[/C][C]-1.1773[/C][C]0.122444[/C][/ROW]
[ROW][C]17[/C][C]-0.183492[/C][C]-1.2713[/C][C]0.104879[/C][/ROW]
[ROW][C]18[/C][C]-0.004977[/C][C]-0.0345[/C][C]0.486318[/C][/ROW]
[ROW][C]19[/C][C]-0.031382[/C][C]-0.2174[/C][C]0.4144[/C][/ROW]
[ROW][C]20[/C][C]-0.021665[/C][C]-0.1501[/C][C]0.440657[/C][/ROW]
[ROW][C]21[/C][C]0.053733[/C][C]0.3723[/C][C]0.355663[/C][/ROW]
[ROW][C]22[/C][C]0.12456[/C][C]0.863[/C][C]0.196221[/C][/ROW]
[ROW][C]23[/C][C]0.14617[/C][C]1.0127[/C][C]0.158141[/C][/ROW]
[ROW][C]24[/C][C]0.006866[/C][C]0.0476[/C][C]0.481129[/C][/ROW]
[ROW][C]25[/C][C]-0.140106[/C][C]-0.9707[/C][C]0.168286[/C][/ROW]
[ROW][C]26[/C][C]-0.003948[/C][C]-0.0274[/C][C]0.489147[/C][/ROW]
[ROW][C]27[/C][C]0.154[/C][C]1.0669[/C][C]0.145667[/C][/ROW]
[ROW][C]28[/C][C]-0.112485[/C][C]-0.7793[/C][C]0.21981[/C][/ROW]
[ROW][C]29[/C][C]-0.057936[/C][C]-0.4014[/C][C]0.344957[/C][/ROW]
[ROW][C]30[/C][C]-0.039872[/C][C]-0.2762[/C][C]0.391773[/C][/ROW]
[ROW][C]31[/C][C]-0.079906[/C][C]-0.5536[/C][C]0.291211[/C][/ROW]
[ROW][C]32[/C][C]0.034595[/C][C]0.2397[/C][C]0.405798[/C][/ROW]
[ROW][C]33[/C][C]-0.064861[/C][C]-0.4494[/C][C]0.327594[/C][/ROW]
[ROW][C]34[/C][C]0.053895[/C][C]0.3734[/C][C]0.355249[/C][/ROW]
[ROW][C]35[/C][C]-0.028841[/C][C]-0.1998[/C][C]0.421233[/C][/ROW]
[ROW][C]36[/C][C]-0.060729[/C][C]-0.4207[/C][C]0.337911[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35033&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35033&T=2

As an alternative you can also use a QR Code:  

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

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.17288-1.19780.118448
2-0.071559-0.49580.311158
3-0.068289-0.47310.319136
40.0572050.39630.346811
5-0.126434-0.8760.192708
60.1171030.81130.210596
70.0687460.47630.318017
8-0.001143-0.00790.496857
90.0753680.52220.301979
10-0.126812-0.87860.192003
110.3573782.4760.008433
12-0.30076-2.08370.021266
13-0.15643-1.08380.141938
140.0733160.5080.306907
15-0.157054-1.08810.140991
16-0.169926-1.17730.122444
17-0.183492-1.27130.104879
18-0.004977-0.03450.486318
19-0.031382-0.21740.4144
20-0.021665-0.15010.440657
210.0537330.37230.355663
220.124560.8630.196221
230.146171.01270.158141
240.0068660.04760.481129
25-0.140106-0.97070.168286
26-0.003948-0.02740.489147
270.1541.06690.145667
28-0.112485-0.77930.21981
29-0.057936-0.40140.344957
30-0.039872-0.27620.391773
31-0.079906-0.55360.291211
320.0345950.23970.405798
33-0.064861-0.44940.327594
340.0538950.37340.355249
35-0.028841-0.19980.421233
36-0.060729-0.42070.337911



Parameters (Session):
par1 = 36 ; par2 = 0.0 ; par3 = 1 ; par4 = 1 ; par5 = 12 ;
Parameters (R input):
par1 = 36 ; par2 = 0.0 ; par3 = 1 ; par4 = 1 ; par5 = 12 ;
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 (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='lags',ylab='ACF')
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')