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R Software Module

rwasp_autocorrelation.wasp

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(Partial) Autocorrelation Function

Date of computation

Sat, 12 Mar 2016 14:57:46 +0000

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Mar/12/t1457794832dw1dks3mv5qyd1i.htm/, Retrieved Sun, 05 May 2024 15:35:55 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=293922, Retrieved Sun, 05 May 2024 15:35:55 +0000

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109

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-       [(Partial) Autocorrelation Function] [consumptieprijsin...] [2016-03-12 14:57:46] [567a9be58124adae7ccc8a0c8709ba48] [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	'Gertrude Mary Cox' @ cox.wessa.net

\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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=293922&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=293922&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=293922&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	'Gertrude Mary Cox' @ cox.wessa.net

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.975839	10.6898	0
2	0.951916	10.4277	0
3	0.928228	10.1682	0
4	0.905361	9.9177	0
5	0.882981	9.6726	0
6	0.860364	9.4248	0
7	0.837073	9.1697	0
8	0.813886	8.9157	0
9	0.79083	8.6631	0
10	0.768423	8.4177	0
11	0.746418	8.1766	0
12	0.723787	7.9287	0
13	0.699863	7.6666	0
14	0.675998	7.4052	0
15	0.653987	7.1641	0
16	0.631457	6.9173	0
17	0.608693	6.6679	0
18	0.585777	6.4169	0
19	0.562159	6.1581	0
20	0.538212	5.8958	0
21	0.514422	5.6352	0
22	0.490909	5.3776	0
23	0.467989	5.1266	1e-06
24	0.444577	4.8701	2e-06
25	0.420439	4.6057	5e-06
26	0.396222	4.3404	1.5e-05
27	0.37116	4.0659	4.3e-05
28	0.346623	3.7971	0.000116
29	0.322842	3.5366	0.000289
30	0.298752	3.2727	0.000696
31	0.274065	3.0022	0.001631
32	0.248881	2.7263	0.003682
33	0.223943	2.4532	0.007799
34	0.199904	2.1898	0.015235
35	0.177094	1.94	0.027365
36	0.154589	1.6934	0.046484
37	0.13099	1.4349	0.076956
38	0.108051	1.1836	0.119448
39	0.087197	0.9552	0.170701
40	0.067192	0.7361	0.231567
41	0.04816	0.5276	0.299387
42	0.028867	0.3162	0.37619
43	0.009246	0.1013	0.459748
44	-0.010532	-0.1154	0.454172
45	-0.03038	-0.3328	0.369933
46	-0.050214	-0.5501	0.291646
47	-0.070674	-0.7742	0.220168
48	-0.090387	-0.9901	0.16205

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.975839 & 10.6898 & 0 \tabularnewline
2 & 0.951916 & 10.4277 & 0 \tabularnewline
3 & 0.928228 & 10.1682 & 0 \tabularnewline
4 & 0.905361 & 9.9177 & 0 \tabularnewline
5 & 0.882981 & 9.6726 & 0 \tabularnewline
6 & 0.860364 & 9.4248 & 0 \tabularnewline
7 & 0.837073 & 9.1697 & 0 \tabularnewline
8 & 0.813886 & 8.9157 & 0 \tabularnewline
9 & 0.79083 & 8.6631 & 0 \tabularnewline
10 & 0.768423 & 8.4177 & 0 \tabularnewline
11 & 0.746418 & 8.1766 & 0 \tabularnewline
12 & 0.723787 & 7.9287 & 0 \tabularnewline
13 & 0.699863 & 7.6666 & 0 \tabularnewline
14 & 0.675998 & 7.4052 & 0 \tabularnewline
15 & 0.653987 & 7.1641 & 0 \tabularnewline
16 & 0.631457 & 6.9173 & 0 \tabularnewline
17 & 0.608693 & 6.6679 & 0 \tabularnewline
18 & 0.585777 & 6.4169 & 0 \tabularnewline
19 & 0.562159 & 6.1581 & 0 \tabularnewline
20 & 0.538212 & 5.8958 & 0 \tabularnewline
21 & 0.514422 & 5.6352 & 0 \tabularnewline
22 & 0.490909 & 5.3776 & 0 \tabularnewline
23 & 0.467989 & 5.1266 & 1e-06 \tabularnewline
24 & 0.444577 & 4.8701 & 2e-06 \tabularnewline
25 & 0.420439 & 4.6057 & 5e-06 \tabularnewline
26 & 0.396222 & 4.3404 & 1.5e-05 \tabularnewline
27 & 0.37116 & 4.0659 & 4.3e-05 \tabularnewline
28 & 0.346623 & 3.7971 & 0.000116 \tabularnewline
29 & 0.322842 & 3.5366 & 0.000289 \tabularnewline
30 & 0.298752 & 3.2727 & 0.000696 \tabularnewline
31 & 0.274065 & 3.0022 & 0.001631 \tabularnewline
32 & 0.248881 & 2.7263 & 0.003682 \tabularnewline
33 & 0.223943 & 2.4532 & 0.007799 \tabularnewline
34 & 0.199904 & 2.1898 & 0.015235 \tabularnewline
35 & 0.177094 & 1.94 & 0.027365 \tabularnewline
36 & 0.154589 & 1.6934 & 0.046484 \tabularnewline
37 & 0.13099 & 1.4349 & 0.076956 \tabularnewline
38 & 0.108051 & 1.1836 & 0.119448 \tabularnewline
39 & 0.087197 & 0.9552 & 0.170701 \tabularnewline
40 & 0.067192 & 0.7361 & 0.231567 \tabularnewline
41 & 0.04816 & 0.5276 & 0.299387 \tabularnewline
42 & 0.028867 & 0.3162 & 0.37619 \tabularnewline
43 & 0.009246 & 0.1013 & 0.459748 \tabularnewline
44 & -0.010532 & -0.1154 & 0.454172 \tabularnewline
45 & -0.03038 & -0.3328 & 0.369933 \tabularnewline
46 & -0.050214 & -0.5501 & 0.291646 \tabularnewline
47 & -0.070674 & -0.7742 & 0.220168 \tabularnewline
48 & -0.090387 & -0.9901 & 0.16205 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=293922&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]0.975839[/C][C]10.6898[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.951916[/C][C]10.4277[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.928228[/C][C]10.1682[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.905361[/C][C]9.9177[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.882981[/C][C]9.6726[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.860364[/C][C]9.4248[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.837073[/C][C]9.1697[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]0.813886[/C][C]8.9157[/C][C]0[/C][/ROW]
[ROW][C]9[/C][C]0.79083[/C][C]8.6631[/C][C]0[/C][/ROW]
[ROW][C]10[/C][C]0.768423[/C][C]8.4177[/C][C]0[/C][/ROW]
[ROW][C]11[/C][C]0.746418[/C][C]8.1766[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.723787[/C][C]7.9287[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.699863[/C][C]7.6666[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]0.675998[/C][C]7.4052[/C][C]0[/C][/ROW]
[ROW][C]15[/C][C]0.653987[/C][C]7.1641[/C][C]0[/C][/ROW]
[ROW][C]16[/C][C]0.631457[/C][C]6.9173[/C][C]0[/C][/ROW]
[ROW][C]17[/C][C]0.608693[/C][C]6.6679[/C][C]0[/C][/ROW]
[ROW][C]18[/C][C]0.585777[/C][C]6.4169[/C][C]0[/C][/ROW]
[ROW][C]19[/C][C]0.562159[/C][C]6.1581[/C][C]0[/C][/ROW]
[ROW][C]20[/C][C]0.538212[/C][C]5.8958[/C][C]0[/C][/ROW]
[ROW][C]21[/C][C]0.514422[/C][C]5.6352[/C][C]0[/C][/ROW]
[ROW][C]22[/C][C]0.490909[/C][C]5.3776[/C][C]0[/C][/ROW]
[ROW][C]23[/C][C]0.467989[/C][C]5.1266[/C][C]1e-06[/C][/ROW]
[ROW][C]24[/C][C]0.444577[/C][C]4.8701[/C][C]2e-06[/C][/ROW]
[ROW][C]25[/C][C]0.420439[/C][C]4.6057[/C][C]5e-06[/C][/ROW]
[ROW][C]26[/C][C]0.396222[/C][C]4.3404[/C][C]1.5e-05[/C][/ROW]
[ROW][C]27[/C][C]0.37116[/C][C]4.0659[/C][C]4.3e-05[/C][/ROW]
[ROW][C]28[/C][C]0.346623[/C][C]3.7971[/C][C]0.000116[/C][/ROW]
[ROW][C]29[/C][C]0.322842[/C][C]3.5366[/C][C]0.000289[/C][/ROW]
[ROW][C]30[/C][C]0.298752[/C][C]3.2727[/C][C]0.000696[/C][/ROW]
[ROW][C]31[/C][C]0.274065[/C][C]3.0022[/C][C]0.001631[/C][/ROW]
[ROW][C]32[/C][C]0.248881[/C][C]2.7263[/C][C]0.003682[/C][/ROW]
[ROW][C]33[/C][C]0.223943[/C][C]2.4532[/C][C]0.007799[/C][/ROW]
[ROW][C]34[/C][C]0.199904[/C][C]2.1898[/C][C]0.015235[/C][/ROW]
[ROW][C]35[/C][C]0.177094[/C][C]1.94[/C][C]0.027365[/C][/ROW]
[ROW][C]36[/C][C]0.154589[/C][C]1.6934[/C][C]0.046484[/C][/ROW]
[ROW][C]37[/C][C]0.13099[/C][C]1.4349[/C][C]0.076956[/C][/ROW]
[ROW][C]38[/C][C]0.108051[/C][C]1.1836[/C][C]0.119448[/C][/ROW]
[ROW][C]39[/C][C]0.087197[/C][C]0.9552[/C][C]0.170701[/C][/ROW]
[ROW][C]40[/C][C]0.067192[/C][C]0.7361[/C][C]0.231567[/C][/ROW]
[ROW][C]41[/C][C]0.04816[/C][C]0.5276[/C][C]0.299387[/C][/ROW]
[ROW][C]42[/C][C]0.028867[/C][C]0.3162[/C][C]0.37619[/C][/ROW]
[ROW][C]43[/C][C]0.009246[/C][C]0.1013[/C][C]0.459748[/C][/ROW]
[ROW][C]44[/C][C]-0.010532[/C][C]-0.1154[/C][C]0.454172[/C][/ROW]
[ROW][C]45[/C][C]-0.03038[/C][C]-0.3328[/C][C]0.369933[/C][/ROW]
[ROW][C]46[/C][C]-0.050214[/C][C]-0.5501[/C][C]0.291646[/C][/ROW]
[ROW][C]47[/C][C]-0.070674[/C][C]-0.7742[/C][C]0.220168[/C][/ROW]
[ROW][C]48[/C][C]-0.090387[/C][C]-0.9901[/C][C]0.16205[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=293922&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=293922&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	0.975839	10.6898	0
2	0.951916	10.4277	0
3	0.928228	10.1682	0
4	0.905361	9.9177	0
5	0.882981	9.6726	0
6	0.860364	9.4248	0
7	0.837073	9.1697	0
8	0.813886	8.9157	0
9	0.79083	8.6631	0
10	0.768423	8.4177	0
11	0.746418	8.1766	0
12	0.723787	7.9287	0
13	0.699863	7.6666	0
14	0.675998	7.4052	0
15	0.653987	7.1641	0
16	0.631457	6.9173	0
17	0.608693	6.6679	0
18	0.585777	6.4169	0
19	0.562159	6.1581	0
20	0.538212	5.8958	0
21	0.514422	5.6352	0
22	0.490909	5.3776	0
23	0.467989	5.1266	1e-06
24	0.444577	4.8701	2e-06
25	0.420439	4.6057	5e-06
26	0.396222	4.3404	1.5e-05
27	0.37116	4.0659	4.3e-05
28	0.346623	3.7971	0.000116
29	0.322842	3.5366	0.000289
30	0.298752	3.2727	0.000696
31	0.274065	3.0022	0.001631
32	0.248881	2.7263	0.003682
33	0.223943	2.4532	0.007799
34	0.199904	2.1898	0.015235
35	0.177094	1.94	0.027365
36	0.154589	1.6934	0.046484
37	0.13099	1.4349	0.076956
38	0.108051	1.1836	0.119448
39	0.087197	0.9552	0.170701
40	0.067192	0.7361	0.231567
41	0.04816	0.5276	0.299387
42	0.028867	0.3162	0.37619
43	0.009246	0.1013	0.459748
44	-0.010532	-0.1154	0.454172
45	-0.03038	-0.3328	0.369933
46	-0.050214	-0.5501	0.291646
47	-0.070674	-0.7742	0.220168
48	-0.090387	-0.9901	0.16205

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.975839	10.6898	0
2	-0.007245	-0.0794	0.468438
3	-0.007302	-0.08	0.468191
4	0.004949	0.0542	0.478427
5	-0.001616	-0.0177	0.492952
6	-0.016604	-0.1819	0.427988
7	-0.025948	-0.2842	0.388357
8	-0.010324	-0.1131	0.455072
9	-0.010187	-0.1116	0.455666
10	0.000224	0.0025	0.499022
11	-0.004297	-0.0471	0.481266
12	-0.02528	-0.2769	0.391155
13	-0.039669	-0.4346	0.332333
14	-0.012736	-0.1395	0.44464
15	0.024106	0.2641	0.396089
16	-0.025409	-0.2783	0.390613
17	-0.019137	-0.2096	0.417152
18	-0.015542	-0.1703	0.432549
19	-0.028008	-0.3068	0.379757
20	-0.022898	-0.2508	0.401185
21	-0.013899	-0.1523	0.439619
22	-0.010747	-0.1177	0.45324
23	-0.003762	-0.0412	0.483597
24	-0.024159	-0.2646	0.395868
25	-0.0299	-0.3275	0.371916
26	-0.019583	-0.2145	0.415254
27	-0.037471	-0.4105	0.341094
28	-0.007912	-0.0867	0.46554
29	-0.001512	-0.0166	0.493408
30	-0.025015	-0.274	0.392268
31	-0.030019	-0.3288	0.371423
32	-0.028664	-0.314	0.377034
33	-0.016005	-0.1753	0.430561
34	-0.003703	-0.0406	0.483857
35	0.005067	0.0555	0.477913
36	-0.011432	-0.1252	0.450275
37	-0.039764	-0.4356	0.331959
38	-0.005555	-0.0609	0.475788
39	0.023842	0.2612	0.397204
40	-0.003169	-0.0347	0.486183
41	-0.001143	-0.0125	0.495015
42	-0.019869	-0.2177	0.414032
43	-0.020911	-0.2291	0.409603
44	-0.022133	-0.2425	0.404421
45	-0.023111	-0.2532	0.400285
46	-0.023543	-0.2579	0.398463
47	-0.036532	-0.4002	0.344865
48	-0.003437	-0.0377	0.485014

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.975839 & 10.6898 & 0 \tabularnewline
2 & -0.007245 & -0.0794 & 0.468438 \tabularnewline
3 & -0.007302 & -0.08 & 0.468191 \tabularnewline
4 & 0.004949 & 0.0542 & 0.478427 \tabularnewline
5 & -0.001616 & -0.0177 & 0.492952 \tabularnewline
6 & -0.016604 & -0.1819 & 0.427988 \tabularnewline
7 & -0.025948 & -0.2842 & 0.388357 \tabularnewline
8 & -0.010324 & -0.1131 & 0.455072 \tabularnewline
9 & -0.010187 & -0.1116 & 0.455666 \tabularnewline
10 & 0.000224 & 0.0025 & 0.499022 \tabularnewline
11 & -0.004297 & -0.0471 & 0.481266 \tabularnewline
12 & -0.02528 & -0.2769 & 0.391155 \tabularnewline
13 & -0.039669 & -0.4346 & 0.332333 \tabularnewline
14 & -0.012736 & -0.1395 & 0.44464 \tabularnewline
15 & 0.024106 & 0.2641 & 0.396089 \tabularnewline
16 & -0.025409 & -0.2783 & 0.390613 \tabularnewline
17 & -0.019137 & -0.2096 & 0.417152 \tabularnewline
18 & -0.015542 & -0.1703 & 0.432549 \tabularnewline
19 & -0.028008 & -0.3068 & 0.379757 \tabularnewline
20 & -0.022898 & -0.2508 & 0.401185 \tabularnewline
21 & -0.013899 & -0.1523 & 0.439619 \tabularnewline
22 & -0.010747 & -0.1177 & 0.45324 \tabularnewline
23 & -0.003762 & -0.0412 & 0.483597 \tabularnewline
24 & -0.024159 & -0.2646 & 0.395868 \tabularnewline
25 & -0.0299 & -0.3275 & 0.371916 \tabularnewline
26 & -0.019583 & -0.2145 & 0.415254 \tabularnewline
27 & -0.037471 & -0.4105 & 0.341094 \tabularnewline
28 & -0.007912 & -0.0867 & 0.46554 \tabularnewline
29 & -0.001512 & -0.0166 & 0.493408 \tabularnewline
30 & -0.025015 & -0.274 & 0.392268 \tabularnewline
31 & -0.030019 & -0.3288 & 0.371423 \tabularnewline
32 & -0.028664 & -0.314 & 0.377034 \tabularnewline
33 & -0.016005 & -0.1753 & 0.430561 \tabularnewline
34 & -0.003703 & -0.0406 & 0.483857 \tabularnewline
35 & 0.005067 & 0.0555 & 0.477913 \tabularnewline
36 & -0.011432 & -0.1252 & 0.450275 \tabularnewline
37 & -0.039764 & -0.4356 & 0.331959 \tabularnewline
38 & -0.005555 & -0.0609 & 0.475788 \tabularnewline
39 & 0.023842 & 0.2612 & 0.397204 \tabularnewline
40 & -0.003169 & -0.0347 & 0.486183 \tabularnewline
41 & -0.001143 & -0.0125 & 0.495015 \tabularnewline
42 & -0.019869 & -0.2177 & 0.414032 \tabularnewline
43 & -0.020911 & -0.2291 & 0.409603 \tabularnewline
44 & -0.022133 & -0.2425 & 0.404421 \tabularnewline
45 & -0.023111 & -0.2532 & 0.400285 \tabularnewline
46 & -0.023543 & -0.2579 & 0.398463 \tabularnewline
47 & -0.036532 & -0.4002 & 0.344865 \tabularnewline
48 & -0.003437 & -0.0377 & 0.485014 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=293922&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]0.975839[/C][C]10.6898[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.007245[/C][C]-0.0794[/C][C]0.468438[/C][/ROW]
[ROW][C]3[/C][C]-0.007302[/C][C]-0.08[/C][C]0.468191[/C][/ROW]
[ROW][C]4[/C][C]0.004949[/C][C]0.0542[/C][C]0.478427[/C][/ROW]
[ROW][C]5[/C][C]-0.001616[/C][C]-0.0177[/C][C]0.492952[/C][/ROW]
[ROW][C]6[/C][C]-0.016604[/C][C]-0.1819[/C][C]0.427988[/C][/ROW]
[ROW][C]7[/C][C]-0.025948[/C][C]-0.2842[/C][C]0.388357[/C][/ROW]
[ROW][C]8[/C][C]-0.010324[/C][C]-0.1131[/C][C]0.455072[/C][/ROW]
[ROW][C]9[/C][C]-0.010187[/C][C]-0.1116[/C][C]0.455666[/C][/ROW]
[ROW][C]10[/C][C]0.000224[/C][C]0.0025[/C][C]0.499022[/C][/ROW]
[ROW][C]11[/C][C]-0.004297[/C][C]-0.0471[/C][C]0.481266[/C][/ROW]
[ROW][C]12[/C][C]-0.02528[/C][C]-0.2769[/C][C]0.391155[/C][/ROW]
[ROW][C]13[/C][C]-0.039669[/C][C]-0.4346[/C][C]0.332333[/C][/ROW]
[ROW][C]14[/C][C]-0.012736[/C][C]-0.1395[/C][C]0.44464[/C][/ROW]
[ROW][C]15[/C][C]0.024106[/C][C]0.2641[/C][C]0.396089[/C][/ROW]
[ROW][C]16[/C][C]-0.025409[/C][C]-0.2783[/C][C]0.390613[/C][/ROW]
[ROW][C]17[/C][C]-0.019137[/C][C]-0.2096[/C][C]0.417152[/C][/ROW]
[ROW][C]18[/C][C]-0.015542[/C][C]-0.1703[/C][C]0.432549[/C][/ROW]
[ROW][C]19[/C][C]-0.028008[/C][C]-0.3068[/C][C]0.379757[/C][/ROW]
[ROW][C]20[/C][C]-0.022898[/C][C]-0.2508[/C][C]0.401185[/C][/ROW]
[ROW][C]21[/C][C]-0.013899[/C][C]-0.1523[/C][C]0.439619[/C][/ROW]
[ROW][C]22[/C][C]-0.010747[/C][C]-0.1177[/C][C]0.45324[/C][/ROW]
[ROW][C]23[/C][C]-0.003762[/C][C]-0.0412[/C][C]0.483597[/C][/ROW]
[ROW][C]24[/C][C]-0.024159[/C][C]-0.2646[/C][C]0.395868[/C][/ROW]
[ROW][C]25[/C][C]-0.0299[/C][C]-0.3275[/C][C]0.371916[/C][/ROW]
[ROW][C]26[/C][C]-0.019583[/C][C]-0.2145[/C][C]0.415254[/C][/ROW]
[ROW][C]27[/C][C]-0.037471[/C][C]-0.4105[/C][C]0.341094[/C][/ROW]
[ROW][C]28[/C][C]-0.007912[/C][C]-0.0867[/C][C]0.46554[/C][/ROW]
[ROW][C]29[/C][C]-0.001512[/C][C]-0.0166[/C][C]0.493408[/C][/ROW]
[ROW][C]30[/C][C]-0.025015[/C][C]-0.274[/C][C]0.392268[/C][/ROW]
[ROW][C]31[/C][C]-0.030019[/C][C]-0.3288[/C][C]0.371423[/C][/ROW]
[ROW][C]32[/C][C]-0.028664[/C][C]-0.314[/C][C]0.377034[/C][/ROW]
[ROW][C]33[/C][C]-0.016005[/C][C]-0.1753[/C][C]0.430561[/C][/ROW]
[ROW][C]34[/C][C]-0.003703[/C][C]-0.0406[/C][C]0.483857[/C][/ROW]
[ROW][C]35[/C][C]0.005067[/C][C]0.0555[/C][C]0.477913[/C][/ROW]
[ROW][C]36[/C][C]-0.011432[/C][C]-0.1252[/C][C]0.450275[/C][/ROW]
[ROW][C]37[/C][C]-0.039764[/C][C]-0.4356[/C][C]0.331959[/C][/ROW]
[ROW][C]38[/C][C]-0.005555[/C][C]-0.0609[/C][C]0.475788[/C][/ROW]
[ROW][C]39[/C][C]0.023842[/C][C]0.2612[/C][C]0.397204[/C][/ROW]
[ROW][C]40[/C][C]-0.003169[/C][C]-0.0347[/C][C]0.486183[/C][/ROW]
[ROW][C]41[/C][C]-0.001143[/C][C]-0.0125[/C][C]0.495015[/C][/ROW]
[ROW][C]42[/C][C]-0.019869[/C][C]-0.2177[/C][C]0.414032[/C][/ROW]
[ROW][C]43[/C][C]-0.020911[/C][C]-0.2291[/C][C]0.409603[/C][/ROW]
[ROW][C]44[/C][C]-0.022133[/C][C]-0.2425[/C][C]0.404421[/C][/ROW]
[ROW][C]45[/C][C]-0.023111[/C][C]-0.2532[/C][C]0.400285[/C][/ROW]
[ROW][C]46[/C][C]-0.023543[/C][C]-0.2579[/C][C]0.398463[/C][/ROW]
[ROW][C]47[/C][C]-0.036532[/C][C]-0.4002[/C][C]0.344865[/C][/ROW]
[ROW][C]48[/C][C]-0.003437[/C][C]-0.0377[/C][C]0.485014[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=293922&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=293922&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	0.975839	10.6898	0
2	-0.007245	-0.0794	0.468438
3	-0.007302	-0.08	0.468191
4	0.004949	0.0542	0.478427
5	-0.001616	-0.0177	0.492952
6	-0.016604	-0.1819	0.427988
7	-0.025948	-0.2842	0.388357
8	-0.010324	-0.1131	0.455072
9	-0.010187	-0.1116	0.455666
10	0.000224	0.0025	0.499022
11	-0.004297	-0.0471	0.481266
12	-0.02528	-0.2769	0.391155
13	-0.039669	-0.4346	0.332333
14	-0.012736	-0.1395	0.44464
15	0.024106	0.2641	0.396089
16	-0.025409	-0.2783	0.390613
17	-0.019137	-0.2096	0.417152
18	-0.015542	-0.1703	0.432549
19	-0.028008	-0.3068	0.379757
20	-0.022898	-0.2508	0.401185
21	-0.013899	-0.1523	0.439619
22	-0.010747	-0.1177	0.45324
23	-0.003762	-0.0412	0.483597
24	-0.024159	-0.2646	0.395868
25	-0.0299	-0.3275	0.371916
26	-0.019583	-0.2145	0.415254
27	-0.037471	-0.4105	0.341094
28	-0.007912	-0.0867	0.46554
29	-0.001512	-0.0166	0.493408
30	-0.025015	-0.274	0.392268
31	-0.030019	-0.3288	0.371423
32	-0.028664	-0.314	0.377034
33	-0.016005	-0.1753	0.430561
34	-0.003703	-0.0406	0.483857
35	0.005067	0.0555	0.477913
36	-0.011432	-0.1252	0.450275
37	-0.039764	-0.4356	0.331959
38	-0.005555	-0.0609	0.475788
39	0.023842	0.2612	0.397204
40	-0.003169	-0.0347	0.486183
41	-0.001143	-0.0125	0.495015
42	-0.019869	-0.2177	0.414032
43	-0.020911	-0.2291	0.409603
44	-0.022133	-0.2425	0.404421
45	-0.023111	-0.2532	0.400285
46	-0.023543	-0.2579	0.398463
47	-0.036532	-0.4002	0.344865
48	-0.003437	-0.0377	0.485014

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Figure 3

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

Parameters (R input):

par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; 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)
x <- na.omit(x)
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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code