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R Software Module

rwasp_autocorrelation.wasp

Title produced by software

(Partial) Autocorrelation Function

Date of computation

Mon, 08 Dec 2008 12:29:38 -0700

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Dec/08/t1228764629ykn18wxgnbyscmt.htm/, Retrieved Thu, 16 May 2024 13:19:23 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=30818, Retrieved Thu, 16 May 2024 13:19:23 +0000

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Estimated Impact

226

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

-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
F RMP   [Variance Reduction Matrix] [step1.1] [2008-12-08 18:32:25] [922d8ae7bd2fd460a62d9020ccd4931a]
F RMP     [(Partial) Autocorrelation Function] [step2] [2008-12-08 18:51:58] [922d8ae7bd2fd460a62d9020ccd4931a]
F RMP       [Spectral Analysis] [step24] [2008-12-08 19:05:43] [922d8ae7bd2fd460a62d9020ccd4931a]
-   P         [Spectral Analysis] [step242] [2008-12-08 19:08:43] [922d8ae7bd2fd460a62d9020ccd4931a]
F   P           [Spectral Analysis] [step25] [2008-12-08 19:10:33] [922d8ae7bd2fd460a62d9020ccd4931a]
- RMP             [(Partial) Autocorrelation Function] [step4] [2008-12-08 19:25:51] [922d8ae7bd2fd460a62d9020ccd4931a]
F   PD                [(Partial) Autocorrelation Function] [step43] [2008-12-08 19:29:38] [89a49ebb3ece8e9a225c7f9f53a14c57] [Current]

Feedback Forum

2008-12-16 17:43:26 [Lana Van Wesemael] [reply] 
Goed besproken. 
Om een AR proces te ontdekken moeten we naar de eerste coëfficiënten van de ACF kijken en deze dan vergelijken met de patronen die op moodle beschikbaar staan. Om een SAR proces te ontdekken kijken we naar de seizoenale coëfficiënten van de ACF en vergelijken deze met de patronen met andere woorden we kijken naar de  streepjes op lag 12,24,36,… Om dan de orde te ontdekken van deze processen kijken we naar de PCAF en tellen hier het aantal significante streepjes die zich bevinden tussen de eerste 5 coëfficiënten (AR)  of de seizoenale coëfficiënten (SAR).  
Om een MA proces te ontdekken moeten we naar de eerste coëfficiënten van de PACF kijken en deze dan vergelijken met de patronen die op moodle beschikbaar staan. Om een SMA proces te ontdekken kijken we naar de seizoenale coëfficiënten van de PCFA en vergelijken deze met de patronen met andere woorden we kijken naar de  streepjes op lag 12,24,36,… Om dan de orde te ontdekken van deze processen kijken we naar de ACF  en tellen hier het aantal significante streepjes die zich bevinden tussen de eerste 5 coëfficiënten (AR)  of de seizoenale coëfficiënten (SAR).  

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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	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30818&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30818&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30818&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	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.070231	0.6001	0.275164
2	0.066054	0.5644	0.287119
3	0.260101	2.2223	0.014681
4	-0.069934	-0.5975	0.276006
5	0.082281	0.703	0.242143
6	0.185271	1.583	0.058878
7	-0.122086	-1.0431	0.150172
8	0.108632	0.9282	0.178194
9	0.251431	2.1482	0.017507
10	-0.129002	-1.1022	0.137
11	-0.044564	-0.3808	0.352245
12	-0.123261	-1.0531	0.147875
13	-0.215744	-1.8433	0.034671
14	0.07198	0.615	0.270235
15	-0.050639	-0.4327	0.33327
16	-0.107029	-0.9145	0.181743
17	0.197931	1.6911	0.04754
18	0.023137	0.1977	0.42192
19	-0.212359	-1.8144	0.036863
20	-0.012	-0.1025	0.45931
21	-0.00585	-0.05	0.480136
22	-0.155844	-1.3315	0.093578
23	0.128873	1.1011	0.137238
24	-0.247945	-2.1184	0.018771
25	-0.106843	-0.9129	0.182159
26	0.063796	0.5451	0.293682
27	-0.009877	-0.0844	0.46649
28	-0.111128	-0.9495	0.172754
29	0.021599	0.1845	0.427049
30	-0.042122	-0.3599	0.359984
31	0.062636	0.5352	0.297083
32	0.140451	1.2	0.117006
33	-0.137049	-1.171	0.122713
34	0.061747	0.5276	0.299699
35	0.157184	1.343	0.09172
36	0.041714	0.3564	0.361284
37	0.194653	1.6631	0.050288
38	0.093219	0.7965	0.214173
39	-0.0503	-0.4298	0.334317
40	0.05596	0.4781	0.316997
41	-0.029457	-0.2517	0.400996
42	-0.128084	-1.0944	0.138699
43	0.031335	0.2677	0.394834
44	0.045345	0.3874	0.349783
45	-0.112536	-0.9615	0.169736
46	0.091593	0.7826	0.218205
47	-0.06646	-0.5678	0.285944
48	-0.127544	-1.0897	0.139706

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.070231 & 0.6001 & 0.275164 \tabularnewline
2 & 0.066054 & 0.5644 & 0.287119 \tabularnewline
3 & 0.260101 & 2.2223 & 0.014681 \tabularnewline
4 & -0.069934 & -0.5975 & 0.276006 \tabularnewline
5 & 0.082281 & 0.703 & 0.242143 \tabularnewline
6 & 0.185271 & 1.583 & 0.058878 \tabularnewline
7 & -0.122086 & -1.0431 & 0.150172 \tabularnewline
8 & 0.108632 & 0.9282 & 0.178194 \tabularnewline
9 & 0.251431 & 2.1482 & 0.017507 \tabularnewline
10 & -0.129002 & -1.1022 & 0.137 \tabularnewline
11 & -0.044564 & -0.3808 & 0.352245 \tabularnewline
12 & -0.123261 & -1.0531 & 0.147875 \tabularnewline
13 & -0.215744 & -1.8433 & 0.034671 \tabularnewline
14 & 0.07198 & 0.615 & 0.270235 \tabularnewline
15 & -0.050639 & -0.4327 & 0.33327 \tabularnewline
16 & -0.107029 & -0.9145 & 0.181743 \tabularnewline
17 & 0.197931 & 1.6911 & 0.04754 \tabularnewline
18 & 0.023137 & 0.1977 & 0.42192 \tabularnewline
19 & -0.212359 & -1.8144 & 0.036863 \tabularnewline
20 & -0.012 & -0.1025 & 0.45931 \tabularnewline
21 & -0.00585 & -0.05 & 0.480136 \tabularnewline
22 & -0.155844 & -1.3315 & 0.093578 \tabularnewline
23 & 0.128873 & 1.1011 & 0.137238 \tabularnewline
24 & -0.247945 & -2.1184 & 0.018771 \tabularnewline
25 & -0.106843 & -0.9129 & 0.182159 \tabularnewline
26 & 0.063796 & 0.5451 & 0.293682 \tabularnewline
27 & -0.009877 & -0.0844 & 0.46649 \tabularnewline
28 & -0.111128 & -0.9495 & 0.172754 \tabularnewline
29 & 0.021599 & 0.1845 & 0.427049 \tabularnewline
30 & -0.042122 & -0.3599 & 0.359984 \tabularnewline
31 & 0.062636 & 0.5352 & 0.297083 \tabularnewline
32 & 0.140451 & 1.2 & 0.117006 \tabularnewline
33 & -0.137049 & -1.171 & 0.122713 \tabularnewline
34 & 0.061747 & 0.5276 & 0.299699 \tabularnewline
35 & 0.157184 & 1.343 & 0.09172 \tabularnewline
36 & 0.041714 & 0.3564 & 0.361284 \tabularnewline
37 & 0.194653 & 1.6631 & 0.050288 \tabularnewline
38 & 0.093219 & 0.7965 & 0.214173 \tabularnewline
39 & -0.0503 & -0.4298 & 0.334317 \tabularnewline
40 & 0.05596 & 0.4781 & 0.316997 \tabularnewline
41 & -0.029457 & -0.2517 & 0.400996 \tabularnewline
42 & -0.128084 & -1.0944 & 0.138699 \tabularnewline
43 & 0.031335 & 0.2677 & 0.394834 \tabularnewline
44 & 0.045345 & 0.3874 & 0.349783 \tabularnewline
45 & -0.112536 & -0.9615 & 0.169736 \tabularnewline
46 & 0.091593 & 0.7826 & 0.218205 \tabularnewline
47 & -0.06646 & -0.5678 & 0.285944 \tabularnewline
48 & -0.127544 & -1.0897 & 0.139706 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30818&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]0.070231[/C][C]0.6001[/C][C]0.275164[/C][/ROW]
[ROW][C]2[/C][C]0.066054[/C][C]0.5644[/C][C]0.287119[/C][/ROW]
[ROW][C]3[/C][C]0.260101[/C][C]2.2223[/C][C]0.014681[/C][/ROW]
[ROW][C]4[/C][C]-0.069934[/C][C]-0.5975[/C][C]0.276006[/C][/ROW]
[ROW][C]5[/C][C]0.082281[/C][C]0.703[/C][C]0.242143[/C][/ROW]
[ROW][C]6[/C][C]0.185271[/C][C]1.583[/C][C]0.058878[/C][/ROW]
[ROW][C]7[/C][C]-0.122086[/C][C]-1.0431[/C][C]0.150172[/C][/ROW]
[ROW][C]8[/C][C]0.108632[/C][C]0.9282[/C][C]0.178194[/C][/ROW]
[ROW][C]9[/C][C]0.251431[/C][C]2.1482[/C][C]0.017507[/C][/ROW]
[ROW][C]10[/C][C]-0.129002[/C][C]-1.1022[/C][C]0.137[/C][/ROW]
[ROW][C]11[/C][C]-0.044564[/C][C]-0.3808[/C][C]0.352245[/C][/ROW]
[ROW][C]12[/C][C]-0.123261[/C][C]-1.0531[/C][C]0.147875[/C][/ROW]
[ROW][C]13[/C][C]-0.215744[/C][C]-1.8433[/C][C]0.034671[/C][/ROW]
[ROW][C]14[/C][C]0.07198[/C][C]0.615[/C][C]0.270235[/C][/ROW]
[ROW][C]15[/C][C]-0.050639[/C][C]-0.4327[/C][C]0.33327[/C][/ROW]
[ROW][C]16[/C][C]-0.107029[/C][C]-0.9145[/C][C]0.181743[/C][/ROW]
[ROW][C]17[/C][C]0.197931[/C][C]1.6911[/C][C]0.04754[/C][/ROW]
[ROW][C]18[/C][C]0.023137[/C][C]0.1977[/C][C]0.42192[/C][/ROW]
[ROW][C]19[/C][C]-0.212359[/C][C]-1.8144[/C][C]0.036863[/C][/ROW]
[ROW][C]20[/C][C]-0.012[/C][C]-0.1025[/C][C]0.45931[/C][/ROW]
[ROW][C]21[/C][C]-0.00585[/C][C]-0.05[/C][C]0.480136[/C][/ROW]
[ROW][C]22[/C][C]-0.155844[/C][C]-1.3315[/C][C]0.093578[/C][/ROW]
[ROW][C]23[/C][C]0.128873[/C][C]1.1011[/C][C]0.137238[/C][/ROW]
[ROW][C]24[/C][C]-0.247945[/C][C]-2.1184[/C][C]0.018771[/C][/ROW]
[ROW][C]25[/C][C]-0.106843[/C][C]-0.9129[/C][C]0.182159[/C][/ROW]
[ROW][C]26[/C][C]0.063796[/C][C]0.5451[/C][C]0.293682[/C][/ROW]
[ROW][C]27[/C][C]-0.009877[/C][C]-0.0844[/C][C]0.46649[/C][/ROW]
[ROW][C]28[/C][C]-0.111128[/C][C]-0.9495[/C][C]0.172754[/C][/ROW]
[ROW][C]29[/C][C]0.021599[/C][C]0.1845[/C][C]0.427049[/C][/ROW]
[ROW][C]30[/C][C]-0.042122[/C][C]-0.3599[/C][C]0.359984[/C][/ROW]
[ROW][C]31[/C][C]0.062636[/C][C]0.5352[/C][C]0.297083[/C][/ROW]
[ROW][C]32[/C][C]0.140451[/C][C]1.2[/C][C]0.117006[/C][/ROW]
[ROW][C]33[/C][C]-0.137049[/C][C]-1.171[/C][C]0.122713[/C][/ROW]
[ROW][C]34[/C][C]0.061747[/C][C]0.5276[/C][C]0.299699[/C][/ROW]
[ROW][C]35[/C][C]0.157184[/C][C]1.343[/C][C]0.09172[/C][/ROW]
[ROW][C]36[/C][C]0.041714[/C][C]0.3564[/C][C]0.361284[/C][/ROW]
[ROW][C]37[/C][C]0.194653[/C][C]1.6631[/C][C]0.050288[/C][/ROW]
[ROW][C]38[/C][C]0.093219[/C][C]0.7965[/C][C]0.214173[/C][/ROW]
[ROW][C]39[/C][C]-0.0503[/C][C]-0.4298[/C][C]0.334317[/C][/ROW]
[ROW][C]40[/C][C]0.05596[/C][C]0.4781[/C][C]0.316997[/C][/ROW]
[ROW][C]41[/C][C]-0.029457[/C][C]-0.2517[/C][C]0.400996[/C][/ROW]
[ROW][C]42[/C][C]-0.128084[/C][C]-1.0944[/C][C]0.138699[/C][/ROW]
[ROW][C]43[/C][C]0.031335[/C][C]0.2677[/C][C]0.394834[/C][/ROW]
[ROW][C]44[/C][C]0.045345[/C][C]0.3874[/C][C]0.349783[/C][/ROW]
[ROW][C]45[/C][C]-0.112536[/C][C]-0.9615[/C][C]0.169736[/C][/ROW]
[ROW][C]46[/C][C]0.091593[/C][C]0.7826[/C][C]0.218205[/C][/ROW]
[ROW][C]47[/C][C]-0.06646[/C][C]-0.5678[/C][C]0.285944[/C][/ROW]
[ROW][C]48[/C][C]-0.127544[/C][C]-1.0897[/C][C]0.139706[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30818&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30818&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	0.070231	0.6001	0.275164
2	0.066054	0.5644	0.287119
3	0.260101	2.2223	0.014681
4	-0.069934	-0.5975	0.276006
5	0.082281	0.703	0.242143
6	0.185271	1.583	0.058878
7	-0.122086	-1.0431	0.150172
8	0.108632	0.9282	0.178194
9	0.251431	2.1482	0.017507
10	-0.129002	-1.1022	0.137
11	-0.044564	-0.3808	0.352245
12	-0.123261	-1.0531	0.147875
13	-0.215744	-1.8433	0.034671
14	0.07198	0.615	0.270235
15	-0.050639	-0.4327	0.33327
16	-0.107029	-0.9145	0.181743
17	0.197931	1.6911	0.04754
18	0.023137	0.1977	0.42192
19	-0.212359	-1.8144	0.036863
20	-0.012	-0.1025	0.45931
21	-0.00585	-0.05	0.480136
22	-0.155844	-1.3315	0.093578
23	0.128873	1.1011	0.137238
24	-0.247945	-2.1184	0.018771
25	-0.106843	-0.9129	0.182159
26	0.063796	0.5451	0.293682
27	-0.009877	-0.0844	0.46649
28	-0.111128	-0.9495	0.172754
29	0.021599	0.1845	0.427049
30	-0.042122	-0.3599	0.359984
31	0.062636	0.5352	0.297083
32	0.140451	1.2	0.117006
33	-0.137049	-1.171	0.122713
34	0.061747	0.5276	0.299699
35	0.157184	1.343	0.09172
36	0.041714	0.3564	0.361284
37	0.194653	1.6631	0.050288
38	0.093219	0.7965	0.214173
39	-0.0503	-0.4298	0.334317
40	0.05596	0.4781	0.316997
41	-0.029457	-0.2517	0.400996
42	-0.128084	-1.0944	0.138699
43	0.031335	0.2677	0.394834
44	0.045345	0.3874	0.349783
45	-0.112536	-0.9615	0.169736
46	0.091593	0.7826	0.218205
47	-0.06646	-0.5678	0.285944
48	-0.127544	-1.0897	0.139706

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.070231	0.6001	0.275164
2	0.061424	0.5248	0.300653
3	0.253637	2.1671	0.016746
4	-0.111901	-0.9561	0.171092
5	0.071611	0.6118	0.271271
6	0.127889	1.0927	0.139063
7	-0.118297	-1.0107	0.157741
8	0.077329	0.6607	0.255444
9	0.212708	1.8174	0.036632
10	-0.120868	-1.0327	0.152577
11	-0.155834	-1.3314	0.093593
12	-0.208715	-1.7833	0.03935
13	-0.090685	-0.7748	0.220476
14	0.085783	0.7329	0.232973
15	-0.009341	-0.0798	0.468303
16	0.022714	0.1941	0.423329
17	0.187684	1.6036	0.056563
18	0.046698	0.399	0.345533
19	-0.237872	-2.0324	0.022877
20	-0.086671	-0.7405	0.230681
21	0.223965	1.9136	0.029799
22	-0.09806	-0.8378	0.202432
23	-0.05734	-0.4899	0.312832
24	-0.337338	-2.8822	0.002592
25	-0.015047	-0.1286	0.449029
26	-0.067974	-0.5808	0.281592
27	0.217559	1.8588	0.033541
28	0.066126	0.565	0.286909
29	0.165261	1.412	0.081101
30	-0.003606	-0.0308	0.487753
31	-0.025244	-0.2157	0.414919
32	0.023064	0.1971	0.422166
33	0.032155	0.2747	0.392149
34	0.041038	0.3506	0.36344
35	0.01746	0.1492	0.440912
36	-0.008951	-0.0765	0.469623
37	0.067941	0.5805	0.281688
38	-0.09634	-0.8231	0.206558
39	-0.086695	-0.7407	0.23062
40	-0.070363	-0.6012	0.274792
41	0.054502	0.4657	0.321421
42	0.016494	0.1409	0.44416
43	-0.040113	-0.3427	0.366394
44	-0.04496	-0.3841	0.350996
45	-0.069717	-0.5957	0.276622
46	0.024402	0.2085	0.417714
47	0.080415	0.6871	0.24711
48	-0.127	-1.0851	0.140727

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.070231 & 0.6001 & 0.275164 \tabularnewline
2 & 0.061424 & 0.5248 & 0.300653 \tabularnewline
3 & 0.253637 & 2.1671 & 0.016746 \tabularnewline
4 & -0.111901 & -0.9561 & 0.171092 \tabularnewline
5 & 0.071611 & 0.6118 & 0.271271 \tabularnewline
6 & 0.127889 & 1.0927 & 0.139063 \tabularnewline
7 & -0.118297 & -1.0107 & 0.157741 \tabularnewline
8 & 0.077329 & 0.6607 & 0.255444 \tabularnewline
9 & 0.212708 & 1.8174 & 0.036632 \tabularnewline
10 & -0.120868 & -1.0327 & 0.152577 \tabularnewline
11 & -0.155834 & -1.3314 & 0.093593 \tabularnewline
12 & -0.208715 & -1.7833 & 0.03935 \tabularnewline
13 & -0.090685 & -0.7748 & 0.220476 \tabularnewline
14 & 0.085783 & 0.7329 & 0.232973 \tabularnewline
15 & -0.009341 & -0.0798 & 0.468303 \tabularnewline
16 & 0.022714 & 0.1941 & 0.423329 \tabularnewline
17 & 0.187684 & 1.6036 & 0.056563 \tabularnewline
18 & 0.046698 & 0.399 & 0.345533 \tabularnewline
19 & -0.237872 & -2.0324 & 0.022877 \tabularnewline
20 & -0.086671 & -0.7405 & 0.230681 \tabularnewline
21 & 0.223965 & 1.9136 & 0.029799 \tabularnewline
22 & -0.09806 & -0.8378 & 0.202432 \tabularnewline
23 & -0.05734 & -0.4899 & 0.312832 \tabularnewline
24 & -0.337338 & -2.8822 & 0.002592 \tabularnewline
25 & -0.015047 & -0.1286 & 0.449029 \tabularnewline
26 & -0.067974 & -0.5808 & 0.281592 \tabularnewline
27 & 0.217559 & 1.8588 & 0.033541 \tabularnewline
28 & 0.066126 & 0.565 & 0.286909 \tabularnewline
29 & 0.165261 & 1.412 & 0.081101 \tabularnewline
30 & -0.003606 & -0.0308 & 0.487753 \tabularnewline
31 & -0.025244 & -0.2157 & 0.414919 \tabularnewline
32 & 0.023064 & 0.1971 & 0.422166 \tabularnewline
33 & 0.032155 & 0.2747 & 0.392149 \tabularnewline
34 & 0.041038 & 0.3506 & 0.36344 \tabularnewline
35 & 0.01746 & 0.1492 & 0.440912 \tabularnewline
36 & -0.008951 & -0.0765 & 0.469623 \tabularnewline
37 & 0.067941 & 0.5805 & 0.281688 \tabularnewline
38 & -0.09634 & -0.8231 & 0.206558 \tabularnewline
39 & -0.086695 & -0.7407 & 0.23062 \tabularnewline
40 & -0.070363 & -0.6012 & 0.274792 \tabularnewline
41 & 0.054502 & 0.4657 & 0.321421 \tabularnewline
42 & 0.016494 & 0.1409 & 0.44416 \tabularnewline
43 & -0.040113 & -0.3427 & 0.366394 \tabularnewline
44 & -0.04496 & -0.3841 & 0.350996 \tabularnewline
45 & -0.069717 & -0.5957 & 0.276622 \tabularnewline
46 & 0.024402 & 0.2085 & 0.417714 \tabularnewline
47 & 0.080415 & 0.6871 & 0.24711 \tabularnewline
48 & -0.127 & -1.0851 & 0.140727 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30818&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]0.070231[/C][C]0.6001[/C][C]0.275164[/C][/ROW]
[ROW][C]2[/C][C]0.061424[/C][C]0.5248[/C][C]0.300653[/C][/ROW]
[ROW][C]3[/C][C]0.253637[/C][C]2.1671[/C][C]0.016746[/C][/ROW]
[ROW][C]4[/C][C]-0.111901[/C][C]-0.9561[/C][C]0.171092[/C][/ROW]
[ROW][C]5[/C][C]0.071611[/C][C]0.6118[/C][C]0.271271[/C][/ROW]
[ROW][C]6[/C][C]0.127889[/C][C]1.0927[/C][C]0.139063[/C][/ROW]
[ROW][C]7[/C][C]-0.118297[/C][C]-1.0107[/C][C]0.157741[/C][/ROW]
[ROW][C]8[/C][C]0.077329[/C][C]0.6607[/C][C]0.255444[/C][/ROW]
[ROW][C]9[/C][C]0.212708[/C][C]1.8174[/C][C]0.036632[/C][/ROW]
[ROW][C]10[/C][C]-0.120868[/C][C]-1.0327[/C][C]0.152577[/C][/ROW]
[ROW][C]11[/C][C]-0.155834[/C][C]-1.3314[/C][C]0.093593[/C][/ROW]
[ROW][C]12[/C][C]-0.208715[/C][C]-1.7833[/C][C]0.03935[/C][/ROW]
[ROW][C]13[/C][C]-0.090685[/C][C]-0.7748[/C][C]0.220476[/C][/ROW]
[ROW][C]14[/C][C]0.085783[/C][C]0.7329[/C][C]0.232973[/C][/ROW]
[ROW][C]15[/C][C]-0.009341[/C][C]-0.0798[/C][C]0.468303[/C][/ROW]
[ROW][C]16[/C][C]0.022714[/C][C]0.1941[/C][C]0.423329[/C][/ROW]
[ROW][C]17[/C][C]0.187684[/C][C]1.6036[/C][C]0.056563[/C][/ROW]
[ROW][C]18[/C][C]0.046698[/C][C]0.399[/C][C]0.345533[/C][/ROW]
[ROW][C]19[/C][C]-0.237872[/C][C]-2.0324[/C][C]0.022877[/C][/ROW]
[ROW][C]20[/C][C]-0.086671[/C][C]-0.7405[/C][C]0.230681[/C][/ROW]
[ROW][C]21[/C][C]0.223965[/C][C]1.9136[/C][C]0.029799[/C][/ROW]
[ROW][C]22[/C][C]-0.09806[/C][C]-0.8378[/C][C]0.202432[/C][/ROW]
[ROW][C]23[/C][C]-0.05734[/C][C]-0.4899[/C][C]0.312832[/C][/ROW]
[ROW][C]24[/C][C]-0.337338[/C][C]-2.8822[/C][C]0.002592[/C][/ROW]
[ROW][C]25[/C][C]-0.015047[/C][C]-0.1286[/C][C]0.449029[/C][/ROW]
[ROW][C]26[/C][C]-0.067974[/C][C]-0.5808[/C][C]0.281592[/C][/ROW]
[ROW][C]27[/C][C]0.217559[/C][C]1.8588[/C][C]0.033541[/C][/ROW]
[ROW][C]28[/C][C]0.066126[/C][C]0.565[/C][C]0.286909[/C][/ROW]
[ROW][C]29[/C][C]0.165261[/C][C]1.412[/C][C]0.081101[/C][/ROW]
[ROW][C]30[/C][C]-0.003606[/C][C]-0.0308[/C][C]0.487753[/C][/ROW]
[ROW][C]31[/C][C]-0.025244[/C][C]-0.2157[/C][C]0.414919[/C][/ROW]
[ROW][C]32[/C][C]0.023064[/C][C]0.1971[/C][C]0.422166[/C][/ROW]
[ROW][C]33[/C][C]0.032155[/C][C]0.2747[/C][C]0.392149[/C][/ROW]
[ROW][C]34[/C][C]0.041038[/C][C]0.3506[/C][C]0.36344[/C][/ROW]
[ROW][C]35[/C][C]0.01746[/C][C]0.1492[/C][C]0.440912[/C][/ROW]
[ROW][C]36[/C][C]-0.008951[/C][C]-0.0765[/C][C]0.469623[/C][/ROW]
[ROW][C]37[/C][C]0.067941[/C][C]0.5805[/C][C]0.281688[/C][/ROW]
[ROW][C]38[/C][C]-0.09634[/C][C]-0.8231[/C][C]0.206558[/C][/ROW]
[ROW][C]39[/C][C]-0.086695[/C][C]-0.7407[/C][C]0.23062[/C][/ROW]
[ROW][C]40[/C][C]-0.070363[/C][C]-0.6012[/C][C]0.274792[/C][/ROW]
[ROW][C]41[/C][C]0.054502[/C][C]0.4657[/C][C]0.321421[/C][/ROW]
[ROW][C]42[/C][C]0.016494[/C][C]0.1409[/C][C]0.44416[/C][/ROW]
[ROW][C]43[/C][C]-0.040113[/C][C]-0.3427[/C][C]0.366394[/C][/ROW]
[ROW][C]44[/C][C]-0.04496[/C][C]-0.3841[/C][C]0.350996[/C][/ROW]
[ROW][C]45[/C][C]-0.069717[/C][C]-0.5957[/C][C]0.276622[/C][/ROW]
[ROW][C]46[/C][C]0.024402[/C][C]0.2085[/C][C]0.417714[/C][/ROW]
[ROW][C]47[/C][C]0.080415[/C][C]0.6871[/C][C]0.24711[/C][/ROW]
[ROW][C]48[/C][C]-0.127[/C][C]-1.0851[/C][C]0.140727[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30818&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30818&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	0.070231	0.6001	0.275164
2	0.061424	0.5248	0.300653
3	0.253637	2.1671	0.016746
4	-0.111901	-0.9561	0.171092
5	0.071611	0.6118	0.271271
6	0.127889	1.0927	0.139063
7	-0.118297	-1.0107	0.157741
8	0.077329	0.6607	0.255444
9	0.212708	1.8174	0.036632
10	-0.120868	-1.0327	0.152577
11	-0.155834	-1.3314	0.093593
12	-0.208715	-1.7833	0.03935
13	-0.090685	-0.7748	0.220476
14	0.085783	0.7329	0.232973
15	-0.009341	-0.0798	0.468303
16	0.022714	0.1941	0.423329
17	0.187684	1.6036	0.056563
18	0.046698	0.399	0.345533
19	-0.237872	-2.0324	0.022877
20	-0.086671	-0.7405	0.230681
21	0.223965	1.9136	0.029799
22	-0.09806	-0.8378	0.202432
23	-0.05734	-0.4899	0.312832
24	-0.337338	-2.8822	0.002592
25	-0.015047	-0.1286	0.449029
26	-0.067974	-0.5808	0.281592
27	0.217559	1.8588	0.033541
28	0.066126	0.565	0.286909
29	0.165261	1.412	0.081101
30	-0.003606	-0.0308	0.487753
31	-0.025244	-0.2157	0.414919
32	0.023064	0.1971	0.422166
33	0.032155	0.2747	0.392149
34	0.041038	0.3506	0.36344
35	0.01746	0.1492	0.440912
36	-0.008951	-0.0765	0.469623
37	0.067941	0.5805	0.281688
38	-0.09634	-0.8231	0.206558
39	-0.086695	-0.7407	0.23062
40	-0.070363	-0.6012	0.274792
41	0.054502	0.4657	0.321421
42	0.016494	0.1409	0.44416
43	-0.040113	-0.3427	0.366394
44	-0.04496	-0.3841	0.350996
45	-0.069717	-0.5957	0.276622
46	0.024402	0.2085	0.417714
47	0.080415	0.6871	0.24711
48	-0.127	-1.0851	0.140727

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 48 ; par2 = -0.1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ;

Parameters (R input):

par1 = 48 ; par2 = -0.1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ;

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 (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='pic1.png')
racf <- acf(x,par1,main='Autocorrelation',xlab='lags',ylab='ACF')
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
dev.off()
(myacf <- c(racf$acf))
(mypacf <- c(rpacf$acf))
lengthx <- length(x)
sqrtn <- sqrt(lengthx)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','ACF(k)','click here for more information about the Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 2:(par1+1)) {
a<-table.row.start(a)
a<-table.element(a,i-1,header=TRUE)
a<-table.element(a,round(myacf[i],6))
mytstat <- myacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Partial Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','PACF(k)','click here for more information about the Partial Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:par1) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,round(mypacf[i],6))
mytstat <- mypacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code