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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 computationMon, 14 Dec 2009 03:10:41 -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/14/t12607855041b0pvokb84k2yze.htm/, Retrieved Sun, 05 May 2024 19:33:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=67497, Retrieved Sun, 05 May 2024 19:33:28 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact119
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 12:19:56] [b98453cac15ba1066b407e146608df68]
-   PD          [(Partial) Autocorrelation Function] [] [2009-12-14 10:10:41] [d39d4e1021a28f94dc953cf77db656ab] [Current]
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Dataseries X:
95,1
97,0
112,7
102,9
97,4
111,4
87,4
96,8
114,1
110,3
103,9
101,6
94,6
95,9
104,7
102,8
98,1
113,9
80,9
95,7
113,2
105,9
108,8
102,3
99,0
100,7
115,5
100,7
109,9
114,6
85,4
100,5
114,8
116,5
112,9
102,0
106,0
105,3
118,8
106,1
109,3
117,2
92,5
104,2
112,5
122,4
113,3
100,0
110,7
112,8
109,8
117,3
109,1
115,9
96,0
99,8
116,8
115,7
99,4
94,3




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=67497&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=67497&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67497&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
10.0192590.13340.447205
20.2097281.4530.07636
30.271581.88160.032984
40.0418540.290.386542
50.1378030.95470.17225
60.1311670.90880.18401
7-0.031635-0.21920.413722
80.066420.46020.323735
90.0781390.54140.295382
10-0.096778-0.67050.252876
110.0487650.33790.368473
12-0.051848-0.35920.360506
13-0.050276-0.34830.36456
14-0.093837-0.65010.259357
150.0124850.08650.465715
16-0.153869-1.0660.14587
17-0.037308-0.25850.398571
18-0.033291-0.23060.409285
19-0.167336-1.15930.126027
20-0.071402-0.49470.311538
21-0.083611-0.57930.282557
22-0.250703-1.73690.044408
230.1219750.84510.201133
24-0.259312-1.79660.039349
25-0.128243-0.88850.189354
26-0.019309-0.13380.447068
27-0.130405-0.90350.185394
28-0.075683-0.52430.301225
29-0.068718-0.47610.318083
30-0.119001-0.82450.206877
31-0.132938-0.9210.180823
32-0.038997-0.27020.39409
33-0.160954-1.11510.135174
34-0.005351-0.03710.48529
35-0.061104-0.42330.336968
360.0463430.32110.374775

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.019259 & 0.1334 & 0.447205 \tabularnewline
2 & 0.209728 & 1.453 & 0.07636 \tabularnewline
3 & 0.27158 & 1.8816 & 0.032984 \tabularnewline
4 & 0.041854 & 0.29 & 0.386542 \tabularnewline
5 & 0.137803 & 0.9547 & 0.17225 \tabularnewline
6 & 0.131167 & 0.9088 & 0.18401 \tabularnewline
7 & -0.031635 & -0.2192 & 0.413722 \tabularnewline
8 & 0.06642 & 0.4602 & 0.323735 \tabularnewline
9 & 0.078139 & 0.5414 & 0.295382 \tabularnewline
10 & -0.096778 & -0.6705 & 0.252876 \tabularnewline
11 & 0.048765 & 0.3379 & 0.368473 \tabularnewline
12 & -0.051848 & -0.3592 & 0.360506 \tabularnewline
13 & -0.050276 & -0.3483 & 0.36456 \tabularnewline
14 & -0.093837 & -0.6501 & 0.259357 \tabularnewline
15 & 0.012485 & 0.0865 & 0.465715 \tabularnewline
16 & -0.153869 & -1.066 & 0.14587 \tabularnewline
17 & -0.037308 & -0.2585 & 0.398571 \tabularnewline
18 & -0.033291 & -0.2306 & 0.409285 \tabularnewline
19 & -0.167336 & -1.1593 & 0.126027 \tabularnewline
20 & -0.071402 & -0.4947 & 0.311538 \tabularnewline
21 & -0.083611 & -0.5793 & 0.282557 \tabularnewline
22 & -0.250703 & -1.7369 & 0.044408 \tabularnewline
23 & 0.121975 & 0.8451 & 0.201133 \tabularnewline
24 & -0.259312 & -1.7966 & 0.039349 \tabularnewline
25 & -0.128243 & -0.8885 & 0.189354 \tabularnewline
26 & -0.019309 & -0.1338 & 0.447068 \tabularnewline
27 & -0.130405 & -0.9035 & 0.185394 \tabularnewline
28 & -0.075683 & -0.5243 & 0.301225 \tabularnewline
29 & -0.068718 & -0.4761 & 0.318083 \tabularnewline
30 & -0.119001 & -0.8245 & 0.206877 \tabularnewline
31 & -0.132938 & -0.921 & 0.180823 \tabularnewline
32 & -0.038997 & -0.2702 & 0.39409 \tabularnewline
33 & -0.160954 & -1.1151 & 0.135174 \tabularnewline
34 & -0.005351 & -0.0371 & 0.48529 \tabularnewline
35 & -0.061104 & -0.4233 & 0.336968 \tabularnewline
36 & 0.046343 & 0.3211 & 0.374775 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67497&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]0.019259[/C][C]0.1334[/C][C]0.447205[/C][/ROW]
[ROW][C]2[/C][C]0.209728[/C][C]1.453[/C][C]0.07636[/C][/ROW]
[ROW][C]3[/C][C]0.27158[/C][C]1.8816[/C][C]0.032984[/C][/ROW]
[ROW][C]4[/C][C]0.041854[/C][C]0.29[/C][C]0.386542[/C][/ROW]
[ROW][C]5[/C][C]0.137803[/C][C]0.9547[/C][C]0.17225[/C][/ROW]
[ROW][C]6[/C][C]0.131167[/C][C]0.9088[/C][C]0.18401[/C][/ROW]
[ROW][C]7[/C][C]-0.031635[/C][C]-0.2192[/C][C]0.413722[/C][/ROW]
[ROW][C]8[/C][C]0.06642[/C][C]0.4602[/C][C]0.323735[/C][/ROW]
[ROW][C]9[/C][C]0.078139[/C][C]0.5414[/C][C]0.295382[/C][/ROW]
[ROW][C]10[/C][C]-0.096778[/C][C]-0.6705[/C][C]0.252876[/C][/ROW]
[ROW][C]11[/C][C]0.048765[/C][C]0.3379[/C][C]0.368473[/C][/ROW]
[ROW][C]12[/C][C]-0.051848[/C][C]-0.3592[/C][C]0.360506[/C][/ROW]
[ROW][C]13[/C][C]-0.050276[/C][C]-0.3483[/C][C]0.36456[/C][/ROW]
[ROW][C]14[/C][C]-0.093837[/C][C]-0.6501[/C][C]0.259357[/C][/ROW]
[ROW][C]15[/C][C]0.012485[/C][C]0.0865[/C][C]0.465715[/C][/ROW]
[ROW][C]16[/C][C]-0.153869[/C][C]-1.066[/C][C]0.14587[/C][/ROW]
[ROW][C]17[/C][C]-0.037308[/C][C]-0.2585[/C][C]0.398571[/C][/ROW]
[ROW][C]18[/C][C]-0.033291[/C][C]-0.2306[/C][C]0.409285[/C][/ROW]
[ROW][C]19[/C][C]-0.167336[/C][C]-1.1593[/C][C]0.126027[/C][/ROW]
[ROW][C]20[/C][C]-0.071402[/C][C]-0.4947[/C][C]0.311538[/C][/ROW]
[ROW][C]21[/C][C]-0.083611[/C][C]-0.5793[/C][C]0.282557[/C][/ROW]
[ROW][C]22[/C][C]-0.250703[/C][C]-1.7369[/C][C]0.044408[/C][/ROW]
[ROW][C]23[/C][C]0.121975[/C][C]0.8451[/C][C]0.201133[/C][/ROW]
[ROW][C]24[/C][C]-0.259312[/C][C]-1.7966[/C][C]0.039349[/C][/ROW]
[ROW][C]25[/C][C]-0.128243[/C][C]-0.8885[/C][C]0.189354[/C][/ROW]
[ROW][C]26[/C][C]-0.019309[/C][C]-0.1338[/C][C]0.447068[/C][/ROW]
[ROW][C]27[/C][C]-0.130405[/C][C]-0.9035[/C][C]0.185394[/C][/ROW]
[ROW][C]28[/C][C]-0.075683[/C][C]-0.5243[/C][C]0.301225[/C][/ROW]
[ROW][C]29[/C][C]-0.068718[/C][C]-0.4761[/C][C]0.318083[/C][/ROW]
[ROW][C]30[/C][C]-0.119001[/C][C]-0.8245[/C][C]0.206877[/C][/ROW]
[ROW][C]31[/C][C]-0.132938[/C][C]-0.921[/C][C]0.180823[/C][/ROW]
[ROW][C]32[/C][C]-0.038997[/C][C]-0.2702[/C][C]0.39409[/C][/ROW]
[ROW][C]33[/C][C]-0.160954[/C][C]-1.1151[/C][C]0.135174[/C][/ROW]
[ROW][C]34[/C][C]-0.005351[/C][C]-0.0371[/C][C]0.48529[/C][/ROW]
[ROW][C]35[/C][C]-0.061104[/C][C]-0.4233[/C][C]0.336968[/C][/ROW]
[ROW][C]36[/C][C]0.046343[/C][C]0.3211[/C][C]0.374775[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67497&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67497&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
10.0192590.13340.447205
20.2097281.4530.07636
30.271581.88160.032984
40.0418540.290.386542
50.1378030.95470.17225
60.1311670.90880.18401
7-0.031635-0.21920.413722
80.066420.46020.323735
90.0781390.54140.295382
10-0.096778-0.67050.252876
110.0487650.33790.368473
12-0.051848-0.35920.360506
13-0.050276-0.34830.36456
14-0.093837-0.65010.259357
150.0124850.08650.465715
16-0.153869-1.0660.14587
17-0.037308-0.25850.398571
18-0.033291-0.23060.409285
19-0.167336-1.15930.126027
20-0.071402-0.49470.311538
21-0.083611-0.57930.282557
22-0.250703-1.73690.044408
230.1219750.84510.201133
24-0.259312-1.79660.039349
25-0.128243-0.88850.189354
26-0.019309-0.13380.447068
27-0.130405-0.90350.185394
28-0.075683-0.52430.301225
29-0.068718-0.47610.318083
30-0.119001-0.82450.206877
31-0.132938-0.9210.180823
32-0.038997-0.27020.39409
33-0.160954-1.11510.135174
34-0.005351-0.03710.48529
35-0.061104-0.42330.336968
360.0463430.32110.374775







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.0192590.13340.447205
20.2094351.4510.076641
30.2765831.91620.030651
40.0057590.03990.48417
50.029540.20470.419351
60.0606690.42030.338062
7-0.079406-0.55010.292387
8-0.022792-0.15790.437595
90.0573380.39730.346472
10-0.094145-0.65230.258674
11-0.007609-0.05270.479087
12-0.047198-0.3270.372546
13-0.011575-0.08020.468208
14-0.115447-0.79980.213873
150.0598010.41430.340246
16-0.088241-0.61130.271927
17-0.018392-0.12740.449568
180.0177030.12270.451447
19-0.085287-0.59090.278684
20-0.076353-0.5290.299625
21-0.022931-0.15890.43722
22-0.176055-1.21970.11426
230.1980451.37210.088207
24-0.196863-1.36390.089479
25-0.041357-0.28650.387854
26-0.048649-0.33710.368774
270.0440430.30510.380791
28-0.050419-0.34930.364191
29-0.059654-0.41330.340616
30-0.056134-0.38890.349532
31-0.113536-0.78660.217692
32-0.073165-0.50690.307271
33-0.043328-0.30020.382665
34-0.013862-0.0960.461946
350.0035180.02440.490328
360.05980.41430.340249

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.019259 & 0.1334 & 0.447205 \tabularnewline
2 & 0.209435 & 1.451 & 0.076641 \tabularnewline
3 & 0.276583 & 1.9162 & 0.030651 \tabularnewline
4 & 0.005759 & 0.0399 & 0.48417 \tabularnewline
5 & 0.02954 & 0.2047 & 0.419351 \tabularnewline
6 & 0.060669 & 0.4203 & 0.338062 \tabularnewline
7 & -0.079406 & -0.5501 & 0.292387 \tabularnewline
8 & -0.022792 & -0.1579 & 0.437595 \tabularnewline
9 & 0.057338 & 0.3973 & 0.346472 \tabularnewline
10 & -0.094145 & -0.6523 & 0.258674 \tabularnewline
11 & -0.007609 & -0.0527 & 0.479087 \tabularnewline
12 & -0.047198 & -0.327 & 0.372546 \tabularnewline
13 & -0.011575 & -0.0802 & 0.468208 \tabularnewline
14 & -0.115447 & -0.7998 & 0.213873 \tabularnewline
15 & 0.059801 & 0.4143 & 0.340246 \tabularnewline
16 & -0.088241 & -0.6113 & 0.271927 \tabularnewline
17 & -0.018392 & -0.1274 & 0.449568 \tabularnewline
18 & 0.017703 & 0.1227 & 0.451447 \tabularnewline
19 & -0.085287 & -0.5909 & 0.278684 \tabularnewline
20 & -0.076353 & -0.529 & 0.299625 \tabularnewline
21 & -0.022931 & -0.1589 & 0.43722 \tabularnewline
22 & -0.176055 & -1.2197 & 0.11426 \tabularnewline
23 & 0.198045 & 1.3721 & 0.088207 \tabularnewline
24 & -0.196863 & -1.3639 & 0.089479 \tabularnewline
25 & -0.041357 & -0.2865 & 0.387854 \tabularnewline
26 & -0.048649 & -0.3371 & 0.368774 \tabularnewline
27 & 0.044043 & 0.3051 & 0.380791 \tabularnewline
28 & -0.050419 & -0.3493 & 0.364191 \tabularnewline
29 & -0.059654 & -0.4133 & 0.340616 \tabularnewline
30 & -0.056134 & -0.3889 & 0.349532 \tabularnewline
31 & -0.113536 & -0.7866 & 0.217692 \tabularnewline
32 & -0.073165 & -0.5069 & 0.307271 \tabularnewline
33 & -0.043328 & -0.3002 & 0.382665 \tabularnewline
34 & -0.013862 & -0.096 & 0.461946 \tabularnewline
35 & 0.003518 & 0.0244 & 0.490328 \tabularnewline
36 & 0.0598 & 0.4143 & 0.340249 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67497&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]0.019259[/C][C]0.1334[/C][C]0.447205[/C][/ROW]
[ROW][C]2[/C][C]0.209435[/C][C]1.451[/C][C]0.076641[/C][/ROW]
[ROW][C]3[/C][C]0.276583[/C][C]1.9162[/C][C]0.030651[/C][/ROW]
[ROW][C]4[/C][C]0.005759[/C][C]0.0399[/C][C]0.48417[/C][/ROW]
[ROW][C]5[/C][C]0.02954[/C][C]0.2047[/C][C]0.419351[/C][/ROW]
[ROW][C]6[/C][C]0.060669[/C][C]0.4203[/C][C]0.338062[/C][/ROW]
[ROW][C]7[/C][C]-0.079406[/C][C]-0.5501[/C][C]0.292387[/C][/ROW]
[ROW][C]8[/C][C]-0.022792[/C][C]-0.1579[/C][C]0.437595[/C][/ROW]
[ROW][C]9[/C][C]0.057338[/C][C]0.3973[/C][C]0.346472[/C][/ROW]
[ROW][C]10[/C][C]-0.094145[/C][C]-0.6523[/C][C]0.258674[/C][/ROW]
[ROW][C]11[/C][C]-0.007609[/C][C]-0.0527[/C][C]0.479087[/C][/ROW]
[ROW][C]12[/C][C]-0.047198[/C][C]-0.327[/C][C]0.372546[/C][/ROW]
[ROW][C]13[/C][C]-0.011575[/C][C]-0.0802[/C][C]0.468208[/C][/ROW]
[ROW][C]14[/C][C]-0.115447[/C][C]-0.7998[/C][C]0.213873[/C][/ROW]
[ROW][C]15[/C][C]0.059801[/C][C]0.4143[/C][C]0.340246[/C][/ROW]
[ROW][C]16[/C][C]-0.088241[/C][C]-0.6113[/C][C]0.271927[/C][/ROW]
[ROW][C]17[/C][C]-0.018392[/C][C]-0.1274[/C][C]0.449568[/C][/ROW]
[ROW][C]18[/C][C]0.017703[/C][C]0.1227[/C][C]0.451447[/C][/ROW]
[ROW][C]19[/C][C]-0.085287[/C][C]-0.5909[/C][C]0.278684[/C][/ROW]
[ROW][C]20[/C][C]-0.076353[/C][C]-0.529[/C][C]0.299625[/C][/ROW]
[ROW][C]21[/C][C]-0.022931[/C][C]-0.1589[/C][C]0.43722[/C][/ROW]
[ROW][C]22[/C][C]-0.176055[/C][C]-1.2197[/C][C]0.11426[/C][/ROW]
[ROW][C]23[/C][C]0.198045[/C][C]1.3721[/C][C]0.088207[/C][/ROW]
[ROW][C]24[/C][C]-0.196863[/C][C]-1.3639[/C][C]0.089479[/C][/ROW]
[ROW][C]25[/C][C]-0.041357[/C][C]-0.2865[/C][C]0.387854[/C][/ROW]
[ROW][C]26[/C][C]-0.048649[/C][C]-0.3371[/C][C]0.368774[/C][/ROW]
[ROW][C]27[/C][C]0.044043[/C][C]0.3051[/C][C]0.380791[/C][/ROW]
[ROW][C]28[/C][C]-0.050419[/C][C]-0.3493[/C][C]0.364191[/C][/ROW]
[ROW][C]29[/C][C]-0.059654[/C][C]-0.4133[/C][C]0.340616[/C][/ROW]
[ROW][C]30[/C][C]-0.056134[/C][C]-0.3889[/C][C]0.349532[/C][/ROW]
[ROW][C]31[/C][C]-0.113536[/C][C]-0.7866[/C][C]0.217692[/C][/ROW]
[ROW][C]32[/C][C]-0.073165[/C][C]-0.5069[/C][C]0.307271[/C][/ROW]
[ROW][C]33[/C][C]-0.043328[/C][C]-0.3002[/C][C]0.382665[/C][/ROW]
[ROW][C]34[/C][C]-0.013862[/C][C]-0.096[/C][C]0.461946[/C][/ROW]
[ROW][C]35[/C][C]0.003518[/C][C]0.0244[/C][C]0.490328[/C][/ROW]
[ROW][C]36[/C][C]0.0598[/C][C]0.4143[/C][C]0.340249[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67497&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67497&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
10.0192590.13340.447205
20.2094351.4510.076641
30.2765831.91620.030651
40.0057590.03990.48417
50.029540.20470.419351
60.0606690.42030.338062
7-0.079406-0.55010.292387
8-0.022792-0.15790.437595
90.0573380.39730.346472
10-0.094145-0.65230.258674
11-0.007609-0.05270.479087
12-0.047198-0.3270.372546
13-0.011575-0.08020.468208
14-0.115447-0.79980.213873
150.0598010.41430.340246
16-0.088241-0.61130.271927
17-0.018392-0.12740.449568
180.0177030.12270.451447
19-0.085287-0.59090.278684
20-0.076353-0.5290.299625
21-0.022931-0.15890.43722
22-0.176055-1.21970.11426
230.1980451.37210.088207
24-0.196863-1.36390.089479
25-0.041357-0.28650.387854
26-0.048649-0.33710.368774
270.0440430.30510.380791
28-0.050419-0.34930.364191
29-0.059654-0.41330.340616
30-0.056134-0.38890.349532
31-0.113536-0.78660.217692
32-0.073165-0.50690.307271
33-0.043328-0.30020.382665
34-0.013862-0.0960.461946
350.0035180.02440.490328
360.05980.41430.340249



Parameters (Session):
par1 = 36 ; par2 = 2.0 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 2.0 ; par3 = 0 ; 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')