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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationFri, 27 Nov 2009 06:34:10 -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/27/t1259328912uepikinxrhqgz6l.htm/, Retrieved Sun, 28 Apr 2024 19:06:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60741, Retrieved Sun, 28 Apr 2024 19:06:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact126
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 PD          [(Partial) Autocorrelation Function] [autocorrelation d...] [2009-11-27 13:34:10] [d41d8cd98f00b204e9800998ecf8427e] [Current]
-   P             [(Partial) Autocorrelation Function] [autocorrelation d...] [2009-11-27 13:49:39] [74be16979710d4c4e7c6647856088456]
-   P             [(Partial) Autocorrelation Function] [Autocorrelation d...] [2009-11-27 13:55:44] [74be16979710d4c4e7c6647856088456]
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Dataseries X:
5.4
5.4
5.6
5.7
5.8
5.8
5.8
5.9
6.1
6.4
6.4
6.3
6.2
6.2
6.3
6.4
6.5
6.6
6.6
6.6
6.8
7
7.2
7.3
7.5
7.6
7.6
7.7
7.7
7.7
7.7
7.6
7.7
7.9
7.9
7.9
7.8
7.6
7.4
7
7
7.2
7.5
7.8
7.8
7.7
7.6
7.5
7.5
7.5
7.5
7.6
7.9
7.6
7.5
7.5
7.6
7.7
7.9
7.9




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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 & 0 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60741&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]0 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=60741&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60741&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 time0 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.431483.31430.000787
20.0407420.31290.377714
3-0.228419-1.75450.042267
4-0.325768-2.50230.007566
5-0.17268-1.32640.094913
60.0283110.21750.414299
70.1139850.87550.192417
80.2251391.72930.04449
90.1780231.36740.08834
100.0304410.23380.407967
11-0.069238-0.53180.298422
12-0.160326-1.23150.111513
13-0.131146-1.00740.158939
14-0.00383-0.02940.488315
150.028990.22270.412279
160.065450.50270.308513
17-0.007438-0.05710.477316
180.0363020.27880.390671
190.042040.32290.373951
200.0048250.03710.485282
21-0.072722-0.55860.289277
22-0.057084-0.43850.331324
23-0.053676-0.41230.340811
24-0.017216-0.13220.447624
250.0536070.41180.341004
260.0262920.2020.420323
270.0442610.340.367542
280.0034060.02620.489609
29-0.147816-1.13540.1304
30-0.200902-1.54320.06407
31-0.145951-1.12110.1334
32-0.075129-0.57710.283043
330.0201550.15480.438749
340.1216990.93480.176853
350.0550720.4230.33691
36-0.020145-0.15470.438778

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.43148 & 3.3143 & 0.000787 \tabularnewline
2 & 0.040742 & 0.3129 & 0.377714 \tabularnewline
3 & -0.228419 & -1.7545 & 0.042267 \tabularnewline
4 & -0.325768 & -2.5023 & 0.007566 \tabularnewline
5 & -0.17268 & -1.3264 & 0.094913 \tabularnewline
6 & 0.028311 & 0.2175 & 0.414299 \tabularnewline
7 & 0.113985 & 0.8755 & 0.192417 \tabularnewline
8 & 0.225139 & 1.7293 & 0.04449 \tabularnewline
9 & 0.178023 & 1.3674 & 0.08834 \tabularnewline
10 & 0.030441 & 0.2338 & 0.407967 \tabularnewline
11 & -0.069238 & -0.5318 & 0.298422 \tabularnewline
12 & -0.160326 & -1.2315 & 0.111513 \tabularnewline
13 & -0.131146 & -1.0074 & 0.158939 \tabularnewline
14 & -0.00383 & -0.0294 & 0.488315 \tabularnewline
15 & 0.02899 & 0.2227 & 0.412279 \tabularnewline
16 & 0.06545 & 0.5027 & 0.308513 \tabularnewline
17 & -0.007438 & -0.0571 & 0.477316 \tabularnewline
18 & 0.036302 & 0.2788 & 0.390671 \tabularnewline
19 & 0.04204 & 0.3229 & 0.373951 \tabularnewline
20 & 0.004825 & 0.0371 & 0.485282 \tabularnewline
21 & -0.072722 & -0.5586 & 0.289277 \tabularnewline
22 & -0.057084 & -0.4385 & 0.331324 \tabularnewline
23 & -0.053676 & -0.4123 & 0.340811 \tabularnewline
24 & -0.017216 & -0.1322 & 0.447624 \tabularnewline
25 & 0.053607 & 0.4118 & 0.341004 \tabularnewline
26 & 0.026292 & 0.202 & 0.420323 \tabularnewline
27 & 0.044261 & 0.34 & 0.367542 \tabularnewline
28 & 0.003406 & 0.0262 & 0.489609 \tabularnewline
29 & -0.147816 & -1.1354 & 0.1304 \tabularnewline
30 & -0.200902 & -1.5432 & 0.06407 \tabularnewline
31 & -0.145951 & -1.1211 & 0.1334 \tabularnewline
32 & -0.075129 & -0.5771 & 0.283043 \tabularnewline
33 & 0.020155 & 0.1548 & 0.438749 \tabularnewline
34 & 0.121699 & 0.9348 & 0.176853 \tabularnewline
35 & 0.055072 & 0.423 & 0.33691 \tabularnewline
36 & -0.020145 & -0.1547 & 0.438778 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60741&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]0.43148[/C][C]3.3143[/C][C]0.000787[/C][/ROW]
[ROW][C]2[/C][C]0.040742[/C][C]0.3129[/C][C]0.377714[/C][/ROW]
[ROW][C]3[/C][C]-0.228419[/C][C]-1.7545[/C][C]0.042267[/C][/ROW]
[ROW][C]4[/C][C]-0.325768[/C][C]-2.5023[/C][C]0.007566[/C][/ROW]
[ROW][C]5[/C][C]-0.17268[/C][C]-1.3264[/C][C]0.094913[/C][/ROW]
[ROW][C]6[/C][C]0.028311[/C][C]0.2175[/C][C]0.414299[/C][/ROW]
[ROW][C]7[/C][C]0.113985[/C][C]0.8755[/C][C]0.192417[/C][/ROW]
[ROW][C]8[/C][C]0.225139[/C][C]1.7293[/C][C]0.04449[/C][/ROW]
[ROW][C]9[/C][C]0.178023[/C][C]1.3674[/C][C]0.08834[/C][/ROW]
[ROW][C]10[/C][C]0.030441[/C][C]0.2338[/C][C]0.407967[/C][/ROW]
[ROW][C]11[/C][C]-0.069238[/C][C]-0.5318[/C][C]0.298422[/C][/ROW]
[ROW][C]12[/C][C]-0.160326[/C][C]-1.2315[/C][C]0.111513[/C][/ROW]
[ROW][C]13[/C][C]-0.131146[/C][C]-1.0074[/C][C]0.158939[/C][/ROW]
[ROW][C]14[/C][C]-0.00383[/C][C]-0.0294[/C][C]0.488315[/C][/ROW]
[ROW][C]15[/C][C]0.02899[/C][C]0.2227[/C][C]0.412279[/C][/ROW]
[ROW][C]16[/C][C]0.06545[/C][C]0.5027[/C][C]0.308513[/C][/ROW]
[ROW][C]17[/C][C]-0.007438[/C][C]-0.0571[/C][C]0.477316[/C][/ROW]
[ROW][C]18[/C][C]0.036302[/C][C]0.2788[/C][C]0.390671[/C][/ROW]
[ROW][C]19[/C][C]0.04204[/C][C]0.3229[/C][C]0.373951[/C][/ROW]
[ROW][C]20[/C][C]0.004825[/C][C]0.0371[/C][C]0.485282[/C][/ROW]
[ROW][C]21[/C][C]-0.072722[/C][C]-0.5586[/C][C]0.289277[/C][/ROW]
[ROW][C]22[/C][C]-0.057084[/C][C]-0.4385[/C][C]0.331324[/C][/ROW]
[ROW][C]23[/C][C]-0.053676[/C][C]-0.4123[/C][C]0.340811[/C][/ROW]
[ROW][C]24[/C][C]-0.017216[/C][C]-0.1322[/C][C]0.447624[/C][/ROW]
[ROW][C]25[/C][C]0.053607[/C][C]0.4118[/C][C]0.341004[/C][/ROW]
[ROW][C]26[/C][C]0.026292[/C][C]0.202[/C][C]0.420323[/C][/ROW]
[ROW][C]27[/C][C]0.044261[/C][C]0.34[/C][C]0.367542[/C][/ROW]
[ROW][C]28[/C][C]0.003406[/C][C]0.0262[/C][C]0.489609[/C][/ROW]
[ROW][C]29[/C][C]-0.147816[/C][C]-1.1354[/C][C]0.1304[/C][/ROW]
[ROW][C]30[/C][C]-0.200902[/C][C]-1.5432[/C][C]0.06407[/C][/ROW]
[ROW][C]31[/C][C]-0.145951[/C][C]-1.1211[/C][C]0.1334[/C][/ROW]
[ROW][C]32[/C][C]-0.075129[/C][C]-0.5771[/C][C]0.283043[/C][/ROW]
[ROW][C]33[/C][C]0.020155[/C][C]0.1548[/C][C]0.438749[/C][/ROW]
[ROW][C]34[/C][C]0.121699[/C][C]0.9348[/C][C]0.176853[/C][/ROW]
[ROW][C]35[/C][C]0.055072[/C][C]0.423[/C][C]0.33691[/C][/ROW]
[ROW][C]36[/C][C]-0.020145[/C][C]-0.1547[/C][C]0.438778[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60741&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60741&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
10.431483.31430.000787
20.0407420.31290.377714
3-0.228419-1.75450.042267
4-0.325768-2.50230.007566
5-0.17268-1.32640.094913
60.0283110.21750.414299
70.1139850.87550.192417
80.2251391.72930.04449
90.1780231.36740.08834
100.0304410.23380.407967
11-0.069238-0.53180.298422
12-0.160326-1.23150.111513
13-0.131146-1.00740.158939
14-0.00383-0.02940.488315
150.028990.22270.412279
160.065450.50270.308513
17-0.007438-0.05710.477316
180.0363020.27880.390671
190.042040.32290.373951
200.0048250.03710.485282
21-0.072722-0.55860.289277
22-0.057084-0.43850.331324
23-0.053676-0.41230.340811
24-0.017216-0.13220.447624
250.0536070.41180.341004
260.0262920.2020.420323
270.0442610.340.367542
280.0034060.02620.489609
29-0.147816-1.13540.1304
30-0.200902-1.54320.06407
31-0.145951-1.12110.1334
32-0.075129-0.57710.283043
330.0201550.15480.438749
340.1216990.93480.176853
350.0550720.4230.33691
36-0.020145-0.15470.438778







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.431483.31430.000787
2-0.178704-1.37270.087528
3-0.218361-1.67730.049391
4-0.161989-1.24430.109162
50.0362770.27870.390743
60.0549780.42230.337172
7-0.022316-0.17140.432243
80.1448541.11260.135187
90.0453090.3480.36453
10-0.031412-0.24130.405089
110.0014890.01140.495456
12-0.050899-0.3910.348616
13-0.000469-0.00360.498568
140.0355450.2730.392893
15-0.059529-0.45720.324585
16-0.002706-0.02080.491745
17-0.097331-0.74760.228832
180.1215310.93350.177184
190.017230.13230.44758
20-0.023929-0.18380.4274
21-0.067157-0.51580.303947
220.0323550.24850.402295
23-0.017514-0.13450.446723
24-0.034863-0.26780.394898
250.0568980.4370.331838
26-0.041719-0.32040.37488
270.0288170.22130.412794
28-0.037405-0.28730.38744
29-0.165569-1.27180.104225
30-0.089109-0.68450.248182
310.0009780.00750.497015
32-0.061567-0.47290.319013
33-0.069241-0.53190.298413
340.0430050.33030.371161
35-0.041566-0.31930.375324
36-0.063601-0.48850.313492

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.43148 & 3.3143 & 0.000787 \tabularnewline
2 & -0.178704 & -1.3727 & 0.087528 \tabularnewline
3 & -0.218361 & -1.6773 & 0.049391 \tabularnewline
4 & -0.161989 & -1.2443 & 0.109162 \tabularnewline
5 & 0.036277 & 0.2787 & 0.390743 \tabularnewline
6 & 0.054978 & 0.4223 & 0.337172 \tabularnewline
7 & -0.022316 & -0.1714 & 0.432243 \tabularnewline
8 & 0.144854 & 1.1126 & 0.135187 \tabularnewline
9 & 0.045309 & 0.348 & 0.36453 \tabularnewline
10 & -0.031412 & -0.2413 & 0.405089 \tabularnewline
11 & 0.001489 & 0.0114 & 0.495456 \tabularnewline
12 & -0.050899 & -0.391 & 0.348616 \tabularnewline
13 & -0.000469 & -0.0036 & 0.498568 \tabularnewline
14 & 0.035545 & 0.273 & 0.392893 \tabularnewline
15 & -0.059529 & -0.4572 & 0.324585 \tabularnewline
16 & -0.002706 & -0.0208 & 0.491745 \tabularnewline
17 & -0.097331 & -0.7476 & 0.228832 \tabularnewline
18 & 0.121531 & 0.9335 & 0.177184 \tabularnewline
19 & 0.01723 & 0.1323 & 0.44758 \tabularnewline
20 & -0.023929 & -0.1838 & 0.4274 \tabularnewline
21 & -0.067157 & -0.5158 & 0.303947 \tabularnewline
22 & 0.032355 & 0.2485 & 0.402295 \tabularnewline
23 & -0.017514 & -0.1345 & 0.446723 \tabularnewline
24 & -0.034863 & -0.2678 & 0.394898 \tabularnewline
25 & 0.056898 & 0.437 & 0.331838 \tabularnewline
26 & -0.041719 & -0.3204 & 0.37488 \tabularnewline
27 & 0.028817 & 0.2213 & 0.412794 \tabularnewline
28 & -0.037405 & -0.2873 & 0.38744 \tabularnewline
29 & -0.165569 & -1.2718 & 0.104225 \tabularnewline
30 & -0.089109 & -0.6845 & 0.248182 \tabularnewline
31 & 0.000978 & 0.0075 & 0.497015 \tabularnewline
32 & -0.061567 & -0.4729 & 0.319013 \tabularnewline
33 & -0.069241 & -0.5319 & 0.298413 \tabularnewline
34 & 0.043005 & 0.3303 & 0.371161 \tabularnewline
35 & -0.041566 & -0.3193 & 0.375324 \tabularnewline
36 & -0.063601 & -0.4885 & 0.313492 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60741&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]0.43148[/C][C]3.3143[/C][C]0.000787[/C][/ROW]
[ROW][C]2[/C][C]-0.178704[/C][C]-1.3727[/C][C]0.087528[/C][/ROW]
[ROW][C]3[/C][C]-0.218361[/C][C]-1.6773[/C][C]0.049391[/C][/ROW]
[ROW][C]4[/C][C]-0.161989[/C][C]-1.2443[/C][C]0.109162[/C][/ROW]
[ROW][C]5[/C][C]0.036277[/C][C]0.2787[/C][C]0.390743[/C][/ROW]
[ROW][C]6[/C][C]0.054978[/C][C]0.4223[/C][C]0.337172[/C][/ROW]
[ROW][C]7[/C][C]-0.022316[/C][C]-0.1714[/C][C]0.432243[/C][/ROW]
[ROW][C]8[/C][C]0.144854[/C][C]1.1126[/C][C]0.135187[/C][/ROW]
[ROW][C]9[/C][C]0.045309[/C][C]0.348[/C][C]0.36453[/C][/ROW]
[ROW][C]10[/C][C]-0.031412[/C][C]-0.2413[/C][C]0.405089[/C][/ROW]
[ROW][C]11[/C][C]0.001489[/C][C]0.0114[/C][C]0.495456[/C][/ROW]
[ROW][C]12[/C][C]-0.050899[/C][C]-0.391[/C][C]0.348616[/C][/ROW]
[ROW][C]13[/C][C]-0.000469[/C][C]-0.0036[/C][C]0.498568[/C][/ROW]
[ROW][C]14[/C][C]0.035545[/C][C]0.273[/C][C]0.392893[/C][/ROW]
[ROW][C]15[/C][C]-0.059529[/C][C]-0.4572[/C][C]0.324585[/C][/ROW]
[ROW][C]16[/C][C]-0.002706[/C][C]-0.0208[/C][C]0.491745[/C][/ROW]
[ROW][C]17[/C][C]-0.097331[/C][C]-0.7476[/C][C]0.228832[/C][/ROW]
[ROW][C]18[/C][C]0.121531[/C][C]0.9335[/C][C]0.177184[/C][/ROW]
[ROW][C]19[/C][C]0.01723[/C][C]0.1323[/C][C]0.44758[/C][/ROW]
[ROW][C]20[/C][C]-0.023929[/C][C]-0.1838[/C][C]0.4274[/C][/ROW]
[ROW][C]21[/C][C]-0.067157[/C][C]-0.5158[/C][C]0.303947[/C][/ROW]
[ROW][C]22[/C][C]0.032355[/C][C]0.2485[/C][C]0.402295[/C][/ROW]
[ROW][C]23[/C][C]-0.017514[/C][C]-0.1345[/C][C]0.446723[/C][/ROW]
[ROW][C]24[/C][C]-0.034863[/C][C]-0.2678[/C][C]0.394898[/C][/ROW]
[ROW][C]25[/C][C]0.056898[/C][C]0.437[/C][C]0.331838[/C][/ROW]
[ROW][C]26[/C][C]-0.041719[/C][C]-0.3204[/C][C]0.37488[/C][/ROW]
[ROW][C]27[/C][C]0.028817[/C][C]0.2213[/C][C]0.412794[/C][/ROW]
[ROW][C]28[/C][C]-0.037405[/C][C]-0.2873[/C][C]0.38744[/C][/ROW]
[ROW][C]29[/C][C]-0.165569[/C][C]-1.2718[/C][C]0.104225[/C][/ROW]
[ROW][C]30[/C][C]-0.089109[/C][C]-0.6845[/C][C]0.248182[/C][/ROW]
[ROW][C]31[/C][C]0.000978[/C][C]0.0075[/C][C]0.497015[/C][/ROW]
[ROW][C]32[/C][C]-0.061567[/C][C]-0.4729[/C][C]0.319013[/C][/ROW]
[ROW][C]33[/C][C]-0.069241[/C][C]-0.5319[/C][C]0.298413[/C][/ROW]
[ROW][C]34[/C][C]0.043005[/C][C]0.3303[/C][C]0.371161[/C][/ROW]
[ROW][C]35[/C][C]-0.041566[/C][C]-0.3193[/C][C]0.375324[/C][/ROW]
[ROW][C]36[/C][C]-0.063601[/C][C]-0.4885[/C][C]0.313492[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60741&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60741&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
10.431483.31430.000787
2-0.178704-1.37270.087528
3-0.218361-1.67730.049391
4-0.161989-1.24430.109162
50.0362770.27870.390743
60.0549780.42230.337172
7-0.022316-0.17140.432243
80.1448541.11260.135187
90.0453090.3480.36453
10-0.031412-0.24130.405089
110.0014890.01140.495456
12-0.050899-0.3910.348616
13-0.000469-0.00360.498568
140.0355450.2730.392893
15-0.059529-0.45720.324585
16-0.002706-0.02080.491745
17-0.097331-0.74760.228832
180.1215310.93350.177184
190.017230.13230.44758
20-0.023929-0.18380.4274
21-0.067157-0.51580.303947
220.0323550.24850.402295
23-0.017514-0.13450.446723
24-0.034863-0.26780.394898
250.0568980.4370.331838
26-0.041719-0.32040.37488
270.0288170.22130.412794
28-0.037405-0.28730.38744
29-0.165569-1.27180.104225
30-0.089109-0.68450.248182
310.0009780.00750.497015
32-0.061567-0.47290.319013
33-0.069241-0.53190.298413
340.0430050.33030.371161
35-0.041566-0.31930.375324
36-0.063601-0.48850.313492



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