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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 computationFri, 04 Dec 2009 07:08:10 -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/Dec/04/t1259935762eo7f138smnsbx4k.htm/, Retrieved Sat, 27 Apr 2024 15:00:29 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63559, Retrieved Sat, 27 Apr 2024 15:00:29 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact133
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]
- R  D        [(Partial) Autocorrelation Function] [ACF Link 2] [2009-11-25 18:57:31] [1f74ef2f756548f1f3a7b6136ea56d7f]
-    D          [(Partial) Autocorrelation Function] [ACF d=1 D=0] [2009-12-02 19:11:03] [1f74ef2f756548f1f3a7b6136ea56d7f]
-   PD              [(Partial) Autocorrelation Function] [WS9 ACF : d=2, D=...] [2009-12-04 14:08:10] [ac4f1d4b47349b2602192853b2bc5b72] [Current]
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Dataseries X:
9.3
9.3
8.7
8.2
8.3
8.5
8.6
8.5
8.2
8.1
7.9
8.6
8.7
8.7
8.5
8.4
8.5
8.7
8.7
8.6
8.5
8.3
8
8.2
8.1
8.1
8
7.9
7.9
8
8
7.9
8
7.7
7.2
7.5
7.3
7
7
7
7.2
7.3
7.1
6.8
6.4
6.1
6.5
7.7
7.9
7.5
6.9
6.6
6.9
7.7
8
8
7.7
7.3
7.4
8.1
8.3




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=63559&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=63559&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63559&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
1-0.033229-0.25520.399714
2-0.29232-2.24530.014253
3-0.294222-2.260.013765
4-0.248659-1.910.0305
50.0736370.56560.2869
60.4274373.28320.000864
70.1607831.2350.110864
8-0.086625-0.66540.254201
9-0.211438-1.62410.054844
10-0.212132-1.62940.054276
11-0.058233-0.44730.328151
120.4847563.72350.000221
13-0.125582-0.96460.169338
14-0.083167-0.63880.262706
150.0153260.11770.453343
16-0.069883-0.53680.296719
17-0.011587-0.0890.464691
180.1238570.95140.17265
19-0.000105-8e-040.49968
20-0.056264-0.43220.333595
21-0.003652-0.02810.488858
22-0.074723-0.5740.28409
23-0.005793-0.04450.482329
240.2932952.25280.014001
25-0.190628-1.46420.074218
26-0.060629-0.46570.321572
270.0047560.03650.485491
28-0.040929-0.31440.377171
290.0443970.3410.367151
300.1015640.78010.219218
310.0490280.37660.353915
32-0.080776-0.62040.268676
33-0.166104-1.27590.103501
340.0047860.03680.485399
350.0758140.58230.281278
360.2463871.89250.031664

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.033229 & -0.2552 & 0.399714 \tabularnewline
2 & -0.29232 & -2.2453 & 0.014253 \tabularnewline
3 & -0.294222 & -2.26 & 0.013765 \tabularnewline
4 & -0.248659 & -1.91 & 0.0305 \tabularnewline
5 & 0.073637 & 0.5656 & 0.2869 \tabularnewline
6 & 0.427437 & 3.2832 & 0.000864 \tabularnewline
7 & 0.160783 & 1.235 & 0.110864 \tabularnewline
8 & -0.086625 & -0.6654 & 0.254201 \tabularnewline
9 & -0.211438 & -1.6241 & 0.054844 \tabularnewline
10 & -0.212132 & -1.6294 & 0.054276 \tabularnewline
11 & -0.058233 & -0.4473 & 0.328151 \tabularnewline
12 & 0.484756 & 3.7235 & 0.000221 \tabularnewline
13 & -0.125582 & -0.9646 & 0.169338 \tabularnewline
14 & -0.083167 & -0.6388 & 0.262706 \tabularnewline
15 & 0.015326 & 0.1177 & 0.453343 \tabularnewline
16 & -0.069883 & -0.5368 & 0.296719 \tabularnewline
17 & -0.011587 & -0.089 & 0.464691 \tabularnewline
18 & 0.123857 & 0.9514 & 0.17265 \tabularnewline
19 & -0.000105 & -8e-04 & 0.49968 \tabularnewline
20 & -0.056264 & -0.4322 & 0.333595 \tabularnewline
21 & -0.003652 & -0.0281 & 0.488858 \tabularnewline
22 & -0.074723 & -0.574 & 0.28409 \tabularnewline
23 & -0.005793 & -0.0445 & 0.482329 \tabularnewline
24 & 0.293295 & 2.2528 & 0.014001 \tabularnewline
25 & -0.190628 & -1.4642 & 0.074218 \tabularnewline
26 & -0.060629 & -0.4657 & 0.321572 \tabularnewline
27 & 0.004756 & 0.0365 & 0.485491 \tabularnewline
28 & -0.040929 & -0.3144 & 0.377171 \tabularnewline
29 & 0.044397 & 0.341 & 0.367151 \tabularnewline
30 & 0.101564 & 0.7801 & 0.219218 \tabularnewline
31 & 0.049028 & 0.3766 & 0.353915 \tabularnewline
32 & -0.080776 & -0.6204 & 0.268676 \tabularnewline
33 & -0.166104 & -1.2759 & 0.103501 \tabularnewline
34 & 0.004786 & 0.0368 & 0.485399 \tabularnewline
35 & 0.075814 & 0.5823 & 0.281278 \tabularnewline
36 & 0.246387 & 1.8925 & 0.031664 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63559&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]-0.033229[/C][C]-0.2552[/C][C]0.399714[/C][/ROW]
[ROW][C]2[/C][C]-0.29232[/C][C]-2.2453[/C][C]0.014253[/C][/ROW]
[ROW][C]3[/C][C]-0.294222[/C][C]-2.26[/C][C]0.013765[/C][/ROW]
[ROW][C]4[/C][C]-0.248659[/C][C]-1.91[/C][C]0.0305[/C][/ROW]
[ROW][C]5[/C][C]0.073637[/C][C]0.5656[/C][C]0.2869[/C][/ROW]
[ROW][C]6[/C][C]0.427437[/C][C]3.2832[/C][C]0.000864[/C][/ROW]
[ROW][C]7[/C][C]0.160783[/C][C]1.235[/C][C]0.110864[/C][/ROW]
[ROW][C]8[/C][C]-0.086625[/C][C]-0.6654[/C][C]0.254201[/C][/ROW]
[ROW][C]9[/C][C]-0.211438[/C][C]-1.6241[/C][C]0.054844[/C][/ROW]
[ROW][C]10[/C][C]-0.212132[/C][C]-1.6294[/C][C]0.054276[/C][/ROW]
[ROW][C]11[/C][C]-0.058233[/C][C]-0.4473[/C][C]0.328151[/C][/ROW]
[ROW][C]12[/C][C]0.484756[/C][C]3.7235[/C][C]0.000221[/C][/ROW]
[ROW][C]13[/C][C]-0.125582[/C][C]-0.9646[/C][C]0.169338[/C][/ROW]
[ROW][C]14[/C][C]-0.083167[/C][C]-0.6388[/C][C]0.262706[/C][/ROW]
[ROW][C]15[/C][C]0.015326[/C][C]0.1177[/C][C]0.453343[/C][/ROW]
[ROW][C]16[/C][C]-0.069883[/C][C]-0.5368[/C][C]0.296719[/C][/ROW]
[ROW][C]17[/C][C]-0.011587[/C][C]-0.089[/C][C]0.464691[/C][/ROW]
[ROW][C]18[/C][C]0.123857[/C][C]0.9514[/C][C]0.17265[/C][/ROW]
[ROW][C]19[/C][C]-0.000105[/C][C]-8e-04[/C][C]0.49968[/C][/ROW]
[ROW][C]20[/C][C]-0.056264[/C][C]-0.4322[/C][C]0.333595[/C][/ROW]
[ROW][C]21[/C][C]-0.003652[/C][C]-0.0281[/C][C]0.488858[/C][/ROW]
[ROW][C]22[/C][C]-0.074723[/C][C]-0.574[/C][C]0.28409[/C][/ROW]
[ROW][C]23[/C][C]-0.005793[/C][C]-0.0445[/C][C]0.482329[/C][/ROW]
[ROW][C]24[/C][C]0.293295[/C][C]2.2528[/C][C]0.014001[/C][/ROW]
[ROW][C]25[/C][C]-0.190628[/C][C]-1.4642[/C][C]0.074218[/C][/ROW]
[ROW][C]26[/C][C]-0.060629[/C][C]-0.4657[/C][C]0.321572[/C][/ROW]
[ROW][C]27[/C][C]0.004756[/C][C]0.0365[/C][C]0.485491[/C][/ROW]
[ROW][C]28[/C][C]-0.040929[/C][C]-0.3144[/C][C]0.377171[/C][/ROW]
[ROW][C]29[/C][C]0.044397[/C][C]0.341[/C][C]0.367151[/C][/ROW]
[ROW][C]30[/C][C]0.101564[/C][C]0.7801[/C][C]0.219218[/C][/ROW]
[ROW][C]31[/C][C]0.049028[/C][C]0.3766[/C][C]0.353915[/C][/ROW]
[ROW][C]32[/C][C]-0.080776[/C][C]-0.6204[/C][C]0.268676[/C][/ROW]
[ROW][C]33[/C][C]-0.166104[/C][C]-1.2759[/C][C]0.103501[/C][/ROW]
[ROW][C]34[/C][C]0.004786[/C][C]0.0368[/C][C]0.485399[/C][/ROW]
[ROW][C]35[/C][C]0.075814[/C][C]0.5823[/C][C]0.281278[/C][/ROW]
[ROW][C]36[/C][C]0.246387[/C][C]1.8925[/C][C]0.031664[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63559&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63559&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
1-0.033229-0.25520.399714
2-0.29232-2.24530.014253
3-0.294222-2.260.013765
4-0.248659-1.910.0305
50.0736370.56560.2869
60.4274373.28320.000864
70.1607831.2350.110864
8-0.086625-0.66540.254201
9-0.211438-1.62410.054844
10-0.212132-1.62940.054276
11-0.058233-0.44730.328151
120.4847563.72350.000221
13-0.125582-0.96460.169338
14-0.083167-0.63880.262706
150.0153260.11770.453343
16-0.069883-0.53680.296719
17-0.011587-0.0890.464691
180.1238570.95140.17265
19-0.000105-8e-040.49968
20-0.056264-0.43220.333595
21-0.003652-0.02810.488858
22-0.074723-0.5740.28409
23-0.005793-0.04450.482329
240.2932952.25280.014001
25-0.190628-1.46420.074218
26-0.060629-0.46570.321572
270.0047560.03650.485491
28-0.040929-0.31440.377171
290.0443970.3410.367151
300.1015640.78010.219218
310.0490280.37660.353915
32-0.080776-0.62040.268676
33-0.166104-1.27590.103501
340.0047860.03680.485399
350.0758140.58230.281278
360.2463871.89250.031664







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.033229-0.25520.399714
2-0.293748-2.25630.013885
3-0.346826-2.6640.00497
4-0.489509-3.760.000196
5-0.455758-3.50070.000445
6-0.16403-1.25990.106327
7-0.181669-1.39540.084059
8-0.129459-0.99440.162047
9-0.086851-0.66710.25365
10-0.0793-0.60910.272394
11-0.204344-1.56960.060929
120.3943433.0290.001819
13-0.230836-1.77310.040688
14-0.154901-1.18980.119442
15-0.071386-0.54830.292769
16-0.009682-0.07440.470485
17-0.075537-0.58020.281991
18-0.148249-1.13870.12971
190.0148560.11410.454769
200.0236110.18140.428352
210.1418411.08950.140181
22-0.079856-0.61340.270989
23-0.034559-0.26550.395793
240.167481.28640.101658
250.0672960.51690.303575
260.0668980.51390.304637
27-0.098985-0.76030.225046
280.014970.1150.454423
290.0393820.30250.381667
30-0.062848-0.48270.315533
310.0302490.23230.408536
320.0114350.08780.465155
33-0.230417-1.76990.040958
340.0077980.05990.476218
35-0.063671-0.48910.313303
36-0.041721-0.32050.374873

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.033229 & -0.2552 & 0.399714 \tabularnewline
2 & -0.293748 & -2.2563 & 0.013885 \tabularnewline
3 & -0.346826 & -2.664 & 0.00497 \tabularnewline
4 & -0.489509 & -3.76 & 0.000196 \tabularnewline
5 & -0.455758 & -3.5007 & 0.000445 \tabularnewline
6 & -0.16403 & -1.2599 & 0.106327 \tabularnewline
7 & -0.181669 & -1.3954 & 0.084059 \tabularnewline
8 & -0.129459 & -0.9944 & 0.162047 \tabularnewline
9 & -0.086851 & -0.6671 & 0.25365 \tabularnewline
10 & -0.0793 & -0.6091 & 0.272394 \tabularnewline
11 & -0.204344 & -1.5696 & 0.060929 \tabularnewline
12 & 0.394343 & 3.029 & 0.001819 \tabularnewline
13 & -0.230836 & -1.7731 & 0.040688 \tabularnewline
14 & -0.154901 & -1.1898 & 0.119442 \tabularnewline
15 & -0.071386 & -0.5483 & 0.292769 \tabularnewline
16 & -0.009682 & -0.0744 & 0.470485 \tabularnewline
17 & -0.075537 & -0.5802 & 0.281991 \tabularnewline
18 & -0.148249 & -1.1387 & 0.12971 \tabularnewline
19 & 0.014856 & 0.1141 & 0.454769 \tabularnewline
20 & 0.023611 & 0.1814 & 0.428352 \tabularnewline
21 & 0.141841 & 1.0895 & 0.140181 \tabularnewline
22 & -0.079856 & -0.6134 & 0.270989 \tabularnewline
23 & -0.034559 & -0.2655 & 0.395793 \tabularnewline
24 & 0.16748 & 1.2864 & 0.101658 \tabularnewline
25 & 0.067296 & 0.5169 & 0.303575 \tabularnewline
26 & 0.066898 & 0.5139 & 0.304637 \tabularnewline
27 & -0.098985 & -0.7603 & 0.225046 \tabularnewline
28 & 0.01497 & 0.115 & 0.454423 \tabularnewline
29 & 0.039382 & 0.3025 & 0.381667 \tabularnewline
30 & -0.062848 & -0.4827 & 0.315533 \tabularnewline
31 & 0.030249 & 0.2323 & 0.408536 \tabularnewline
32 & 0.011435 & 0.0878 & 0.465155 \tabularnewline
33 & -0.230417 & -1.7699 & 0.040958 \tabularnewline
34 & 0.007798 & 0.0599 & 0.476218 \tabularnewline
35 & -0.063671 & -0.4891 & 0.313303 \tabularnewline
36 & -0.041721 & -0.3205 & 0.374873 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63559&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]-0.033229[/C][C]-0.2552[/C][C]0.399714[/C][/ROW]
[ROW][C]2[/C][C]-0.293748[/C][C]-2.2563[/C][C]0.013885[/C][/ROW]
[ROW][C]3[/C][C]-0.346826[/C][C]-2.664[/C][C]0.00497[/C][/ROW]
[ROW][C]4[/C][C]-0.489509[/C][C]-3.76[/C][C]0.000196[/C][/ROW]
[ROW][C]5[/C][C]-0.455758[/C][C]-3.5007[/C][C]0.000445[/C][/ROW]
[ROW][C]6[/C][C]-0.16403[/C][C]-1.2599[/C][C]0.106327[/C][/ROW]
[ROW][C]7[/C][C]-0.181669[/C][C]-1.3954[/C][C]0.084059[/C][/ROW]
[ROW][C]8[/C][C]-0.129459[/C][C]-0.9944[/C][C]0.162047[/C][/ROW]
[ROW][C]9[/C][C]-0.086851[/C][C]-0.6671[/C][C]0.25365[/C][/ROW]
[ROW][C]10[/C][C]-0.0793[/C][C]-0.6091[/C][C]0.272394[/C][/ROW]
[ROW][C]11[/C][C]-0.204344[/C][C]-1.5696[/C][C]0.060929[/C][/ROW]
[ROW][C]12[/C][C]0.394343[/C][C]3.029[/C][C]0.001819[/C][/ROW]
[ROW][C]13[/C][C]-0.230836[/C][C]-1.7731[/C][C]0.040688[/C][/ROW]
[ROW][C]14[/C][C]-0.154901[/C][C]-1.1898[/C][C]0.119442[/C][/ROW]
[ROW][C]15[/C][C]-0.071386[/C][C]-0.5483[/C][C]0.292769[/C][/ROW]
[ROW][C]16[/C][C]-0.009682[/C][C]-0.0744[/C][C]0.470485[/C][/ROW]
[ROW][C]17[/C][C]-0.075537[/C][C]-0.5802[/C][C]0.281991[/C][/ROW]
[ROW][C]18[/C][C]-0.148249[/C][C]-1.1387[/C][C]0.12971[/C][/ROW]
[ROW][C]19[/C][C]0.014856[/C][C]0.1141[/C][C]0.454769[/C][/ROW]
[ROW][C]20[/C][C]0.023611[/C][C]0.1814[/C][C]0.428352[/C][/ROW]
[ROW][C]21[/C][C]0.141841[/C][C]1.0895[/C][C]0.140181[/C][/ROW]
[ROW][C]22[/C][C]-0.079856[/C][C]-0.6134[/C][C]0.270989[/C][/ROW]
[ROW][C]23[/C][C]-0.034559[/C][C]-0.2655[/C][C]0.395793[/C][/ROW]
[ROW][C]24[/C][C]0.16748[/C][C]1.2864[/C][C]0.101658[/C][/ROW]
[ROW][C]25[/C][C]0.067296[/C][C]0.5169[/C][C]0.303575[/C][/ROW]
[ROW][C]26[/C][C]0.066898[/C][C]0.5139[/C][C]0.304637[/C][/ROW]
[ROW][C]27[/C][C]-0.098985[/C][C]-0.7603[/C][C]0.225046[/C][/ROW]
[ROW][C]28[/C][C]0.01497[/C][C]0.115[/C][C]0.454423[/C][/ROW]
[ROW][C]29[/C][C]0.039382[/C][C]0.3025[/C][C]0.381667[/C][/ROW]
[ROW][C]30[/C][C]-0.062848[/C][C]-0.4827[/C][C]0.315533[/C][/ROW]
[ROW][C]31[/C][C]0.030249[/C][C]0.2323[/C][C]0.408536[/C][/ROW]
[ROW][C]32[/C][C]0.011435[/C][C]0.0878[/C][C]0.465155[/C][/ROW]
[ROW][C]33[/C][C]-0.230417[/C][C]-1.7699[/C][C]0.040958[/C][/ROW]
[ROW][C]34[/C][C]0.007798[/C][C]0.0599[/C][C]0.476218[/C][/ROW]
[ROW][C]35[/C][C]-0.063671[/C][C]-0.4891[/C][C]0.313303[/C][/ROW]
[ROW][C]36[/C][C]-0.041721[/C][C]-0.3205[/C][C]0.374873[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63559&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63559&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
1-0.033229-0.25520.399714
2-0.293748-2.25630.013885
3-0.346826-2.6640.00497
4-0.489509-3.760.000196
5-0.455758-3.50070.000445
6-0.16403-1.25990.106327
7-0.181669-1.39540.084059
8-0.129459-0.99440.162047
9-0.086851-0.66710.25365
10-0.0793-0.60910.272394
11-0.204344-1.56960.060929
120.3943433.0290.001819
13-0.230836-1.77310.040688
14-0.154901-1.18980.119442
15-0.071386-0.54830.292769
16-0.009682-0.07440.470485
17-0.075537-0.58020.281991
18-0.148249-1.13870.12971
190.0148560.11410.454769
200.0236110.18140.428352
210.1418411.08950.140181
22-0.079856-0.61340.270989
23-0.034559-0.26550.395793
240.167481.28640.101658
250.0672960.51690.303575
260.0668980.51390.304637
27-0.098985-0.76030.225046
280.014970.1150.454423
290.0393820.30250.381667
30-0.062848-0.48270.315533
310.0302490.23230.408536
320.0114350.08780.465155
33-0.230417-1.76990.040958
340.0077980.05990.476218
35-0.063671-0.48910.313303
36-0.041721-0.32050.374873



Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 2 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 2 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; 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')