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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 computationWed, 29 Dec 2010 13:06:26 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/29/t12936278547fm5kynqhrin1xl.htm/, Retrieved Fri, 03 May 2024 09:11:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=116784, Retrieved Fri, 03 May 2024 09:11:15 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact181
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]
-    D        [(Partial) Autocorrelation Function] [] [2009-11-24 09:55:25] [fef2f8976fa1eef1b54e2cee317fe737]
-    D          [(Partial) Autocorrelation Function] [] [2009-12-18 11:14:21] [fef2f8976fa1eef1b54e2cee317fe737]
- R               [(Partial) Autocorrelation Function] [Paper: ACF] [2010-12-22 20:09:28] [29e492448d11757ae0fad5ef6e7f8e86]
-   PD                [(Partial) Autocorrelation Function] [] [2010-12-29 13:06:26] [e180d4cd19004beeddc12e67012247dc] [Current]
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Dataseries X:
01.303763
01.416094
01.052458
01.312283
01.309429
01.492409
01.026556
01.005406
01.334886
01.393873
01.128092
01.122787
01.213104
01.253528
01.094796
00.912944
01.195130
00.927499
00.965333
01.198078
00.966362
00.973685
00.994801
00.826262
00.688888
00.781307
00.604791
01.086240
00.774026
01.026032
00.676435
00.830525
00.791624
00.752391
00.670202
00.880336
00.914297
00.961042
00.930194
00.867966
00.989160
00.997288
00.798744
00.975379
00.934721
00.973234
00.815300
00.940209
00.794493
00.931340
00.922050
00.784517
00.822098
00.891026
00.807306
00.951441
01.147907
01.172609
01.281051
01.165962
00.978911
01.410951
01.197838
01.288368
01.102253
01.197657
01.299984
01.198611
01.299252
01.097604
01.399770
01.398396
01.401880
01.699717
01.397610
01.500135
01.400136
01.400427
01.341477
01.338580
01.482977
01.163253
01.328468
01.234550
01.484741
01.336579
01.339292
01.405225
01.333491
01.149740




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116784&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116784&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116784&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'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.535555-4.69956e-06
20.1450551.27280.103451
3-0.083213-0.73020.233746
4-0.015594-0.13680.445757
50.1103980.96870.167853
6-0.129527-1.13660.129616
7-0.025165-0.22080.412908
80.0970670.85180.198495
90.100440.88140.190433
10-0.178388-1.56530.060801
110.2607342.28790.012443
12-0.426546-3.74290.000174
130.2647642.32330.011402
14-0.059315-0.52050.30211
15-0.045288-0.39740.346087
160.0933030.81870.207734
17-0.090888-0.79750.213796
180.1279981.12320.132425
19-0.054847-0.48130.31584
20-0.062552-0.54890.292334
210.0596610.52350.301057
22-0.009274-0.08140.467677
230.0180670.15850.437225
24-0.014336-0.12580.450109
25-0.072117-0.63280.264363
260.1002280.87950.190935
27-0.059541-0.52250.301423
280.0243120.21330.415812
29-0.001533-0.01350.494651
30-0.004275-0.03750.485085
310.0593670.52090.301952
32-0.020743-0.1820.428024
33-0.136932-1.20160.116606
340.1122750.98520.163803
35-0.050894-0.44660.328211
360.0604780.53070.29858

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.535555 & -4.6995 & 6e-06 \tabularnewline
2 & 0.145055 & 1.2728 & 0.103451 \tabularnewline
3 & -0.083213 & -0.7302 & 0.233746 \tabularnewline
4 & -0.015594 & -0.1368 & 0.445757 \tabularnewline
5 & 0.110398 & 0.9687 & 0.167853 \tabularnewline
6 & -0.129527 & -1.1366 & 0.129616 \tabularnewline
7 & -0.025165 & -0.2208 & 0.412908 \tabularnewline
8 & 0.097067 & 0.8518 & 0.198495 \tabularnewline
9 & 0.10044 & 0.8814 & 0.190433 \tabularnewline
10 & -0.178388 & -1.5653 & 0.060801 \tabularnewline
11 & 0.260734 & 2.2879 & 0.012443 \tabularnewline
12 & -0.426546 & -3.7429 & 0.000174 \tabularnewline
13 & 0.264764 & 2.3233 & 0.011402 \tabularnewline
14 & -0.059315 & -0.5205 & 0.30211 \tabularnewline
15 & -0.045288 & -0.3974 & 0.346087 \tabularnewline
16 & 0.093303 & 0.8187 & 0.207734 \tabularnewline
17 & -0.090888 & -0.7975 & 0.213796 \tabularnewline
18 & 0.127998 & 1.1232 & 0.132425 \tabularnewline
19 & -0.054847 & -0.4813 & 0.31584 \tabularnewline
20 & -0.062552 & -0.5489 & 0.292334 \tabularnewline
21 & 0.059661 & 0.5235 & 0.301057 \tabularnewline
22 & -0.009274 & -0.0814 & 0.467677 \tabularnewline
23 & 0.018067 & 0.1585 & 0.437225 \tabularnewline
24 & -0.014336 & -0.1258 & 0.450109 \tabularnewline
25 & -0.072117 & -0.6328 & 0.264363 \tabularnewline
26 & 0.100228 & 0.8795 & 0.190935 \tabularnewline
27 & -0.059541 & -0.5225 & 0.301423 \tabularnewline
28 & 0.024312 & 0.2133 & 0.415812 \tabularnewline
29 & -0.001533 & -0.0135 & 0.494651 \tabularnewline
30 & -0.004275 & -0.0375 & 0.485085 \tabularnewline
31 & 0.059367 & 0.5209 & 0.301952 \tabularnewline
32 & -0.020743 & -0.182 & 0.428024 \tabularnewline
33 & -0.136932 & -1.2016 & 0.116606 \tabularnewline
34 & 0.112275 & 0.9852 & 0.163803 \tabularnewline
35 & -0.050894 & -0.4466 & 0.328211 \tabularnewline
36 & 0.060478 & 0.5307 & 0.29858 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116784&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]-0.535555[/C][C]-4.6995[/C][C]6e-06[/C][/ROW]
[ROW][C]2[/C][C]0.145055[/C][C]1.2728[/C][C]0.103451[/C][/ROW]
[ROW][C]3[/C][C]-0.083213[/C][C]-0.7302[/C][C]0.233746[/C][/ROW]
[ROW][C]4[/C][C]-0.015594[/C][C]-0.1368[/C][C]0.445757[/C][/ROW]
[ROW][C]5[/C][C]0.110398[/C][C]0.9687[/C][C]0.167853[/C][/ROW]
[ROW][C]6[/C][C]-0.129527[/C][C]-1.1366[/C][C]0.129616[/C][/ROW]
[ROW][C]7[/C][C]-0.025165[/C][C]-0.2208[/C][C]0.412908[/C][/ROW]
[ROW][C]8[/C][C]0.097067[/C][C]0.8518[/C][C]0.198495[/C][/ROW]
[ROW][C]9[/C][C]0.10044[/C][C]0.8814[/C][C]0.190433[/C][/ROW]
[ROW][C]10[/C][C]-0.178388[/C][C]-1.5653[/C][C]0.060801[/C][/ROW]
[ROW][C]11[/C][C]0.260734[/C][C]2.2879[/C][C]0.012443[/C][/ROW]
[ROW][C]12[/C][C]-0.426546[/C][C]-3.7429[/C][C]0.000174[/C][/ROW]
[ROW][C]13[/C][C]0.264764[/C][C]2.3233[/C][C]0.011402[/C][/ROW]
[ROW][C]14[/C][C]-0.059315[/C][C]-0.5205[/C][C]0.30211[/C][/ROW]
[ROW][C]15[/C][C]-0.045288[/C][C]-0.3974[/C][C]0.346087[/C][/ROW]
[ROW][C]16[/C][C]0.093303[/C][C]0.8187[/C][C]0.207734[/C][/ROW]
[ROW][C]17[/C][C]-0.090888[/C][C]-0.7975[/C][C]0.213796[/C][/ROW]
[ROW][C]18[/C][C]0.127998[/C][C]1.1232[/C][C]0.132425[/C][/ROW]
[ROW][C]19[/C][C]-0.054847[/C][C]-0.4813[/C][C]0.31584[/C][/ROW]
[ROW][C]20[/C][C]-0.062552[/C][C]-0.5489[/C][C]0.292334[/C][/ROW]
[ROW][C]21[/C][C]0.059661[/C][C]0.5235[/C][C]0.301057[/C][/ROW]
[ROW][C]22[/C][C]-0.009274[/C][C]-0.0814[/C][C]0.467677[/C][/ROW]
[ROW][C]23[/C][C]0.018067[/C][C]0.1585[/C][C]0.437225[/C][/ROW]
[ROW][C]24[/C][C]-0.014336[/C][C]-0.1258[/C][C]0.450109[/C][/ROW]
[ROW][C]25[/C][C]-0.072117[/C][C]-0.6328[/C][C]0.264363[/C][/ROW]
[ROW][C]26[/C][C]0.100228[/C][C]0.8795[/C][C]0.190935[/C][/ROW]
[ROW][C]27[/C][C]-0.059541[/C][C]-0.5225[/C][C]0.301423[/C][/ROW]
[ROW][C]28[/C][C]0.024312[/C][C]0.2133[/C][C]0.415812[/C][/ROW]
[ROW][C]29[/C][C]-0.001533[/C][C]-0.0135[/C][C]0.494651[/C][/ROW]
[ROW][C]30[/C][C]-0.004275[/C][C]-0.0375[/C][C]0.485085[/C][/ROW]
[ROW][C]31[/C][C]0.059367[/C][C]0.5209[/C][C]0.301952[/C][/ROW]
[ROW][C]32[/C][C]-0.020743[/C][C]-0.182[/C][C]0.428024[/C][/ROW]
[ROW][C]33[/C][C]-0.136932[/C][C]-1.2016[/C][C]0.116606[/C][/ROW]
[ROW][C]34[/C][C]0.112275[/C][C]0.9852[/C][C]0.163803[/C][/ROW]
[ROW][C]35[/C][C]-0.050894[/C][C]-0.4466[/C][C]0.328211[/C][/ROW]
[ROW][C]36[/C][C]0.060478[/C][C]0.5307[/C][C]0.29858[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116784&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116784&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
1-0.535555-4.69956e-06
20.1450551.27280.103451
3-0.083213-0.73020.233746
4-0.015594-0.13680.445757
50.1103980.96870.167853
6-0.129527-1.13660.129616
7-0.025165-0.22080.412908
80.0970670.85180.198495
90.100440.88140.190433
10-0.178388-1.56530.060801
110.2607342.28790.012443
12-0.426546-3.74290.000174
130.2647642.32330.011402
14-0.059315-0.52050.30211
15-0.045288-0.39740.346087
160.0933030.81870.207734
17-0.090888-0.79750.213796
180.1279981.12320.132425
19-0.054847-0.48130.31584
20-0.062552-0.54890.292334
210.0596610.52350.301057
22-0.009274-0.08140.467677
230.0180670.15850.437225
24-0.014336-0.12580.450109
25-0.072117-0.63280.264363
260.1002280.87950.190935
27-0.059541-0.52250.301423
280.0243120.21330.415812
29-0.001533-0.01350.494651
30-0.004275-0.03750.485085
310.0593670.52090.301952
32-0.020743-0.1820.428024
33-0.136932-1.20160.116606
340.1122750.98520.163803
35-0.050894-0.44660.328211
360.0604780.53070.29858







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.535555-4.69956e-06
2-0.198778-1.74430.042552
3-0.140937-1.23670.109975
4-0.156197-1.37060.087237
50.0362570.31820.375614
6-0.060874-0.53420.297381
7-0.192081-1.68550.04797
8-0.027245-0.23910.405843
90.2302712.02060.023398
10-0.027422-0.24060.40524
110.2689332.35990.010407
12-0.232151-2.03710.022537
13-0.202887-1.78030.039484
14-0.018588-0.16310.43543
15-0.038231-0.33550.36909
16-0.000581-0.00510.497974
170.0160630.1410.444139
180.0304690.26740.394953
19-0.037202-0.32640.372485
20-0.050223-0.44070.330329
210.1787461.56850.060434
220.0032560.02860.48864
230.1775931.55840.061623
24-0.065233-0.57240.284353
25-0.234647-2.0590.021437
26-0.019581-0.17180.432012
27-0.091319-0.80130.212706
280.0542290.47590.317762
290.0724270.63550.263479
300.0424760.37270.355189
310.0688820.60440.273666
320.0089220.07830.468899
33-0.060576-0.53160.298283
34-0.073846-0.6480.259457
350.0355270.31170.378038
360.0335110.29410.384752

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.535555 & -4.6995 & 6e-06 \tabularnewline
2 & -0.198778 & -1.7443 & 0.042552 \tabularnewline
3 & -0.140937 & -1.2367 & 0.109975 \tabularnewline
4 & -0.156197 & -1.3706 & 0.087237 \tabularnewline
5 & 0.036257 & 0.3182 & 0.375614 \tabularnewline
6 & -0.060874 & -0.5342 & 0.297381 \tabularnewline
7 & -0.192081 & -1.6855 & 0.04797 \tabularnewline
8 & -0.027245 & -0.2391 & 0.405843 \tabularnewline
9 & 0.230271 & 2.0206 & 0.023398 \tabularnewline
10 & -0.027422 & -0.2406 & 0.40524 \tabularnewline
11 & 0.268933 & 2.3599 & 0.010407 \tabularnewline
12 & -0.232151 & -2.0371 & 0.022537 \tabularnewline
13 & -0.202887 & -1.7803 & 0.039484 \tabularnewline
14 & -0.018588 & -0.1631 & 0.43543 \tabularnewline
15 & -0.038231 & -0.3355 & 0.36909 \tabularnewline
16 & -0.000581 & -0.0051 & 0.497974 \tabularnewline
17 & 0.016063 & 0.141 & 0.444139 \tabularnewline
18 & 0.030469 & 0.2674 & 0.394953 \tabularnewline
19 & -0.037202 & -0.3264 & 0.372485 \tabularnewline
20 & -0.050223 & -0.4407 & 0.330329 \tabularnewline
21 & 0.178746 & 1.5685 & 0.060434 \tabularnewline
22 & 0.003256 & 0.0286 & 0.48864 \tabularnewline
23 & 0.177593 & 1.5584 & 0.061623 \tabularnewline
24 & -0.065233 & -0.5724 & 0.284353 \tabularnewline
25 & -0.234647 & -2.059 & 0.021437 \tabularnewline
26 & -0.019581 & -0.1718 & 0.432012 \tabularnewline
27 & -0.091319 & -0.8013 & 0.212706 \tabularnewline
28 & 0.054229 & 0.4759 & 0.317762 \tabularnewline
29 & 0.072427 & 0.6355 & 0.263479 \tabularnewline
30 & 0.042476 & 0.3727 & 0.355189 \tabularnewline
31 & 0.068882 & 0.6044 & 0.273666 \tabularnewline
32 & 0.008922 & 0.0783 & 0.468899 \tabularnewline
33 & -0.060576 & -0.5316 & 0.298283 \tabularnewline
34 & -0.073846 & -0.648 & 0.259457 \tabularnewline
35 & 0.035527 & 0.3117 & 0.378038 \tabularnewline
36 & 0.033511 & 0.2941 & 0.384752 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116784&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]-0.535555[/C][C]-4.6995[/C][C]6e-06[/C][/ROW]
[ROW][C]2[/C][C]-0.198778[/C][C]-1.7443[/C][C]0.042552[/C][/ROW]
[ROW][C]3[/C][C]-0.140937[/C][C]-1.2367[/C][C]0.109975[/C][/ROW]
[ROW][C]4[/C][C]-0.156197[/C][C]-1.3706[/C][C]0.087237[/C][/ROW]
[ROW][C]5[/C][C]0.036257[/C][C]0.3182[/C][C]0.375614[/C][/ROW]
[ROW][C]6[/C][C]-0.060874[/C][C]-0.5342[/C][C]0.297381[/C][/ROW]
[ROW][C]7[/C][C]-0.192081[/C][C]-1.6855[/C][C]0.04797[/C][/ROW]
[ROW][C]8[/C][C]-0.027245[/C][C]-0.2391[/C][C]0.405843[/C][/ROW]
[ROW][C]9[/C][C]0.230271[/C][C]2.0206[/C][C]0.023398[/C][/ROW]
[ROW][C]10[/C][C]-0.027422[/C][C]-0.2406[/C][C]0.40524[/C][/ROW]
[ROW][C]11[/C][C]0.268933[/C][C]2.3599[/C][C]0.010407[/C][/ROW]
[ROW][C]12[/C][C]-0.232151[/C][C]-2.0371[/C][C]0.022537[/C][/ROW]
[ROW][C]13[/C][C]-0.202887[/C][C]-1.7803[/C][C]0.039484[/C][/ROW]
[ROW][C]14[/C][C]-0.018588[/C][C]-0.1631[/C][C]0.43543[/C][/ROW]
[ROW][C]15[/C][C]-0.038231[/C][C]-0.3355[/C][C]0.36909[/C][/ROW]
[ROW][C]16[/C][C]-0.000581[/C][C]-0.0051[/C][C]0.497974[/C][/ROW]
[ROW][C]17[/C][C]0.016063[/C][C]0.141[/C][C]0.444139[/C][/ROW]
[ROW][C]18[/C][C]0.030469[/C][C]0.2674[/C][C]0.394953[/C][/ROW]
[ROW][C]19[/C][C]-0.037202[/C][C]-0.3264[/C][C]0.372485[/C][/ROW]
[ROW][C]20[/C][C]-0.050223[/C][C]-0.4407[/C][C]0.330329[/C][/ROW]
[ROW][C]21[/C][C]0.178746[/C][C]1.5685[/C][C]0.060434[/C][/ROW]
[ROW][C]22[/C][C]0.003256[/C][C]0.0286[/C][C]0.48864[/C][/ROW]
[ROW][C]23[/C][C]0.177593[/C][C]1.5584[/C][C]0.061623[/C][/ROW]
[ROW][C]24[/C][C]-0.065233[/C][C]-0.5724[/C][C]0.284353[/C][/ROW]
[ROW][C]25[/C][C]-0.234647[/C][C]-2.059[/C][C]0.021437[/C][/ROW]
[ROW][C]26[/C][C]-0.019581[/C][C]-0.1718[/C][C]0.432012[/C][/ROW]
[ROW][C]27[/C][C]-0.091319[/C][C]-0.8013[/C][C]0.212706[/C][/ROW]
[ROW][C]28[/C][C]0.054229[/C][C]0.4759[/C][C]0.317762[/C][/ROW]
[ROW][C]29[/C][C]0.072427[/C][C]0.6355[/C][C]0.263479[/C][/ROW]
[ROW][C]30[/C][C]0.042476[/C][C]0.3727[/C][C]0.355189[/C][/ROW]
[ROW][C]31[/C][C]0.068882[/C][C]0.6044[/C][C]0.273666[/C][/ROW]
[ROW][C]32[/C][C]0.008922[/C][C]0.0783[/C][C]0.468899[/C][/ROW]
[ROW][C]33[/C][C]-0.060576[/C][C]-0.5316[/C][C]0.298283[/C][/ROW]
[ROW][C]34[/C][C]-0.073846[/C][C]-0.648[/C][C]0.259457[/C][/ROW]
[ROW][C]35[/C][C]0.035527[/C][C]0.3117[/C][C]0.378038[/C][/ROW]
[ROW][C]36[/C][C]0.033511[/C][C]0.2941[/C][C]0.384752[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116784&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116784&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
1-0.535555-4.69956e-06
2-0.198778-1.74430.042552
3-0.140937-1.23670.109975
4-0.156197-1.37060.087237
50.0362570.31820.375614
6-0.060874-0.53420.297381
7-0.192081-1.68550.04797
8-0.027245-0.23910.405843
90.2302712.02060.023398
10-0.027422-0.24060.40524
110.2689332.35990.010407
12-0.232151-2.03710.022537
13-0.202887-1.78030.039484
14-0.018588-0.16310.43543
15-0.038231-0.33550.36909
16-0.000581-0.00510.497974
170.0160630.1410.444139
180.0304690.26740.394953
19-0.037202-0.32640.372485
20-0.050223-0.44070.330329
210.1787461.56850.060434
220.0032560.02860.48864
230.1775931.55840.061623
24-0.065233-0.57240.284353
25-0.234647-2.0590.021437
26-0.019581-0.17180.432012
27-0.091319-0.80130.212706
280.0542290.47590.317762
290.0724270.63550.263479
300.0424760.37270.355189
310.0688820.60440.273666
320.0089220.07830.468899
33-0.060576-0.53160.298283
34-0.073846-0.6480.259457
350.0355270.31170.378038
360.0335110.29410.384752



Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ; par8 = ;
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 (par8 != '') par8 <- as.numeric(par8)
ox <- x
if (par8 == '') {
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
} else {
x <- log(x,base=par8)
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='picts.png')
op <- par(mfrow=c(2,1))
plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')
if (par8=='') {
mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
} else {
mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
}
plot(x,type='l', main=mytitle,xlab='time',ylab='value')
par(op)
dev.off()
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)
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')