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R Software Module

rwasp_autocorrelation.wasp

Title produced by software

(Partial) Autocorrelation Function

Date of computation

Wed, 15 Dec 2010 16:36:14 +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/2010/Dec/15/t12924309192yik33q8m0xv2b6.htm/, Retrieved Sun, 11 May 2025 16:27:10 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=110546, Retrieved Sun, 11 May 2025 16:27:10 +0000

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User-defined keywords

Estimated Impact

243

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [(Partial) Autocorrelation Function] [Identifying Integ...] [2009-11-22 12:16:10] [b98453cac15ba1066b407e146608df68]
-    D        [(Partial) Autocorrelation Function] [Model 1 (d = 0, D...] [2009-11-24 17:27:24] [ee7c2e7343f5b1451e62c5c16ec521f1]
-    D          [(Partial) Autocorrelation Function] [Methode 1 (D=0, d=0)] [2009-11-27 12:01:23] [76ab39dc7a55316678260825bd5ad46c]
-    D            [(Partial) Autocorrelation Function] [methode 1 (d=0 D= 0)] [2009-11-27 20:21:42] [4b453aa14d54730625f8d3de5f1f6d82]
-    D              [(Partial) Autocorrelation Function] [koffie en thee] [2009-12-16 19:04:55] [7773f496f69461f4a67891f0ef752622]
-    D                [(Partial) Autocorrelation Function] [Appelen Jonagold ...] [2009-12-17 16:51:16] [7773f496f69461f4a67891f0ef752622]
- R PD                    [(Partial) Autocorrelation Function] [autocorrelatie] [2010-12-15 16:36:14] [c1f1b5e209adb4577289f490325e36f2] [Current]
-   P                       [(Partial) Autocorrelation Function] [autocorrelation] [2010-12-23 07:04:44] [717f3d787904f94c39256c5c1fc72d4c] 

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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=110546&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=110546&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110546&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	0.010312	0.0792	0.468569
2	-0.02522	-0.1937	0.423532
3	0.164612	1.2644	0.105527
4	-0.07536	-0.5789	0.282446
5	0.142692	1.096	0.138758
6	0.031885	0.2449	0.403688
7	-0.33584	-2.5796	0.006201
8	-0.113863	-0.8746	0.192669
9	-0.068943	-0.5296	0.299202
10	-0.091364	-0.7018	0.242788
11	0.013489	0.1036	0.458916
12	-0.219313	-1.6846	0.048677
13	-0.153105	-1.176	0.122155
14	0.121003	0.9294	0.178223
15	0.11676	0.8968	0.186722
16	0.029299	0.225	0.41136
17	0.028083	0.2157	0.41498
18	-0.01639	-0.1259	0.450123
19	-0.031704	-0.2435	0.404223
20	0.157038	1.2062	0.116271
21	-0.063181	-0.4853	0.314629
22	0.000185	0.0014	0.499436
23	-0.085253	-0.6548	0.257559
24	0.000286	0.0022	0.499126
25	0.106983	0.8218	0.207263
26	-0.018354	-0.141	0.444182
27	-0.090608	-0.696	0.24459
28	-0.087058	-0.6687	0.253146
29	-0.081978	-0.6297	0.265667
30	-0.070313	-0.5401	0.295586
31	0.032391	0.2488	0.402189
32	0.002995	0.023	0.490862
33	-0.088474	-0.6796	0.249713
34	-0.073928	-0.5679	0.286144
35	0.15919	1.2228	0.113141
36	0.007161	0.055	0.478159
37	0.003971	0.0305	0.487886
38	0.045846	0.3522	0.362989
39	0.019665	0.1511	0.440225
40	0.169856	1.3047	0.098533
41	0.096348	0.7401	0.231098
42	-0.027427	-0.2107	0.416934
43	-0.006085	-0.0467	0.481439
44	-0.023351	-0.1794	0.429133
45	-0.02593	-0.1992	0.421407
46	0.038689	0.2972	0.383689
47	-0.059664	-0.4583	0.324214
48	-0.080268	-0.6166	0.269952
49	0.022266	0.171	0.432395
50	-0.042182	-0.324	0.37354
51	0.038078	0.2925	0.385473
52	-0.039035	-0.2998	0.382678
53	-0.010648	-0.0818	0.467546
54	-0.008181	-0.0628	0.475053
55	0.040089	0.3079	0.379609
56	0.001052	0.0081	0.49679
57	0.025663	0.1971	0.422205
58	-0.012867	-0.0988	0.460802
59	NA	NA	NA
60	NA	NA	NA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.010312 & 0.0792 & 0.468569 \tabularnewline
2 & -0.02522 & -0.1937 & 0.423532 \tabularnewline
3 & 0.164612 & 1.2644 & 0.105527 \tabularnewline
4 & -0.07536 & -0.5789 & 0.282446 \tabularnewline
5 & 0.142692 & 1.096 & 0.138758 \tabularnewline
6 & 0.031885 & 0.2449 & 0.403688 \tabularnewline
7 & -0.33584 & -2.5796 & 0.006201 \tabularnewline
8 & -0.113863 & -0.8746 & 0.192669 \tabularnewline
9 & -0.068943 & -0.5296 & 0.299202 \tabularnewline
10 & -0.091364 & -0.7018 & 0.242788 \tabularnewline
11 & 0.013489 & 0.1036 & 0.458916 \tabularnewline
12 & -0.219313 & -1.6846 & 0.048677 \tabularnewline
13 & -0.153105 & -1.176 & 0.122155 \tabularnewline
14 & 0.121003 & 0.9294 & 0.178223 \tabularnewline
15 & 0.11676 & 0.8968 & 0.186722 \tabularnewline
16 & 0.029299 & 0.225 & 0.41136 \tabularnewline
17 & 0.028083 & 0.2157 & 0.41498 \tabularnewline
18 & -0.01639 & -0.1259 & 0.450123 \tabularnewline
19 & -0.031704 & -0.2435 & 0.404223 \tabularnewline
20 & 0.157038 & 1.2062 & 0.116271 \tabularnewline
21 & -0.063181 & -0.4853 & 0.314629 \tabularnewline
22 & 0.000185 & 0.0014 & 0.499436 \tabularnewline
23 & -0.085253 & -0.6548 & 0.257559 \tabularnewline
24 & 0.000286 & 0.0022 & 0.499126 \tabularnewline
25 & 0.106983 & 0.8218 & 0.207263 \tabularnewline
26 & -0.018354 & -0.141 & 0.444182 \tabularnewline
27 & -0.090608 & -0.696 & 0.24459 \tabularnewline
28 & -0.087058 & -0.6687 & 0.253146 \tabularnewline
29 & -0.081978 & -0.6297 & 0.265667 \tabularnewline
30 & -0.070313 & -0.5401 & 0.295586 \tabularnewline
31 & 0.032391 & 0.2488 & 0.402189 \tabularnewline
32 & 0.002995 & 0.023 & 0.490862 \tabularnewline
33 & -0.088474 & -0.6796 & 0.249713 \tabularnewline
34 & -0.073928 & -0.5679 & 0.286144 \tabularnewline
35 & 0.15919 & 1.2228 & 0.113141 \tabularnewline
36 & 0.007161 & 0.055 & 0.478159 \tabularnewline
37 & 0.003971 & 0.0305 & 0.487886 \tabularnewline
38 & 0.045846 & 0.3522 & 0.362989 \tabularnewline
39 & 0.019665 & 0.1511 & 0.440225 \tabularnewline
40 & 0.169856 & 1.3047 & 0.098533 \tabularnewline
41 & 0.096348 & 0.7401 & 0.231098 \tabularnewline
42 & -0.027427 & -0.2107 & 0.416934 \tabularnewline
43 & -0.006085 & -0.0467 & 0.481439 \tabularnewline
44 & -0.023351 & -0.1794 & 0.429133 \tabularnewline
45 & -0.02593 & -0.1992 & 0.421407 \tabularnewline
46 & 0.038689 & 0.2972 & 0.383689 \tabularnewline
47 & -0.059664 & -0.4583 & 0.324214 \tabularnewline
48 & -0.080268 & -0.6166 & 0.269952 \tabularnewline
49 & 0.022266 & 0.171 & 0.432395 \tabularnewline
50 & -0.042182 & -0.324 & 0.37354 \tabularnewline
51 & 0.038078 & 0.2925 & 0.385473 \tabularnewline
52 & -0.039035 & -0.2998 & 0.382678 \tabularnewline
53 & -0.010648 & -0.0818 & 0.467546 \tabularnewline
54 & -0.008181 & -0.0628 & 0.475053 \tabularnewline
55 & 0.040089 & 0.3079 & 0.379609 \tabularnewline
56 & 0.001052 & 0.0081 & 0.49679 \tabularnewline
57 & 0.025663 & 0.1971 & 0.422205 \tabularnewline
58 & -0.012867 & -0.0988 & 0.460802 \tabularnewline
59 & NA & NA & NA \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110546&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]0.010312[/C][C]0.0792[/C][C]0.468569[/C][/ROW]
[ROW][C]2[/C][C]-0.02522[/C][C]-0.1937[/C][C]0.423532[/C][/ROW]
[ROW][C]3[/C][C]0.164612[/C][C]1.2644[/C][C]0.105527[/C][/ROW]
[ROW][C]4[/C][C]-0.07536[/C][C]-0.5789[/C][C]0.282446[/C][/ROW]
[ROW][C]5[/C][C]0.142692[/C][C]1.096[/C][C]0.138758[/C][/ROW]
[ROW][C]6[/C][C]0.031885[/C][C]0.2449[/C][C]0.403688[/C][/ROW]
[ROW][C]7[/C][C]-0.33584[/C][C]-2.5796[/C][C]0.006201[/C][/ROW]
[ROW][C]8[/C][C]-0.113863[/C][C]-0.8746[/C][C]0.192669[/C][/ROW]
[ROW][C]9[/C][C]-0.068943[/C][C]-0.5296[/C][C]0.299202[/C][/ROW]
[ROW][C]10[/C][C]-0.091364[/C][C]-0.7018[/C][C]0.242788[/C][/ROW]
[ROW][C]11[/C][C]0.013489[/C][C]0.1036[/C][C]0.458916[/C][/ROW]
[ROW][C]12[/C][C]-0.219313[/C][C]-1.6846[/C][C]0.048677[/C][/ROW]
[ROW][C]13[/C][C]-0.153105[/C][C]-1.176[/C][C]0.122155[/C][/ROW]
[ROW][C]14[/C][C]0.121003[/C][C]0.9294[/C][C]0.178223[/C][/ROW]
[ROW][C]15[/C][C]0.11676[/C][C]0.8968[/C][C]0.186722[/C][/ROW]
[ROW][C]16[/C][C]0.029299[/C][C]0.225[/C][C]0.41136[/C][/ROW]
[ROW][C]17[/C][C]0.028083[/C][C]0.2157[/C][C]0.41498[/C][/ROW]
[ROW][C]18[/C][C]-0.01639[/C][C]-0.1259[/C][C]0.450123[/C][/ROW]
[ROW][C]19[/C][C]-0.031704[/C][C]-0.2435[/C][C]0.404223[/C][/ROW]
[ROW][C]20[/C][C]0.157038[/C][C]1.2062[/C][C]0.116271[/C][/ROW]
[ROW][C]21[/C][C]-0.063181[/C][C]-0.4853[/C][C]0.314629[/C][/ROW]
[ROW][C]22[/C][C]0.000185[/C][C]0.0014[/C][C]0.499436[/C][/ROW]
[ROW][C]23[/C][C]-0.085253[/C][C]-0.6548[/C][C]0.257559[/C][/ROW]
[ROW][C]24[/C][C]0.000286[/C][C]0.0022[/C][C]0.499126[/C][/ROW]
[ROW][C]25[/C][C]0.106983[/C][C]0.8218[/C][C]0.207263[/C][/ROW]
[ROW][C]26[/C][C]-0.018354[/C][C]-0.141[/C][C]0.444182[/C][/ROW]
[ROW][C]27[/C][C]-0.090608[/C][C]-0.696[/C][C]0.24459[/C][/ROW]
[ROW][C]28[/C][C]-0.087058[/C][C]-0.6687[/C][C]0.253146[/C][/ROW]
[ROW][C]29[/C][C]-0.081978[/C][C]-0.6297[/C][C]0.265667[/C][/ROW]
[ROW][C]30[/C][C]-0.070313[/C][C]-0.5401[/C][C]0.295586[/C][/ROW]
[ROW][C]31[/C][C]0.032391[/C][C]0.2488[/C][C]0.402189[/C][/ROW]
[ROW][C]32[/C][C]0.002995[/C][C]0.023[/C][C]0.490862[/C][/ROW]
[ROW][C]33[/C][C]-0.088474[/C][C]-0.6796[/C][C]0.249713[/C][/ROW]
[ROW][C]34[/C][C]-0.073928[/C][C]-0.5679[/C][C]0.286144[/C][/ROW]
[ROW][C]35[/C][C]0.15919[/C][C]1.2228[/C][C]0.113141[/C][/ROW]
[ROW][C]36[/C][C]0.007161[/C][C]0.055[/C][C]0.478159[/C][/ROW]
[ROW][C]37[/C][C]0.003971[/C][C]0.0305[/C][C]0.487886[/C][/ROW]
[ROW][C]38[/C][C]0.045846[/C][C]0.3522[/C][C]0.362989[/C][/ROW]
[ROW][C]39[/C][C]0.019665[/C][C]0.1511[/C][C]0.440225[/C][/ROW]
[ROW][C]40[/C][C]0.169856[/C][C]1.3047[/C][C]0.098533[/C][/ROW]
[ROW][C]41[/C][C]0.096348[/C][C]0.7401[/C][C]0.231098[/C][/ROW]
[ROW][C]42[/C][C]-0.027427[/C][C]-0.2107[/C][C]0.416934[/C][/ROW]
[ROW][C]43[/C][C]-0.006085[/C][C]-0.0467[/C][C]0.481439[/C][/ROW]
[ROW][C]44[/C][C]-0.023351[/C][C]-0.1794[/C][C]0.429133[/C][/ROW]
[ROW][C]45[/C][C]-0.02593[/C][C]-0.1992[/C][C]0.421407[/C][/ROW]
[ROW][C]46[/C][C]0.038689[/C][C]0.2972[/C][C]0.383689[/C][/ROW]
[ROW][C]47[/C][C]-0.059664[/C][C]-0.4583[/C][C]0.324214[/C][/ROW]
[ROW][C]48[/C][C]-0.080268[/C][C]-0.6166[/C][C]0.269952[/C][/ROW]
[ROW][C]49[/C][C]0.022266[/C][C]0.171[/C][C]0.432395[/C][/ROW]
[ROW][C]50[/C][C]-0.042182[/C][C]-0.324[/C][C]0.37354[/C][/ROW]
[ROW][C]51[/C][C]0.038078[/C][C]0.2925[/C][C]0.385473[/C][/ROW]
[ROW][C]52[/C][C]-0.039035[/C][C]-0.2998[/C][C]0.382678[/C][/ROW]
[ROW][C]53[/C][C]-0.010648[/C][C]-0.0818[/C][C]0.467546[/C][/ROW]
[ROW][C]54[/C][C]-0.008181[/C][C]-0.0628[/C][C]0.475053[/C][/ROW]
[ROW][C]55[/C][C]0.040089[/C][C]0.3079[/C][C]0.379609[/C][/ROW]
[ROW][C]56[/C][C]0.001052[/C][C]0.0081[/C][C]0.49679[/C][/ROW]
[ROW][C]57[/C][C]0.025663[/C][C]0.1971[/C][C]0.422205[/C][/ROW]
[ROW][C]58[/C][C]-0.012867[/C][C]-0.0988[/C][C]0.460802[/C][/ROW]
[ROW][C]59[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110546&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110546&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	0.010312	0.0792	0.468569
2	-0.02522	-0.1937	0.423532
3	0.164612	1.2644	0.105527
4	-0.07536	-0.5789	0.282446
5	0.142692	1.096	0.138758
6	0.031885	0.2449	0.403688
7	-0.33584	-2.5796	0.006201
8	-0.113863	-0.8746	0.192669
9	-0.068943	-0.5296	0.299202
10	-0.091364	-0.7018	0.242788
11	0.013489	0.1036	0.458916
12	-0.219313	-1.6846	0.048677
13	-0.153105	-1.176	0.122155
14	0.121003	0.9294	0.178223
15	0.11676	0.8968	0.186722
16	0.029299	0.225	0.41136
17	0.028083	0.2157	0.41498
18	-0.01639	-0.1259	0.450123
19	-0.031704	-0.2435	0.404223
20	0.157038	1.2062	0.116271
21	-0.063181	-0.4853	0.314629
22	0.000185	0.0014	0.499436
23	-0.085253	-0.6548	0.257559
24	0.000286	0.0022	0.499126
25	0.106983	0.8218	0.207263
26	-0.018354	-0.141	0.444182
27	-0.090608	-0.696	0.24459
28	-0.087058	-0.6687	0.253146
29	-0.081978	-0.6297	0.265667
30	-0.070313	-0.5401	0.295586
31	0.032391	0.2488	0.402189
32	0.002995	0.023	0.490862
33	-0.088474	-0.6796	0.249713
34	-0.073928	-0.5679	0.286144
35	0.15919	1.2228	0.113141
36	0.007161	0.055	0.478159
37	0.003971	0.0305	0.487886
38	0.045846	0.3522	0.362989
39	0.019665	0.1511	0.440225
40	0.169856	1.3047	0.098533
41	0.096348	0.7401	0.231098
42	-0.027427	-0.2107	0.416934
43	-0.006085	-0.0467	0.481439
44	-0.023351	-0.1794	0.429133
45	-0.02593	-0.1992	0.421407
46	0.038689	0.2972	0.383689
47	-0.059664	-0.4583	0.324214
48	-0.080268	-0.6166	0.269952
49	0.022266	0.171	0.432395
50	-0.042182	-0.324	0.37354
51	0.038078	0.2925	0.385473
52	-0.039035	-0.2998	0.382678
53	-0.010648	-0.0818	0.467546
54	-0.008181	-0.0628	0.475053
55	0.040089	0.3079	0.379609
56	0.001052	0.0081	0.49679
57	0.025663	0.1971	0.422205
58	-0.012867	-0.0988	0.460802
59	NA	NA	NA
60	NA	NA	NA

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.010312	0.0792	0.468569
2	-0.025329	-0.1946	0.423206
3	0.165264	1.2694	0.104639
4	-0.082489	-0.6336	0.264391
5	0.160259	1.231	0.111609
6	-0.010949	-0.0841	0.466631
7	-0.3163	-2.4295	0.00909
8	-0.169722	-1.3037	0.098707
9	-0.08035	-0.6172	0.269745
10	-0.016749	-0.1287	0.449036
11	0.018004	0.1383	0.445242
12	-0.139218	-1.0694	0.144633
13	-0.116396	-0.8941	0.187462
14	0.02634	0.2023	0.42018
15	0.12312	0.9457	0.174078
16	0.000373	0.0029	0.498863
17	-0.007993	-0.0614	0.475627
18	-0.027437	-0.2107	0.416905
19	-0.19422	-1.4918	0.070536
20	-0.008999	-0.0691	0.472563
21	-0.096973	-0.7449	0.229656
22	0.106219	0.8159	0.208925
23	-0.103272	-0.7933	0.215405
24	0.064538	0.4957	0.310964
25	0.028002	0.2151	0.415221
26	-0.016012	-0.123	0.451267
27	-0.041495	-0.3187	0.375529
28	-0.136355	-1.0474	0.149602
29	-0.130052	-0.9989	0.160949
30	-0.2228	-1.7114	0.046134
31	-0.030774	-0.2364	0.406977
32	0.0896	0.6882	0.247003
33	-0.019515	-0.1499	0.440678
34	-0.101734	-0.7814	0.218836
35	0.097296	0.7473	0.228912
36	-0.07473	-0.574	0.28407
37	-0.07273	-0.5587	0.289257
38	-0.058997	-0.4532	0.326045
39	0.030397	0.2335	0.408098
40	-0.006913	-0.0531	0.478917
41	-0.001659	-0.0127	0.494938
42	-0.078115	-0.6	0.275397
43	-0.005215	-0.0401	0.484093
44	0.010324	0.0793	0.468531
45	-0.017391	-0.1336	0.447093
46	-0.039734	-0.3052	0.380642
47	-0.000504	-0.0039	0.498462
48	0.0131	0.1006	0.460095
49	-0.045019	-0.3458	0.365362
50	-0.087848	-0.6748	0.251227
51	0.033159	0.2547	0.39992
52	-0.051481	-0.3954	0.346974
53	0.029662	0.2278	0.410281
54	-0.015093	-0.1159	0.45405
55	-0.013203	-0.1014	0.459782
56	-0.068738	-0.528	0.299744
57	-0.082338	-0.6324	0.264769
58	-0.004965	-0.0381	0.484855
59	NA	NA	NA
60	NA	NA	NA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.010312 & 0.0792 & 0.468569 \tabularnewline
2 & -0.025329 & -0.1946 & 0.423206 \tabularnewline
3 & 0.165264 & 1.2694 & 0.104639 \tabularnewline
4 & -0.082489 & -0.6336 & 0.264391 \tabularnewline
5 & 0.160259 & 1.231 & 0.111609 \tabularnewline
6 & -0.010949 & -0.0841 & 0.466631 \tabularnewline
7 & -0.3163 & -2.4295 & 0.00909 \tabularnewline
8 & -0.169722 & -1.3037 & 0.098707 \tabularnewline
9 & -0.08035 & -0.6172 & 0.269745 \tabularnewline
10 & -0.016749 & -0.1287 & 0.449036 \tabularnewline
11 & 0.018004 & 0.1383 & 0.445242 \tabularnewline
12 & -0.139218 & -1.0694 & 0.144633 \tabularnewline
13 & -0.116396 & -0.8941 & 0.187462 \tabularnewline
14 & 0.02634 & 0.2023 & 0.42018 \tabularnewline
15 & 0.12312 & 0.9457 & 0.174078 \tabularnewline
16 & 0.000373 & 0.0029 & 0.498863 \tabularnewline
17 & -0.007993 & -0.0614 & 0.475627 \tabularnewline
18 & -0.027437 & -0.2107 & 0.416905 \tabularnewline
19 & -0.19422 & -1.4918 & 0.070536 \tabularnewline
20 & -0.008999 & -0.0691 & 0.472563 \tabularnewline
21 & -0.096973 & -0.7449 & 0.229656 \tabularnewline
22 & 0.106219 & 0.8159 & 0.208925 \tabularnewline
23 & -0.103272 & -0.7933 & 0.215405 \tabularnewline
24 & 0.064538 & 0.4957 & 0.310964 \tabularnewline
25 & 0.028002 & 0.2151 & 0.415221 \tabularnewline
26 & -0.016012 & -0.123 & 0.451267 \tabularnewline
27 & -0.041495 & -0.3187 & 0.375529 \tabularnewline
28 & -0.136355 & -1.0474 & 0.149602 \tabularnewline
29 & -0.130052 & -0.9989 & 0.160949 \tabularnewline
30 & -0.2228 & -1.7114 & 0.046134 \tabularnewline
31 & -0.030774 & -0.2364 & 0.406977 \tabularnewline
32 & 0.0896 & 0.6882 & 0.247003 \tabularnewline
33 & -0.019515 & -0.1499 & 0.440678 \tabularnewline
34 & -0.101734 & -0.7814 & 0.218836 \tabularnewline
35 & 0.097296 & 0.7473 & 0.228912 \tabularnewline
36 & -0.07473 & -0.574 & 0.28407 \tabularnewline
37 & -0.07273 & -0.5587 & 0.289257 \tabularnewline
38 & -0.058997 & -0.4532 & 0.326045 \tabularnewline
39 & 0.030397 & 0.2335 & 0.408098 \tabularnewline
40 & -0.006913 & -0.0531 & 0.478917 \tabularnewline
41 & -0.001659 & -0.0127 & 0.494938 \tabularnewline
42 & -0.078115 & -0.6 & 0.275397 \tabularnewline
43 & -0.005215 & -0.0401 & 0.484093 \tabularnewline
44 & 0.010324 & 0.0793 & 0.468531 \tabularnewline
45 & -0.017391 & -0.1336 & 0.447093 \tabularnewline
46 & -0.039734 & -0.3052 & 0.380642 \tabularnewline
47 & -0.000504 & -0.0039 & 0.498462 \tabularnewline
48 & 0.0131 & 0.1006 & 0.460095 \tabularnewline
49 & -0.045019 & -0.3458 & 0.365362 \tabularnewline
50 & -0.087848 & -0.6748 & 0.251227 \tabularnewline
51 & 0.033159 & 0.2547 & 0.39992 \tabularnewline
52 & -0.051481 & -0.3954 & 0.346974 \tabularnewline
53 & 0.029662 & 0.2278 & 0.410281 \tabularnewline
54 & -0.015093 & -0.1159 & 0.45405 \tabularnewline
55 & -0.013203 & -0.1014 & 0.459782 \tabularnewline
56 & -0.068738 & -0.528 & 0.299744 \tabularnewline
57 & -0.082338 & -0.6324 & 0.264769 \tabularnewline
58 & -0.004965 & -0.0381 & 0.484855 \tabularnewline
59 & NA & NA & NA \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110546&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]0.010312[/C][C]0.0792[/C][C]0.468569[/C][/ROW]
[ROW][C]2[/C][C]-0.025329[/C][C]-0.1946[/C][C]0.423206[/C][/ROW]
[ROW][C]3[/C][C]0.165264[/C][C]1.2694[/C][C]0.104639[/C][/ROW]
[ROW][C]4[/C][C]-0.082489[/C][C]-0.6336[/C][C]0.264391[/C][/ROW]
[ROW][C]5[/C][C]0.160259[/C][C]1.231[/C][C]0.111609[/C][/ROW]
[ROW][C]6[/C][C]-0.010949[/C][C]-0.0841[/C][C]0.466631[/C][/ROW]
[ROW][C]7[/C][C]-0.3163[/C][C]-2.4295[/C][C]0.00909[/C][/ROW]
[ROW][C]8[/C][C]-0.169722[/C][C]-1.3037[/C][C]0.098707[/C][/ROW]
[ROW][C]9[/C][C]-0.08035[/C][C]-0.6172[/C][C]0.269745[/C][/ROW]
[ROW][C]10[/C][C]-0.016749[/C][C]-0.1287[/C][C]0.449036[/C][/ROW]
[ROW][C]11[/C][C]0.018004[/C][C]0.1383[/C][C]0.445242[/C][/ROW]
[ROW][C]12[/C][C]-0.139218[/C][C]-1.0694[/C][C]0.144633[/C][/ROW]
[ROW][C]13[/C][C]-0.116396[/C][C]-0.8941[/C][C]0.187462[/C][/ROW]
[ROW][C]14[/C][C]0.02634[/C][C]0.2023[/C][C]0.42018[/C][/ROW]
[ROW][C]15[/C][C]0.12312[/C][C]0.9457[/C][C]0.174078[/C][/ROW]
[ROW][C]16[/C][C]0.000373[/C][C]0.0029[/C][C]0.498863[/C][/ROW]
[ROW][C]17[/C][C]-0.007993[/C][C]-0.0614[/C][C]0.475627[/C][/ROW]
[ROW][C]18[/C][C]-0.027437[/C][C]-0.2107[/C][C]0.416905[/C][/ROW]
[ROW][C]19[/C][C]-0.19422[/C][C]-1.4918[/C][C]0.070536[/C][/ROW]
[ROW][C]20[/C][C]-0.008999[/C][C]-0.0691[/C][C]0.472563[/C][/ROW]
[ROW][C]21[/C][C]-0.096973[/C][C]-0.7449[/C][C]0.229656[/C][/ROW]
[ROW][C]22[/C][C]0.106219[/C][C]0.8159[/C][C]0.208925[/C][/ROW]
[ROW][C]23[/C][C]-0.103272[/C][C]-0.7933[/C][C]0.215405[/C][/ROW]
[ROW][C]24[/C][C]0.064538[/C][C]0.4957[/C][C]0.310964[/C][/ROW]
[ROW][C]25[/C][C]0.028002[/C][C]0.2151[/C][C]0.415221[/C][/ROW]
[ROW][C]26[/C][C]-0.016012[/C][C]-0.123[/C][C]0.451267[/C][/ROW]
[ROW][C]27[/C][C]-0.041495[/C][C]-0.3187[/C][C]0.375529[/C][/ROW]
[ROW][C]28[/C][C]-0.136355[/C][C]-1.0474[/C][C]0.149602[/C][/ROW]
[ROW][C]29[/C][C]-0.130052[/C][C]-0.9989[/C][C]0.160949[/C][/ROW]
[ROW][C]30[/C][C]-0.2228[/C][C]-1.7114[/C][C]0.046134[/C][/ROW]
[ROW][C]31[/C][C]-0.030774[/C][C]-0.2364[/C][C]0.406977[/C][/ROW]
[ROW][C]32[/C][C]0.0896[/C][C]0.6882[/C][C]0.247003[/C][/ROW]
[ROW][C]33[/C][C]-0.019515[/C][C]-0.1499[/C][C]0.440678[/C][/ROW]
[ROW][C]34[/C][C]-0.101734[/C][C]-0.7814[/C][C]0.218836[/C][/ROW]
[ROW][C]35[/C][C]0.097296[/C][C]0.7473[/C][C]0.228912[/C][/ROW]
[ROW][C]36[/C][C]-0.07473[/C][C]-0.574[/C][C]0.28407[/C][/ROW]
[ROW][C]37[/C][C]-0.07273[/C][C]-0.5587[/C][C]0.289257[/C][/ROW]
[ROW][C]38[/C][C]-0.058997[/C][C]-0.4532[/C][C]0.326045[/C][/ROW]
[ROW][C]39[/C][C]0.030397[/C][C]0.2335[/C][C]0.408098[/C][/ROW]
[ROW][C]40[/C][C]-0.006913[/C][C]-0.0531[/C][C]0.478917[/C][/ROW]
[ROW][C]41[/C][C]-0.001659[/C][C]-0.0127[/C][C]0.494938[/C][/ROW]
[ROW][C]42[/C][C]-0.078115[/C][C]-0.6[/C][C]0.275397[/C][/ROW]
[ROW][C]43[/C][C]-0.005215[/C][C]-0.0401[/C][C]0.484093[/C][/ROW]
[ROW][C]44[/C][C]0.010324[/C][C]0.0793[/C][C]0.468531[/C][/ROW]
[ROW][C]45[/C][C]-0.017391[/C][C]-0.1336[/C][C]0.447093[/C][/ROW]
[ROW][C]46[/C][C]-0.039734[/C][C]-0.3052[/C][C]0.380642[/C][/ROW]
[ROW][C]47[/C][C]-0.000504[/C][C]-0.0039[/C][C]0.498462[/C][/ROW]
[ROW][C]48[/C][C]0.0131[/C][C]0.1006[/C][C]0.460095[/C][/ROW]
[ROW][C]49[/C][C]-0.045019[/C][C]-0.3458[/C][C]0.365362[/C][/ROW]
[ROW][C]50[/C][C]-0.087848[/C][C]-0.6748[/C][C]0.251227[/C][/ROW]
[ROW][C]51[/C][C]0.033159[/C][C]0.2547[/C][C]0.39992[/C][/ROW]
[ROW][C]52[/C][C]-0.051481[/C][C]-0.3954[/C][C]0.346974[/C][/ROW]
[ROW][C]53[/C][C]0.029662[/C][C]0.2278[/C][C]0.410281[/C][/ROW]
[ROW][C]54[/C][C]-0.015093[/C][C]-0.1159[/C][C]0.45405[/C][/ROW]
[ROW][C]55[/C][C]-0.013203[/C][C]-0.1014[/C][C]0.459782[/C][/ROW]
[ROW][C]56[/C][C]-0.068738[/C][C]-0.528[/C][C]0.299744[/C][/ROW]
[ROW][C]57[/C][C]-0.082338[/C][C]-0.6324[/C][C]0.264769[/C][/ROW]
[ROW][C]58[/C][C]-0.004965[/C][C]-0.0381[/C][C]0.484855[/C][/ROW]
[ROW][C]59[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110546&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110546&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	0.010312	0.0792	0.468569
2	-0.025329	-0.1946	0.423206
3	0.165264	1.2694	0.104639
4	-0.082489	-0.6336	0.264391
5	0.160259	1.231	0.111609
6	-0.010949	-0.0841	0.466631
7	-0.3163	-2.4295	0.00909
8	-0.169722	-1.3037	0.098707
9	-0.08035	-0.6172	0.269745
10	-0.016749	-0.1287	0.449036
11	0.018004	0.1383	0.445242
12	-0.139218	-1.0694	0.144633
13	-0.116396	-0.8941	0.187462
14	0.02634	0.2023	0.42018
15	0.12312	0.9457	0.174078
16	0.000373	0.0029	0.498863
17	-0.007993	-0.0614	0.475627
18	-0.027437	-0.2107	0.416905
19	-0.19422	-1.4918	0.070536
20	-0.008999	-0.0691	0.472563
21	-0.096973	-0.7449	0.229656
22	0.106219	0.8159	0.208925
23	-0.103272	-0.7933	0.215405
24	0.064538	0.4957	0.310964
25	0.028002	0.2151	0.415221
26	-0.016012	-0.123	0.451267
27	-0.041495	-0.3187	0.375529
28	-0.136355	-1.0474	0.149602
29	-0.130052	-0.9989	0.160949
30	-0.2228	-1.7114	0.046134
31	-0.030774	-0.2364	0.406977
32	0.0896	0.6882	0.247003
33	-0.019515	-0.1499	0.440678
34	-0.101734	-0.7814	0.218836
35	0.097296	0.7473	0.228912
36	-0.07473	-0.574	0.28407
37	-0.07273	-0.5587	0.289257
38	-0.058997	-0.4532	0.326045
39	0.030397	0.2335	0.408098
40	-0.006913	-0.0531	0.478917
41	-0.001659	-0.0127	0.494938
42	-0.078115	-0.6	0.275397
43	-0.005215	-0.0401	0.484093
44	0.010324	0.0793	0.468531
45	-0.017391	-0.1336	0.447093
46	-0.039734	-0.3052	0.380642
47	-0.000504	-0.0039	0.498462
48	0.0131	0.1006	0.460095
49	-0.045019	-0.3458	0.365362
50	-0.087848	-0.6748	0.251227
51	0.033159	0.2547	0.39992
52	-0.051481	-0.3954	0.346974
53	0.029662	0.2278	0.410281
54	-0.015093	-0.1159	0.45405
55	-0.013203	-0.1014	0.459782
56	-0.068738	-0.528	0.299744
57	-0.082338	-0.6324	0.264769
58	-0.004965	-0.0381	0.484855
59	NA	NA	NA
60	NA	NA	NA

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 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 12 ; par5 = 1 ; par6 = 0 ; par7 = 0 ;

Parameters (R input):

par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = MA ; 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)
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