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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, 01 Dec 2009 10:36:30 -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/01/t1259689054qtojbmyqqsmzxq2.htm/, Retrieved Fri, 19 Apr 2024 15:31:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62140, Retrieved Fri, 19 Apr 2024 15:31:20 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact137

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]
- R  D        [(Partial) Autocorrelation Function] [] [2009-11-24 16:19:12] [b7349fb284cae6f1172638396d27b11f]
- R               [(Partial) Autocorrelation Function] [] [2009-12-01 17:36:30] [6dfcce621b31349cab7f0d189e6f8a9d] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
116222
110924
103753
99983
93302
91496
119321
139261
133739
123913
113438
109416
109406
105645
101328
97686
93093
91382
122257
139183
139887
131822
116805
113706
113012
110452
107005
102841
98173
98181
137277
147579
146571
138920
130340
128140
127059
122860
117702
113537
108366
111078
150739
159129
157928
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

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=62140&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=62140&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62140&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
10.7938326.73590
20.4376143.71332e-04
30.1299571.10270.136909
4-0.038519-0.32680.372367
5-0.079472-0.67430.251128
6-0.08053-0.68330.248299
7-0.068686-0.58280.280917
8-0.029462-0.250.401652
90.1087210.92250.179667
100.3539523.00340.001835
110.6366835.40240
120.7837796.65060
130.59275.02922e-06
140.2863752.430.008797
150.0168090.14260.443492
16-0.1357-1.15150.126678
17-0.178447-1.51420.06718
18-0.185241-1.57180.060188
19-0.177945-1.50990.067721
20-0.147966-1.25550.106673
21-0.034909-0.29620.383962
220.1617721.37270.087056
230.3832343.25180.000873
240.482174.09135.5e-05
250.3149362.67230.004655
260.0721550.61230.271148
27-0.135275-1.14780.127417
28-0.253611-2.1520.017377
29-0.294489-2.49880.007372
30-0.306401-2.59990.005654
31-0.297201-2.52180.006944
32-0.264979-2.24840.013806
33-0.168089-1.42630.079055
34-0.009951-0.08440.466472
350.1636121.38830.084663
360.2330361.97740.025914

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.793832 & 6.7359 & 0 \tabularnewline
2 & 0.437614 & 3.7133 & 2e-04 \tabularnewline
3 & 0.129957 & 1.1027 & 0.136909 \tabularnewline
4 & -0.038519 & -0.3268 & 0.372367 \tabularnewline
5 & -0.079472 & -0.6743 & 0.251128 \tabularnewline
6 & -0.08053 & -0.6833 & 0.248299 \tabularnewline
7 & -0.068686 & -0.5828 & 0.280917 \tabularnewline
8 & -0.029462 & -0.25 & 0.401652 \tabularnewline
9 & 0.108721 & 0.9225 & 0.179667 \tabularnewline
10 & 0.353952 & 3.0034 & 0.001835 \tabularnewline
11 & 0.636683 & 5.4024 & 0 \tabularnewline
12 & 0.783779 & 6.6506 & 0 \tabularnewline
13 & 0.5927 & 5.0292 & 2e-06 \tabularnewline
14 & 0.286375 & 2.43 & 0.008797 \tabularnewline
15 & 0.016809 & 0.1426 & 0.443492 \tabularnewline
16 & -0.1357 & -1.1515 & 0.126678 \tabularnewline
17 & -0.178447 & -1.5142 & 0.06718 \tabularnewline
18 & -0.185241 & -1.5718 & 0.060188 \tabularnewline
19 & -0.177945 & -1.5099 & 0.067721 \tabularnewline
20 & -0.147966 & -1.2555 & 0.106673 \tabularnewline
21 & -0.034909 & -0.2962 & 0.383962 \tabularnewline
22 & 0.161772 & 1.3727 & 0.087056 \tabularnewline
23 & 0.383234 & 3.2518 & 0.000873 \tabularnewline
24 & 0.48217 & 4.0913 & 5.5e-05 \tabularnewline
25 & 0.314936 & 2.6723 & 0.004655 \tabularnewline
26 & 0.072155 & 0.6123 & 0.271148 \tabularnewline
27 & -0.135275 & -1.1478 & 0.127417 \tabularnewline
28 & -0.253611 & -2.152 & 0.017377 \tabularnewline
29 & -0.294489 & -2.4988 & 0.007372 \tabularnewline
30 & -0.306401 & -2.5999 & 0.005654 \tabularnewline
31 & -0.297201 & -2.5218 & 0.006944 \tabularnewline
32 & -0.264979 & -2.2484 & 0.013806 \tabularnewline
33 & -0.168089 & -1.4263 & 0.079055 \tabularnewline
34 & -0.009951 & -0.0844 & 0.466472 \tabularnewline
35 & 0.163612 & 1.3883 & 0.084663 \tabularnewline
36 & 0.233036 & 1.9774 & 0.025914 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62140&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]0.793832[/C][C]6.7359[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.437614[/C][C]3.7133[/C][C]2e-04[/C][/ROW]
[ROW][C]3[/C][C]0.129957[/C][C]1.1027[/C][C]0.136909[/C][/ROW]
[ROW][C]4[/C][C]-0.038519[/C][C]-0.3268[/C][C]0.372367[/C][/ROW]
[ROW][C]5[/C][C]-0.079472[/C][C]-0.6743[/C][C]0.251128[/C][/ROW]
[ROW][C]6[/C][C]-0.08053[/C][C]-0.6833[/C][C]0.248299[/C][/ROW]
[ROW][C]7[/C][C]-0.068686[/C][C]-0.5828[/C][C]0.280917[/C][/ROW]
[ROW][C]8[/C][C]-0.029462[/C][C]-0.25[/C][C]0.401652[/C][/ROW]
[ROW][C]9[/C][C]0.108721[/C][C]0.9225[/C][C]0.179667[/C][/ROW]
[ROW][C]10[/C][C]0.353952[/C][C]3.0034[/C][C]0.001835[/C][/ROW]
[ROW][C]11[/C][C]0.636683[/C][C]5.4024[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.783779[/C][C]6.6506[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.5927[/C][C]5.0292[/C][C]2e-06[/C][/ROW]
[ROW][C]14[/C][C]0.286375[/C][C]2.43[/C][C]0.008797[/C][/ROW]
[ROW][C]15[/C][C]0.016809[/C][C]0.1426[/C][C]0.443492[/C][/ROW]
[ROW][C]16[/C][C]-0.1357[/C][C]-1.1515[/C][C]0.126678[/C][/ROW]
[ROW][C]17[/C][C]-0.178447[/C][C]-1.5142[/C][C]0.06718[/C][/ROW]
[ROW][C]18[/C][C]-0.185241[/C][C]-1.5718[/C][C]0.060188[/C][/ROW]
[ROW][C]19[/C][C]-0.177945[/C][C]-1.5099[/C][C]0.067721[/C][/ROW]
[ROW][C]20[/C][C]-0.147966[/C][C]-1.2555[/C][C]0.106673[/C][/ROW]
[ROW][C]21[/C][C]-0.034909[/C][C]-0.2962[/C][C]0.383962[/C][/ROW]
[ROW][C]22[/C][C]0.161772[/C][C]1.3727[/C][C]0.087056[/C][/ROW]
[ROW][C]23[/C][C]0.383234[/C][C]3.2518[/C][C]0.000873[/C][/ROW]
[ROW][C]24[/C][C]0.48217[/C][C]4.0913[/C][C]5.5e-05[/C][/ROW]
[ROW][C]25[/C][C]0.314936[/C][C]2.6723[/C][C]0.004655[/C][/ROW]
[ROW][C]26[/C][C]0.072155[/C][C]0.6123[/C][C]0.271148[/C][/ROW]
[ROW][C]27[/C][C]-0.135275[/C][C]-1.1478[/C][C]0.127417[/C][/ROW]
[ROW][C]28[/C][C]-0.253611[/C][C]-2.152[/C][C]0.017377[/C][/ROW]
[ROW][C]29[/C][C]-0.294489[/C][C]-2.4988[/C][C]0.007372[/C][/ROW]
[ROW][C]30[/C][C]-0.306401[/C][C]-2.5999[/C][C]0.005654[/C][/ROW]
[ROW][C]31[/C][C]-0.297201[/C][C]-2.5218[/C][C]0.006944[/C][/ROW]
[ROW][C]32[/C][C]-0.264979[/C][C]-2.2484[/C][C]0.013806[/C][/ROW]
[ROW][C]33[/C][C]-0.168089[/C][C]-1.4263[/C][C]0.079055[/C][/ROW]
[ROW][C]34[/C][C]-0.009951[/C][C]-0.0844[/C][C]0.466472[/C][/ROW]
[ROW][C]35[/C][C]0.163612[/C][C]1.3883[/C][C]0.084663[/C][/ROW]
[ROW][C]36[/C][C]0.233036[/C][C]1.9774[/C][C]0.025914[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62140&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62140&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
10.7938326.73590
20.4376143.71332e-04
30.1299571.10270.136909
4-0.038519-0.32680.372367
5-0.079472-0.67430.251128
6-0.08053-0.68330.248299
7-0.068686-0.58280.280917
8-0.029462-0.250.401652
90.1087210.92250.179667
100.3539523.00340.001835
110.6366835.40240
120.7837796.65060
130.59275.02922e-06
140.2863752.430.008797
150.0168090.14260.443492
16-0.1357-1.15150.126678
17-0.178447-1.51420.06718
18-0.185241-1.57180.060188
19-0.177945-1.50990.067721
20-0.147966-1.25550.106673
21-0.034909-0.29620.383962
220.1617721.37270.087056
230.3832343.25180.000873
240.482174.09135.5e-05
250.3149362.67230.004655
260.0721550.61230.271148
27-0.135275-1.14780.127417
28-0.253611-2.1520.017377
29-0.294489-2.49880.007372
30-0.306401-2.59990.005654
31-0.297201-2.52180.006944
32-0.264979-2.24840.013806
33-0.168089-1.42630.079055
34-0.009951-0.08440.466472
350.1636121.38830.084663
360.2330361.97740.025914






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.7938326.73590
2-0.520656-4.41791.7e-05
30.0556670.47240.319052
40.0517220.43890.331033
50.0113280.09610.461847
6-0.10932-0.92760.178354
70.0471960.40050.344998
80.0872250.74010.230813
90.3208762.72270.004058
100.332222.8190.003109
110.4092383.47250.000438
120.1177080.99880.160623
13-0.602203-5.10991e-06
140.362093.07240.001498
15-0.17023-1.44440.076475
16-0.124368-1.05530.147408
17-0.086868-0.73710.231729
18-0.054434-0.46190.322776
19-0.095803-0.81290.209472
20-0.088545-0.75130.227451
21-0.046021-0.39050.348661
22-0.102329-0.86830.194061
23-0.109592-0.92990.177761
24-0.061731-0.52380.301011
250.0189530.16080.436341
26-0.007095-0.06020.47608
270.0126670.10750.457353
28-0.080736-0.68510.24775
29-0.041327-0.35070.36343
300.0500870.4250.336051
310.0151750.12880.448952
32-0.042673-0.36210.359171
33-0.062213-0.52790.299598
340.0064880.05510.478125
35-0.019953-0.16930.433016
36-0.003165-0.02690.489324

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.793832 & 6.7359 & 0 \tabularnewline
2 & -0.520656 & -4.4179 & 1.7e-05 \tabularnewline
3 & 0.055667 & 0.4724 & 0.319052 \tabularnewline
4 & 0.051722 & 0.4389 & 0.331033 \tabularnewline
5 & 0.011328 & 0.0961 & 0.461847 \tabularnewline
6 & -0.10932 & -0.9276 & 0.178354 \tabularnewline
7 & 0.047196 & 0.4005 & 0.344998 \tabularnewline
8 & 0.087225 & 0.7401 & 0.230813 \tabularnewline
9 & 0.320876 & 2.7227 & 0.004058 \tabularnewline
10 & 0.33222 & 2.819 & 0.003109 \tabularnewline
11 & 0.409238 & 3.4725 & 0.000438 \tabularnewline
12 & 0.117708 & 0.9988 & 0.160623 \tabularnewline
13 & -0.602203 & -5.1099 & 1e-06 \tabularnewline
14 & 0.36209 & 3.0724 & 0.001498 \tabularnewline
15 & -0.17023 & -1.4444 & 0.076475 \tabularnewline
16 & -0.124368 & -1.0553 & 0.147408 \tabularnewline
17 & -0.086868 & -0.7371 & 0.231729 \tabularnewline
18 & -0.054434 & -0.4619 & 0.322776 \tabularnewline
19 & -0.095803 & -0.8129 & 0.209472 \tabularnewline
20 & -0.088545 & -0.7513 & 0.227451 \tabularnewline
21 & -0.046021 & -0.3905 & 0.348661 \tabularnewline
22 & -0.102329 & -0.8683 & 0.194061 \tabularnewline
23 & -0.109592 & -0.9299 & 0.177761 \tabularnewline
24 & -0.061731 & -0.5238 & 0.301011 \tabularnewline
25 & 0.018953 & 0.1608 & 0.436341 \tabularnewline
26 & -0.007095 & -0.0602 & 0.47608 \tabularnewline
27 & 0.012667 & 0.1075 & 0.457353 \tabularnewline
28 & -0.080736 & -0.6851 & 0.24775 \tabularnewline
29 & -0.041327 & -0.3507 & 0.36343 \tabularnewline
30 & 0.050087 & 0.425 & 0.336051 \tabularnewline
31 & 0.015175 & 0.1288 & 0.448952 \tabularnewline
32 & -0.042673 & -0.3621 & 0.359171 \tabularnewline
33 & -0.062213 & -0.5279 & 0.299598 \tabularnewline
34 & 0.006488 & 0.0551 & 0.478125 \tabularnewline
35 & -0.019953 & -0.1693 & 0.433016 \tabularnewline
36 & -0.003165 & -0.0269 & 0.489324 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62140&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]0.793832[/C][C]6.7359[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.520656[/C][C]-4.4179[/C][C]1.7e-05[/C][/ROW]
[ROW][C]3[/C][C]0.055667[/C][C]0.4724[/C][C]0.319052[/C][/ROW]
[ROW][C]4[/C][C]0.051722[/C][C]0.4389[/C][C]0.331033[/C][/ROW]
[ROW][C]5[/C][C]0.011328[/C][C]0.0961[/C][C]0.461847[/C][/ROW]
[ROW][C]6[/C][C]-0.10932[/C][C]-0.9276[/C][C]0.178354[/C][/ROW]
[ROW][C]7[/C][C]0.047196[/C][C]0.4005[/C][C]0.344998[/C][/ROW]
[ROW][C]8[/C][C]0.087225[/C][C]0.7401[/C][C]0.230813[/C][/ROW]
[ROW][C]9[/C][C]0.320876[/C][C]2.7227[/C][C]0.004058[/C][/ROW]
[ROW][C]10[/C][C]0.33222[/C][C]2.819[/C][C]0.003109[/C][/ROW]
[ROW][C]11[/C][C]0.409238[/C][C]3.4725[/C][C]0.000438[/C][/ROW]
[ROW][C]12[/C][C]0.117708[/C][C]0.9988[/C][C]0.160623[/C][/ROW]
[ROW][C]13[/C][C]-0.602203[/C][C]-5.1099[/C][C]1e-06[/C][/ROW]
[ROW][C]14[/C][C]0.36209[/C][C]3.0724[/C][C]0.001498[/C][/ROW]
[ROW][C]15[/C][C]-0.17023[/C][C]-1.4444[/C][C]0.076475[/C][/ROW]
[ROW][C]16[/C][C]-0.124368[/C][C]-1.0553[/C][C]0.147408[/C][/ROW]
[ROW][C]17[/C][C]-0.086868[/C][C]-0.7371[/C][C]0.231729[/C][/ROW]
[ROW][C]18[/C][C]-0.054434[/C][C]-0.4619[/C][C]0.322776[/C][/ROW]
[ROW][C]19[/C][C]-0.095803[/C][C]-0.8129[/C][C]0.209472[/C][/ROW]
[ROW][C]20[/C][C]-0.088545[/C][C]-0.7513[/C][C]0.227451[/C][/ROW]
[ROW][C]21[/C][C]-0.046021[/C][C]-0.3905[/C][C]0.348661[/C][/ROW]
[ROW][C]22[/C][C]-0.102329[/C][C]-0.8683[/C][C]0.194061[/C][/ROW]
[ROW][C]23[/C][C]-0.109592[/C][C]-0.9299[/C][C]0.177761[/C][/ROW]
[ROW][C]24[/C][C]-0.061731[/C][C]-0.5238[/C][C]0.301011[/C][/ROW]
[ROW][C]25[/C][C]0.018953[/C][C]0.1608[/C][C]0.436341[/C][/ROW]
[ROW][C]26[/C][C]-0.007095[/C][C]-0.0602[/C][C]0.47608[/C][/ROW]
[ROW][C]27[/C][C]0.012667[/C][C]0.1075[/C][C]0.457353[/C][/ROW]
[ROW][C]28[/C][C]-0.080736[/C][C]-0.6851[/C][C]0.24775[/C][/ROW]
[ROW][C]29[/C][C]-0.041327[/C][C]-0.3507[/C][C]0.36343[/C][/ROW]
[ROW][C]30[/C][C]0.050087[/C][C]0.425[/C][C]0.336051[/C][/ROW]
[ROW][C]31[/C][C]0.015175[/C][C]0.1288[/C][C]0.448952[/C][/ROW]
[ROW][C]32[/C][C]-0.042673[/C][C]-0.3621[/C][C]0.359171[/C][/ROW]
[ROW][C]33[/C][C]-0.062213[/C][C]-0.5279[/C][C]0.299598[/C][/ROW]
[ROW][C]34[/C][C]0.006488[/C][C]0.0551[/C][C]0.478125[/C][/ROW]
[ROW][C]35[/C][C]-0.019953[/C][C]-0.1693[/C][C]0.433016[/C][/ROW]
[ROW][C]36[/C][C]-0.003165[/C][C]-0.0269[/C][C]0.489324[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62140&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62140&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
10.7938326.73590
2-0.520656-4.41791.7e-05
30.0556670.47240.319052
40.0517220.43890.331033
50.0113280.09610.461847
6-0.10932-0.92760.178354
70.0471960.40050.344998
80.0872250.74010.230813
90.3208762.72270.004058
100.332222.8190.003109
110.4092383.47250.000438
120.1177080.99880.160623
13-0.602203-5.10991e-06
140.362093.07240.001498
15-0.17023-1.44440.076475
16-0.124368-1.05530.147408
17-0.086868-0.73710.231729
18-0.054434-0.46190.322776
19-0.095803-0.81290.209472
20-0.088545-0.75130.227451
21-0.046021-0.39050.348661
22-0.102329-0.86830.194061
23-0.109592-0.92990.177761
24-0.061731-0.52380.301011
250.0189530.16080.436341
26-0.007095-0.06020.47608
270.0126670.10750.457353
28-0.080736-0.68510.24775
29-0.041327-0.35070.36343
300.0500870.4250.336051
310.0151750.12880.448952
32-0.042673-0.36210.359171
33-0.062213-0.52790.299598
340.0064880.05510.478125
35-0.019953-0.16930.433016
36-0.003165-0.02690.489324


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')