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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 computationSun, 13 Dec 2009 08:12:12 -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/13/t1260717189dvp7p8s4lup65sc.htm/, Retrieved Sat, 27 Apr 2024 17:15:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=67321, Retrieved Sat, 27 Apr 2024 17:15:26 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact124

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] [WS8 D=0 en d=0] [2009-11-25 16:06:53] [445b292c553470d9fed8bc2796fd3a00]
-    D          [(Partial) Autocorrelation Function] [ws 8 d=0 D=0] [2009-11-25 20:46:27] [134dc66689e3d457a82860db6471d419]
-   PD              [(Partial) Autocorrelation Function] [WS8] [2009-12-13 15:12:12] [5cd0e65b1f56b3935a0672588b930e12] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
181.10
191.20
206.20
212.00
224.70
231.30
229.30
227.40
253.90
265.90
277.70
292.10
282.90
292.80
311.00
330.90
350.00
348.50
360.90
345.90
308.80
320.00
322.00
322.90
343.30
354.70
376.60
383.20
392.50
388.20
407.40
412.50
419.80
418.10
389.20
391.60
412.90
385.90
385.50
350.20
336.30
318.50
345.40
377.40
359.50
315.60
307.80
277.40
186.90
160.00
149.10
148.90
137.90
134.00
157.50
175.10
181.00
182.20
207.80
219.40

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=67321&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=67321&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67321&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
10.2538371.74020.044183
2-0.002747-0.01880.492526
30.0856560.58720.27993
4-0.081299-0.55740.289965
5-0.113699-0.77950.219802
60.0140040.0960.461961
70.0835620.57290.284732
80.0757040.5190.303097
9-0.143121-0.98120.165761
10-0.038312-0.26270.396984
110.0031920.02190.491317
12-0.231046-1.5840.059954
13-0.126059-0.86420.195929
140.0637090.43680.332141
15-0.038356-0.2630.396868
16-0.127609-0.87480.193053
17-0.031707-0.21740.414429
18-0.073917-0.50680.307349
19-0.030025-0.20580.418903
20-0.051209-0.35110.363553
21-0.013681-0.09380.462836
22-0.060947-0.41780.338985
23-0.16309-1.11810.134606
24-0.105815-0.72540.235892
250.1325120.90850.184136
260.0314210.21540.415189
270.1604361.09990.13849
280.2401711.64650.053163
29-0.00667-0.04570.481862
30-0.066866-0.45840.324385
31-0.065528-0.44920.327664
32-0.034948-0.23960.405843
33-0.012162-0.08340.466954
34-0.008139-0.05580.477869
350.0461010.31610.37668
36-0.038846-0.26630.395581

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.253837 & 1.7402 & 0.044183 \tabularnewline
2 & -0.002747 & -0.0188 & 0.492526 \tabularnewline
3 & 0.085656 & 0.5872 & 0.27993 \tabularnewline
4 & -0.081299 & -0.5574 & 0.289965 \tabularnewline
5 & -0.113699 & -0.7795 & 0.219802 \tabularnewline
6 & 0.014004 & 0.096 & 0.461961 \tabularnewline
7 & 0.083562 & 0.5729 & 0.284732 \tabularnewline
8 & 0.075704 & 0.519 & 0.303097 \tabularnewline
9 & -0.143121 & -0.9812 & 0.165761 \tabularnewline
10 & -0.038312 & -0.2627 & 0.396984 \tabularnewline
11 & 0.003192 & 0.0219 & 0.491317 \tabularnewline
12 & -0.231046 & -1.584 & 0.059954 \tabularnewline
13 & -0.126059 & -0.8642 & 0.195929 \tabularnewline
14 & 0.063709 & 0.4368 & 0.332141 \tabularnewline
15 & -0.038356 & -0.263 & 0.396868 \tabularnewline
16 & -0.127609 & -0.8748 & 0.193053 \tabularnewline
17 & -0.031707 & -0.2174 & 0.414429 \tabularnewline
18 & -0.073917 & -0.5068 & 0.307349 \tabularnewline
19 & -0.030025 & -0.2058 & 0.418903 \tabularnewline
20 & -0.051209 & -0.3511 & 0.363553 \tabularnewline
21 & -0.013681 & -0.0938 & 0.462836 \tabularnewline
22 & -0.060947 & -0.4178 & 0.338985 \tabularnewline
23 & -0.16309 & -1.1181 & 0.134606 \tabularnewline
24 & -0.105815 & -0.7254 & 0.235892 \tabularnewline
25 & 0.132512 & 0.9085 & 0.184136 \tabularnewline
26 & 0.031421 & 0.2154 & 0.415189 \tabularnewline
27 & 0.160436 & 1.0999 & 0.13849 \tabularnewline
28 & 0.240171 & 1.6465 & 0.053163 \tabularnewline
29 & -0.00667 & -0.0457 & 0.481862 \tabularnewline
30 & -0.066866 & -0.4584 & 0.324385 \tabularnewline
31 & -0.065528 & -0.4492 & 0.327664 \tabularnewline
32 & -0.034948 & -0.2396 & 0.405843 \tabularnewline
33 & -0.012162 & -0.0834 & 0.466954 \tabularnewline
34 & -0.008139 & -0.0558 & 0.477869 \tabularnewline
35 & 0.046101 & 0.3161 & 0.37668 \tabularnewline
36 & -0.038846 & -0.2663 & 0.395581 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67321&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]0.253837[/C][C]1.7402[/C][C]0.044183[/C][/ROW]
[ROW][C]2[/C][C]-0.002747[/C][C]-0.0188[/C][C]0.492526[/C][/ROW]
[ROW][C]3[/C][C]0.085656[/C][C]0.5872[/C][C]0.27993[/C][/ROW]
[ROW][C]4[/C][C]-0.081299[/C][C]-0.5574[/C][C]0.289965[/C][/ROW]
[ROW][C]5[/C][C]-0.113699[/C][C]-0.7795[/C][C]0.219802[/C][/ROW]
[ROW][C]6[/C][C]0.014004[/C][C]0.096[/C][C]0.461961[/C][/ROW]
[ROW][C]7[/C][C]0.083562[/C][C]0.5729[/C][C]0.284732[/C][/ROW]
[ROW][C]8[/C][C]0.075704[/C][C]0.519[/C][C]0.303097[/C][/ROW]
[ROW][C]9[/C][C]-0.143121[/C][C]-0.9812[/C][C]0.165761[/C][/ROW]
[ROW][C]10[/C][C]-0.038312[/C][C]-0.2627[/C][C]0.396984[/C][/ROW]
[ROW][C]11[/C][C]0.003192[/C][C]0.0219[/C][C]0.491317[/C][/ROW]
[ROW][C]12[/C][C]-0.231046[/C][C]-1.584[/C][C]0.059954[/C][/ROW]
[ROW][C]13[/C][C]-0.126059[/C][C]-0.8642[/C][C]0.195929[/C][/ROW]
[ROW][C]14[/C][C]0.063709[/C][C]0.4368[/C][C]0.332141[/C][/ROW]
[ROW][C]15[/C][C]-0.038356[/C][C]-0.263[/C][C]0.396868[/C][/ROW]
[ROW][C]16[/C][C]-0.127609[/C][C]-0.8748[/C][C]0.193053[/C][/ROW]
[ROW][C]17[/C][C]-0.031707[/C][C]-0.2174[/C][C]0.414429[/C][/ROW]
[ROW][C]18[/C][C]-0.073917[/C][C]-0.5068[/C][C]0.307349[/C][/ROW]
[ROW][C]19[/C][C]-0.030025[/C][C]-0.2058[/C][C]0.418903[/C][/ROW]
[ROW][C]20[/C][C]-0.051209[/C][C]-0.3511[/C][C]0.363553[/C][/ROW]
[ROW][C]21[/C][C]-0.013681[/C][C]-0.0938[/C][C]0.462836[/C][/ROW]
[ROW][C]22[/C][C]-0.060947[/C][C]-0.4178[/C][C]0.338985[/C][/ROW]
[ROW][C]23[/C][C]-0.16309[/C][C]-1.1181[/C][C]0.134606[/C][/ROW]
[ROW][C]24[/C][C]-0.105815[/C][C]-0.7254[/C][C]0.235892[/C][/ROW]
[ROW][C]25[/C][C]0.132512[/C][C]0.9085[/C][C]0.184136[/C][/ROW]
[ROW][C]26[/C][C]0.031421[/C][C]0.2154[/C][C]0.415189[/C][/ROW]
[ROW][C]27[/C][C]0.160436[/C][C]1.0999[/C][C]0.13849[/C][/ROW]
[ROW][C]28[/C][C]0.240171[/C][C]1.6465[/C][C]0.053163[/C][/ROW]
[ROW][C]29[/C][C]-0.00667[/C][C]-0.0457[/C][C]0.481862[/C][/ROW]
[ROW][C]30[/C][C]-0.066866[/C][C]-0.4584[/C][C]0.324385[/C][/ROW]
[ROW][C]31[/C][C]-0.065528[/C][C]-0.4492[/C][C]0.327664[/C][/ROW]
[ROW][C]32[/C][C]-0.034948[/C][C]-0.2396[/C][C]0.405843[/C][/ROW]
[ROW][C]33[/C][C]-0.012162[/C][C]-0.0834[/C][C]0.466954[/C][/ROW]
[ROW][C]34[/C][C]-0.008139[/C][C]-0.0558[/C][C]0.477869[/C][/ROW]
[ROW][C]35[/C][C]0.046101[/C][C]0.3161[/C][C]0.37668[/C][/ROW]
[ROW][C]36[/C][C]-0.038846[/C][C]-0.2663[/C][C]0.395581[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67321&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67321&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
10.2538371.74020.044183
2-0.002747-0.01880.492526
30.0856560.58720.27993
4-0.081299-0.55740.289965
5-0.113699-0.77950.219802
60.0140040.0960.461961
70.0835620.57290.284732
80.0757040.5190.303097
9-0.143121-0.98120.165761
10-0.038312-0.26270.396984
110.0031920.02190.491317
12-0.231046-1.5840.059954
13-0.126059-0.86420.195929
140.0637090.43680.332141
15-0.038356-0.2630.396868
16-0.127609-0.87480.193053
17-0.031707-0.21740.414429
18-0.073917-0.50680.307349
19-0.030025-0.20580.418903
20-0.051209-0.35110.363553
21-0.013681-0.09380.462836
22-0.060947-0.41780.338985
23-0.16309-1.11810.134606
24-0.105815-0.72540.235892
250.1325120.90850.184136
260.0314210.21540.415189
270.1604361.09990.13849
280.2401711.64650.053163
29-0.00667-0.04570.481862
30-0.066866-0.45840.324385
31-0.065528-0.44920.327664
32-0.034948-0.23960.405843
33-0.012162-0.08340.466954
34-0.008139-0.05580.477869
350.0461010.31610.37668
36-0.038846-0.26630.395581






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.2538371.74020.044183
2-0.071807-0.49230.312404
30.1124170.77070.222374
4-0.145934-1.00050.161102
5-0.046781-0.32070.374923
60.041050.28140.38981
70.0886630.60780.27311
80.0459120.31480.377171
9-0.215712-1.47890.072926
100.0518880.35570.361819
11-0.010662-0.07310.47102
12-0.188459-1.2920.101335
13-0.039779-0.27270.393135
140.0538640.36930.35679
15-0.035085-0.24050.405482
16-0.133439-0.91480.182481
17-0.009213-0.06320.474952
18-0.09734-0.66730.253913
190.0823020.56420.287639
20-0.068697-0.4710.319923
21-0.072656-0.49810.310366
22-0.119294-0.81780.208788
23-0.094847-0.65020.259352
24-0.0816-0.55940.289265
250.1236210.84750.200504
26-0.026606-0.18240.428025
270.1529681.04870.14984
280.076230.52260.30185
29-0.117135-0.8030.212999
30-0.047697-0.3270.372562
31-0.073583-0.50450.308147
320.0185770.12740.449601
33-0.090567-0.62090.268833
34-0.035738-0.2450.403759
35-0.072875-0.49960.309841
36-0.121949-0.8360.203681

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.253837 & 1.7402 & 0.044183 \tabularnewline
2 & -0.071807 & -0.4923 & 0.312404 \tabularnewline
3 & 0.112417 & 0.7707 & 0.222374 \tabularnewline
4 & -0.145934 & -1.0005 & 0.161102 \tabularnewline
5 & -0.046781 & -0.3207 & 0.374923 \tabularnewline
6 & 0.04105 & 0.2814 & 0.38981 \tabularnewline
7 & 0.088663 & 0.6078 & 0.27311 \tabularnewline
8 & 0.045912 & 0.3148 & 0.377171 \tabularnewline
9 & -0.215712 & -1.4789 & 0.072926 \tabularnewline
10 & 0.051888 & 0.3557 & 0.361819 \tabularnewline
11 & -0.010662 & -0.0731 & 0.47102 \tabularnewline
12 & -0.188459 & -1.292 & 0.101335 \tabularnewline
13 & -0.039779 & -0.2727 & 0.393135 \tabularnewline
14 & 0.053864 & 0.3693 & 0.35679 \tabularnewline
15 & -0.035085 & -0.2405 & 0.405482 \tabularnewline
16 & -0.133439 & -0.9148 & 0.182481 \tabularnewline
17 & -0.009213 & -0.0632 & 0.474952 \tabularnewline
18 & -0.09734 & -0.6673 & 0.253913 \tabularnewline
19 & 0.082302 & 0.5642 & 0.287639 \tabularnewline
20 & -0.068697 & -0.471 & 0.319923 \tabularnewline
21 & -0.072656 & -0.4981 & 0.310366 \tabularnewline
22 & -0.119294 & -0.8178 & 0.208788 \tabularnewline
23 & -0.094847 & -0.6502 & 0.259352 \tabularnewline
24 & -0.0816 & -0.5594 & 0.289265 \tabularnewline
25 & 0.123621 & 0.8475 & 0.200504 \tabularnewline
26 & -0.026606 & -0.1824 & 0.428025 \tabularnewline
27 & 0.152968 & 1.0487 & 0.14984 \tabularnewline
28 & 0.07623 & 0.5226 & 0.30185 \tabularnewline
29 & -0.117135 & -0.803 & 0.212999 \tabularnewline
30 & -0.047697 & -0.327 & 0.372562 \tabularnewline
31 & -0.073583 & -0.5045 & 0.308147 \tabularnewline
32 & 0.018577 & 0.1274 & 0.449601 \tabularnewline
33 & -0.090567 & -0.6209 & 0.268833 \tabularnewline
34 & -0.035738 & -0.245 & 0.403759 \tabularnewline
35 & -0.072875 & -0.4996 & 0.309841 \tabularnewline
36 & -0.121949 & -0.836 & 0.203681 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67321&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]0.253837[/C][C]1.7402[/C][C]0.044183[/C][/ROW]
[ROW][C]2[/C][C]-0.071807[/C][C]-0.4923[/C][C]0.312404[/C][/ROW]
[ROW][C]3[/C][C]0.112417[/C][C]0.7707[/C][C]0.222374[/C][/ROW]
[ROW][C]4[/C][C]-0.145934[/C][C]-1.0005[/C][C]0.161102[/C][/ROW]
[ROW][C]5[/C][C]-0.046781[/C][C]-0.3207[/C][C]0.374923[/C][/ROW]
[ROW][C]6[/C][C]0.04105[/C][C]0.2814[/C][C]0.38981[/C][/ROW]
[ROW][C]7[/C][C]0.088663[/C][C]0.6078[/C][C]0.27311[/C][/ROW]
[ROW][C]8[/C][C]0.045912[/C][C]0.3148[/C][C]0.377171[/C][/ROW]
[ROW][C]9[/C][C]-0.215712[/C][C]-1.4789[/C][C]0.072926[/C][/ROW]
[ROW][C]10[/C][C]0.051888[/C][C]0.3557[/C][C]0.361819[/C][/ROW]
[ROW][C]11[/C][C]-0.010662[/C][C]-0.0731[/C][C]0.47102[/C][/ROW]
[ROW][C]12[/C][C]-0.188459[/C][C]-1.292[/C][C]0.101335[/C][/ROW]
[ROW][C]13[/C][C]-0.039779[/C][C]-0.2727[/C][C]0.393135[/C][/ROW]
[ROW][C]14[/C][C]0.053864[/C][C]0.3693[/C][C]0.35679[/C][/ROW]
[ROW][C]15[/C][C]-0.035085[/C][C]-0.2405[/C][C]0.405482[/C][/ROW]
[ROW][C]16[/C][C]-0.133439[/C][C]-0.9148[/C][C]0.182481[/C][/ROW]
[ROW][C]17[/C][C]-0.009213[/C][C]-0.0632[/C][C]0.474952[/C][/ROW]
[ROW][C]18[/C][C]-0.09734[/C][C]-0.6673[/C][C]0.253913[/C][/ROW]
[ROW][C]19[/C][C]0.082302[/C][C]0.5642[/C][C]0.287639[/C][/ROW]
[ROW][C]20[/C][C]-0.068697[/C][C]-0.471[/C][C]0.319923[/C][/ROW]
[ROW][C]21[/C][C]-0.072656[/C][C]-0.4981[/C][C]0.310366[/C][/ROW]
[ROW][C]22[/C][C]-0.119294[/C][C]-0.8178[/C][C]0.208788[/C][/ROW]
[ROW][C]23[/C][C]-0.094847[/C][C]-0.6502[/C][C]0.259352[/C][/ROW]
[ROW][C]24[/C][C]-0.0816[/C][C]-0.5594[/C][C]0.289265[/C][/ROW]
[ROW][C]25[/C][C]0.123621[/C][C]0.8475[/C][C]0.200504[/C][/ROW]
[ROW][C]26[/C][C]-0.026606[/C][C]-0.1824[/C][C]0.428025[/C][/ROW]
[ROW][C]27[/C][C]0.152968[/C][C]1.0487[/C][C]0.14984[/C][/ROW]
[ROW][C]28[/C][C]0.07623[/C][C]0.5226[/C][C]0.30185[/C][/ROW]
[ROW][C]29[/C][C]-0.117135[/C][C]-0.803[/C][C]0.212999[/C][/ROW]
[ROW][C]30[/C][C]-0.047697[/C][C]-0.327[/C][C]0.372562[/C][/ROW]
[ROW][C]31[/C][C]-0.073583[/C][C]-0.5045[/C][C]0.308147[/C][/ROW]
[ROW][C]32[/C][C]0.018577[/C][C]0.1274[/C][C]0.449601[/C][/ROW]
[ROW][C]33[/C][C]-0.090567[/C][C]-0.6209[/C][C]0.268833[/C][/ROW]
[ROW][C]34[/C][C]-0.035738[/C][C]-0.245[/C][C]0.403759[/C][/ROW]
[ROW][C]35[/C][C]-0.072875[/C][C]-0.4996[/C][C]0.309841[/C][/ROW]
[ROW][C]36[/C][C]-0.121949[/C][C]-0.836[/C][C]0.203681[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67321&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67321&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
10.2538371.74020.044183
2-0.071807-0.49230.312404
30.1124170.77070.222374
4-0.145934-1.00050.161102
5-0.046781-0.32070.374923
60.041050.28140.38981
70.0886630.60780.27311
80.0459120.31480.377171
9-0.215712-1.47890.072926
100.0518880.35570.361819
11-0.010662-0.07310.47102
12-0.188459-1.2920.101335
13-0.039779-0.27270.393135
140.0538640.36930.35679
15-0.035085-0.24050.405482
16-0.133439-0.91480.182481
17-0.009213-0.06320.474952
18-0.09734-0.66730.253913
190.0823020.56420.287639
20-0.068697-0.4710.319923
21-0.072656-0.49810.310366
22-0.119294-0.81780.208788
23-0.094847-0.65020.259352
24-0.0816-0.55940.289265
250.1236210.84750.200504
26-0.026606-0.18240.428025
270.1529681.04870.14984
280.076230.52260.30185
29-0.117135-0.8030.212999
30-0.047697-0.3270.372562
31-0.073583-0.50450.308147
320.0185770.12740.449601
33-0.090567-0.62090.268833
34-0.035738-0.2450.403759
35-0.072875-0.49960.309841
36-0.121949-0.8360.203681


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; 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')