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rwasp_autocorrelation.wasp

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(Partial) Autocorrelation Function

Date of computation

Sat, 12 Mar 2016 12:32:16 +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/t14577859716rkd3od39pg5m55.htm/, Retrieved Sun, 05 May 2024 13:22:05 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=293905, Retrieved Sun, 05 May 2024 13:22:05 +0000

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-       [(Partial) Autocorrelation Function] [] [2016-03-12 12:32:16] [56edb0d8f6220d107203045c2c4d5731] [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	1 seconds
R Server	'Sir Ronald Aylmer Fisher' @ fisher.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 & 1 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=293905&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]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=293905&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=293905&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	1 seconds
R Server	'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.98174	10.7544	0
2	0.962754	10.5464	0
3	0.943159	10.3318	0
4	0.923352	10.1148	0
5	0.903507	9.8974	0
6	0.882911	9.6718	0
7	0.861593	9.4383	0
8	0.840523	9.2075	0
9	0.819479	8.9769	0
10	0.79832	8.7452	0
11	0.777238	8.5142	0
12	0.755697	8.2782	0
13	0.733502	8.0351	0
14	0.711024	7.7889	0
15	0.688588	7.5431	0
16	0.665692	7.2923	0
17	0.642295	7.036	0
18	0.618446	6.7747	0
19	0.594472	6.5121	0
20	0.570436	6.2488	0
21	0.546191	5.9832	0
22	0.521514	5.7129	0
23	0.496325	5.437	0
24	0.470476	5.1538	1e-06
25	0.445769	4.8832	2e-06
26	0.421047	4.6123	5e-06
27	0.395551	4.333	1.5e-05
28	0.369829	4.0513	4.5e-05
29	0.343545	3.7633	0.00013
30	0.317013	3.4727	0.000359
31	0.289981	3.1766	0.000947
32	0.26255	2.8761	0.002383
33	0.23515	2.5759	0.005605
34	0.207406	2.272	0.012433
35	0.179843	1.9701	0.025566
36	0.152147	1.6667	0.049092
37	0.124303	1.3617	0.087927
38	0.096807	1.0605	0.145532
39	0.069364	0.7598	0.22442
40	0.042244	0.4628	0.322189
41	0.015763	0.1727	0.431598
42	-0.010783	-0.1181	0.453086
43	-0.037265	-0.4082	0.341922
44	-0.063817	-0.6991	0.242927
45	-0.089933	-0.9852	0.163261
46	-0.115422	-1.2644	0.104272
47	-0.13976	-1.531	0.064202
48	-0.163609	-1.7922	0.037806

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.98174 & 10.7544 & 0 \tabularnewline
2 & 0.962754 & 10.5464 & 0 \tabularnewline
3 & 0.943159 & 10.3318 & 0 \tabularnewline
4 & 0.923352 & 10.1148 & 0 \tabularnewline
5 & 0.903507 & 9.8974 & 0 \tabularnewline
6 & 0.882911 & 9.6718 & 0 \tabularnewline
7 & 0.861593 & 9.4383 & 0 \tabularnewline
8 & 0.840523 & 9.2075 & 0 \tabularnewline
9 & 0.819479 & 8.9769 & 0 \tabularnewline
10 & 0.79832 & 8.7452 & 0 \tabularnewline
11 & 0.777238 & 8.5142 & 0 \tabularnewline
12 & 0.755697 & 8.2782 & 0 \tabularnewline
13 & 0.733502 & 8.0351 & 0 \tabularnewline
14 & 0.711024 & 7.7889 & 0 \tabularnewline
15 & 0.688588 & 7.5431 & 0 \tabularnewline
16 & 0.665692 & 7.2923 & 0 \tabularnewline
17 & 0.642295 & 7.036 & 0 \tabularnewline
18 & 0.618446 & 6.7747 & 0 \tabularnewline
19 & 0.594472 & 6.5121 & 0 \tabularnewline
20 & 0.570436 & 6.2488 & 0 \tabularnewline
21 & 0.546191 & 5.9832 & 0 \tabularnewline
22 & 0.521514 & 5.7129 & 0 \tabularnewline
23 & 0.496325 & 5.437 & 0 \tabularnewline
24 & 0.470476 & 5.1538 & 1e-06 \tabularnewline
25 & 0.445769 & 4.8832 & 2e-06 \tabularnewline
26 & 0.421047 & 4.6123 & 5e-06 \tabularnewline
27 & 0.395551 & 4.333 & 1.5e-05 \tabularnewline
28 & 0.369829 & 4.0513 & 4.5e-05 \tabularnewline
29 & 0.343545 & 3.7633 & 0.00013 \tabularnewline
30 & 0.317013 & 3.4727 & 0.000359 \tabularnewline
31 & 0.289981 & 3.1766 & 0.000947 \tabularnewline
32 & 0.26255 & 2.8761 & 0.002383 \tabularnewline
33 & 0.23515 & 2.5759 & 0.005605 \tabularnewline
34 & 0.207406 & 2.272 & 0.012433 \tabularnewline
35 & 0.179843 & 1.9701 & 0.025566 \tabularnewline
36 & 0.152147 & 1.6667 & 0.049092 \tabularnewline
37 & 0.124303 & 1.3617 & 0.087927 \tabularnewline
38 & 0.096807 & 1.0605 & 0.145532 \tabularnewline
39 & 0.069364 & 0.7598 & 0.22442 \tabularnewline
40 & 0.042244 & 0.4628 & 0.322189 \tabularnewline
41 & 0.015763 & 0.1727 & 0.431598 \tabularnewline
42 & -0.010783 & -0.1181 & 0.453086 \tabularnewline
43 & -0.037265 & -0.4082 & 0.341922 \tabularnewline
44 & -0.063817 & -0.6991 & 0.242927 \tabularnewline
45 & -0.089933 & -0.9852 & 0.163261 \tabularnewline
46 & -0.115422 & -1.2644 & 0.104272 \tabularnewline
47 & -0.13976 & -1.531 & 0.064202 \tabularnewline
48 & -0.163609 & -1.7922 & 0.037806 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=293905&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]0.98174[/C][C]10.7544[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.962754[/C][C]10.5464[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.943159[/C][C]10.3318[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.923352[/C][C]10.1148[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.903507[/C][C]9.8974[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.882911[/C][C]9.6718[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.861593[/C][C]9.4383[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]0.840523[/C][C]9.2075[/C][C]0[/C][/ROW]
[ROW][C]9[/C][C]0.819479[/C][C]8.9769[/C][C]0[/C][/ROW]
[ROW][C]10[/C][C]0.79832[/C][C]8.7452[/C][C]0[/C][/ROW]
[ROW][C]11[/C][C]0.777238[/C][C]8.5142[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.755697[/C][C]8.2782[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.733502[/C][C]8.0351[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]0.711024[/C][C]7.7889[/C][C]0[/C][/ROW]
[ROW][C]15[/C][C]0.688588[/C][C]7.5431[/C][C]0[/C][/ROW]
[ROW][C]16[/C][C]0.665692[/C][C]7.2923[/C][C]0[/C][/ROW]
[ROW][C]17[/C][C]0.642295[/C][C]7.036[/C][C]0[/C][/ROW]
[ROW][C]18[/C][C]0.618446[/C][C]6.7747[/C][C]0[/C][/ROW]
[ROW][C]19[/C][C]0.594472[/C][C]6.5121[/C][C]0[/C][/ROW]
[ROW][C]20[/C][C]0.570436[/C][C]6.2488[/C][C]0[/C][/ROW]
[ROW][C]21[/C][C]0.546191[/C][C]5.9832[/C][C]0[/C][/ROW]
[ROW][C]22[/C][C]0.521514[/C][C]5.7129[/C][C]0[/C][/ROW]
[ROW][C]23[/C][C]0.496325[/C][C]5.437[/C][C]0[/C][/ROW]
[ROW][C]24[/C][C]0.470476[/C][C]5.1538[/C][C]1e-06[/C][/ROW]
[ROW][C]25[/C][C]0.445769[/C][C]4.8832[/C][C]2e-06[/C][/ROW]
[ROW][C]26[/C][C]0.421047[/C][C]4.6123[/C][C]5e-06[/C][/ROW]
[ROW][C]27[/C][C]0.395551[/C][C]4.333[/C][C]1.5e-05[/C][/ROW]
[ROW][C]28[/C][C]0.369829[/C][C]4.0513[/C][C]4.5e-05[/C][/ROW]
[ROW][C]29[/C][C]0.343545[/C][C]3.7633[/C][C]0.00013[/C][/ROW]
[ROW][C]30[/C][C]0.317013[/C][C]3.4727[/C][C]0.000359[/C][/ROW]
[ROW][C]31[/C][C]0.289981[/C][C]3.1766[/C][C]0.000947[/C][/ROW]
[ROW][C]32[/C][C]0.26255[/C][C]2.8761[/C][C]0.002383[/C][/ROW]
[ROW][C]33[/C][C]0.23515[/C][C]2.5759[/C][C]0.005605[/C][/ROW]
[ROW][C]34[/C][C]0.207406[/C][C]2.272[/C][C]0.012433[/C][/ROW]
[ROW][C]35[/C][C]0.179843[/C][C]1.9701[/C][C]0.025566[/C][/ROW]
[ROW][C]36[/C][C]0.152147[/C][C]1.6667[/C][C]0.049092[/C][/ROW]
[ROW][C]37[/C][C]0.124303[/C][C]1.3617[/C][C]0.087927[/C][/ROW]
[ROW][C]38[/C][C]0.096807[/C][C]1.0605[/C][C]0.145532[/C][/ROW]
[ROW][C]39[/C][C]0.069364[/C][C]0.7598[/C][C]0.22442[/C][/ROW]
[ROW][C]40[/C][C]0.042244[/C][C]0.4628[/C][C]0.322189[/C][/ROW]
[ROW][C]41[/C][C]0.015763[/C][C]0.1727[/C][C]0.431598[/C][/ROW]
[ROW][C]42[/C][C]-0.010783[/C][C]-0.1181[/C][C]0.453086[/C][/ROW]
[ROW][C]43[/C][C]-0.037265[/C][C]-0.4082[/C][C]0.341922[/C][/ROW]
[ROW][C]44[/C][C]-0.063817[/C][C]-0.6991[/C][C]0.242927[/C][/ROW]
[ROW][C]45[/C][C]-0.089933[/C][C]-0.9852[/C][C]0.163261[/C][/ROW]
[ROW][C]46[/C][C]-0.115422[/C][C]-1.2644[/C][C]0.104272[/C][/ROW]
[ROW][C]47[/C][C]-0.13976[/C][C]-1.531[/C][C]0.064202[/C][/ROW]
[ROW][C]48[/C][C]-0.163609[/C][C]-1.7922[/C][C]0.037806[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=293905&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=293905&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	0.98174	10.7544	0
2	0.962754	10.5464	0
3	0.943159	10.3318	0
4	0.923352	10.1148	0
5	0.903507	9.8974	0
6	0.882911	9.6718	0
7	0.861593	9.4383	0
8	0.840523	9.2075	0
9	0.819479	8.9769	0
10	0.79832	8.7452	0
11	0.777238	8.5142	0
12	0.755697	8.2782	0
13	0.733502	8.0351	0
14	0.711024	7.7889	0
15	0.688588	7.5431	0
16	0.665692	7.2923	0
17	0.642295	7.036	0
18	0.618446	6.7747	0
19	0.594472	6.5121	0
20	0.570436	6.2488	0
21	0.546191	5.9832	0
22	0.521514	5.7129	0
23	0.496325	5.437	0
24	0.470476	5.1538	1e-06
25	0.445769	4.8832	2e-06
26	0.421047	4.6123	5e-06
27	0.395551	4.333	1.5e-05
28	0.369829	4.0513	4.5e-05
29	0.343545	3.7633	0.00013
30	0.317013	3.4727	0.000359
31	0.289981	3.1766	0.000947
32	0.26255	2.8761	0.002383
33	0.23515	2.5759	0.005605
34	0.207406	2.272	0.012433
35	0.179843	1.9701	0.025566
36	0.152147	1.6667	0.049092
37	0.124303	1.3617	0.087927
38	0.096807	1.0605	0.145532
39	0.069364	0.7598	0.22442
40	0.042244	0.4628	0.322189
41	0.015763	0.1727	0.431598
42	-0.010783	-0.1181	0.453086
43	-0.037265	-0.4082	0.341922
44	-0.063817	-0.6991	0.242927
45	-0.089933	-0.9852	0.163261
46	-0.115422	-1.2644	0.104272
47	-0.13976	-1.531	0.064202
48	-0.163609	-1.7922	0.037806

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.98174	10.7544	0
2	-0.029307	-0.321	0.374369
3	-0.026087	-0.2858	0.387774
4	-0.015349	-0.1681	0.433379
5	-0.010845	-0.1188	0.452817
6	-0.031042	-0.3401	0.367206
7	-0.0301	-0.3297	0.371091
8	-0.003237	-0.0355	0.485887
9	-0.010187	-0.1116	0.455668
10	-0.014835	-0.1625	0.43559
11	-0.009221	-0.101	0.459856
12	-0.023822	-0.261	0.397286
13	-0.029962	-0.3282	0.371661
14	-0.020062	-0.2198	0.413211
15	-0.010947	-0.1199	0.452374
16	-0.025762	-0.2822	0.389134
17	-0.026988	-0.2956	0.384009
18	-0.024932	-0.2731	0.392615
19	-0.016659	-0.1825	0.427754
20	-0.016494	-0.1807	0.428462
21	-0.020788	-0.2277	0.410125
22	-0.026667	-0.2921	0.38535
23	-0.02937	-0.3217	0.374108
24	-0.034135	-0.3739	0.354557
25	0.015458	0.1693	0.432908
26	-0.017886	-0.1959	0.422499
27	-0.03929	-0.4304	0.333839
28	-0.023038	-0.2524	0.400592
29	-0.032213	-0.3529	0.362398
30	-0.026451	-0.2898	0.386252
31	-0.035286	-0.3865	0.349891
32	-0.030392	-0.3329	0.369885
33	-0.019081	-0.209	0.417395
34	-0.031244	-0.3423	0.366378
35	-0.016535	-0.1811	0.428285
36	-0.027144	-0.2973	0.383359
37	-0.029147	-0.3193	0.375033
38	-0.015168	-0.1662	0.434157
39	-0.022697	-0.2486	0.402035
40	-0.016858	-0.1847	0.426898
41	-0.009246	-0.1013	0.459746
42	-0.02835	-0.3106	0.378338
43	-0.024813	-0.2718	0.393118
44	-0.029056	-0.3183	0.375409
45	-0.015574	-0.1706	0.432412
46	-0.011832	-0.1296	0.448545
47	0.002674	0.0293	0.488341
48	-0.015458	-0.1693	0.432909

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.98174 & 10.7544 & 0 \tabularnewline
2 & -0.029307 & -0.321 & 0.374369 \tabularnewline
3 & -0.026087 & -0.2858 & 0.387774 \tabularnewline
4 & -0.015349 & -0.1681 & 0.433379 \tabularnewline
5 & -0.010845 & -0.1188 & 0.452817 \tabularnewline
6 & -0.031042 & -0.3401 & 0.367206 \tabularnewline
7 & -0.0301 & -0.3297 & 0.371091 \tabularnewline
8 & -0.003237 & -0.0355 & 0.485887 \tabularnewline
9 & -0.010187 & -0.1116 & 0.455668 \tabularnewline
10 & -0.014835 & -0.1625 & 0.43559 \tabularnewline
11 & -0.009221 & -0.101 & 0.459856 \tabularnewline
12 & -0.023822 & -0.261 & 0.397286 \tabularnewline
13 & -0.029962 & -0.3282 & 0.371661 \tabularnewline
14 & -0.020062 & -0.2198 & 0.413211 \tabularnewline
15 & -0.010947 & -0.1199 & 0.452374 \tabularnewline
16 & -0.025762 & -0.2822 & 0.389134 \tabularnewline
17 & -0.026988 & -0.2956 & 0.384009 \tabularnewline
18 & -0.024932 & -0.2731 & 0.392615 \tabularnewline
19 & -0.016659 & -0.1825 & 0.427754 \tabularnewline
20 & -0.016494 & -0.1807 & 0.428462 \tabularnewline
21 & -0.020788 & -0.2277 & 0.410125 \tabularnewline
22 & -0.026667 & -0.2921 & 0.38535 \tabularnewline
23 & -0.02937 & -0.3217 & 0.374108 \tabularnewline
24 & -0.034135 & -0.3739 & 0.354557 \tabularnewline
25 & 0.015458 & 0.1693 & 0.432908 \tabularnewline
26 & -0.017886 & -0.1959 & 0.422499 \tabularnewline
27 & -0.03929 & -0.4304 & 0.333839 \tabularnewline
28 & -0.023038 & -0.2524 & 0.400592 \tabularnewline
29 & -0.032213 & -0.3529 & 0.362398 \tabularnewline
30 & -0.026451 & -0.2898 & 0.386252 \tabularnewline
31 & -0.035286 & -0.3865 & 0.349891 \tabularnewline
32 & -0.030392 & -0.3329 & 0.369885 \tabularnewline
33 & -0.019081 & -0.209 & 0.417395 \tabularnewline
34 & -0.031244 & -0.3423 & 0.366378 \tabularnewline
35 & -0.016535 & -0.1811 & 0.428285 \tabularnewline
36 & -0.027144 & -0.2973 & 0.383359 \tabularnewline
37 & -0.029147 & -0.3193 & 0.375033 \tabularnewline
38 & -0.015168 & -0.1662 & 0.434157 \tabularnewline
39 & -0.022697 & -0.2486 & 0.402035 \tabularnewline
40 & -0.016858 & -0.1847 & 0.426898 \tabularnewline
41 & -0.009246 & -0.1013 & 0.459746 \tabularnewline
42 & -0.02835 & -0.3106 & 0.378338 \tabularnewline
43 & -0.024813 & -0.2718 & 0.393118 \tabularnewline
44 & -0.029056 & -0.3183 & 0.375409 \tabularnewline
45 & -0.015574 & -0.1706 & 0.432412 \tabularnewline
46 & -0.011832 & -0.1296 & 0.448545 \tabularnewline
47 & 0.002674 & 0.0293 & 0.488341 \tabularnewline
48 & -0.015458 & -0.1693 & 0.432909 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=293905&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]0.98174[/C][C]10.7544[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.029307[/C][C]-0.321[/C][C]0.374369[/C][/ROW]
[ROW][C]3[/C][C]-0.026087[/C][C]-0.2858[/C][C]0.387774[/C][/ROW]
[ROW][C]4[/C][C]-0.015349[/C][C]-0.1681[/C][C]0.433379[/C][/ROW]
[ROW][C]5[/C][C]-0.010845[/C][C]-0.1188[/C][C]0.452817[/C][/ROW]
[ROW][C]6[/C][C]-0.031042[/C][C]-0.3401[/C][C]0.367206[/C][/ROW]
[ROW][C]7[/C][C]-0.0301[/C][C]-0.3297[/C][C]0.371091[/C][/ROW]
[ROW][C]8[/C][C]-0.003237[/C][C]-0.0355[/C][C]0.485887[/C][/ROW]
[ROW][C]9[/C][C]-0.010187[/C][C]-0.1116[/C][C]0.455668[/C][/ROW]
[ROW][C]10[/C][C]-0.014835[/C][C]-0.1625[/C][C]0.43559[/C][/ROW]
[ROW][C]11[/C][C]-0.009221[/C][C]-0.101[/C][C]0.459856[/C][/ROW]
[ROW][C]12[/C][C]-0.023822[/C][C]-0.261[/C][C]0.397286[/C][/ROW]
[ROW][C]13[/C][C]-0.029962[/C][C]-0.3282[/C][C]0.371661[/C][/ROW]
[ROW][C]14[/C][C]-0.020062[/C][C]-0.2198[/C][C]0.413211[/C][/ROW]
[ROW][C]15[/C][C]-0.010947[/C][C]-0.1199[/C][C]0.452374[/C][/ROW]
[ROW][C]16[/C][C]-0.025762[/C][C]-0.2822[/C][C]0.389134[/C][/ROW]
[ROW][C]17[/C][C]-0.026988[/C][C]-0.2956[/C][C]0.384009[/C][/ROW]
[ROW][C]18[/C][C]-0.024932[/C][C]-0.2731[/C][C]0.392615[/C][/ROW]
[ROW][C]19[/C][C]-0.016659[/C][C]-0.1825[/C][C]0.427754[/C][/ROW]
[ROW][C]20[/C][C]-0.016494[/C][C]-0.1807[/C][C]0.428462[/C][/ROW]
[ROW][C]21[/C][C]-0.020788[/C][C]-0.2277[/C][C]0.410125[/C][/ROW]
[ROW][C]22[/C][C]-0.026667[/C][C]-0.2921[/C][C]0.38535[/C][/ROW]
[ROW][C]23[/C][C]-0.02937[/C][C]-0.3217[/C][C]0.374108[/C][/ROW]
[ROW][C]24[/C][C]-0.034135[/C][C]-0.3739[/C][C]0.354557[/C][/ROW]
[ROW][C]25[/C][C]0.015458[/C][C]0.1693[/C][C]0.432908[/C][/ROW]
[ROW][C]26[/C][C]-0.017886[/C][C]-0.1959[/C][C]0.422499[/C][/ROW]
[ROW][C]27[/C][C]-0.03929[/C][C]-0.4304[/C][C]0.333839[/C][/ROW]
[ROW][C]28[/C][C]-0.023038[/C][C]-0.2524[/C][C]0.400592[/C][/ROW]
[ROW][C]29[/C][C]-0.032213[/C][C]-0.3529[/C][C]0.362398[/C][/ROW]
[ROW][C]30[/C][C]-0.026451[/C][C]-0.2898[/C][C]0.386252[/C][/ROW]
[ROW][C]31[/C][C]-0.035286[/C][C]-0.3865[/C][C]0.349891[/C][/ROW]
[ROW][C]32[/C][C]-0.030392[/C][C]-0.3329[/C][C]0.369885[/C][/ROW]
[ROW][C]33[/C][C]-0.019081[/C][C]-0.209[/C][C]0.417395[/C][/ROW]
[ROW][C]34[/C][C]-0.031244[/C][C]-0.3423[/C][C]0.366378[/C][/ROW]
[ROW][C]35[/C][C]-0.016535[/C][C]-0.1811[/C][C]0.428285[/C][/ROW]
[ROW][C]36[/C][C]-0.027144[/C][C]-0.2973[/C][C]0.383359[/C][/ROW]
[ROW][C]37[/C][C]-0.029147[/C][C]-0.3193[/C][C]0.375033[/C][/ROW]
[ROW][C]38[/C][C]-0.015168[/C][C]-0.1662[/C][C]0.434157[/C][/ROW]
[ROW][C]39[/C][C]-0.022697[/C][C]-0.2486[/C][C]0.402035[/C][/ROW]
[ROW][C]40[/C][C]-0.016858[/C][C]-0.1847[/C][C]0.426898[/C][/ROW]
[ROW][C]41[/C][C]-0.009246[/C][C]-0.1013[/C][C]0.459746[/C][/ROW]
[ROW][C]42[/C][C]-0.02835[/C][C]-0.3106[/C][C]0.378338[/C][/ROW]
[ROW][C]43[/C][C]-0.024813[/C][C]-0.2718[/C][C]0.393118[/C][/ROW]
[ROW][C]44[/C][C]-0.029056[/C][C]-0.3183[/C][C]0.375409[/C][/ROW]
[ROW][C]45[/C][C]-0.015574[/C][C]-0.1706[/C][C]0.432412[/C][/ROW]
[ROW][C]46[/C][C]-0.011832[/C][C]-0.1296[/C][C]0.448545[/C][/ROW]
[ROW][C]47[/C][C]0.002674[/C][C]0.0293[/C][C]0.488341[/C][/ROW]
[ROW][C]48[/C][C]-0.015458[/C][C]-0.1693[/C][C]0.432909[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=293905&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=293905&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	0.98174	10.7544	0
2	-0.029307	-0.321	0.374369
3	-0.026087	-0.2858	0.387774
4	-0.015349	-0.1681	0.433379
5	-0.010845	-0.1188	0.452817
6	-0.031042	-0.3401	0.367206
7	-0.0301	-0.3297	0.371091
8	-0.003237	-0.0355	0.485887
9	-0.010187	-0.1116	0.455668
10	-0.014835	-0.1625	0.43559
11	-0.009221	-0.101	0.459856
12	-0.023822	-0.261	0.397286
13	-0.029962	-0.3282	0.371661
14	-0.020062	-0.2198	0.413211
15	-0.010947	-0.1199	0.452374
16	-0.025762	-0.2822	0.389134
17	-0.026988	-0.2956	0.384009
18	-0.024932	-0.2731	0.392615
19	-0.016659	-0.1825	0.427754
20	-0.016494	-0.1807	0.428462
21	-0.020788	-0.2277	0.410125
22	-0.026667	-0.2921	0.38535
23	-0.02937	-0.3217	0.374108
24	-0.034135	-0.3739	0.354557
25	0.015458	0.1693	0.432908
26	-0.017886	-0.1959	0.422499
27	-0.03929	-0.4304	0.333839
28	-0.023038	-0.2524	0.400592
29	-0.032213	-0.3529	0.362398
30	-0.026451	-0.2898	0.386252
31	-0.035286	-0.3865	0.349891
32	-0.030392	-0.3329	0.369885
33	-0.019081	-0.209	0.417395
34	-0.031244	-0.3423	0.366378
35	-0.016535	-0.1811	0.428285
36	-0.027144	-0.2973	0.383359
37	-0.029147	-0.3193	0.375033
38	-0.015168	-0.1662	0.434157
39	-0.022697	-0.2486	0.402035
40	-0.016858	-0.1847	0.426898
41	-0.009246	-0.1013	0.459746
42	-0.02835	-0.3106	0.378338
43	-0.024813	-0.2718	0.393118
44	-0.029056	-0.3183	0.375409
45	-0.015574	-0.1706	0.432412
46	-0.011832	-0.1296	0.448545
47	0.002674	0.0293	0.488341
48	-0.015458	-0.1693	0.432909

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