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R Software Module

rwasp_autocorrelation.wasp

Title produced by software

(Partial) Autocorrelation Function

Date of computation

Thu, 16 Dec 2010 18:45:46 +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/2010/Dec/16/t12925250148f9mfp35qa0shab.htm/, Retrieved Tue, 30 Apr 2024 04:31:05 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=111174, Retrieved Tue, 30 Apr 2024 04:31:05 +0000

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IsPrivate?

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User-defined keywords

Estimated Impact

181

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

-     [Multiple Regression] [Q1 The Seatbeltlaw] [2007-11-14 19:27:43] [8cd6641b921d30ebe00b648d1481bba0]
- RMPD  [Multiple Regression] [Seatbelt] [2009-11-12 13:54:52] [b98453cac15ba1066b407e146608df68]
-    D    [Multiple Regression] [WS7] [2009-11-18 17:01:04] [8b1aef4e7013bd33fbc2a5833375c5f5]
-   PD      [Multiple Regression] [WS7(2)] [2009-11-20 19:01:46] [7d268329e554b8694908ba13e6e6f258]
-   P         [Multiple Regression] [WS7(3)] [2009-11-21 10:22:47] [7d268329e554b8694908ba13e6e6f258]
-   PD          [Multiple Regression] [WS7(4)] [2009-11-21 10:55:20] [7d268329e554b8694908ba13e6e6f258]
- RMPD            [Univariate Data Series] [Niet-werkende wer...] [2009-11-25 19:16:52] [9717cb857c153ca3061376906953b329]
- RMP               [Univariate Explorative Data Analysis] [Univariate EDA] [2009-12-17 13:35:10] [9717cb857c153ca3061376906953b329]
-    D                [Univariate Explorative Data Analysis] [] [2010-12-16 18:32:59] [bcc4ad4a6c0f95d5b548de29638ac6c2]
- RMP                     [(Partial) Autocorrelation Function] [] [2010-12-16 18:45:46] [4e3652732e77bb1a104cdb5f8d687d01] [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	4 seconds
R Server	'George Udny Yule' @ 72.249.76.132

\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 & 4 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=111174&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=111174&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=111174&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	4 seconds
R Server	'George Udny Yule' @ 72.249.76.132

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.155785	1.3034	0.098357
2	0.155908	1.3044	0.098181
3	0.184191	1.5411	0.063906
4	0.162539	1.3599	0.089112
5	0.087633	0.7332	0.232946
6	0.115831	0.9691	0.167913
7	0.009518	0.0796	0.468378
8	0.115227	0.9641	0.169169
9	-0.004877	-0.0408	0.483784
10	-0.080696	-0.6751	0.250903
11	0.195174	1.6329	0.053486
12	-0.009484	-0.0793	0.468491
13	-0.093917	-0.7858	0.217328
14	0.140101	1.1722	0.122551
15	0.016263	0.1361	0.446079
16	-0.001906	-0.0159	0.493661
17	-0.019397	-0.1623	0.435774
18	-0.02448	-0.2048	0.419157
19	0.091104	0.7622	0.224241
20	-0.01589	-0.1329	0.447307
21	-0.190442	-1.5933	0.057794
22	-0.059299	-0.4961	0.310677
23	0.017121	0.1432	0.443253
24	-0.235349	-1.9691	0.026452
25	-0.053513	-0.4477	0.327868
26	-0.252421	-2.1119	0.019132
27	-0.223422	-1.8693	0.032883
28	-0.197055	-1.6487	0.051847
29	-0.093648	-0.7835	0.217984
30	-0.133258	-1.1149	0.13435
31	-0.002139	-0.0179	0.492887
32	-0.17894	-1.4971	0.069429
33	0.044578	0.373	0.355151
34	0.001307	0.0109	0.495652
35	0.011899	0.0996	0.46049
36	-0.044388	-0.3714	0.355739
37	-0.062752	-0.525	0.300613
38	-0.042499	-0.3556	0.361615
39	-0.039517	-0.3306	0.370957
40	-0.034653	-0.2899	0.386363
41	-0.049713	-0.4159	0.339368
42	-0.008695	-0.0727	0.471107
43	-0.045468	-0.3804	0.352394
44	-0.022914	-0.1917	0.424261
45	-0.041359	-0.346	0.365178
46	-0.051873	-0.434	0.33281
47	0.004219	0.0353	0.485972
48	0.029652	0.2481	0.402396

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.155785 & 1.3034 & 0.098357 \tabularnewline
2 & 0.155908 & 1.3044 & 0.098181 \tabularnewline
3 & 0.184191 & 1.5411 & 0.063906 \tabularnewline
4 & 0.162539 & 1.3599 & 0.089112 \tabularnewline
5 & 0.087633 & 0.7332 & 0.232946 \tabularnewline
6 & 0.115831 & 0.9691 & 0.167913 \tabularnewline
7 & 0.009518 & 0.0796 & 0.468378 \tabularnewline
8 & 0.115227 & 0.9641 & 0.169169 \tabularnewline
9 & -0.004877 & -0.0408 & 0.483784 \tabularnewline
10 & -0.080696 & -0.6751 & 0.250903 \tabularnewline
11 & 0.195174 & 1.6329 & 0.053486 \tabularnewline
12 & -0.009484 & -0.0793 & 0.468491 \tabularnewline
13 & -0.093917 & -0.7858 & 0.217328 \tabularnewline
14 & 0.140101 & 1.1722 & 0.122551 \tabularnewline
15 & 0.016263 & 0.1361 & 0.446079 \tabularnewline
16 & -0.001906 & -0.0159 & 0.493661 \tabularnewline
17 & -0.019397 & -0.1623 & 0.435774 \tabularnewline
18 & -0.02448 & -0.2048 & 0.419157 \tabularnewline
19 & 0.091104 & 0.7622 & 0.224241 \tabularnewline
20 & -0.01589 & -0.1329 & 0.447307 \tabularnewline
21 & -0.190442 & -1.5933 & 0.057794 \tabularnewline
22 & -0.059299 & -0.4961 & 0.310677 \tabularnewline
23 & 0.017121 & 0.1432 & 0.443253 \tabularnewline
24 & -0.235349 & -1.9691 & 0.026452 \tabularnewline
25 & -0.053513 & -0.4477 & 0.327868 \tabularnewline
26 & -0.252421 & -2.1119 & 0.019132 \tabularnewline
27 & -0.223422 & -1.8693 & 0.032883 \tabularnewline
28 & -0.197055 & -1.6487 & 0.051847 \tabularnewline
29 & -0.093648 & -0.7835 & 0.217984 \tabularnewline
30 & -0.133258 & -1.1149 & 0.13435 \tabularnewline
31 & -0.002139 & -0.0179 & 0.492887 \tabularnewline
32 & -0.17894 & -1.4971 & 0.069429 \tabularnewline
33 & 0.044578 & 0.373 & 0.355151 \tabularnewline
34 & 0.001307 & 0.0109 & 0.495652 \tabularnewline
35 & 0.011899 & 0.0996 & 0.46049 \tabularnewline
36 & -0.044388 & -0.3714 & 0.355739 \tabularnewline
37 & -0.062752 & -0.525 & 0.300613 \tabularnewline
38 & -0.042499 & -0.3556 & 0.361615 \tabularnewline
39 & -0.039517 & -0.3306 & 0.370957 \tabularnewline
40 & -0.034653 & -0.2899 & 0.386363 \tabularnewline
41 & -0.049713 & -0.4159 & 0.339368 \tabularnewline
42 & -0.008695 & -0.0727 & 0.471107 \tabularnewline
43 & -0.045468 & -0.3804 & 0.352394 \tabularnewline
44 & -0.022914 & -0.1917 & 0.424261 \tabularnewline
45 & -0.041359 & -0.346 & 0.365178 \tabularnewline
46 & -0.051873 & -0.434 & 0.33281 \tabularnewline
47 & 0.004219 & 0.0353 & 0.485972 \tabularnewline
48 & 0.029652 & 0.2481 & 0.402396 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=111174&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]0.155785[/C][C]1.3034[/C][C]0.098357[/C][/ROW]
[ROW][C]2[/C][C]0.155908[/C][C]1.3044[/C][C]0.098181[/C][/ROW]
[ROW][C]3[/C][C]0.184191[/C][C]1.5411[/C][C]0.063906[/C][/ROW]
[ROW][C]4[/C][C]0.162539[/C][C]1.3599[/C][C]0.089112[/C][/ROW]
[ROW][C]5[/C][C]0.087633[/C][C]0.7332[/C][C]0.232946[/C][/ROW]
[ROW][C]6[/C][C]0.115831[/C][C]0.9691[/C][C]0.167913[/C][/ROW]
[ROW][C]7[/C][C]0.009518[/C][C]0.0796[/C][C]0.468378[/C][/ROW]
[ROW][C]8[/C][C]0.115227[/C][C]0.9641[/C][C]0.169169[/C][/ROW]
[ROW][C]9[/C][C]-0.004877[/C][C]-0.0408[/C][C]0.483784[/C][/ROW]
[ROW][C]10[/C][C]-0.080696[/C][C]-0.6751[/C][C]0.250903[/C][/ROW]
[ROW][C]11[/C][C]0.195174[/C][C]1.6329[/C][C]0.053486[/C][/ROW]
[ROW][C]12[/C][C]-0.009484[/C][C]-0.0793[/C][C]0.468491[/C][/ROW]
[ROW][C]13[/C][C]-0.093917[/C][C]-0.7858[/C][C]0.217328[/C][/ROW]
[ROW][C]14[/C][C]0.140101[/C][C]1.1722[/C][C]0.122551[/C][/ROW]
[ROW][C]15[/C][C]0.016263[/C][C]0.1361[/C][C]0.446079[/C][/ROW]
[ROW][C]16[/C][C]-0.001906[/C][C]-0.0159[/C][C]0.493661[/C][/ROW]
[ROW][C]17[/C][C]-0.019397[/C][C]-0.1623[/C][C]0.435774[/C][/ROW]
[ROW][C]18[/C][C]-0.02448[/C][C]-0.2048[/C][C]0.419157[/C][/ROW]
[ROW][C]19[/C][C]0.091104[/C][C]0.7622[/C][C]0.224241[/C][/ROW]
[ROW][C]20[/C][C]-0.01589[/C][C]-0.1329[/C][C]0.447307[/C][/ROW]
[ROW][C]21[/C][C]-0.190442[/C][C]-1.5933[/C][C]0.057794[/C][/ROW]
[ROW][C]22[/C][C]-0.059299[/C][C]-0.4961[/C][C]0.310677[/C][/ROW]
[ROW][C]23[/C][C]0.017121[/C][C]0.1432[/C][C]0.443253[/C][/ROW]
[ROW][C]24[/C][C]-0.235349[/C][C]-1.9691[/C][C]0.026452[/C][/ROW]
[ROW][C]25[/C][C]-0.053513[/C][C]-0.4477[/C][C]0.327868[/C][/ROW]
[ROW][C]26[/C][C]-0.252421[/C][C]-2.1119[/C][C]0.019132[/C][/ROW]
[ROW][C]27[/C][C]-0.223422[/C][C]-1.8693[/C][C]0.032883[/C][/ROW]
[ROW][C]28[/C][C]-0.197055[/C][C]-1.6487[/C][C]0.051847[/C][/ROW]
[ROW][C]29[/C][C]-0.093648[/C][C]-0.7835[/C][C]0.217984[/C][/ROW]
[ROW][C]30[/C][C]-0.133258[/C][C]-1.1149[/C][C]0.13435[/C][/ROW]
[ROW][C]31[/C][C]-0.002139[/C][C]-0.0179[/C][C]0.492887[/C][/ROW]
[ROW][C]32[/C][C]-0.17894[/C][C]-1.4971[/C][C]0.069429[/C][/ROW]
[ROW][C]33[/C][C]0.044578[/C][C]0.373[/C][C]0.355151[/C][/ROW]
[ROW][C]34[/C][C]0.001307[/C][C]0.0109[/C][C]0.495652[/C][/ROW]
[ROW][C]35[/C][C]0.011899[/C][C]0.0996[/C][C]0.46049[/C][/ROW]
[ROW][C]36[/C][C]-0.044388[/C][C]-0.3714[/C][C]0.355739[/C][/ROW]
[ROW][C]37[/C][C]-0.062752[/C][C]-0.525[/C][C]0.300613[/C][/ROW]
[ROW][C]38[/C][C]-0.042499[/C][C]-0.3556[/C][C]0.361615[/C][/ROW]
[ROW][C]39[/C][C]-0.039517[/C][C]-0.3306[/C][C]0.370957[/C][/ROW]
[ROW][C]40[/C][C]-0.034653[/C][C]-0.2899[/C][C]0.386363[/C][/ROW]
[ROW][C]41[/C][C]-0.049713[/C][C]-0.4159[/C][C]0.339368[/C][/ROW]
[ROW][C]42[/C][C]-0.008695[/C][C]-0.0727[/C][C]0.471107[/C][/ROW]
[ROW][C]43[/C][C]-0.045468[/C][C]-0.3804[/C][C]0.352394[/C][/ROW]
[ROW][C]44[/C][C]-0.022914[/C][C]-0.1917[/C][C]0.424261[/C][/ROW]
[ROW][C]45[/C][C]-0.041359[/C][C]-0.346[/C][C]0.365178[/C][/ROW]
[ROW][C]46[/C][C]-0.051873[/C][C]-0.434[/C][C]0.33281[/C][/ROW]
[ROW][C]47[/C][C]0.004219[/C][C]0.0353[/C][C]0.485972[/C][/ROW]
[ROW][C]48[/C][C]0.029652[/C][C]0.2481[/C][C]0.402396[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=111174&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=111174&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	0.155785	1.3034	0.098357
2	0.155908	1.3044	0.098181
3	0.184191	1.5411	0.063906
4	0.162539	1.3599	0.089112
5	0.087633	0.7332	0.232946
6	0.115831	0.9691	0.167913
7	0.009518	0.0796	0.468378
8	0.115227	0.9641	0.169169
9	-0.004877	-0.0408	0.483784
10	-0.080696	-0.6751	0.250903
11	0.195174	1.6329	0.053486
12	-0.009484	-0.0793	0.468491
13	-0.093917	-0.7858	0.217328
14	0.140101	1.1722	0.122551
15	0.016263	0.1361	0.446079
16	-0.001906	-0.0159	0.493661
17	-0.019397	-0.1623	0.435774
18	-0.02448	-0.2048	0.419157
19	0.091104	0.7622	0.224241
20	-0.01589	-0.1329	0.447307
21	-0.190442	-1.5933	0.057794
22	-0.059299	-0.4961	0.310677
23	0.017121	0.1432	0.443253
24	-0.235349	-1.9691	0.026452
25	-0.053513	-0.4477	0.327868
26	-0.252421	-2.1119	0.019132
27	-0.223422	-1.8693	0.032883
28	-0.197055	-1.6487	0.051847
29	-0.093648	-0.7835	0.217984
30	-0.133258	-1.1149	0.13435
31	-0.002139	-0.0179	0.492887
32	-0.17894	-1.4971	0.069429
33	0.044578	0.373	0.355151
34	0.001307	0.0109	0.495652
35	0.011899	0.0996	0.46049
36	-0.044388	-0.3714	0.355739
37	-0.062752	-0.525	0.300613
38	-0.042499	-0.3556	0.361615
39	-0.039517	-0.3306	0.370957
40	-0.034653	-0.2899	0.386363
41	-0.049713	-0.4159	0.339368
42	-0.008695	-0.0727	0.471107
43	-0.045468	-0.3804	0.352394
44	-0.022914	-0.1917	0.424261
45	-0.041359	-0.346	0.365178
46	-0.051873	-0.434	0.33281
47	0.004219	0.0353	0.485972
48	0.029652	0.2481	0.402396

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.155785	1.3034	0.098357
2	0.134914	1.1288	0.131424
3	0.1484	1.2416	0.109264
4	0.107132	0.8963	0.186573
5	0.015935	0.1333	0.447161
6	0.051071	0.4273	0.335241
7	-0.063753	-0.5334	0.297724
8	0.077931	0.652	0.258264
9	-0.058153	-0.4865	0.314053
10	-0.115697	-0.968	0.16819
11	0.218605	1.829	0.035831
12	-0.059616	-0.4988	0.309749
13	-0.108645	-0.909	0.183238
14	0.159967	1.3384	0.092552
15	-0.028095	-0.2351	0.407425
16	-0.01439	-0.1204	0.452256
17	-0.056071	-0.4691	0.320221
18	-0.007288	-0.061	0.475775
19	0.086238	0.7215	0.236498
20	-0.061263	-0.5126	0.304936
21	-0.142988	-1.1963	0.117804
22	-0.108484	-0.9076	0.18359
23	0.089794	0.7513	0.227505
24	-0.148738	-1.2444	0.108746
25	-0.044332	-0.3709	0.355912
26	-0.206495	-1.7277	0.04423
27	-0.126556	-1.0588	0.146656
28	-0.062187	-0.5203	0.30225
29	0.073226	0.6127	0.271044
30	-0.057376	-0.48	0.316348
31	0.086097	0.7203	0.236857
32	-0.00899	-0.0752	0.47013
33	0.112293	0.9395	0.175349
34	-0.050018	-0.4185	0.338438
35	0.151091	1.2641	0.10519
36	-0.067498	-0.5647	0.287031
37	-0.124167	-1.0389	0.151223
38	0.051597	0.4317	0.333647
39	-0.092643	-0.7751	0.220444
40	0.080581	0.6742	0.251205
41	0.004699	0.0393	0.484374
42	-0.042915	-0.3591	0.360318
43	0.019463	0.1628	0.435558
44	-0.010023	-0.0839	0.466703
45	-0.038568	-0.3227	0.373948
46	-0.055875	-0.4675	0.320802
47	-0.002396	-0.02	0.492031
48	-0.002945	-0.0246	0.490206

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.155785 & 1.3034 & 0.098357 \tabularnewline
2 & 0.134914 & 1.1288 & 0.131424 \tabularnewline
3 & 0.1484 & 1.2416 & 0.109264 \tabularnewline
4 & 0.107132 & 0.8963 & 0.186573 \tabularnewline
5 & 0.015935 & 0.1333 & 0.447161 \tabularnewline
6 & 0.051071 & 0.4273 & 0.335241 \tabularnewline
7 & -0.063753 & -0.5334 & 0.297724 \tabularnewline
8 & 0.077931 & 0.652 & 0.258264 \tabularnewline
9 & -0.058153 & -0.4865 & 0.314053 \tabularnewline
10 & -0.115697 & -0.968 & 0.16819 \tabularnewline
11 & 0.218605 & 1.829 & 0.035831 \tabularnewline
12 & -0.059616 & -0.4988 & 0.309749 \tabularnewline
13 & -0.108645 & -0.909 & 0.183238 \tabularnewline
14 & 0.159967 & 1.3384 & 0.092552 \tabularnewline
15 & -0.028095 & -0.2351 & 0.407425 \tabularnewline
16 & -0.01439 & -0.1204 & 0.452256 \tabularnewline
17 & -0.056071 & -0.4691 & 0.320221 \tabularnewline
18 & -0.007288 & -0.061 & 0.475775 \tabularnewline
19 & 0.086238 & 0.7215 & 0.236498 \tabularnewline
20 & -0.061263 & -0.5126 & 0.304936 \tabularnewline
21 & -0.142988 & -1.1963 & 0.117804 \tabularnewline
22 & -0.108484 & -0.9076 & 0.18359 \tabularnewline
23 & 0.089794 & 0.7513 & 0.227505 \tabularnewline
24 & -0.148738 & -1.2444 & 0.108746 \tabularnewline
25 & -0.044332 & -0.3709 & 0.355912 \tabularnewline
26 & -0.206495 & -1.7277 & 0.04423 \tabularnewline
27 & -0.126556 & -1.0588 & 0.146656 \tabularnewline
28 & -0.062187 & -0.5203 & 0.30225 \tabularnewline
29 & 0.073226 & 0.6127 & 0.271044 \tabularnewline
30 & -0.057376 & -0.48 & 0.316348 \tabularnewline
31 & 0.086097 & 0.7203 & 0.236857 \tabularnewline
32 & -0.00899 & -0.0752 & 0.47013 \tabularnewline
33 & 0.112293 & 0.9395 & 0.175349 \tabularnewline
34 & -0.050018 & -0.4185 & 0.338438 \tabularnewline
35 & 0.151091 & 1.2641 & 0.10519 \tabularnewline
36 & -0.067498 & -0.5647 & 0.287031 \tabularnewline
37 & -0.124167 & -1.0389 & 0.151223 \tabularnewline
38 & 0.051597 & 0.4317 & 0.333647 \tabularnewline
39 & -0.092643 & -0.7751 & 0.220444 \tabularnewline
40 & 0.080581 & 0.6742 & 0.251205 \tabularnewline
41 & 0.004699 & 0.0393 & 0.484374 \tabularnewline
42 & -0.042915 & -0.3591 & 0.360318 \tabularnewline
43 & 0.019463 & 0.1628 & 0.435558 \tabularnewline
44 & -0.010023 & -0.0839 & 0.466703 \tabularnewline
45 & -0.038568 & -0.3227 & 0.373948 \tabularnewline
46 & -0.055875 & -0.4675 & 0.320802 \tabularnewline
47 & -0.002396 & -0.02 & 0.492031 \tabularnewline
48 & -0.002945 & -0.0246 & 0.490206 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=111174&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]0.155785[/C][C]1.3034[/C][C]0.098357[/C][/ROW]
[ROW][C]2[/C][C]0.134914[/C][C]1.1288[/C][C]0.131424[/C][/ROW]
[ROW][C]3[/C][C]0.1484[/C][C]1.2416[/C][C]0.109264[/C][/ROW]
[ROW][C]4[/C][C]0.107132[/C][C]0.8963[/C][C]0.186573[/C][/ROW]
[ROW][C]5[/C][C]0.015935[/C][C]0.1333[/C][C]0.447161[/C][/ROW]
[ROW][C]6[/C][C]0.051071[/C][C]0.4273[/C][C]0.335241[/C][/ROW]
[ROW][C]7[/C][C]-0.063753[/C][C]-0.5334[/C][C]0.297724[/C][/ROW]
[ROW][C]8[/C][C]0.077931[/C][C]0.652[/C][C]0.258264[/C][/ROW]
[ROW][C]9[/C][C]-0.058153[/C][C]-0.4865[/C][C]0.314053[/C][/ROW]
[ROW][C]10[/C][C]-0.115697[/C][C]-0.968[/C][C]0.16819[/C][/ROW]
[ROW][C]11[/C][C]0.218605[/C][C]1.829[/C][C]0.035831[/C][/ROW]
[ROW][C]12[/C][C]-0.059616[/C][C]-0.4988[/C][C]0.309749[/C][/ROW]
[ROW][C]13[/C][C]-0.108645[/C][C]-0.909[/C][C]0.183238[/C][/ROW]
[ROW][C]14[/C][C]0.159967[/C][C]1.3384[/C][C]0.092552[/C][/ROW]
[ROW][C]15[/C][C]-0.028095[/C][C]-0.2351[/C][C]0.407425[/C][/ROW]
[ROW][C]16[/C][C]-0.01439[/C][C]-0.1204[/C][C]0.452256[/C][/ROW]
[ROW][C]17[/C][C]-0.056071[/C][C]-0.4691[/C][C]0.320221[/C][/ROW]
[ROW][C]18[/C][C]-0.007288[/C][C]-0.061[/C][C]0.475775[/C][/ROW]
[ROW][C]19[/C][C]0.086238[/C][C]0.7215[/C][C]0.236498[/C][/ROW]
[ROW][C]20[/C][C]-0.061263[/C][C]-0.5126[/C][C]0.304936[/C][/ROW]
[ROW][C]21[/C][C]-0.142988[/C][C]-1.1963[/C][C]0.117804[/C][/ROW]
[ROW][C]22[/C][C]-0.108484[/C][C]-0.9076[/C][C]0.18359[/C][/ROW]
[ROW][C]23[/C][C]0.089794[/C][C]0.7513[/C][C]0.227505[/C][/ROW]
[ROW][C]24[/C][C]-0.148738[/C][C]-1.2444[/C][C]0.108746[/C][/ROW]
[ROW][C]25[/C][C]-0.044332[/C][C]-0.3709[/C][C]0.355912[/C][/ROW]
[ROW][C]26[/C][C]-0.206495[/C][C]-1.7277[/C][C]0.04423[/C][/ROW]
[ROW][C]27[/C][C]-0.126556[/C][C]-1.0588[/C][C]0.146656[/C][/ROW]
[ROW][C]28[/C][C]-0.062187[/C][C]-0.5203[/C][C]0.30225[/C][/ROW]
[ROW][C]29[/C][C]0.073226[/C][C]0.6127[/C][C]0.271044[/C][/ROW]
[ROW][C]30[/C][C]-0.057376[/C][C]-0.48[/C][C]0.316348[/C][/ROW]
[ROW][C]31[/C][C]0.086097[/C][C]0.7203[/C][C]0.236857[/C][/ROW]
[ROW][C]32[/C][C]-0.00899[/C][C]-0.0752[/C][C]0.47013[/C][/ROW]
[ROW][C]33[/C][C]0.112293[/C][C]0.9395[/C][C]0.175349[/C][/ROW]
[ROW][C]34[/C][C]-0.050018[/C][C]-0.4185[/C][C]0.338438[/C][/ROW]
[ROW][C]35[/C][C]0.151091[/C][C]1.2641[/C][C]0.10519[/C][/ROW]
[ROW][C]36[/C][C]-0.067498[/C][C]-0.5647[/C][C]0.287031[/C][/ROW]
[ROW][C]37[/C][C]-0.124167[/C][C]-1.0389[/C][C]0.151223[/C][/ROW]
[ROW][C]38[/C][C]0.051597[/C][C]0.4317[/C][C]0.333647[/C][/ROW]
[ROW][C]39[/C][C]-0.092643[/C][C]-0.7751[/C][C]0.220444[/C][/ROW]
[ROW][C]40[/C][C]0.080581[/C][C]0.6742[/C][C]0.251205[/C][/ROW]
[ROW][C]41[/C][C]0.004699[/C][C]0.0393[/C][C]0.484374[/C][/ROW]
[ROW][C]42[/C][C]-0.042915[/C][C]-0.3591[/C][C]0.360318[/C][/ROW]
[ROW][C]43[/C][C]0.019463[/C][C]0.1628[/C][C]0.435558[/C][/ROW]
[ROW][C]44[/C][C]-0.010023[/C][C]-0.0839[/C][C]0.466703[/C][/ROW]
[ROW][C]45[/C][C]-0.038568[/C][C]-0.3227[/C][C]0.373948[/C][/ROW]
[ROW][C]46[/C][C]-0.055875[/C][C]-0.4675[/C][C]0.320802[/C][/ROW]
[ROW][C]47[/C][C]-0.002396[/C][C]-0.02[/C][C]0.492031[/C][/ROW]
[ROW][C]48[/C][C]-0.002945[/C][C]-0.0246[/C][C]0.490206[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=111174&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=111174&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	0.155785	1.3034	0.098357
2	0.134914	1.1288	0.131424
3	0.1484	1.2416	0.109264
4	0.107132	0.8963	0.186573
5	0.015935	0.1333	0.447161
6	0.051071	0.4273	0.335241
7	-0.063753	-0.5334	0.297724
8	0.077931	0.652	0.258264
9	-0.058153	-0.4865	0.314053
10	-0.115697	-0.968	0.16819
11	0.218605	1.829	0.035831
12	-0.059616	-0.4988	0.309749
13	-0.108645	-0.909	0.183238
14	0.159967	1.3384	0.092552
15	-0.028095	-0.2351	0.407425
16	-0.01439	-0.1204	0.452256
17	-0.056071	-0.4691	0.320221
18	-0.007288	-0.061	0.475775
19	0.086238	0.7215	0.236498
20	-0.061263	-0.5126	0.304936
21	-0.142988	-1.1963	0.117804
22	-0.108484	-0.9076	0.18359
23	0.089794	0.7513	0.227505
24	-0.148738	-1.2444	0.108746
25	-0.044332	-0.3709	0.355912
26	-0.206495	-1.7277	0.04423
27	-0.126556	-1.0588	0.146656
28	-0.062187	-0.5203	0.30225
29	0.073226	0.6127	0.271044
30	-0.057376	-0.48	0.316348
31	0.086097	0.7203	0.236857
32	-0.00899	-0.0752	0.47013
33	0.112293	0.9395	0.175349
34	-0.050018	-0.4185	0.338438
35	0.151091	1.2641	0.10519
36	-0.067498	-0.5647	0.287031
37	-0.124167	-1.0389	0.151223
38	0.051597	0.4317	0.333647
39	-0.092643	-0.7751	0.220444
40	0.080581	0.6742	0.251205
41	0.004699	0.0393	0.484374
42	-0.042915	-0.3591	0.360318
43	0.019463	0.1628	0.435558
44	-0.010023	-0.0839	0.466703
45	-0.038568	-0.3227	0.373948
46	-0.055875	-0.4675	0.320802
47	-0.002396	-0.02	0.492031
48	-0.002945	-0.0246	0.490206

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 = 1 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

Parameters (R input):

par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; 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)
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