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Description of Statistical Computation

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 computationSat, 21 Nov 2009 04:06:04 -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/21/t12588016055i0ivahetain5ox.htm/, Retrieved Sat, 27 Apr 2024 18:34:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=58530, Retrieved Sat, 27 Apr 2024 18:34:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact179

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Kendall tau Correlation Matrix] [Correlatie tussen...] [2007-11-03 21:44:17] [0b2d8ed757c467aee7199cdee05779c9]
- RMPD  [(Partial) Autocorrelation Function] [WS 8 01] [2009-11-21 08:59:55] [6e4e01d7eb22a9f33d58ebb35753a195]
-   PD    [(Partial) Autocorrelation Function] [WS 8 02] [2009-11-21 11:01:08] [6e4e01d7eb22a9f33d58ebb35753a195]
-   P       [(Partial) Autocorrelation Function] [WS 8 03] [2009-11-21 11:02:54] [6e4e01d7eb22a9f33d58ebb35753a195]
-   P           [(Partial) Autocorrelation Function] [WS 8 04] [2009-11-21 11:06:04] [2e4ef2c1b76db9b31c0a03b96e94ad77] [Current]
-   P             [(Partial) Autocorrelation Function] [ws 8 01b] [2009-11-24 22:56:18] [6e4e01d7eb22a9f33d58ebb35753a195]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
103.63
103.64
103.66
103.77
103.88
103.91
103.91
103.92
104.05
104.23
104.30
104.31
104.31
104.34
104.55
104.65
104.73
104.75
104.75
104.76
104.94
105.29
105.38
105.43
105.43
105.42
105.52
105.69
105.72
105.74
105.74
105.74
105.95
106.17
106.34
106.37
106.37
106.36
106.44
106.29
106.23
106.23
106.23
106.23
106.34
106.44
106.44
106.48
106.50
106.57
106.40
106.37
106.25
106.21
106.21
106.24
106.19
106.08
106.13
106.09

Tables (Output of Computation)





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=58530&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=58530&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=58530&T=0

As an alternative you can also use a QR Code:  
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
1-0.198391-1.51090.068122
2-0.149249-1.13670.13018
3-0.246446-1.87690.032784
4-0.058306-0.4440.32933
50.0266860.20320.419833
60.2434821.85430.034391
70.1497551.14050.129382
8-0.296049-2.25460.013974
9-0.086071-0.65550.25737
10-0.221537-1.68720.048471
110.3438522.61870.005622
120.0863980.6580.256576
130.1666661.26930.104703
14-0.178258-1.35760.089929
15-0.080577-0.61370.27092
16-0.173725-1.32310.095505
170.2386261.81730.037167
180.061950.47180.31942
19-0.140522-1.07020.144486
200.0192360.14650.442018
21-0.058519-0.44570.328747
220.0046220.03520.486021
230.0017260.01310.494779
240.1896841.44460.076977
25-0.13848-1.05460.147984
260.01690.12870.449018
27-0.086336-0.65750.256724
280.1427011.08680.140816
29-0.036388-0.27710.391335
30-0.020028-0.15250.43965
31-0.032624-0.24850.402328
32-0.03717-0.28310.389061
330.0360260.27440.39239
340.0415140.31620.376509
350.0923230.70310.2424
36-0.220342-1.67810.049357

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.198391 & -1.5109 & 0.068122 \tabularnewline
2 & -0.149249 & -1.1367 & 0.13018 \tabularnewline
3 & -0.246446 & -1.8769 & 0.032784 \tabularnewline
4 & -0.058306 & -0.444 & 0.32933 \tabularnewline
5 & 0.026686 & 0.2032 & 0.419833 \tabularnewline
6 & 0.243482 & 1.8543 & 0.034391 \tabularnewline
7 & 0.149755 & 1.1405 & 0.129382 \tabularnewline
8 & -0.296049 & -2.2546 & 0.013974 \tabularnewline
9 & -0.086071 & -0.6555 & 0.25737 \tabularnewline
10 & -0.221537 & -1.6872 & 0.048471 \tabularnewline
11 & 0.343852 & 2.6187 & 0.005622 \tabularnewline
12 & 0.086398 & 0.658 & 0.256576 \tabularnewline
13 & 0.166666 & 1.2693 & 0.104703 \tabularnewline
14 & -0.178258 & -1.3576 & 0.089929 \tabularnewline
15 & -0.080577 & -0.6137 & 0.27092 \tabularnewline
16 & -0.173725 & -1.3231 & 0.095505 \tabularnewline
17 & 0.238626 & 1.8173 & 0.037167 \tabularnewline
18 & 0.06195 & 0.4718 & 0.31942 \tabularnewline
19 & -0.140522 & -1.0702 & 0.144486 \tabularnewline
20 & 0.019236 & 0.1465 & 0.442018 \tabularnewline
21 & -0.058519 & -0.4457 & 0.328747 \tabularnewline
22 & 0.004622 & 0.0352 & 0.486021 \tabularnewline
23 & 0.001726 & 0.0131 & 0.494779 \tabularnewline
24 & 0.189684 & 1.4446 & 0.076977 \tabularnewline
25 & -0.13848 & -1.0546 & 0.147984 \tabularnewline
26 & 0.0169 & 0.1287 & 0.449018 \tabularnewline
27 & -0.086336 & -0.6575 & 0.256724 \tabularnewline
28 & 0.142701 & 1.0868 & 0.140816 \tabularnewline
29 & -0.036388 & -0.2771 & 0.391335 \tabularnewline
30 & -0.020028 & -0.1525 & 0.43965 \tabularnewline
31 & -0.032624 & -0.2485 & 0.402328 \tabularnewline
32 & -0.03717 & -0.2831 & 0.389061 \tabularnewline
33 & 0.036026 & 0.2744 & 0.39239 \tabularnewline
34 & 0.041514 & 0.3162 & 0.376509 \tabularnewline
35 & 0.092323 & 0.7031 & 0.2424 \tabularnewline
36 & -0.220342 & -1.6781 & 0.049357 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=58530&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]-0.198391[/C][C]-1.5109[/C][C]0.068122[/C][/ROW]
[ROW][C]2[/C][C]-0.149249[/C][C]-1.1367[/C][C]0.13018[/C][/ROW]
[ROW][C]3[/C][C]-0.246446[/C][C]-1.8769[/C][C]0.032784[/C][/ROW]
[ROW][C]4[/C][C]-0.058306[/C][C]-0.444[/C][C]0.32933[/C][/ROW]
[ROW][C]5[/C][C]0.026686[/C][C]0.2032[/C][C]0.419833[/C][/ROW]
[ROW][C]6[/C][C]0.243482[/C][C]1.8543[/C][C]0.034391[/C][/ROW]
[ROW][C]7[/C][C]0.149755[/C][C]1.1405[/C][C]0.129382[/C][/ROW]
[ROW][C]8[/C][C]-0.296049[/C][C]-2.2546[/C][C]0.013974[/C][/ROW]
[ROW][C]9[/C][C]-0.086071[/C][C]-0.6555[/C][C]0.25737[/C][/ROW]
[ROW][C]10[/C][C]-0.221537[/C][C]-1.6872[/C][C]0.048471[/C][/ROW]
[ROW][C]11[/C][C]0.343852[/C][C]2.6187[/C][C]0.005622[/C][/ROW]
[ROW][C]12[/C][C]0.086398[/C][C]0.658[/C][C]0.256576[/C][/ROW]
[ROW][C]13[/C][C]0.166666[/C][C]1.2693[/C][C]0.104703[/C][/ROW]
[ROW][C]14[/C][C]-0.178258[/C][C]-1.3576[/C][C]0.089929[/C][/ROW]
[ROW][C]15[/C][C]-0.080577[/C][C]-0.6137[/C][C]0.27092[/C][/ROW]
[ROW][C]16[/C][C]-0.173725[/C][C]-1.3231[/C][C]0.095505[/C][/ROW]
[ROW][C]17[/C][C]0.238626[/C][C]1.8173[/C][C]0.037167[/C][/ROW]
[ROW][C]18[/C][C]0.06195[/C][C]0.4718[/C][C]0.31942[/C][/ROW]
[ROW][C]19[/C][C]-0.140522[/C][C]-1.0702[/C][C]0.144486[/C][/ROW]
[ROW][C]20[/C][C]0.019236[/C][C]0.1465[/C][C]0.442018[/C][/ROW]
[ROW][C]21[/C][C]-0.058519[/C][C]-0.4457[/C][C]0.328747[/C][/ROW]
[ROW][C]22[/C][C]0.004622[/C][C]0.0352[/C][C]0.486021[/C][/ROW]
[ROW][C]23[/C][C]0.001726[/C][C]0.0131[/C][C]0.494779[/C][/ROW]
[ROW][C]24[/C][C]0.189684[/C][C]1.4446[/C][C]0.076977[/C][/ROW]
[ROW][C]25[/C][C]-0.13848[/C][C]-1.0546[/C][C]0.147984[/C][/ROW]
[ROW][C]26[/C][C]0.0169[/C][C]0.1287[/C][C]0.449018[/C][/ROW]
[ROW][C]27[/C][C]-0.086336[/C][C]-0.6575[/C][C]0.256724[/C][/ROW]
[ROW][C]28[/C][C]0.142701[/C][C]1.0868[/C][C]0.140816[/C][/ROW]
[ROW][C]29[/C][C]-0.036388[/C][C]-0.2771[/C][C]0.391335[/C][/ROW]
[ROW][C]30[/C][C]-0.020028[/C][C]-0.1525[/C][C]0.43965[/C][/ROW]
[ROW][C]31[/C][C]-0.032624[/C][C]-0.2485[/C][C]0.402328[/C][/ROW]
[ROW][C]32[/C][C]-0.03717[/C][C]-0.2831[/C][C]0.389061[/C][/ROW]
[ROW][C]33[/C][C]0.036026[/C][C]0.2744[/C][C]0.39239[/C][/ROW]
[ROW][C]34[/C][C]0.041514[/C][C]0.3162[/C][C]0.376509[/C][/ROW]
[ROW][C]35[/C][C]0.092323[/C][C]0.7031[/C][C]0.2424[/C][/ROW]
[ROW][C]36[/C][C]-0.220342[/C][C]-1.6781[/C][C]0.049357[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=58530&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=58530&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.198391-1.51090.068122
2-0.149249-1.13670.13018
3-0.246446-1.87690.032784
4-0.058306-0.4440.32933
50.0266860.20320.419833
60.2434821.85430.034391
70.1497551.14050.129382
8-0.296049-2.25460.013974
9-0.086071-0.65550.25737
10-0.221537-1.68720.048471
110.3438522.61870.005622
120.0863980.6580.256576
130.1666661.26930.104703
14-0.178258-1.35760.089929
15-0.080577-0.61370.27092
16-0.173725-1.32310.095505
170.2386261.81730.037167
180.061950.47180.31942
19-0.140522-1.07020.144486
200.0192360.14650.442018
21-0.058519-0.44570.328747
220.0046220.03520.486021
230.0017260.01310.494779
240.1896841.44460.076977
25-0.13848-1.05460.147984
260.01690.12870.449018
27-0.086336-0.65750.256724
280.1427011.08680.140816
29-0.036388-0.27710.391335
30-0.020028-0.15250.43965
31-0.032624-0.24850.402328
32-0.03717-0.28310.389061
330.0360260.27440.39239
340.0415140.31620.376509
350.0923230.70310.2424
36-0.220342-1.67810.049357






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.198391-1.51090.068122
2-0.196336-1.49520.070135
3-0.347354-2.64540.005242
4-0.300582-2.28920.012864
5-0.286621-2.18280.016555
6-0.036675-0.27930.390502
70.1380761.05160.148683
8-0.213181-1.62350.054949
9-0.134343-1.02310.155248
10-0.432956-3.29730.000835
11-0.07806-0.59450.277248
12-0.162079-1.23440.111023
130.0188430.14350.443195
140.0142420.10850.457001
150.1678591.27840.103105
16-0.010935-0.08330.46696
170.3032042.30910.012259
180.0370880.28250.389301
19-0.08022-0.61090.271814
20-0.066234-0.50440.307939
210.1774651.35150.090887
220.0892470.67970.249703
230.1314831.00130.160409
240.0595040.45320.326059
250.0587720.44760.328056
26-0.088032-0.67040.252621
27-0.139625-1.06340.146014
28-0.105121-0.80060.213322
29-0.085808-0.65350.258011
30-0.090836-0.69180.245915
310.0040960.03120.48761
32-0.05717-0.43540.332445
33-0.017214-0.13110.448077
34-0.06414-0.48850.313529
35-0.025292-0.19260.423964
36-0.21234-1.61710.055638

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.198391 & -1.5109 & 0.068122 \tabularnewline
2 & -0.196336 & -1.4952 & 0.070135 \tabularnewline
3 & -0.347354 & -2.6454 & 0.005242 \tabularnewline
4 & -0.300582 & -2.2892 & 0.012864 \tabularnewline
5 & -0.286621 & -2.1828 & 0.016555 \tabularnewline
6 & -0.036675 & -0.2793 & 0.390502 \tabularnewline
7 & 0.138076 & 1.0516 & 0.148683 \tabularnewline
8 & -0.213181 & -1.6235 & 0.054949 \tabularnewline
9 & -0.134343 & -1.0231 & 0.155248 \tabularnewline
10 & -0.432956 & -3.2973 & 0.000835 \tabularnewline
11 & -0.07806 & -0.5945 & 0.277248 \tabularnewline
12 & -0.162079 & -1.2344 & 0.111023 \tabularnewline
13 & 0.018843 & 0.1435 & 0.443195 \tabularnewline
14 & 0.014242 & 0.1085 & 0.457001 \tabularnewline
15 & 0.167859 & 1.2784 & 0.103105 \tabularnewline
16 & -0.010935 & -0.0833 & 0.46696 \tabularnewline
17 & 0.303204 & 2.3091 & 0.012259 \tabularnewline
18 & 0.037088 & 0.2825 & 0.389301 \tabularnewline
19 & -0.08022 & -0.6109 & 0.271814 \tabularnewline
20 & -0.066234 & -0.5044 & 0.307939 \tabularnewline
21 & 0.177465 & 1.3515 & 0.090887 \tabularnewline
22 & 0.089247 & 0.6797 & 0.249703 \tabularnewline
23 & 0.131483 & 1.0013 & 0.160409 \tabularnewline
24 & 0.059504 & 0.4532 & 0.326059 \tabularnewline
25 & 0.058772 & 0.4476 & 0.328056 \tabularnewline
26 & -0.088032 & -0.6704 & 0.252621 \tabularnewline
27 & -0.139625 & -1.0634 & 0.146014 \tabularnewline
28 & -0.105121 & -0.8006 & 0.213322 \tabularnewline
29 & -0.085808 & -0.6535 & 0.258011 \tabularnewline
30 & -0.090836 & -0.6918 & 0.245915 \tabularnewline
31 & 0.004096 & 0.0312 & 0.48761 \tabularnewline
32 & -0.05717 & -0.4354 & 0.332445 \tabularnewline
33 & -0.017214 & -0.1311 & 0.448077 \tabularnewline
34 & -0.06414 & -0.4885 & 0.313529 \tabularnewline
35 & -0.025292 & -0.1926 & 0.423964 \tabularnewline
36 & -0.21234 & -1.6171 & 0.055638 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=58530&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]-0.198391[/C][C]-1.5109[/C][C]0.068122[/C][/ROW]
[ROW][C]2[/C][C]-0.196336[/C][C]-1.4952[/C][C]0.070135[/C][/ROW]
[ROW][C]3[/C][C]-0.347354[/C][C]-2.6454[/C][C]0.005242[/C][/ROW]
[ROW][C]4[/C][C]-0.300582[/C][C]-2.2892[/C][C]0.012864[/C][/ROW]
[ROW][C]5[/C][C]-0.286621[/C][C]-2.1828[/C][C]0.016555[/C][/ROW]
[ROW][C]6[/C][C]-0.036675[/C][C]-0.2793[/C][C]0.390502[/C][/ROW]
[ROW][C]7[/C][C]0.138076[/C][C]1.0516[/C][C]0.148683[/C][/ROW]
[ROW][C]8[/C][C]-0.213181[/C][C]-1.6235[/C][C]0.054949[/C][/ROW]
[ROW][C]9[/C][C]-0.134343[/C][C]-1.0231[/C][C]0.155248[/C][/ROW]
[ROW][C]10[/C][C]-0.432956[/C][C]-3.2973[/C][C]0.000835[/C][/ROW]
[ROW][C]11[/C][C]-0.07806[/C][C]-0.5945[/C][C]0.277248[/C][/ROW]
[ROW][C]12[/C][C]-0.162079[/C][C]-1.2344[/C][C]0.111023[/C][/ROW]
[ROW][C]13[/C][C]0.018843[/C][C]0.1435[/C][C]0.443195[/C][/ROW]
[ROW][C]14[/C][C]0.014242[/C][C]0.1085[/C][C]0.457001[/C][/ROW]
[ROW][C]15[/C][C]0.167859[/C][C]1.2784[/C][C]0.103105[/C][/ROW]
[ROW][C]16[/C][C]-0.010935[/C][C]-0.0833[/C][C]0.46696[/C][/ROW]
[ROW][C]17[/C][C]0.303204[/C][C]2.3091[/C][C]0.012259[/C][/ROW]
[ROW][C]18[/C][C]0.037088[/C][C]0.2825[/C][C]0.389301[/C][/ROW]
[ROW][C]19[/C][C]-0.08022[/C][C]-0.6109[/C][C]0.271814[/C][/ROW]
[ROW][C]20[/C][C]-0.066234[/C][C]-0.5044[/C][C]0.307939[/C][/ROW]
[ROW][C]21[/C][C]0.177465[/C][C]1.3515[/C][C]0.090887[/C][/ROW]
[ROW][C]22[/C][C]0.089247[/C][C]0.6797[/C][C]0.249703[/C][/ROW]
[ROW][C]23[/C][C]0.131483[/C][C]1.0013[/C][C]0.160409[/C][/ROW]
[ROW][C]24[/C][C]0.059504[/C][C]0.4532[/C][C]0.326059[/C][/ROW]
[ROW][C]25[/C][C]0.058772[/C][C]0.4476[/C][C]0.328056[/C][/ROW]
[ROW][C]26[/C][C]-0.088032[/C][C]-0.6704[/C][C]0.252621[/C][/ROW]
[ROW][C]27[/C][C]-0.139625[/C][C]-1.0634[/C][C]0.146014[/C][/ROW]
[ROW][C]28[/C][C]-0.105121[/C][C]-0.8006[/C][C]0.213322[/C][/ROW]
[ROW][C]29[/C][C]-0.085808[/C][C]-0.6535[/C][C]0.258011[/C][/ROW]
[ROW][C]30[/C][C]-0.090836[/C][C]-0.6918[/C][C]0.245915[/C][/ROW]
[ROW][C]31[/C][C]0.004096[/C][C]0.0312[/C][C]0.48761[/C][/ROW]
[ROW][C]32[/C][C]-0.05717[/C][C]-0.4354[/C][C]0.332445[/C][/ROW]
[ROW][C]33[/C][C]-0.017214[/C][C]-0.1311[/C][C]0.448077[/C][/ROW]
[ROW][C]34[/C][C]-0.06414[/C][C]-0.4885[/C][C]0.313529[/C][/ROW]
[ROW][C]35[/C][C]-0.025292[/C][C]-0.1926[/C][C]0.423964[/C][/ROW]
[ROW][C]36[/C][C]-0.21234[/C][C]-1.6171[/C][C]0.055638[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=58530&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=58530&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.198391-1.51090.068122
2-0.196336-1.49520.070135
3-0.347354-2.64540.005242
4-0.300582-2.28920.012864
5-0.286621-2.18280.016555
6-0.036675-0.27930.390502
70.1380761.05160.148683
8-0.213181-1.62350.054949
9-0.134343-1.02310.155248
10-0.432956-3.29730.000835
11-0.07806-0.59450.277248
12-0.162079-1.23440.111023
130.0188430.14350.443195
140.0142420.10850.457001
150.1678591.27840.103105
16-0.010935-0.08330.46696
170.3032042.30910.012259
180.0370880.28250.389301
19-0.08022-0.61090.271814
20-0.066234-0.50440.307939
210.1774651.35150.090887
220.0892470.67970.249703
230.1314831.00130.160409
240.0595040.45320.326059
250.0587720.44760.328056
26-0.088032-0.67040.252621
27-0.139625-1.06340.146014
28-0.105121-0.80060.213322
29-0.085808-0.65350.258011
30-0.090836-0.69180.245915
310.0040960.03120.48761
32-0.05717-0.43540.332445
33-0.017214-0.13110.448077
34-0.06414-0.48850.313529
35-0.025292-0.19260.423964
36-0.21234-1.61710.055638


Figures (Output of Computation)

Input Parameters & R Code

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