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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 09:33:53 -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/t1259339707qzs69rhr1qgwjms.htm/, Retrieved Mon, 29 Apr 2024 04:56:13 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60964, Retrieved Mon, 29 Apr 2024 04:56:13 +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)
-       [(Partial) Autocorrelation Function] [] [2009-11-27 16:33:53] [8803431e497d94425e57d35981fe4f1d] [Current]
-   P     [(Partial) Autocorrelation Function] [] [2009-11-27 16:43:06] [898d317f4f946fbfcc4d07699283d43b]
-   P     [(Partial) Autocorrelation Function] [] [2009-11-27 16:47:12] [898d317f4f946fbfcc4d07699283d43b]
- RMP     [Variance Reduction Matrix] [] [2009-11-27 17:11:01] [898d317f4f946fbfcc4d07699283d43b]
- RMP     [Spectral Analysis] [] [2009-11-27 17:24:08] [a8dc04902f2584d6dc8a82e937850322]
- RMP     [Spectral Analysis] [] [2009-11-27 17:29:20] [a8dc04902f2584d6dc8a82e937850322]
- RMP     [Spectral Analysis] [] [2009-11-27 17:32:58] [a8dc04902f2584d6dc8a82e937850322]
- RMP     [Standard Deviation-Mean Plot] [] [2009-11-27 17:40:19] [a8dc04902f2584d6dc8a82e937850322]
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Dataseries X:
12.008	
9.169	
8.788	
8.417	
8.247	
8.197	
8.236	
8.253	
7.733	
8.366	
8.626	
8.863	
10.102	
8.463	
9.114	
8.563	
8.872	
8.301	
8.301	
8.278	
7.736	
7.973	
8.268	
9.476	
11.100	
8.962	
9.173	
8.738	
8.459	
8.078	
8.411	
8.291	
7.810	
8.616	
8.312	
9.692	
9.911	
8.915	
9.452	
9.112	
8.472	
8.230	
8.384	
8.625	
8.221	
8.649	
8.625	
10.443	
10.357	
8.586	
8.892	
8.329	
8.101	
7.922	
8.120	
7.838	
7.735	
8.406	
8.209	
9.451	
10.041	
9.411	
10.405	
8.467	
8.464	
8.102	
7.627	
7.513	
7.510	
8.291	
8.064	
9.383




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=60964&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=60964&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60964&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
10.4207013.56980.00032
20.2270571.92660.028986
3-0.026365-0.22370.411806
4-0.269141-2.28370.01267
5-0.337099-2.86040.002767
6-0.429438-3.64390.000252
7-0.348298-2.95540.002109
8-0.326429-2.76980.003565
9-0.05789-0.49120.312384
100.0810150.68740.247007
110.2821982.39450.009623
120.5912055.01652e-06
130.2487932.11110.019119
140.2372592.01320.023916
150.0318220.270.393959
16-0.16458-1.39650.083426
17-0.226267-1.91990.029414
18-0.312358-2.65040.004939
19-0.264632-2.24550.013904
20-0.27992-2.37520.010102
21-0.077005-0.65340.257786
220.042030.35660.361204
230.3228962.73990.003872
240.5283294.4831.4e-05
250.1610951.36690.087949
260.1269881.07750.14242
27-0.051806-0.43960.330776
28-0.198388-1.68340.048317
29-0.22807-1.93520.028444
30-0.262828-2.23020.014427
31-0.211671-1.79610.038338
32-0.196476-1.66720.049914
33-0.019074-0.16180.435939
340.0373470.31690.376119
350.2593942.2010.01547
360.3583483.04070.001645

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.420701 & 3.5698 & 0.00032 \tabularnewline
2 & 0.227057 & 1.9266 & 0.028986 \tabularnewline
3 & -0.026365 & -0.2237 & 0.411806 \tabularnewline
4 & -0.269141 & -2.2837 & 0.01267 \tabularnewline
5 & -0.337099 & -2.8604 & 0.002767 \tabularnewline
6 & -0.429438 & -3.6439 & 0.000252 \tabularnewline
7 & -0.348298 & -2.9554 & 0.002109 \tabularnewline
8 & -0.326429 & -2.7698 & 0.003565 \tabularnewline
9 & -0.05789 & -0.4912 & 0.312384 \tabularnewline
10 & 0.081015 & 0.6874 & 0.247007 \tabularnewline
11 & 0.282198 & 2.3945 & 0.009623 \tabularnewline
12 & 0.591205 & 5.0165 & 2e-06 \tabularnewline
13 & 0.248793 & 2.1111 & 0.019119 \tabularnewline
14 & 0.237259 & 2.0132 & 0.023916 \tabularnewline
15 & 0.031822 & 0.27 & 0.393959 \tabularnewline
16 & -0.16458 & -1.3965 & 0.083426 \tabularnewline
17 & -0.226267 & -1.9199 & 0.029414 \tabularnewline
18 & -0.312358 & -2.6504 & 0.004939 \tabularnewline
19 & -0.264632 & -2.2455 & 0.013904 \tabularnewline
20 & -0.27992 & -2.3752 & 0.010102 \tabularnewline
21 & -0.077005 & -0.6534 & 0.257786 \tabularnewline
22 & 0.04203 & 0.3566 & 0.361204 \tabularnewline
23 & 0.322896 & 2.7399 & 0.003872 \tabularnewline
24 & 0.528329 & 4.483 & 1.4e-05 \tabularnewline
25 & 0.161095 & 1.3669 & 0.087949 \tabularnewline
26 & 0.126988 & 1.0775 & 0.14242 \tabularnewline
27 & -0.051806 & -0.4396 & 0.330776 \tabularnewline
28 & -0.198388 & -1.6834 & 0.048317 \tabularnewline
29 & -0.22807 & -1.9352 & 0.028444 \tabularnewline
30 & -0.262828 & -2.2302 & 0.014427 \tabularnewline
31 & -0.211671 & -1.7961 & 0.038338 \tabularnewline
32 & -0.196476 & -1.6672 & 0.049914 \tabularnewline
33 & -0.019074 & -0.1618 & 0.435939 \tabularnewline
34 & 0.037347 & 0.3169 & 0.376119 \tabularnewline
35 & 0.259394 & 2.201 & 0.01547 \tabularnewline
36 & 0.358348 & 3.0407 & 0.001645 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60964&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]0.420701[/C][C]3.5698[/C][C]0.00032[/C][/ROW]
[ROW][C]2[/C][C]0.227057[/C][C]1.9266[/C][C]0.028986[/C][/ROW]
[ROW][C]3[/C][C]-0.026365[/C][C]-0.2237[/C][C]0.411806[/C][/ROW]
[ROW][C]4[/C][C]-0.269141[/C][C]-2.2837[/C][C]0.01267[/C][/ROW]
[ROW][C]5[/C][C]-0.337099[/C][C]-2.8604[/C][C]0.002767[/C][/ROW]
[ROW][C]6[/C][C]-0.429438[/C][C]-3.6439[/C][C]0.000252[/C][/ROW]
[ROW][C]7[/C][C]-0.348298[/C][C]-2.9554[/C][C]0.002109[/C][/ROW]
[ROW][C]8[/C][C]-0.326429[/C][C]-2.7698[/C][C]0.003565[/C][/ROW]
[ROW][C]9[/C][C]-0.05789[/C][C]-0.4912[/C][C]0.312384[/C][/ROW]
[ROW][C]10[/C][C]0.081015[/C][C]0.6874[/C][C]0.247007[/C][/ROW]
[ROW][C]11[/C][C]0.282198[/C][C]2.3945[/C][C]0.009623[/C][/ROW]
[ROW][C]12[/C][C]0.591205[/C][C]5.0165[/C][C]2e-06[/C][/ROW]
[ROW][C]13[/C][C]0.248793[/C][C]2.1111[/C][C]0.019119[/C][/ROW]
[ROW][C]14[/C][C]0.237259[/C][C]2.0132[/C][C]0.023916[/C][/ROW]
[ROW][C]15[/C][C]0.031822[/C][C]0.27[/C][C]0.393959[/C][/ROW]
[ROW][C]16[/C][C]-0.16458[/C][C]-1.3965[/C][C]0.083426[/C][/ROW]
[ROW][C]17[/C][C]-0.226267[/C][C]-1.9199[/C][C]0.029414[/C][/ROW]
[ROW][C]18[/C][C]-0.312358[/C][C]-2.6504[/C][C]0.004939[/C][/ROW]
[ROW][C]19[/C][C]-0.264632[/C][C]-2.2455[/C][C]0.013904[/C][/ROW]
[ROW][C]20[/C][C]-0.27992[/C][C]-2.3752[/C][C]0.010102[/C][/ROW]
[ROW][C]21[/C][C]-0.077005[/C][C]-0.6534[/C][C]0.257786[/C][/ROW]
[ROW][C]22[/C][C]0.04203[/C][C]0.3566[/C][C]0.361204[/C][/ROW]
[ROW][C]23[/C][C]0.322896[/C][C]2.7399[/C][C]0.003872[/C][/ROW]
[ROW][C]24[/C][C]0.528329[/C][C]4.483[/C][C]1.4e-05[/C][/ROW]
[ROW][C]25[/C][C]0.161095[/C][C]1.3669[/C][C]0.087949[/C][/ROW]
[ROW][C]26[/C][C]0.126988[/C][C]1.0775[/C][C]0.14242[/C][/ROW]
[ROW][C]27[/C][C]-0.051806[/C][C]-0.4396[/C][C]0.330776[/C][/ROW]
[ROW][C]28[/C][C]-0.198388[/C][C]-1.6834[/C][C]0.048317[/C][/ROW]
[ROW][C]29[/C][C]-0.22807[/C][C]-1.9352[/C][C]0.028444[/C][/ROW]
[ROW][C]30[/C][C]-0.262828[/C][C]-2.2302[/C][C]0.014427[/C][/ROW]
[ROW][C]31[/C][C]-0.211671[/C][C]-1.7961[/C][C]0.038338[/C][/ROW]
[ROW][C]32[/C][C]-0.196476[/C][C]-1.6672[/C][C]0.049914[/C][/ROW]
[ROW][C]33[/C][C]-0.019074[/C][C]-0.1618[/C][C]0.435939[/C][/ROW]
[ROW][C]34[/C][C]0.037347[/C][C]0.3169[/C][C]0.376119[/C][/ROW]
[ROW][C]35[/C][C]0.259394[/C][C]2.201[/C][C]0.01547[/C][/ROW]
[ROW][C]36[/C][C]0.358348[/C][C]3.0407[/C][C]0.001645[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60964&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60964&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
10.4207013.56980.00032
20.2270571.92660.028986
3-0.026365-0.22370.411806
4-0.269141-2.28370.01267
5-0.337099-2.86040.002767
6-0.429438-3.64390.000252
7-0.348298-2.95540.002109
8-0.326429-2.76980.003565
9-0.05789-0.49120.312384
100.0810150.68740.247007
110.2821982.39450.009623
120.5912055.01652e-06
130.2487932.11110.019119
140.2372592.01320.023916
150.0318220.270.393959
16-0.16458-1.39650.083426
17-0.226267-1.91990.029414
18-0.312358-2.65040.004939
19-0.264632-2.24550.013904
20-0.27992-2.37520.010102
21-0.077005-0.65340.257786
220.042030.35660.361204
230.3228962.73990.003872
240.5283294.4831.4e-05
250.1610951.36690.087949
260.1269881.07750.14242
27-0.051806-0.43960.330776
28-0.198388-1.68340.048317
29-0.22807-1.93520.028444
30-0.262828-2.23020.014427
31-0.211671-1.79610.038338
32-0.196476-1.66720.049914
33-0.019074-0.16180.435939
340.0373470.31690.376119
350.2593942.2010.01547
360.3583483.04070.001645







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.4207013.56980.00032
20.0608350.51620.303648
3-0.172776-1.46610.073493
4-0.270365-2.29410.012351
5-0.146616-1.24410.108753
6-0.235724-2.00020.024626
7-0.137322-1.16520.123889
8-0.258259-2.19140.01583
90.0166460.14120.444034
10-0.067662-0.57410.283836
110.0767240.6510.258552
120.3931713.33620.000673
13-0.295759-2.50960.007168
140.0498110.42270.3369
150.0048130.04080.483767
16-0.096384-0.81780.208072
170.033710.2860.387836
18-0.024883-0.21110.416686
19-0.009628-0.08170.467558
20-0.050477-0.42830.334853
21-0.065582-0.55650.289803
220.0823370.69870.24351
230.2011781.70710.046061
240.1551911.31680.096035
25-0.263494-2.23580.014232
26-0.156145-1.32490.094691
270.0356470.30250.38158
28-0.068624-0.58230.281094
29-0.013122-0.11130.455828
300.020720.17580.430467
31-0.017313-0.14690.441809
32-0.008375-0.07110.471772
33-0.065019-0.55170.291429
34-0.079665-0.6760.250611
35-0.053647-0.45520.325165
36-0.04897-0.41550.339496

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.420701 & 3.5698 & 0.00032 \tabularnewline
2 & 0.060835 & 0.5162 & 0.303648 \tabularnewline
3 & -0.172776 & -1.4661 & 0.073493 \tabularnewline
4 & -0.270365 & -2.2941 & 0.012351 \tabularnewline
5 & -0.146616 & -1.2441 & 0.108753 \tabularnewline
6 & -0.235724 & -2.0002 & 0.024626 \tabularnewline
7 & -0.137322 & -1.1652 & 0.123889 \tabularnewline
8 & -0.258259 & -2.1914 & 0.01583 \tabularnewline
9 & 0.016646 & 0.1412 & 0.444034 \tabularnewline
10 & -0.067662 & -0.5741 & 0.283836 \tabularnewline
11 & 0.076724 & 0.651 & 0.258552 \tabularnewline
12 & 0.393171 & 3.3362 & 0.000673 \tabularnewline
13 & -0.295759 & -2.5096 & 0.007168 \tabularnewline
14 & 0.049811 & 0.4227 & 0.3369 \tabularnewline
15 & 0.004813 & 0.0408 & 0.483767 \tabularnewline
16 & -0.096384 & -0.8178 & 0.208072 \tabularnewline
17 & 0.03371 & 0.286 & 0.387836 \tabularnewline
18 & -0.024883 & -0.2111 & 0.416686 \tabularnewline
19 & -0.009628 & -0.0817 & 0.467558 \tabularnewline
20 & -0.050477 & -0.4283 & 0.334853 \tabularnewline
21 & -0.065582 & -0.5565 & 0.289803 \tabularnewline
22 & 0.082337 & 0.6987 & 0.24351 \tabularnewline
23 & 0.201178 & 1.7071 & 0.046061 \tabularnewline
24 & 0.155191 & 1.3168 & 0.096035 \tabularnewline
25 & -0.263494 & -2.2358 & 0.014232 \tabularnewline
26 & -0.156145 & -1.3249 & 0.094691 \tabularnewline
27 & 0.035647 & 0.3025 & 0.38158 \tabularnewline
28 & -0.068624 & -0.5823 & 0.281094 \tabularnewline
29 & -0.013122 & -0.1113 & 0.455828 \tabularnewline
30 & 0.02072 & 0.1758 & 0.430467 \tabularnewline
31 & -0.017313 & -0.1469 & 0.441809 \tabularnewline
32 & -0.008375 & -0.0711 & 0.471772 \tabularnewline
33 & -0.065019 & -0.5517 & 0.291429 \tabularnewline
34 & -0.079665 & -0.676 & 0.250611 \tabularnewline
35 & -0.053647 & -0.4552 & 0.325165 \tabularnewline
36 & -0.04897 & -0.4155 & 0.339496 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60964&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]0.420701[/C][C]3.5698[/C][C]0.00032[/C][/ROW]
[ROW][C]2[/C][C]0.060835[/C][C]0.5162[/C][C]0.303648[/C][/ROW]
[ROW][C]3[/C][C]-0.172776[/C][C]-1.4661[/C][C]0.073493[/C][/ROW]
[ROW][C]4[/C][C]-0.270365[/C][C]-2.2941[/C][C]0.012351[/C][/ROW]
[ROW][C]5[/C][C]-0.146616[/C][C]-1.2441[/C][C]0.108753[/C][/ROW]
[ROW][C]6[/C][C]-0.235724[/C][C]-2.0002[/C][C]0.024626[/C][/ROW]
[ROW][C]7[/C][C]-0.137322[/C][C]-1.1652[/C][C]0.123889[/C][/ROW]
[ROW][C]8[/C][C]-0.258259[/C][C]-2.1914[/C][C]0.01583[/C][/ROW]
[ROW][C]9[/C][C]0.016646[/C][C]0.1412[/C][C]0.444034[/C][/ROW]
[ROW][C]10[/C][C]-0.067662[/C][C]-0.5741[/C][C]0.283836[/C][/ROW]
[ROW][C]11[/C][C]0.076724[/C][C]0.651[/C][C]0.258552[/C][/ROW]
[ROW][C]12[/C][C]0.393171[/C][C]3.3362[/C][C]0.000673[/C][/ROW]
[ROW][C]13[/C][C]-0.295759[/C][C]-2.5096[/C][C]0.007168[/C][/ROW]
[ROW][C]14[/C][C]0.049811[/C][C]0.4227[/C][C]0.3369[/C][/ROW]
[ROW][C]15[/C][C]0.004813[/C][C]0.0408[/C][C]0.483767[/C][/ROW]
[ROW][C]16[/C][C]-0.096384[/C][C]-0.8178[/C][C]0.208072[/C][/ROW]
[ROW][C]17[/C][C]0.03371[/C][C]0.286[/C][C]0.387836[/C][/ROW]
[ROW][C]18[/C][C]-0.024883[/C][C]-0.2111[/C][C]0.416686[/C][/ROW]
[ROW][C]19[/C][C]-0.009628[/C][C]-0.0817[/C][C]0.467558[/C][/ROW]
[ROW][C]20[/C][C]-0.050477[/C][C]-0.4283[/C][C]0.334853[/C][/ROW]
[ROW][C]21[/C][C]-0.065582[/C][C]-0.5565[/C][C]0.289803[/C][/ROW]
[ROW][C]22[/C][C]0.082337[/C][C]0.6987[/C][C]0.24351[/C][/ROW]
[ROW][C]23[/C][C]0.201178[/C][C]1.7071[/C][C]0.046061[/C][/ROW]
[ROW][C]24[/C][C]0.155191[/C][C]1.3168[/C][C]0.096035[/C][/ROW]
[ROW][C]25[/C][C]-0.263494[/C][C]-2.2358[/C][C]0.014232[/C][/ROW]
[ROW][C]26[/C][C]-0.156145[/C][C]-1.3249[/C][C]0.094691[/C][/ROW]
[ROW][C]27[/C][C]0.035647[/C][C]0.3025[/C][C]0.38158[/C][/ROW]
[ROW][C]28[/C][C]-0.068624[/C][C]-0.5823[/C][C]0.281094[/C][/ROW]
[ROW][C]29[/C][C]-0.013122[/C][C]-0.1113[/C][C]0.455828[/C][/ROW]
[ROW][C]30[/C][C]0.02072[/C][C]0.1758[/C][C]0.430467[/C][/ROW]
[ROW][C]31[/C][C]-0.017313[/C][C]-0.1469[/C][C]0.441809[/C][/ROW]
[ROW][C]32[/C][C]-0.008375[/C][C]-0.0711[/C][C]0.471772[/C][/ROW]
[ROW][C]33[/C][C]-0.065019[/C][C]-0.5517[/C][C]0.291429[/C][/ROW]
[ROW][C]34[/C][C]-0.079665[/C][C]-0.676[/C][C]0.250611[/C][/ROW]
[ROW][C]35[/C][C]-0.053647[/C][C]-0.4552[/C][C]0.325165[/C][/ROW]
[ROW][C]36[/C][C]-0.04897[/C][C]-0.4155[/C][C]0.339496[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60964&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60964&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
10.4207013.56980.00032
20.0608350.51620.303648
3-0.172776-1.46610.073493
4-0.270365-2.29410.012351
5-0.146616-1.24410.108753
6-0.235724-2.00020.024626
7-0.137322-1.16520.123889
8-0.258259-2.19140.01583
90.0166460.14120.444034
10-0.067662-0.57410.283836
110.0767240.6510.258552
120.3931713.33620.000673
13-0.295759-2.50960.007168
140.0498110.42270.3369
150.0048130.04080.483767
16-0.096384-0.81780.208072
170.033710.2860.387836
18-0.024883-0.21110.416686
19-0.009628-0.08170.467558
20-0.050477-0.42830.334853
21-0.065582-0.55650.289803
220.0823370.69870.24351
230.2011781.70710.046061
240.1551911.31680.096035
25-0.263494-2.23580.014232
26-0.156145-1.32490.094691
270.0356470.30250.38158
28-0.068624-0.58230.281094
29-0.013122-0.11130.455828
300.020720.17580.430467
31-0.017313-0.14690.441809
32-0.008375-0.07110.471772
33-0.065019-0.55170.291429
34-0.079665-0.6760.250611
35-0.053647-0.45520.325165
36-0.04897-0.41550.339496



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