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rwasp_autocorrelation.wasp

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(Partial) Autocorrelation Function

Date of computation

Wed, 16 Dec 2009 06:50:30 -0700

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/16/t126097147820ad18cryowdl5q.htm/, Retrieved Tue, 30 Apr 2024 20:34:46 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=68339, Retrieved Tue, 30 Apr 2024 20:34:46 +0000

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122

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-       [(Partial) Autocorrelation Function] [ACF (d=0; D=1)] [2009-12-16 13:50:30] [91da2e1ebdd83187f2515f461585cbee] [Current]

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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 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=68339&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=68339&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68339&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.458543	5.0231	1e-06
2	0.445796	4.8835	2e-06
3	0.537995	5.8934	0
4	0.239414	2.6226	0.004928
5	0.292252	3.2015	0.000875
6	0.257462	2.8204	0.002807
7	-1.5e-05	-2e-04	0.499934
8	0.133674	1.4643	0.07286
9	0.06457	0.7073	0.240368
10	-0.130437	-1.4289	0.07782
11	-0.056225	-0.6159	0.269559
12	-0.108003	-1.1831	0.119551
13	-0.180916	-1.9818	0.024892
14	-0.09229	-1.011	0.157029
15	-0.152078	-1.6659	0.049168
16	-0.271266	-2.9716	0.00179
17	-0.094401	-1.0341	0.151582
18	-0.159813	-1.7507	0.04128
19	-0.243453	-2.6669	0.004356
20	-0.114443	-1.2537	0.106202
21	-0.18075	-1.98	0.024995
22	-0.232226	-2.5439	0.006116
23	-0.008926	-0.0978	0.461135
24	-0.233438	-2.5572	0.005899
25	-0.222302	-2.4352	0.008177
26	-0.098157	-1.0753	0.142209
27	-0.211756	-2.3197	0.011024
28	-0.195482	-2.1414	0.017132
29	-0.120404	-1.319	0.094847
30	-0.20196	-2.2124	0.014417
31	-0.102894	-1.1271	0.130965
32	-0.03448	-0.3777	0.353158
33	-0.178633	-1.9568	0.026345
34	-0.0957	-1.0483	0.148294
35	-0.071724	-0.7857	0.216798
36	-0.135295	-1.4821	0.07047

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.458543 & 5.0231 & 1e-06 \tabularnewline
2 & 0.445796 & 4.8835 & 2e-06 \tabularnewline
3 & 0.537995 & 5.8934 & 0 \tabularnewline
4 & 0.239414 & 2.6226 & 0.004928 \tabularnewline
5 & 0.292252 & 3.2015 & 0.000875 \tabularnewline
6 & 0.257462 & 2.8204 & 0.002807 \tabularnewline
7 & -1.5e-05 & -2e-04 & 0.499934 \tabularnewline
8 & 0.133674 & 1.4643 & 0.07286 \tabularnewline
9 & 0.06457 & 0.7073 & 0.240368 \tabularnewline
10 & -0.130437 & -1.4289 & 0.07782 \tabularnewline
11 & -0.056225 & -0.6159 & 0.269559 \tabularnewline
12 & -0.108003 & -1.1831 & 0.119551 \tabularnewline
13 & -0.180916 & -1.9818 & 0.024892 \tabularnewline
14 & -0.09229 & -1.011 & 0.157029 \tabularnewline
15 & -0.152078 & -1.6659 & 0.049168 \tabularnewline
16 & -0.271266 & -2.9716 & 0.00179 \tabularnewline
17 & -0.094401 & -1.0341 & 0.151582 \tabularnewline
18 & -0.159813 & -1.7507 & 0.04128 \tabularnewline
19 & -0.243453 & -2.6669 & 0.004356 \tabularnewline
20 & -0.114443 & -1.2537 & 0.106202 \tabularnewline
21 & -0.18075 & -1.98 & 0.024995 \tabularnewline
22 & -0.232226 & -2.5439 & 0.006116 \tabularnewline
23 & -0.008926 & -0.0978 & 0.461135 \tabularnewline
24 & -0.233438 & -2.5572 & 0.005899 \tabularnewline
25 & -0.222302 & -2.4352 & 0.008177 \tabularnewline
26 & -0.098157 & -1.0753 & 0.142209 \tabularnewline
27 & -0.211756 & -2.3197 & 0.011024 \tabularnewline
28 & -0.195482 & -2.1414 & 0.017132 \tabularnewline
29 & -0.120404 & -1.319 & 0.094847 \tabularnewline
30 & -0.20196 & -2.2124 & 0.014417 \tabularnewline
31 & -0.102894 & -1.1271 & 0.130965 \tabularnewline
32 & -0.03448 & -0.3777 & 0.353158 \tabularnewline
33 & -0.178633 & -1.9568 & 0.026345 \tabularnewline
34 & -0.0957 & -1.0483 & 0.148294 \tabularnewline
35 & -0.071724 & -0.7857 & 0.216798 \tabularnewline
36 & -0.135295 & -1.4821 & 0.07047 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68339&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]0.458543[/C][C]5.0231[/C][C]1e-06[/C][/ROW]
[ROW][C]2[/C][C]0.445796[/C][C]4.8835[/C][C]2e-06[/C][/ROW]
[ROW][C]3[/C][C]0.537995[/C][C]5.8934[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.239414[/C][C]2.6226[/C][C]0.004928[/C][/ROW]
[ROW][C]5[/C][C]0.292252[/C][C]3.2015[/C][C]0.000875[/C][/ROW]
[ROW][C]6[/C][C]0.257462[/C][C]2.8204[/C][C]0.002807[/C][/ROW]
[ROW][C]7[/C][C]-1.5e-05[/C][C]-2e-04[/C][C]0.499934[/C][/ROW]
[ROW][C]8[/C][C]0.133674[/C][C]1.4643[/C][C]0.07286[/C][/ROW]
[ROW][C]9[/C][C]0.06457[/C][C]0.7073[/C][C]0.240368[/C][/ROW]
[ROW][C]10[/C][C]-0.130437[/C][C]-1.4289[/C][C]0.07782[/C][/ROW]
[ROW][C]11[/C][C]-0.056225[/C][C]-0.6159[/C][C]0.269559[/C][/ROW]
[ROW][C]12[/C][C]-0.108003[/C][C]-1.1831[/C][C]0.119551[/C][/ROW]
[ROW][C]13[/C][C]-0.180916[/C][C]-1.9818[/C][C]0.024892[/C][/ROW]
[ROW][C]14[/C][C]-0.09229[/C][C]-1.011[/C][C]0.157029[/C][/ROW]
[ROW][C]15[/C][C]-0.152078[/C][C]-1.6659[/C][C]0.049168[/C][/ROW]
[ROW][C]16[/C][C]-0.271266[/C][C]-2.9716[/C][C]0.00179[/C][/ROW]
[ROW][C]17[/C][C]-0.094401[/C][C]-1.0341[/C][C]0.151582[/C][/ROW]
[ROW][C]18[/C][C]-0.159813[/C][C]-1.7507[/C][C]0.04128[/C][/ROW]
[ROW][C]19[/C][C]-0.243453[/C][C]-2.6669[/C][C]0.004356[/C][/ROW]
[ROW][C]20[/C][C]-0.114443[/C][C]-1.2537[/C][C]0.106202[/C][/ROW]
[ROW][C]21[/C][C]-0.18075[/C][C]-1.98[/C][C]0.024995[/C][/ROW]
[ROW][C]22[/C][C]-0.232226[/C][C]-2.5439[/C][C]0.006116[/C][/ROW]
[ROW][C]23[/C][C]-0.008926[/C][C]-0.0978[/C][C]0.461135[/C][/ROW]
[ROW][C]24[/C][C]-0.233438[/C][C]-2.5572[/C][C]0.005899[/C][/ROW]
[ROW][C]25[/C][C]-0.222302[/C][C]-2.4352[/C][C]0.008177[/C][/ROW]
[ROW][C]26[/C][C]-0.098157[/C][C]-1.0753[/C][C]0.142209[/C][/ROW]
[ROW][C]27[/C][C]-0.211756[/C][C]-2.3197[/C][C]0.011024[/C][/ROW]
[ROW][C]28[/C][C]-0.195482[/C][C]-2.1414[/C][C]0.017132[/C][/ROW]
[ROW][C]29[/C][C]-0.120404[/C][C]-1.319[/C][C]0.094847[/C][/ROW]
[ROW][C]30[/C][C]-0.20196[/C][C]-2.2124[/C][C]0.014417[/C][/ROW]
[ROW][C]31[/C][C]-0.102894[/C][C]-1.1271[/C][C]0.130965[/C][/ROW]
[ROW][C]32[/C][C]-0.03448[/C][C]-0.3777[/C][C]0.353158[/C][/ROW]
[ROW][C]33[/C][C]-0.178633[/C][C]-1.9568[/C][C]0.026345[/C][/ROW]
[ROW][C]34[/C][C]-0.0957[/C][C]-1.0483[/C][C]0.148294[/C][/ROW]
[ROW][C]35[/C][C]-0.071724[/C][C]-0.7857[/C][C]0.216798[/C][/ROW]
[ROW][C]36[/C][C]-0.135295[/C][C]-1.4821[/C][C]0.07047[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68339&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68339&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 k	ACF(k)	T-STAT	P-value
1	0.458543	5.0231	1e-06
2	0.445796	4.8835	2e-06
3	0.537995	5.8934	0
4	0.239414	2.6226	0.004928
5	0.292252	3.2015	0.000875
6	0.257462	2.8204	0.002807
7	-1.5e-05	-2e-04	0.499934
8	0.133674	1.4643	0.07286
9	0.06457	0.7073	0.240368
10	-0.130437	-1.4289	0.07782
11	-0.056225	-0.6159	0.269559
12	-0.108003	-1.1831	0.119551
13	-0.180916	-1.9818	0.024892
14	-0.09229	-1.011	0.157029
15	-0.152078	-1.6659	0.049168
16	-0.271266	-2.9716	0.00179
17	-0.094401	-1.0341	0.151582
18	-0.159813	-1.7507	0.04128
19	-0.243453	-2.6669	0.004356
20	-0.114443	-1.2537	0.106202
21	-0.18075	-1.98	0.024995
22	-0.232226	-2.5439	0.006116
23	-0.008926	-0.0978	0.461135
24	-0.233438	-2.5572	0.005899
25	-0.222302	-2.4352	0.008177
26	-0.098157	-1.0753	0.142209
27	-0.211756	-2.3197	0.011024
28	-0.195482	-2.1414	0.017132
29	-0.120404	-1.319	0.094847
30	-0.20196	-2.2124	0.014417
31	-0.102894	-1.1271	0.130965
32	-0.03448	-0.3777	0.353158
33	-0.178633	-1.9568	0.026345
34	-0.0957	-1.0483	0.148294
35	-0.071724	-0.7857	0.216798
36	-0.135295	-1.4821	0.07047

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.458543	5.0231	1e-06
2	0.298243	3.2671	0.000709
3	0.35829	3.9249	7.3e-05
4	-0.194643	-2.1322	0.017514
5	0.028826	0.3158	0.376363
6	-0.019243	-0.2108	0.416701
7	-0.215527	-2.361	0.009919
8	0.067839	0.7431	0.229425
9	0.015769	0.1727	0.431571
10	-0.139773	-1.5311	0.064184
11	-0.104885	-1.149	0.126429
12	0.017495	0.1916	0.424171
13	0.004323	0.0474	0.481154
14	0.005495	0.0602	0.47605
15	0.013886	0.1521	0.439675
16	-0.191726	-2.1003	0.0189
17	0.075205	0.8238	0.205836
18	0.016372	0.1793	0.428986
19	-0.087003	-0.9531	0.171235
20	-0.032576	-0.3569	0.360915
21	-0.007082	-0.0776	0.469147
22	-0.116677	-1.2781	0.101834
23	0.156071	1.7097	0.044956
24	-0.158805	-1.7396	0.042244
25	-0.116788	-1.2793	0.101622
26	-0.091866	-1.0063	0.158138
27	0.070006	0.7669	0.222329
28	-0.107767	-1.1805	0.120062
29	-0.017608	-0.1929	0.423688
30	0.039455	0.4322	0.333184
31	-0.029031	-0.318	0.375513
32	0.023657	0.2591	0.397983
33	-0.088916	-0.974	0.166002
34	-0.08839	-0.9683	0.167431
35	-0.098211	-1.0758	0.142077
36	-0.014752	-0.1616	0.435944

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.458543 & 5.0231 & 1e-06 \tabularnewline
2 & 0.298243 & 3.2671 & 0.000709 \tabularnewline
3 & 0.35829 & 3.9249 & 7.3e-05 \tabularnewline
4 & -0.194643 & -2.1322 & 0.017514 \tabularnewline
5 & 0.028826 & 0.3158 & 0.376363 \tabularnewline
6 & -0.019243 & -0.2108 & 0.416701 \tabularnewline
7 & -0.215527 & -2.361 & 0.009919 \tabularnewline
8 & 0.067839 & 0.7431 & 0.229425 \tabularnewline
9 & 0.015769 & 0.1727 & 0.431571 \tabularnewline
10 & -0.139773 & -1.5311 & 0.064184 \tabularnewline
11 & -0.104885 & -1.149 & 0.126429 \tabularnewline
12 & 0.017495 & 0.1916 & 0.424171 \tabularnewline
13 & 0.004323 & 0.0474 & 0.481154 \tabularnewline
14 & 0.005495 & 0.0602 & 0.47605 \tabularnewline
15 & 0.013886 & 0.1521 & 0.439675 \tabularnewline
16 & -0.191726 & -2.1003 & 0.0189 \tabularnewline
17 & 0.075205 & 0.8238 & 0.205836 \tabularnewline
18 & 0.016372 & 0.1793 & 0.428986 \tabularnewline
19 & -0.087003 & -0.9531 & 0.171235 \tabularnewline
20 & -0.032576 & -0.3569 & 0.360915 \tabularnewline
21 & -0.007082 & -0.0776 & 0.469147 \tabularnewline
22 & -0.116677 & -1.2781 & 0.101834 \tabularnewline
23 & 0.156071 & 1.7097 & 0.044956 \tabularnewline
24 & -0.158805 & -1.7396 & 0.042244 \tabularnewline
25 & -0.116788 & -1.2793 & 0.101622 \tabularnewline
26 & -0.091866 & -1.0063 & 0.158138 \tabularnewline
27 & 0.070006 & 0.7669 & 0.222329 \tabularnewline
28 & -0.107767 & -1.1805 & 0.120062 \tabularnewline
29 & -0.017608 & -0.1929 & 0.423688 \tabularnewline
30 & 0.039455 & 0.4322 & 0.333184 \tabularnewline
31 & -0.029031 & -0.318 & 0.375513 \tabularnewline
32 & 0.023657 & 0.2591 & 0.397983 \tabularnewline
33 & -0.088916 & -0.974 & 0.166002 \tabularnewline
34 & -0.08839 & -0.9683 & 0.167431 \tabularnewline
35 & -0.098211 & -1.0758 & 0.142077 \tabularnewline
36 & -0.014752 & -0.1616 & 0.435944 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68339&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]0.458543[/C][C]5.0231[/C][C]1e-06[/C][/ROW]
[ROW][C]2[/C][C]0.298243[/C][C]3.2671[/C][C]0.000709[/C][/ROW]
[ROW][C]3[/C][C]0.35829[/C][C]3.9249[/C][C]7.3e-05[/C][/ROW]
[ROW][C]4[/C][C]-0.194643[/C][C]-2.1322[/C][C]0.017514[/C][/ROW]
[ROW][C]5[/C][C]0.028826[/C][C]0.3158[/C][C]0.376363[/C][/ROW]
[ROW][C]6[/C][C]-0.019243[/C][C]-0.2108[/C][C]0.416701[/C][/ROW]
[ROW][C]7[/C][C]-0.215527[/C][C]-2.361[/C][C]0.009919[/C][/ROW]
[ROW][C]8[/C][C]0.067839[/C][C]0.7431[/C][C]0.229425[/C][/ROW]
[ROW][C]9[/C][C]0.015769[/C][C]0.1727[/C][C]0.431571[/C][/ROW]
[ROW][C]10[/C][C]-0.139773[/C][C]-1.5311[/C][C]0.064184[/C][/ROW]
[ROW][C]11[/C][C]-0.104885[/C][C]-1.149[/C][C]0.126429[/C][/ROW]
[ROW][C]12[/C][C]0.017495[/C][C]0.1916[/C][C]0.424171[/C][/ROW]
[ROW][C]13[/C][C]0.004323[/C][C]0.0474[/C][C]0.481154[/C][/ROW]
[ROW][C]14[/C][C]0.005495[/C][C]0.0602[/C][C]0.47605[/C][/ROW]
[ROW][C]15[/C][C]0.013886[/C][C]0.1521[/C][C]0.439675[/C][/ROW]
[ROW][C]16[/C][C]-0.191726[/C][C]-2.1003[/C][C]0.0189[/C][/ROW]
[ROW][C]17[/C][C]0.075205[/C][C]0.8238[/C][C]0.205836[/C][/ROW]
[ROW][C]18[/C][C]0.016372[/C][C]0.1793[/C][C]0.428986[/C][/ROW]
[ROW][C]19[/C][C]-0.087003[/C][C]-0.9531[/C][C]0.171235[/C][/ROW]
[ROW][C]20[/C][C]-0.032576[/C][C]-0.3569[/C][C]0.360915[/C][/ROW]
[ROW][C]21[/C][C]-0.007082[/C][C]-0.0776[/C][C]0.469147[/C][/ROW]
[ROW][C]22[/C][C]-0.116677[/C][C]-1.2781[/C][C]0.101834[/C][/ROW]
[ROW][C]23[/C][C]0.156071[/C][C]1.7097[/C][C]0.044956[/C][/ROW]
[ROW][C]24[/C][C]-0.158805[/C][C]-1.7396[/C][C]0.042244[/C][/ROW]
[ROW][C]25[/C][C]-0.116788[/C][C]-1.2793[/C][C]0.101622[/C][/ROW]
[ROW][C]26[/C][C]-0.091866[/C][C]-1.0063[/C][C]0.158138[/C][/ROW]
[ROW][C]27[/C][C]0.070006[/C][C]0.7669[/C][C]0.222329[/C][/ROW]
[ROW][C]28[/C][C]-0.107767[/C][C]-1.1805[/C][C]0.120062[/C][/ROW]
[ROW][C]29[/C][C]-0.017608[/C][C]-0.1929[/C][C]0.423688[/C][/ROW]
[ROW][C]30[/C][C]0.039455[/C][C]0.4322[/C][C]0.333184[/C][/ROW]
[ROW][C]31[/C][C]-0.029031[/C][C]-0.318[/C][C]0.375513[/C][/ROW]
[ROW][C]32[/C][C]0.023657[/C][C]0.2591[/C][C]0.397983[/C][/ROW]
[ROW][C]33[/C][C]-0.088916[/C][C]-0.974[/C][C]0.166002[/C][/ROW]
[ROW][C]34[/C][C]-0.08839[/C][C]-0.9683[/C][C]0.167431[/C][/ROW]
[ROW][C]35[/C][C]-0.098211[/C][C]-1.0758[/C][C]0.142077[/C][/ROW]
[ROW][C]36[/C][C]-0.014752[/C][C]-0.1616[/C][C]0.435944[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68339&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68339&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 k	PACF(k)	T-STAT	P-value
1	0.458543	5.0231	1e-06
2	0.298243	3.2671	0.000709
3	0.35829	3.9249	7.3e-05
4	-0.194643	-2.1322	0.017514
5	0.028826	0.3158	0.376363
6	-0.019243	-0.2108	0.416701
7	-0.215527	-2.361	0.009919
8	0.067839	0.7431	0.229425
9	0.015769	0.1727	0.431571
10	-0.139773	-1.5311	0.064184
11	-0.104885	-1.149	0.126429
12	0.017495	0.1916	0.424171
13	0.004323	0.0474	0.481154
14	0.005495	0.0602	0.47605
15	0.013886	0.1521	0.439675
16	-0.191726	-2.1003	0.0189
17	0.075205	0.8238	0.205836
18	0.016372	0.1793	0.428986
19	-0.087003	-0.9531	0.171235
20	-0.032576	-0.3569	0.360915
21	-0.007082	-0.0776	0.469147
22	-0.116677	-1.2781	0.101834
23	0.156071	1.7097	0.044956
24	-0.158805	-1.7396	0.042244
25	-0.116788	-1.2793	0.101622
26	-0.091866	-1.0063	0.158138
27	0.070006	0.7669	0.222329
28	-0.107767	-1.1805	0.120062
29	-0.017608	-0.1929	0.423688
30	0.039455	0.4322	0.333184
31	-0.029031	-0.318	0.375513
32	0.023657	0.2591	0.397983
33	-0.088916	-0.974	0.166002
34	-0.08839	-0.9683	0.167431
35	-0.098211	-1.0758	0.142077
36	-0.014752	-0.1616	0.435944

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 36 ; par2 = 0.0 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

Parameters (R input):

par1 = 36 ; par2 = 0.0 ; par3 = 0 ; par4 = 1 ; 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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code