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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 computationThu, 18 Dec 2008 09:54:54 -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/18/t1229619315e2a017g9jtij36o.htm/, Retrieved Sun, 12 May 2024 06:22:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=34888, Retrieved Sun, 12 May 2024 06:22:28 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsACF
Estimated Impact184
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]
- R P               [(Partial) Autocorrelation Function] [ACF] [2008-12-18 16:54:54] [962e6c9020896982bc8283b8971710a9] [Current]
-   P                 [(Partial) Autocorrelation Function] [ACF] [2008-12-24 13:04:28] [b28ef2aea2cd58ceb5ad90223572c703]
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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 time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34888&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34888&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34888&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 time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.077212-0.53490.297581
20.0918250.63620.263839
3-0.13891-0.96240.170337
40.0450020.31180.378278
5-0.218826-1.51610.06803
60.0134140.09290.463171
70.0623070.43170.333955
8-0.036507-0.25290.400702
90.1008540.69870.244044
10-0.035118-0.24330.404403
110.3030792.09980.020514
12-0.272631-1.88880.032482
13-0.016473-0.11410.454805
140.0020610.01430.494333
15-0.057194-0.39630.346837
16-0.269854-1.86960.033823
170.0155620.10780.457295
180.0066290.04590.481778
19-0.069555-0.48190.316037
200.1094460.75830.226
21-0.008974-0.06220.475342
220.1544651.07020.144949
23-0.11627-0.80550.21224
240.0123340.08550.466128
25-0.043936-0.30440.38107
260.0021610.0150.494058
27-0.068215-0.47260.319317
280.0589240.40820.342457
290.0395780.27420.392551
30-0.012337-0.08550.466121
310.0913840.63310.264828
320.0620840.43010.334513
330.060390.41840.338763
34-0.108766-0.75350.2274
35-0.054217-0.37560.354425
36-0.056206-0.38940.349349

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.077212 & -0.5349 & 0.297581 \tabularnewline
2 & 0.091825 & 0.6362 & 0.263839 \tabularnewline
3 & -0.13891 & -0.9624 & 0.170337 \tabularnewline
4 & 0.045002 & 0.3118 & 0.378278 \tabularnewline
5 & -0.218826 & -1.5161 & 0.06803 \tabularnewline
6 & 0.013414 & 0.0929 & 0.463171 \tabularnewline
7 & 0.062307 & 0.4317 & 0.333955 \tabularnewline
8 & -0.036507 & -0.2529 & 0.400702 \tabularnewline
9 & 0.100854 & 0.6987 & 0.244044 \tabularnewline
10 & -0.035118 & -0.2433 & 0.404403 \tabularnewline
11 & 0.303079 & 2.0998 & 0.020514 \tabularnewline
12 & -0.272631 & -1.8888 & 0.032482 \tabularnewline
13 & -0.016473 & -0.1141 & 0.454805 \tabularnewline
14 & 0.002061 & 0.0143 & 0.494333 \tabularnewline
15 & -0.057194 & -0.3963 & 0.346837 \tabularnewline
16 & -0.269854 & -1.8696 & 0.033823 \tabularnewline
17 & 0.015562 & 0.1078 & 0.457295 \tabularnewline
18 & 0.006629 & 0.0459 & 0.481778 \tabularnewline
19 & -0.069555 & -0.4819 & 0.316037 \tabularnewline
20 & 0.109446 & 0.7583 & 0.226 \tabularnewline
21 & -0.008974 & -0.0622 & 0.475342 \tabularnewline
22 & 0.154465 & 1.0702 & 0.144949 \tabularnewline
23 & -0.11627 & -0.8055 & 0.21224 \tabularnewline
24 & 0.012334 & 0.0855 & 0.466128 \tabularnewline
25 & -0.043936 & -0.3044 & 0.38107 \tabularnewline
26 & 0.002161 & 0.015 & 0.494058 \tabularnewline
27 & -0.068215 & -0.4726 & 0.319317 \tabularnewline
28 & 0.058924 & 0.4082 & 0.342457 \tabularnewline
29 & 0.039578 & 0.2742 & 0.392551 \tabularnewline
30 & -0.012337 & -0.0855 & 0.466121 \tabularnewline
31 & 0.091384 & 0.6331 & 0.264828 \tabularnewline
32 & 0.062084 & 0.4301 & 0.334513 \tabularnewline
33 & 0.06039 & 0.4184 & 0.338763 \tabularnewline
34 & -0.108766 & -0.7535 & 0.2274 \tabularnewline
35 & -0.054217 & -0.3756 & 0.354425 \tabularnewline
36 & -0.056206 & -0.3894 & 0.349349 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34888&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]-0.077212[/C][C]-0.5349[/C][C]0.297581[/C][/ROW]
[ROW][C]2[/C][C]0.091825[/C][C]0.6362[/C][C]0.263839[/C][/ROW]
[ROW][C]3[/C][C]-0.13891[/C][C]-0.9624[/C][C]0.170337[/C][/ROW]
[ROW][C]4[/C][C]0.045002[/C][C]0.3118[/C][C]0.378278[/C][/ROW]
[ROW][C]5[/C][C]-0.218826[/C][C]-1.5161[/C][C]0.06803[/C][/ROW]
[ROW][C]6[/C][C]0.013414[/C][C]0.0929[/C][C]0.463171[/C][/ROW]
[ROW][C]7[/C][C]0.062307[/C][C]0.4317[/C][C]0.333955[/C][/ROW]
[ROW][C]8[/C][C]-0.036507[/C][C]-0.2529[/C][C]0.400702[/C][/ROW]
[ROW][C]9[/C][C]0.100854[/C][C]0.6987[/C][C]0.244044[/C][/ROW]
[ROW][C]10[/C][C]-0.035118[/C][C]-0.2433[/C][C]0.404403[/C][/ROW]
[ROW][C]11[/C][C]0.303079[/C][C]2.0998[/C][C]0.020514[/C][/ROW]
[ROW][C]12[/C][C]-0.272631[/C][C]-1.8888[/C][C]0.032482[/C][/ROW]
[ROW][C]13[/C][C]-0.016473[/C][C]-0.1141[/C][C]0.454805[/C][/ROW]
[ROW][C]14[/C][C]0.002061[/C][C]0.0143[/C][C]0.494333[/C][/ROW]
[ROW][C]15[/C][C]-0.057194[/C][C]-0.3963[/C][C]0.346837[/C][/ROW]
[ROW][C]16[/C][C]-0.269854[/C][C]-1.8696[/C][C]0.033823[/C][/ROW]
[ROW][C]17[/C][C]0.015562[/C][C]0.1078[/C][C]0.457295[/C][/ROW]
[ROW][C]18[/C][C]0.006629[/C][C]0.0459[/C][C]0.481778[/C][/ROW]
[ROW][C]19[/C][C]-0.069555[/C][C]-0.4819[/C][C]0.316037[/C][/ROW]
[ROW][C]20[/C][C]0.109446[/C][C]0.7583[/C][C]0.226[/C][/ROW]
[ROW][C]21[/C][C]-0.008974[/C][C]-0.0622[/C][C]0.475342[/C][/ROW]
[ROW][C]22[/C][C]0.154465[/C][C]1.0702[/C][C]0.144949[/C][/ROW]
[ROW][C]23[/C][C]-0.11627[/C][C]-0.8055[/C][C]0.21224[/C][/ROW]
[ROW][C]24[/C][C]0.012334[/C][C]0.0855[/C][C]0.466128[/C][/ROW]
[ROW][C]25[/C][C]-0.043936[/C][C]-0.3044[/C][C]0.38107[/C][/ROW]
[ROW][C]26[/C][C]0.002161[/C][C]0.015[/C][C]0.494058[/C][/ROW]
[ROW][C]27[/C][C]-0.068215[/C][C]-0.4726[/C][C]0.319317[/C][/ROW]
[ROW][C]28[/C][C]0.058924[/C][C]0.4082[/C][C]0.342457[/C][/ROW]
[ROW][C]29[/C][C]0.039578[/C][C]0.2742[/C][C]0.392551[/C][/ROW]
[ROW][C]30[/C][C]-0.012337[/C][C]-0.0855[/C][C]0.466121[/C][/ROW]
[ROW][C]31[/C][C]0.091384[/C][C]0.6331[/C][C]0.264828[/C][/ROW]
[ROW][C]32[/C][C]0.062084[/C][C]0.4301[/C][C]0.334513[/C][/ROW]
[ROW][C]33[/C][C]0.06039[/C][C]0.4184[/C][C]0.338763[/C][/ROW]
[ROW][C]34[/C][C]-0.108766[/C][C]-0.7535[/C][C]0.2274[/C][/ROW]
[ROW][C]35[/C][C]-0.054217[/C][C]-0.3756[/C][C]0.354425[/C][/ROW]
[ROW][C]36[/C][C]-0.056206[/C][C]-0.3894[/C][C]0.349349[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34888&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34888&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
1-0.077212-0.53490.297581
20.0918250.63620.263839
3-0.13891-0.96240.170337
40.0450020.31180.378278
5-0.218826-1.51610.06803
60.0134140.09290.463171
70.0623070.43170.333955
8-0.036507-0.25290.400702
90.1008540.69870.244044
10-0.035118-0.24330.404403
110.3030792.09980.020514
12-0.272631-1.88880.032482
13-0.016473-0.11410.454805
140.0020610.01430.494333
15-0.057194-0.39630.346837
16-0.269854-1.86960.033823
170.0155620.10780.457295
180.0066290.04590.481778
19-0.069555-0.48190.316037
200.1094460.75830.226
21-0.008974-0.06220.475342
220.1544651.07020.144949
23-0.11627-0.80550.21224
240.0123340.08550.466128
25-0.043936-0.30440.38107
260.0021610.0150.494058
27-0.068215-0.47260.319317
280.0589240.40820.342457
290.0395780.27420.392551
30-0.012337-0.08550.466121
310.0913840.63310.264828
320.0620840.43010.334513
330.060390.41840.338763
34-0.108766-0.75350.2274
35-0.054217-0.37560.354425
36-0.056206-0.38940.349349







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.077212-0.53490.297581
20.0863790.59840.276177
3-0.127468-0.88310.190785
40.0203840.14120.444142
5-0.198484-1.37510.087737
6-0.03439-0.23830.406347
70.1038820.71970.237594
8-0.085107-0.58960.279099
90.1016910.70450.242252
10-0.045102-0.31250.378016
110.2913812.01870.024559
12-0.22474-1.5570.063015
13-0.10839-0.7510.228174
140.1727811.19710.11858
15-0.192491-1.33360.094312
16-0.203059-1.40680.082959
17-0.066299-0.45930.324033
18-0.05766-0.39950.345657
19-0.036872-0.25550.399731
20-0.016484-0.11420.454777
21-0.038191-0.26460.396226
220.1091650.75630.226578
230.0434410.3010.382368
24-0.067299-0.46630.32157
25-0.022769-0.15770.437658
260.0986310.68330.24884
270.072620.50310.308588
28-0.145229-1.00620.159688
290.0001740.00120.499522
300.0921670.63860.263075
31-0.066269-0.45910.324108
320.0561480.3890.349497
33-0.02695-0.18670.426335
34-0.073929-0.51220.305432
35-0.032573-0.22570.411207
36-0.085591-0.5930.277986

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.077212 & -0.5349 & 0.297581 \tabularnewline
2 & 0.086379 & 0.5984 & 0.276177 \tabularnewline
3 & -0.127468 & -0.8831 & 0.190785 \tabularnewline
4 & 0.020384 & 0.1412 & 0.444142 \tabularnewline
5 & -0.198484 & -1.3751 & 0.087737 \tabularnewline
6 & -0.03439 & -0.2383 & 0.406347 \tabularnewline
7 & 0.103882 & 0.7197 & 0.237594 \tabularnewline
8 & -0.085107 & -0.5896 & 0.279099 \tabularnewline
9 & 0.101691 & 0.7045 & 0.242252 \tabularnewline
10 & -0.045102 & -0.3125 & 0.378016 \tabularnewline
11 & 0.291381 & 2.0187 & 0.024559 \tabularnewline
12 & -0.22474 & -1.557 & 0.063015 \tabularnewline
13 & -0.10839 & -0.751 & 0.228174 \tabularnewline
14 & 0.172781 & 1.1971 & 0.11858 \tabularnewline
15 & -0.192491 & -1.3336 & 0.094312 \tabularnewline
16 & -0.203059 & -1.4068 & 0.082959 \tabularnewline
17 & -0.066299 & -0.4593 & 0.324033 \tabularnewline
18 & -0.05766 & -0.3995 & 0.345657 \tabularnewline
19 & -0.036872 & -0.2555 & 0.399731 \tabularnewline
20 & -0.016484 & -0.1142 & 0.454777 \tabularnewline
21 & -0.038191 & -0.2646 & 0.396226 \tabularnewline
22 & 0.109165 & 0.7563 & 0.226578 \tabularnewline
23 & 0.043441 & 0.301 & 0.382368 \tabularnewline
24 & -0.067299 & -0.4663 & 0.32157 \tabularnewline
25 & -0.022769 & -0.1577 & 0.437658 \tabularnewline
26 & 0.098631 & 0.6833 & 0.24884 \tabularnewline
27 & 0.07262 & 0.5031 & 0.308588 \tabularnewline
28 & -0.145229 & -1.0062 & 0.159688 \tabularnewline
29 & 0.000174 & 0.0012 & 0.499522 \tabularnewline
30 & 0.092167 & 0.6386 & 0.263075 \tabularnewline
31 & -0.066269 & -0.4591 & 0.324108 \tabularnewline
32 & 0.056148 & 0.389 & 0.349497 \tabularnewline
33 & -0.02695 & -0.1867 & 0.426335 \tabularnewline
34 & -0.073929 & -0.5122 & 0.305432 \tabularnewline
35 & -0.032573 & -0.2257 & 0.411207 \tabularnewline
36 & -0.085591 & -0.593 & 0.277986 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34888&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]-0.077212[/C][C]-0.5349[/C][C]0.297581[/C][/ROW]
[ROW][C]2[/C][C]0.086379[/C][C]0.5984[/C][C]0.276177[/C][/ROW]
[ROW][C]3[/C][C]-0.127468[/C][C]-0.8831[/C][C]0.190785[/C][/ROW]
[ROW][C]4[/C][C]0.020384[/C][C]0.1412[/C][C]0.444142[/C][/ROW]
[ROW][C]5[/C][C]-0.198484[/C][C]-1.3751[/C][C]0.087737[/C][/ROW]
[ROW][C]6[/C][C]-0.03439[/C][C]-0.2383[/C][C]0.406347[/C][/ROW]
[ROW][C]7[/C][C]0.103882[/C][C]0.7197[/C][C]0.237594[/C][/ROW]
[ROW][C]8[/C][C]-0.085107[/C][C]-0.5896[/C][C]0.279099[/C][/ROW]
[ROW][C]9[/C][C]0.101691[/C][C]0.7045[/C][C]0.242252[/C][/ROW]
[ROW][C]10[/C][C]-0.045102[/C][C]-0.3125[/C][C]0.378016[/C][/ROW]
[ROW][C]11[/C][C]0.291381[/C][C]2.0187[/C][C]0.024559[/C][/ROW]
[ROW][C]12[/C][C]-0.22474[/C][C]-1.557[/C][C]0.063015[/C][/ROW]
[ROW][C]13[/C][C]-0.10839[/C][C]-0.751[/C][C]0.228174[/C][/ROW]
[ROW][C]14[/C][C]0.172781[/C][C]1.1971[/C][C]0.11858[/C][/ROW]
[ROW][C]15[/C][C]-0.192491[/C][C]-1.3336[/C][C]0.094312[/C][/ROW]
[ROW][C]16[/C][C]-0.203059[/C][C]-1.4068[/C][C]0.082959[/C][/ROW]
[ROW][C]17[/C][C]-0.066299[/C][C]-0.4593[/C][C]0.324033[/C][/ROW]
[ROW][C]18[/C][C]-0.05766[/C][C]-0.3995[/C][C]0.345657[/C][/ROW]
[ROW][C]19[/C][C]-0.036872[/C][C]-0.2555[/C][C]0.399731[/C][/ROW]
[ROW][C]20[/C][C]-0.016484[/C][C]-0.1142[/C][C]0.454777[/C][/ROW]
[ROW][C]21[/C][C]-0.038191[/C][C]-0.2646[/C][C]0.396226[/C][/ROW]
[ROW][C]22[/C][C]0.109165[/C][C]0.7563[/C][C]0.226578[/C][/ROW]
[ROW][C]23[/C][C]0.043441[/C][C]0.301[/C][C]0.382368[/C][/ROW]
[ROW][C]24[/C][C]-0.067299[/C][C]-0.4663[/C][C]0.32157[/C][/ROW]
[ROW][C]25[/C][C]-0.022769[/C][C]-0.1577[/C][C]0.437658[/C][/ROW]
[ROW][C]26[/C][C]0.098631[/C][C]0.6833[/C][C]0.24884[/C][/ROW]
[ROW][C]27[/C][C]0.07262[/C][C]0.5031[/C][C]0.308588[/C][/ROW]
[ROW][C]28[/C][C]-0.145229[/C][C]-1.0062[/C][C]0.159688[/C][/ROW]
[ROW][C]29[/C][C]0.000174[/C][C]0.0012[/C][C]0.499522[/C][/ROW]
[ROW][C]30[/C][C]0.092167[/C][C]0.6386[/C][C]0.263075[/C][/ROW]
[ROW][C]31[/C][C]-0.066269[/C][C]-0.4591[/C][C]0.324108[/C][/ROW]
[ROW][C]32[/C][C]0.056148[/C][C]0.389[/C][C]0.349497[/C][/ROW]
[ROW][C]33[/C][C]-0.02695[/C][C]-0.1867[/C][C]0.426335[/C][/ROW]
[ROW][C]34[/C][C]-0.073929[/C][C]-0.5122[/C][C]0.305432[/C][/ROW]
[ROW][C]35[/C][C]-0.032573[/C][C]-0.2257[/C][C]0.411207[/C][/ROW]
[ROW][C]36[/C][C]-0.085591[/C][C]-0.593[/C][C]0.277986[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34888&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34888&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
1-0.077212-0.53490.297581
20.0863790.59840.276177
3-0.127468-0.88310.190785
40.0203840.14120.444142
5-0.198484-1.37510.087737
6-0.03439-0.23830.406347
70.1038820.71970.237594
8-0.085107-0.58960.279099
90.1016910.70450.242252
10-0.045102-0.31250.378016
110.2913812.01870.024559
12-0.22474-1.5570.063015
13-0.10839-0.7510.228174
140.1727811.19710.11858
15-0.192491-1.33360.094312
16-0.203059-1.40680.082959
17-0.066299-0.45930.324033
18-0.05766-0.39950.345657
19-0.036872-0.25550.399731
20-0.016484-0.11420.454777
21-0.038191-0.26460.396226
220.1091650.75630.226578
230.0434410.3010.382368
24-0.067299-0.46630.32157
25-0.022769-0.15770.437658
260.0986310.68330.24884
270.072620.50310.308588
28-0.145229-1.00620.159688
290.0001740.00120.499522
300.0921670.63860.263075
31-0.066269-0.45910.324108
320.0561480.3890.349497
33-0.02695-0.18670.426335
34-0.073929-0.51220.305432
35-0.032573-0.22570.411207
36-0.085591-0.5930.277986



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