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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 computationThu, 26 Nov 2009 12:05:22 -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/26/t1259262773g7cb82penkzpvpx.htm/, Retrieved Sun, 28 Apr 2024 22:17:39 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60299, Retrieved Sun, 28 Apr 2024 22:17:39 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact144

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 12:26:39] [b98453cac15ba1066b407e146608df68]
-    D        [(Partial) Autocorrelation Function] [WS 8: ACF (Lambda...] [2009-11-26 15:01:25] [b40728cc9f1a5ce9748a6b7b76867bb9]
-   P           [(Partial) Autocorrelation Function] [WS 8: ACF (Lambda...] [2009-11-26 15:36:56] [b40728cc9f1a5ce9748a6b7b76867bb9]
-                   [(Partial) Autocorrelation Function] [WS 8: ACF (Lambda...] [2009-11-26 19:05:22] [ac86848d66148c9c4c9404e0c9a511eb] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
79.8
83.4
113.6
112.9
104
109.9
99
106.3
128.9
111.1
102.9
130
87
87.5
117.6
103.4
110.8
112.6
102.5
112.4
135.6
105.1
127.7
137
91
90.5
122.4
123.3
124.3
120
118.1
119
142.7
123.6
129.6
151.6
110.4
99.2
130.5
136.2
129.7
128
121.6
135.8
143.8
147.5
136.2
156.6
123.3
104.5
139.8
136.5
112.1
118.5
94.4
102.3
111.4
99.2
87.8
115.8

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60299&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]3 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=60299&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60299&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 time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.576289-3.90860.000151
2-0.009806-0.06650.47363
30.2587121.75470.042987
4-0.176539-1.19730.118652
5-0.045409-0.3080.379745
60.261991.77690.041099
7-0.324746-2.20250.016339
80.2199081.49150.07133
9-0.069962-0.47450.318693
10-0.07485-0.50770.307059
110.1139470.77280.221789
12-0.039703-0.26930.394459
13-0.102675-0.69640.24485
140.1884611.27820.103795
15-0.115595-0.7840.218527
16-0.052189-0.3540.362493
170.1432770.97180.168127
18-0.089565-0.60750.273267
19-0.061002-0.41370.340496
200.1482121.00520.160024
210.0199690.13540.44643
22-0.292647-1.98480.026573
230.3072522.08390.021377
24-0.104946-0.71180.240098
25-0.105005-0.71220.239975
260.1671341.13360.131427
27-0.054512-0.36970.356644
28-0.112974-0.76620.223729
290.2133771.44720.077311
30-0.207708-1.40870.082817
310.1235380.83790.203216
32-0.063426-0.43020.334537
33-0.007846-0.05320.478896
340.0680980.46190.323179
35-0.000151-0.0010.499595
36-0.160347-1.08750.141234

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.576289 & -3.9086 & 0.000151 \tabularnewline
2 & -0.009806 & -0.0665 & 0.47363 \tabularnewline
3 & 0.258712 & 1.7547 & 0.042987 \tabularnewline
4 & -0.176539 & -1.1973 & 0.118652 \tabularnewline
5 & -0.045409 & -0.308 & 0.379745 \tabularnewline
6 & 0.26199 & 1.7769 & 0.041099 \tabularnewline
7 & -0.324746 & -2.2025 & 0.016339 \tabularnewline
8 & 0.219908 & 1.4915 & 0.07133 \tabularnewline
9 & -0.069962 & -0.4745 & 0.318693 \tabularnewline
10 & -0.07485 & -0.5077 & 0.307059 \tabularnewline
11 & 0.113947 & 0.7728 & 0.221789 \tabularnewline
12 & -0.039703 & -0.2693 & 0.394459 \tabularnewline
13 & -0.102675 & -0.6964 & 0.24485 \tabularnewline
14 & 0.188461 & 1.2782 & 0.103795 \tabularnewline
15 & -0.115595 & -0.784 & 0.218527 \tabularnewline
16 & -0.052189 & -0.354 & 0.362493 \tabularnewline
17 & 0.143277 & 0.9718 & 0.168127 \tabularnewline
18 & -0.089565 & -0.6075 & 0.273267 \tabularnewline
19 & -0.061002 & -0.4137 & 0.340496 \tabularnewline
20 & 0.148212 & 1.0052 & 0.160024 \tabularnewline
21 & 0.019969 & 0.1354 & 0.44643 \tabularnewline
22 & -0.292647 & -1.9848 & 0.026573 \tabularnewline
23 & 0.307252 & 2.0839 & 0.021377 \tabularnewline
24 & -0.104946 & -0.7118 & 0.240098 \tabularnewline
25 & -0.105005 & -0.7122 & 0.239975 \tabularnewline
26 & 0.167134 & 1.1336 & 0.131427 \tabularnewline
27 & -0.054512 & -0.3697 & 0.356644 \tabularnewline
28 & -0.112974 & -0.7662 & 0.223729 \tabularnewline
29 & 0.213377 & 1.4472 & 0.077311 \tabularnewline
30 & -0.207708 & -1.4087 & 0.082817 \tabularnewline
31 & 0.123538 & 0.8379 & 0.203216 \tabularnewline
32 & -0.063426 & -0.4302 & 0.334537 \tabularnewline
33 & -0.007846 & -0.0532 & 0.478896 \tabularnewline
34 & 0.068098 & 0.4619 & 0.323179 \tabularnewline
35 & -0.000151 & -0.001 & 0.499595 \tabularnewline
36 & -0.160347 & -1.0875 & 0.141234 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60299&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]-0.576289[/C][C]-3.9086[/C][C]0.000151[/C][/ROW]
[ROW][C]2[/C][C]-0.009806[/C][C]-0.0665[/C][C]0.47363[/C][/ROW]
[ROW][C]3[/C][C]0.258712[/C][C]1.7547[/C][C]0.042987[/C][/ROW]
[ROW][C]4[/C][C]-0.176539[/C][C]-1.1973[/C][C]0.118652[/C][/ROW]
[ROW][C]5[/C][C]-0.045409[/C][C]-0.308[/C][C]0.379745[/C][/ROW]
[ROW][C]6[/C][C]0.26199[/C][C]1.7769[/C][C]0.041099[/C][/ROW]
[ROW][C]7[/C][C]-0.324746[/C][C]-2.2025[/C][C]0.016339[/C][/ROW]
[ROW][C]8[/C][C]0.219908[/C][C]1.4915[/C][C]0.07133[/C][/ROW]
[ROW][C]9[/C][C]-0.069962[/C][C]-0.4745[/C][C]0.318693[/C][/ROW]
[ROW][C]10[/C][C]-0.07485[/C][C]-0.5077[/C][C]0.307059[/C][/ROW]
[ROW][C]11[/C][C]0.113947[/C][C]0.7728[/C][C]0.221789[/C][/ROW]
[ROW][C]12[/C][C]-0.039703[/C][C]-0.2693[/C][C]0.394459[/C][/ROW]
[ROW][C]13[/C][C]-0.102675[/C][C]-0.6964[/C][C]0.24485[/C][/ROW]
[ROW][C]14[/C][C]0.188461[/C][C]1.2782[/C][C]0.103795[/C][/ROW]
[ROW][C]15[/C][C]-0.115595[/C][C]-0.784[/C][C]0.218527[/C][/ROW]
[ROW][C]16[/C][C]-0.052189[/C][C]-0.354[/C][C]0.362493[/C][/ROW]
[ROW][C]17[/C][C]0.143277[/C][C]0.9718[/C][C]0.168127[/C][/ROW]
[ROW][C]18[/C][C]-0.089565[/C][C]-0.6075[/C][C]0.273267[/C][/ROW]
[ROW][C]19[/C][C]-0.061002[/C][C]-0.4137[/C][C]0.340496[/C][/ROW]
[ROW][C]20[/C][C]0.148212[/C][C]1.0052[/C][C]0.160024[/C][/ROW]
[ROW][C]21[/C][C]0.019969[/C][C]0.1354[/C][C]0.44643[/C][/ROW]
[ROW][C]22[/C][C]-0.292647[/C][C]-1.9848[/C][C]0.026573[/C][/ROW]
[ROW][C]23[/C][C]0.307252[/C][C]2.0839[/C][C]0.021377[/C][/ROW]
[ROW][C]24[/C][C]-0.104946[/C][C]-0.7118[/C][C]0.240098[/C][/ROW]
[ROW][C]25[/C][C]-0.105005[/C][C]-0.7122[/C][C]0.239975[/C][/ROW]
[ROW][C]26[/C][C]0.167134[/C][C]1.1336[/C][C]0.131427[/C][/ROW]
[ROW][C]27[/C][C]-0.054512[/C][C]-0.3697[/C][C]0.356644[/C][/ROW]
[ROW][C]28[/C][C]-0.112974[/C][C]-0.7662[/C][C]0.223729[/C][/ROW]
[ROW][C]29[/C][C]0.213377[/C][C]1.4472[/C][C]0.077311[/C][/ROW]
[ROW][C]30[/C][C]-0.207708[/C][C]-1.4087[/C][C]0.082817[/C][/ROW]
[ROW][C]31[/C][C]0.123538[/C][C]0.8379[/C][C]0.203216[/C][/ROW]
[ROW][C]32[/C][C]-0.063426[/C][C]-0.4302[/C][C]0.334537[/C][/ROW]
[ROW][C]33[/C][C]-0.007846[/C][C]-0.0532[/C][C]0.478896[/C][/ROW]
[ROW][C]34[/C][C]0.068098[/C][C]0.4619[/C][C]0.323179[/C][/ROW]
[ROW][C]35[/C][C]-0.000151[/C][C]-0.001[/C][C]0.499595[/C][/ROW]
[ROW][C]36[/C][C]-0.160347[/C][C]-1.0875[/C][C]0.141234[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60299&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60299&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
1-0.576289-3.90860.000151
2-0.009806-0.06650.47363
30.2587121.75470.042987
4-0.176539-1.19730.118652
5-0.045409-0.3080.379745
60.261991.77690.041099
7-0.324746-2.20250.016339
80.2199081.49150.07133
9-0.069962-0.47450.318693
10-0.07485-0.50770.307059
110.1139470.77280.221789
12-0.039703-0.26930.394459
13-0.102675-0.69640.24485
140.1884611.27820.103795
15-0.115595-0.7840.218527
16-0.052189-0.3540.362493
170.1432770.97180.168127
18-0.089565-0.60750.273267
19-0.061002-0.41370.340496
200.1482121.00520.160024
210.0199690.13540.44643
22-0.292647-1.98480.026573
230.3072522.08390.021377
24-0.104946-0.71180.240098
25-0.105005-0.71220.239975
260.1671341.13360.131427
27-0.054512-0.36970.356644
28-0.112974-0.76620.223729
290.2133771.44720.077311
30-0.207708-1.40870.082817
310.1235380.83790.203216
32-0.063426-0.43020.334537
33-0.007846-0.05320.478896
340.0680980.46190.323179
35-0.000151-0.0010.499595
36-0.160347-1.08750.141234






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.576289-3.90860.000151
2-0.511934-3.47210.000567
3-0.091011-0.61730.270052
40.0054970.03730.48521
5-0.108282-0.73440.233215
60.1869541.2680.105592
7-0.072749-0.49340.312036
80.0729490.49480.311561
9-0.063858-0.43310.333481
10-0.091815-0.62270.268272
11-0.033893-0.22990.409604
12-0.029305-0.19880.421665
13-0.070374-0.47730.317703
140.0095960.06510.474196
150.0888290.60250.274911
16-0.05588-0.3790.353218
17-0.001924-0.01310.494822
180.0123220.08360.466881
19-0.093931-0.63710.263619
20-0.040892-0.27730.391378
210.2797231.89720.032047
22-0.179703-1.21880.114566
23-0.089592-0.60760.273207
24-0.023295-0.1580.437577
25-0.085231-0.57810.283019
26-0.027092-0.18380.427509
270.0644250.4370.332095
280.0267410.18140.428437
290.021820.1480.441499
300.01080.07330.470962
310.0045270.03070.487819
32-0.210223-1.42580.080339
33-0.065954-0.44730.328372
340.0071720.04860.480708
350.0417820.28340.389078
360.0142770.09680.46164

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.576289 & -3.9086 & 0.000151 \tabularnewline
2 & -0.511934 & -3.4721 & 0.000567 \tabularnewline
3 & -0.091011 & -0.6173 & 0.270052 \tabularnewline
4 & 0.005497 & 0.0373 & 0.48521 \tabularnewline
5 & -0.108282 & -0.7344 & 0.233215 \tabularnewline
6 & 0.186954 & 1.268 & 0.105592 \tabularnewline
7 & -0.072749 & -0.4934 & 0.312036 \tabularnewline
8 & 0.072949 & 0.4948 & 0.311561 \tabularnewline
9 & -0.063858 & -0.4331 & 0.333481 \tabularnewline
10 & -0.091815 & -0.6227 & 0.268272 \tabularnewline
11 & -0.033893 & -0.2299 & 0.409604 \tabularnewline
12 & -0.029305 & -0.1988 & 0.421665 \tabularnewline
13 & -0.070374 & -0.4773 & 0.317703 \tabularnewline
14 & 0.009596 & 0.0651 & 0.474196 \tabularnewline
15 & 0.088829 & 0.6025 & 0.274911 \tabularnewline
16 & -0.05588 & -0.379 & 0.353218 \tabularnewline
17 & -0.001924 & -0.0131 & 0.494822 \tabularnewline
18 & 0.012322 & 0.0836 & 0.466881 \tabularnewline
19 & -0.093931 & -0.6371 & 0.263619 \tabularnewline
20 & -0.040892 & -0.2773 & 0.391378 \tabularnewline
21 & 0.279723 & 1.8972 & 0.032047 \tabularnewline
22 & -0.179703 & -1.2188 & 0.114566 \tabularnewline
23 & -0.089592 & -0.6076 & 0.273207 \tabularnewline
24 & -0.023295 & -0.158 & 0.437577 \tabularnewline
25 & -0.085231 & -0.5781 & 0.283019 \tabularnewline
26 & -0.027092 & -0.1838 & 0.427509 \tabularnewline
27 & 0.064425 & 0.437 & 0.332095 \tabularnewline
28 & 0.026741 & 0.1814 & 0.428437 \tabularnewline
29 & 0.02182 & 0.148 & 0.441499 \tabularnewline
30 & 0.0108 & 0.0733 & 0.470962 \tabularnewline
31 & 0.004527 & 0.0307 & 0.487819 \tabularnewline
32 & -0.210223 & -1.4258 & 0.080339 \tabularnewline
33 & -0.065954 & -0.4473 & 0.328372 \tabularnewline
34 & 0.007172 & 0.0486 & 0.480708 \tabularnewline
35 & 0.041782 & 0.2834 & 0.389078 \tabularnewline
36 & 0.014277 & 0.0968 & 0.46164 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60299&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]-0.576289[/C][C]-3.9086[/C][C]0.000151[/C][/ROW]
[ROW][C]2[/C][C]-0.511934[/C][C]-3.4721[/C][C]0.000567[/C][/ROW]
[ROW][C]3[/C][C]-0.091011[/C][C]-0.6173[/C][C]0.270052[/C][/ROW]
[ROW][C]4[/C][C]0.005497[/C][C]0.0373[/C][C]0.48521[/C][/ROW]
[ROW][C]5[/C][C]-0.108282[/C][C]-0.7344[/C][C]0.233215[/C][/ROW]
[ROW][C]6[/C][C]0.186954[/C][C]1.268[/C][C]0.105592[/C][/ROW]
[ROW][C]7[/C][C]-0.072749[/C][C]-0.4934[/C][C]0.312036[/C][/ROW]
[ROW][C]8[/C][C]0.072949[/C][C]0.4948[/C][C]0.311561[/C][/ROW]
[ROW][C]9[/C][C]-0.063858[/C][C]-0.4331[/C][C]0.333481[/C][/ROW]
[ROW][C]10[/C][C]-0.091815[/C][C]-0.6227[/C][C]0.268272[/C][/ROW]
[ROW][C]11[/C][C]-0.033893[/C][C]-0.2299[/C][C]0.409604[/C][/ROW]
[ROW][C]12[/C][C]-0.029305[/C][C]-0.1988[/C][C]0.421665[/C][/ROW]
[ROW][C]13[/C][C]-0.070374[/C][C]-0.4773[/C][C]0.317703[/C][/ROW]
[ROW][C]14[/C][C]0.009596[/C][C]0.0651[/C][C]0.474196[/C][/ROW]
[ROW][C]15[/C][C]0.088829[/C][C]0.6025[/C][C]0.274911[/C][/ROW]
[ROW][C]16[/C][C]-0.05588[/C][C]-0.379[/C][C]0.353218[/C][/ROW]
[ROW][C]17[/C][C]-0.001924[/C][C]-0.0131[/C][C]0.494822[/C][/ROW]
[ROW][C]18[/C][C]0.012322[/C][C]0.0836[/C][C]0.466881[/C][/ROW]
[ROW][C]19[/C][C]-0.093931[/C][C]-0.6371[/C][C]0.263619[/C][/ROW]
[ROW][C]20[/C][C]-0.040892[/C][C]-0.2773[/C][C]0.391378[/C][/ROW]
[ROW][C]21[/C][C]0.279723[/C][C]1.8972[/C][C]0.032047[/C][/ROW]
[ROW][C]22[/C][C]-0.179703[/C][C]-1.2188[/C][C]0.114566[/C][/ROW]
[ROW][C]23[/C][C]-0.089592[/C][C]-0.6076[/C][C]0.273207[/C][/ROW]
[ROW][C]24[/C][C]-0.023295[/C][C]-0.158[/C][C]0.437577[/C][/ROW]
[ROW][C]25[/C][C]-0.085231[/C][C]-0.5781[/C][C]0.283019[/C][/ROW]
[ROW][C]26[/C][C]-0.027092[/C][C]-0.1838[/C][C]0.427509[/C][/ROW]
[ROW][C]27[/C][C]0.064425[/C][C]0.437[/C][C]0.332095[/C][/ROW]
[ROW][C]28[/C][C]0.026741[/C][C]0.1814[/C][C]0.428437[/C][/ROW]
[ROW][C]29[/C][C]0.02182[/C][C]0.148[/C][C]0.441499[/C][/ROW]
[ROW][C]30[/C][C]0.0108[/C][C]0.0733[/C][C]0.470962[/C][/ROW]
[ROW][C]31[/C][C]0.004527[/C][C]0.0307[/C][C]0.487819[/C][/ROW]
[ROW][C]32[/C][C]-0.210223[/C][C]-1.4258[/C][C]0.080339[/C][/ROW]
[ROW][C]33[/C][C]-0.065954[/C][C]-0.4473[/C][C]0.328372[/C][/ROW]
[ROW][C]34[/C][C]0.007172[/C][C]0.0486[/C][C]0.480708[/C][/ROW]
[ROW][C]35[/C][C]0.041782[/C][C]0.2834[/C][C]0.389078[/C][/ROW]
[ROW][C]36[/C][C]0.014277[/C][C]0.0968[/C][C]0.46164[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60299&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60299&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
1-0.576289-3.90860.000151
2-0.511934-3.47210.000567
3-0.091011-0.61730.270052
40.0054970.03730.48521
5-0.108282-0.73440.233215
60.1869541.2680.105592
7-0.072749-0.49340.312036
80.0729490.49480.311561
9-0.063858-0.43310.333481
10-0.091815-0.62270.268272
11-0.033893-0.22990.409604
12-0.029305-0.19880.421665
13-0.070374-0.47730.317703
140.0095960.06510.474196
150.0888290.60250.274911
16-0.05588-0.3790.353218
17-0.001924-0.01310.494822
180.0123220.08360.466881
19-0.093931-0.63710.263619
20-0.040892-0.27730.391378
210.2797231.89720.032047
22-0.179703-1.21880.114566
23-0.089592-0.60760.273207
24-0.023295-0.1580.437577
25-0.085231-0.57810.283019
26-0.027092-0.18380.427509
270.0644250.4370.332095
280.0267410.18140.428437
290.021820.1480.441499
300.01080.07330.470962
310.0045270.03070.487819
32-0.210223-1.42580.080339
33-0.065954-0.44730.328372
340.0071720.04860.480708
350.0417820.28340.389078
360.0142770.09680.46164


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = -2.0 ; par3 = 2 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = -2.0 ; par3 = 2 ; 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')