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R Software Module

rwasp_autocorrelation.wasp

Title produced by software

(Partial) Autocorrelation Function

Date of computation

Sun, 07 Dec 2008 06:14:32 -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/07/t122865571905cq1b6v92lbf1e.htm/, Retrieved Sun, 19 May 2024 11:38:40 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=29938, Retrieved Sun, 19 May 2024 11:38:40 +0000

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User-defined keywords

Estimated Impact

210

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

F     [Variance Reduction Matrix] [step 2 uitvoer] [2008-12-05 17:47:26] [3a9fc6d5b5e0e816787b7dbace57e7cd]
F RMPD  [Spectral Analysis] [step 2 uitvoer] [2008-12-05 18:02:42] [3a9fc6d5b5e0e816787b7dbace57e7cd]
F RMP       [(Partial) Autocorrelation Function] [step 3] [2008-12-07 13:14:32] [821c4b3d195be8e737cf8c9dc649d3cf] [Current]
F RMP         [ARIMA Backward Selection] [step 5] [2008-12-07 13:24:10] [3a9fc6d5b5e0e816787b7dbace57e7cd] 
- RMPD          [ARIMA Forecasting] [ARIMA forecasting] [2008-12-09 19:14:50] [3a9fc6d5b5e0e816787b7dbace57e7cd] 
-   P           [ARIMA Backward Selection] [verbetering] [2008-12-16 19:23:33] [3a9fc6d5b5e0e816787b7dbace57e7cd] 
-   P         [(Partial) Autocorrelation Function] [verbetering] [2008-12-16 19:16:45] [3a9fc6d5b5e0e816787b7dbace57e7cd] 

Feedback Forum

2008-12-15 15:38:03 [Natalie De Wilde] [reply] 
Zoals al gezegd bij step 2, is er nog wel een lange termijn trend te zien bij ACF en Spectral Analysis. De seizoenaliteit heb je wel weggewerkt.
2008-12-15 15:44:29 [Natalie De Wilde] [reply] 
Je baseert je op de grafieken bij transformatieparameters d =0 en D=1. Ik weet niet of je dan het juiste model verkrijgt.
2008-12-16 19:19:48 [Gert-Jan Geudens] [reply] 
Niet correct. We zien hier nog duidelijk een lineaire trend. Het volstaat dus niet om enkel seizonaal te differentiëren.  
 
De correcte output kan je hier vinden :  
 
http://www.freestatistics.org/blog/date/2008/Dec/16/t12294550805xuusv7t5g0q8lm.htm 
 
bij d=1 en D=1 bekomen we een stationaire reeks.
2008-12-16 19:22:02 [Gert-Jan Geudens] [reply] 
Step 4 : De gevonden conclusie is waarschijnlijk niet correct aangezien je tijdreeks nog niet stationair is. 
 
Hier kan je de correcte output vinden: 
 
http://www.freestatistics.org/blog/date/2008/Dec/16/t12294550805xuusv7t5g0q8lm.htm  
 
je werkwijze was wel correct. Nu moet je dus, exact hetzelfde doen op bovenstaande output, om het correcte resultaat te bekomen.

Post a new message

Dataseries X:

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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	3 seconds
R Server	'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 3 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29938&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29938&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29938&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	3 seconds
R Server	'Herman Ole Andreas Wold' @ 193.190.124.10:1001

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.509828	3.9491	0.000104
2	0.442776	3.4297	0.000549
3	0.515627	3.994	9e-05
4	0.276785	2.144	0.018049
5	0.236557	1.8324	0.03593
6	0.26752	2.0722	0.021276
7	0.067788	0.5251	0.30073
8	0.083029	0.6431	0.261291
9	0.055572	0.4305	0.334203
10	-0.141031	-1.0924	0.139507
11	-0.122091	-0.9457	0.174044
12	-0.144378	-1.1183	0.133939
13	-0.150551	-1.1662	0.124082
14	-0.061726	-0.4781	0.317147
15	-0.010566	-0.0818	0.467522
16	-0.135023	-1.0459	0.149904
17	0.042905	0.3323	0.370395
18	0.010731	0.0831	0.467015
19	-0.058464	-0.4529	0.326141
20	0.152905	1.1844	0.120463
21	0.078309	0.6066	0.273208
22	0.069063	0.535	0.297328
23	0.184578	1.4297	0.07899
24	0.037683	0.2919	0.38569
25	-0.054177	-0.4197	0.33812
26	0.001799	0.0139	0.494464
27	-0.142919	-1.107	0.136347
28	-0.127517	-0.9877	0.163624
29	-0.105648	-0.8183	0.208199
30	-0.215562	-1.6697	0.05009
31	-0.216111	-1.674	0.04967
32	-0.195751	-1.5163	0.06735
33	-0.257801	-1.9969	0.025188
34	-0.279198	-2.1627	0.017282
35	-0.191612	-1.4842	0.071492
36	-0.251628	-1.9491	0.027981

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.509828 & 3.9491 & 0.000104 \tabularnewline
2 & 0.442776 & 3.4297 & 0.000549 \tabularnewline
3 & 0.515627 & 3.994 & 9e-05 \tabularnewline
4 & 0.276785 & 2.144 & 0.018049 \tabularnewline
5 & 0.236557 & 1.8324 & 0.03593 \tabularnewline
6 & 0.26752 & 2.0722 & 0.021276 \tabularnewline
7 & 0.067788 & 0.5251 & 0.30073 \tabularnewline
8 & 0.083029 & 0.6431 & 0.261291 \tabularnewline
9 & 0.055572 & 0.4305 & 0.334203 \tabularnewline
10 & -0.141031 & -1.0924 & 0.139507 \tabularnewline
11 & -0.122091 & -0.9457 & 0.174044 \tabularnewline
12 & -0.144378 & -1.1183 & 0.133939 \tabularnewline
13 & -0.150551 & -1.1662 & 0.124082 \tabularnewline
14 & -0.061726 & -0.4781 & 0.317147 \tabularnewline
15 & -0.010566 & -0.0818 & 0.467522 \tabularnewline
16 & -0.135023 & -1.0459 & 0.149904 \tabularnewline
17 & 0.042905 & 0.3323 & 0.370395 \tabularnewline
18 & 0.010731 & 0.0831 & 0.467015 \tabularnewline
19 & -0.058464 & -0.4529 & 0.326141 \tabularnewline
20 & 0.152905 & 1.1844 & 0.120463 \tabularnewline
21 & 0.078309 & 0.6066 & 0.273208 \tabularnewline
22 & 0.069063 & 0.535 & 0.297328 \tabularnewline
23 & 0.184578 & 1.4297 & 0.07899 \tabularnewline
24 & 0.037683 & 0.2919 & 0.38569 \tabularnewline
25 & -0.054177 & -0.4197 & 0.33812 \tabularnewline
26 & 0.001799 & 0.0139 & 0.494464 \tabularnewline
27 & -0.142919 & -1.107 & 0.136347 \tabularnewline
28 & -0.127517 & -0.9877 & 0.163624 \tabularnewline
29 & -0.105648 & -0.8183 & 0.208199 \tabularnewline
30 & -0.215562 & -1.6697 & 0.05009 \tabularnewline
31 & -0.216111 & -1.674 & 0.04967 \tabularnewline
32 & -0.195751 & -1.5163 & 0.06735 \tabularnewline
33 & -0.257801 & -1.9969 & 0.025188 \tabularnewline
34 & -0.279198 & -2.1627 & 0.017282 \tabularnewline
35 & -0.191612 & -1.4842 & 0.071492 \tabularnewline
36 & -0.251628 & -1.9491 & 0.027981 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29938&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]0.509828[/C][C]3.9491[/C][C]0.000104[/C][/ROW]
[ROW][C]2[/C][C]0.442776[/C][C]3.4297[/C][C]0.000549[/C][/ROW]
[ROW][C]3[/C][C]0.515627[/C][C]3.994[/C][C]9e-05[/C][/ROW]
[ROW][C]4[/C][C]0.276785[/C][C]2.144[/C][C]0.018049[/C][/ROW]
[ROW][C]5[/C][C]0.236557[/C][C]1.8324[/C][C]0.03593[/C][/ROW]
[ROW][C]6[/C][C]0.26752[/C][C]2.0722[/C][C]0.021276[/C][/ROW]
[ROW][C]7[/C][C]0.067788[/C][C]0.5251[/C][C]0.30073[/C][/ROW]
[ROW][C]8[/C][C]0.083029[/C][C]0.6431[/C][C]0.261291[/C][/ROW]
[ROW][C]9[/C][C]0.055572[/C][C]0.4305[/C][C]0.334203[/C][/ROW]
[ROW][C]10[/C][C]-0.141031[/C][C]-1.0924[/C][C]0.139507[/C][/ROW]
[ROW][C]11[/C][C]-0.122091[/C][C]-0.9457[/C][C]0.174044[/C][/ROW]
[ROW][C]12[/C][C]-0.144378[/C][C]-1.1183[/C][C]0.133939[/C][/ROW]
[ROW][C]13[/C][C]-0.150551[/C][C]-1.1662[/C][C]0.124082[/C][/ROW]
[ROW][C]14[/C][C]-0.061726[/C][C]-0.4781[/C][C]0.317147[/C][/ROW]
[ROW][C]15[/C][C]-0.010566[/C][C]-0.0818[/C][C]0.467522[/C][/ROW]
[ROW][C]16[/C][C]-0.135023[/C][C]-1.0459[/C][C]0.149904[/C][/ROW]
[ROW][C]17[/C][C]0.042905[/C][C]0.3323[/C][C]0.370395[/C][/ROW]
[ROW][C]18[/C][C]0.010731[/C][C]0.0831[/C][C]0.467015[/C][/ROW]
[ROW][C]19[/C][C]-0.058464[/C][C]-0.4529[/C][C]0.326141[/C][/ROW]
[ROW][C]20[/C][C]0.152905[/C][C]1.1844[/C][C]0.120463[/C][/ROW]
[ROW][C]21[/C][C]0.078309[/C][C]0.6066[/C][C]0.273208[/C][/ROW]
[ROW][C]22[/C][C]0.069063[/C][C]0.535[/C][C]0.297328[/C][/ROW]
[ROW][C]23[/C][C]0.184578[/C][C]1.4297[/C][C]0.07899[/C][/ROW]
[ROW][C]24[/C][C]0.037683[/C][C]0.2919[/C][C]0.38569[/C][/ROW]
[ROW][C]25[/C][C]-0.054177[/C][C]-0.4197[/C][C]0.33812[/C][/ROW]
[ROW][C]26[/C][C]0.001799[/C][C]0.0139[/C][C]0.494464[/C][/ROW]
[ROW][C]27[/C][C]-0.142919[/C][C]-1.107[/C][C]0.136347[/C][/ROW]
[ROW][C]28[/C][C]-0.127517[/C][C]-0.9877[/C][C]0.163624[/C][/ROW]
[ROW][C]29[/C][C]-0.105648[/C][C]-0.8183[/C][C]0.208199[/C][/ROW]
[ROW][C]30[/C][C]-0.215562[/C][C]-1.6697[/C][C]0.05009[/C][/ROW]
[ROW][C]31[/C][C]-0.216111[/C][C]-1.674[/C][C]0.04967[/C][/ROW]
[ROW][C]32[/C][C]-0.195751[/C][C]-1.5163[/C][C]0.06735[/C][/ROW]
[ROW][C]33[/C][C]-0.257801[/C][C]-1.9969[/C][C]0.025188[/C][/ROW]
[ROW][C]34[/C][C]-0.279198[/C][C]-2.1627[/C][C]0.017282[/C][/ROW]
[ROW][C]35[/C][C]-0.191612[/C][C]-1.4842[/C][C]0.071492[/C][/ROW]
[ROW][C]36[/C][C]-0.251628[/C][C]-1.9491[/C][C]0.027981[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29938&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29938&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	0.509828	3.9491	0.000104
2	0.442776	3.4297	0.000549
3	0.515627	3.994	9e-05
4	0.276785	2.144	0.018049
5	0.236557	1.8324	0.03593
6	0.26752	2.0722	0.021276
7	0.067788	0.5251	0.30073
8	0.083029	0.6431	0.261291
9	0.055572	0.4305	0.334203
10	-0.141031	-1.0924	0.139507
11	-0.122091	-0.9457	0.174044
12	-0.144378	-1.1183	0.133939
13	-0.150551	-1.1662	0.124082
14	-0.061726	-0.4781	0.317147
15	-0.010566	-0.0818	0.467522
16	-0.135023	-1.0459	0.149904
17	0.042905	0.3323	0.370395
18	0.010731	0.0831	0.467015
19	-0.058464	-0.4529	0.326141
20	0.152905	1.1844	0.120463
21	0.078309	0.6066	0.273208
22	0.069063	0.535	0.297328
23	0.184578	1.4297	0.07899
24	0.037683	0.2919	0.38569
25	-0.054177	-0.4197	0.33812
26	0.001799	0.0139	0.494464
27	-0.142919	-1.107	0.136347
28	-0.127517	-0.9877	0.163624
29	-0.105648	-0.8183	0.208199
30	-0.215562	-1.6697	0.05009
31	-0.216111	-1.674	0.04967
32	-0.195751	-1.5163	0.06735
33	-0.257801	-1.9969	0.025188
34	-0.279198	-2.1627	0.017282
35	-0.191612	-1.4842	0.071492
36	-0.251628	-1.9491	0.027981

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.509828	3.9491	0.000104
2	0.247071	1.9138	0.03021
3	0.316158	2.4489	0.008633
4	-0.156235	-1.2102	0.115476
5	-0.029783	-0.2307	0.409167
6	0.051135	0.3961	0.346721
7	-0.143959	-1.1151	0.134626
8	0.014565	0.1128	0.455275
9	-0.055794	-0.4322	0.33358
10	-0.180595	-1.3989	0.083498
11	-0.06095	-0.4721	0.319278
12	-0.043385	-0.3361	0.369
13	0.137855	1.0678	0.14494
14	0.118673	0.9192	0.180826
15	0.139918	1.0838	0.141394
16	-0.180441	-1.3977	0.083676
17	0.143562	1.112	0.135282
18	-0.045851	-0.3552	0.361858
19	-0.032126	-0.2488	0.402164
20	0.174033	1.3481	0.091354
21	-0.101783	-0.7884	0.216781
22	0.031536	0.2443	0.403926
23	-0.049606	-0.3842	0.351078
24	-0.098564	-0.7635	0.224086
25	-0.11675	-0.9043	0.184716
26	-0.100033	-0.7749	0.220735
27	-0.046265	-0.3584	0.360663
28	-0.017265	-0.1337	0.44703
29	0.015324	0.1187	0.452954
30	-0.050594	-0.3919	0.34826
31	-0.008209	-0.0636	0.474754
32	-0.006282	-0.0487	0.480676
33	0.050686	0.3926	0.347997
34	-0.094311	-0.7305	0.233955
35	-0.012116	-0.0939	0.462769
36	-0.054049	-0.4187	0.338478

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.509828 & 3.9491 & 0.000104 \tabularnewline
2 & 0.247071 & 1.9138 & 0.03021 \tabularnewline
3 & 0.316158 & 2.4489 & 0.008633 \tabularnewline
4 & -0.156235 & -1.2102 & 0.115476 \tabularnewline
5 & -0.029783 & -0.2307 & 0.409167 \tabularnewline
6 & 0.051135 & 0.3961 & 0.346721 \tabularnewline
7 & -0.143959 & -1.1151 & 0.134626 \tabularnewline
8 & 0.014565 & 0.1128 & 0.455275 \tabularnewline
9 & -0.055794 & -0.4322 & 0.33358 \tabularnewline
10 & -0.180595 & -1.3989 & 0.083498 \tabularnewline
11 & -0.06095 & -0.4721 & 0.319278 \tabularnewline
12 & -0.043385 & -0.3361 & 0.369 \tabularnewline
13 & 0.137855 & 1.0678 & 0.14494 \tabularnewline
14 & 0.118673 & 0.9192 & 0.180826 \tabularnewline
15 & 0.139918 & 1.0838 & 0.141394 \tabularnewline
16 & -0.180441 & -1.3977 & 0.083676 \tabularnewline
17 & 0.143562 & 1.112 & 0.135282 \tabularnewline
18 & -0.045851 & -0.3552 & 0.361858 \tabularnewline
19 & -0.032126 & -0.2488 & 0.402164 \tabularnewline
20 & 0.174033 & 1.3481 & 0.091354 \tabularnewline
21 & -0.101783 & -0.7884 & 0.216781 \tabularnewline
22 & 0.031536 & 0.2443 & 0.403926 \tabularnewline
23 & -0.049606 & -0.3842 & 0.351078 \tabularnewline
24 & -0.098564 & -0.7635 & 0.224086 \tabularnewline
25 & -0.11675 & -0.9043 & 0.184716 \tabularnewline
26 & -0.100033 & -0.7749 & 0.220735 \tabularnewline
27 & -0.046265 & -0.3584 & 0.360663 \tabularnewline
28 & -0.017265 & -0.1337 & 0.44703 \tabularnewline
29 & 0.015324 & 0.1187 & 0.452954 \tabularnewline
30 & -0.050594 & -0.3919 & 0.34826 \tabularnewline
31 & -0.008209 & -0.0636 & 0.474754 \tabularnewline
32 & -0.006282 & -0.0487 & 0.480676 \tabularnewline
33 & 0.050686 & 0.3926 & 0.347997 \tabularnewline
34 & -0.094311 & -0.7305 & 0.233955 \tabularnewline
35 & -0.012116 & -0.0939 & 0.462769 \tabularnewline
36 & -0.054049 & -0.4187 & 0.338478 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29938&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]0.509828[/C][C]3.9491[/C][C]0.000104[/C][/ROW]
[ROW][C]2[/C][C]0.247071[/C][C]1.9138[/C][C]0.03021[/C][/ROW]
[ROW][C]3[/C][C]0.316158[/C][C]2.4489[/C][C]0.008633[/C][/ROW]
[ROW][C]4[/C][C]-0.156235[/C][C]-1.2102[/C][C]0.115476[/C][/ROW]
[ROW][C]5[/C][C]-0.029783[/C][C]-0.2307[/C][C]0.409167[/C][/ROW]
[ROW][C]6[/C][C]0.051135[/C][C]0.3961[/C][C]0.346721[/C][/ROW]
[ROW][C]7[/C][C]-0.143959[/C][C]-1.1151[/C][C]0.134626[/C][/ROW]
[ROW][C]8[/C][C]0.014565[/C][C]0.1128[/C][C]0.455275[/C][/ROW]
[ROW][C]9[/C][C]-0.055794[/C][C]-0.4322[/C][C]0.33358[/C][/ROW]
[ROW][C]10[/C][C]-0.180595[/C][C]-1.3989[/C][C]0.083498[/C][/ROW]
[ROW][C]11[/C][C]-0.06095[/C][C]-0.4721[/C][C]0.319278[/C][/ROW]
[ROW][C]12[/C][C]-0.043385[/C][C]-0.3361[/C][C]0.369[/C][/ROW]
[ROW][C]13[/C][C]0.137855[/C][C]1.0678[/C][C]0.14494[/C][/ROW]
[ROW][C]14[/C][C]0.118673[/C][C]0.9192[/C][C]0.180826[/C][/ROW]
[ROW][C]15[/C][C]0.139918[/C][C]1.0838[/C][C]0.141394[/C][/ROW]
[ROW][C]16[/C][C]-0.180441[/C][C]-1.3977[/C][C]0.083676[/C][/ROW]
[ROW][C]17[/C][C]0.143562[/C][C]1.112[/C][C]0.135282[/C][/ROW]
[ROW][C]18[/C][C]-0.045851[/C][C]-0.3552[/C][C]0.361858[/C][/ROW]
[ROW][C]19[/C][C]-0.032126[/C][C]-0.2488[/C][C]0.402164[/C][/ROW]
[ROW][C]20[/C][C]0.174033[/C][C]1.3481[/C][C]0.091354[/C][/ROW]
[ROW][C]21[/C][C]-0.101783[/C][C]-0.7884[/C][C]0.216781[/C][/ROW]
[ROW][C]22[/C][C]0.031536[/C][C]0.2443[/C][C]0.403926[/C][/ROW]
[ROW][C]23[/C][C]-0.049606[/C][C]-0.3842[/C][C]0.351078[/C][/ROW]
[ROW][C]24[/C][C]-0.098564[/C][C]-0.7635[/C][C]0.224086[/C][/ROW]
[ROW][C]25[/C][C]-0.11675[/C][C]-0.9043[/C][C]0.184716[/C][/ROW]
[ROW][C]26[/C][C]-0.100033[/C][C]-0.7749[/C][C]0.220735[/C][/ROW]
[ROW][C]27[/C][C]-0.046265[/C][C]-0.3584[/C][C]0.360663[/C][/ROW]
[ROW][C]28[/C][C]-0.017265[/C][C]-0.1337[/C][C]0.44703[/C][/ROW]
[ROW][C]29[/C][C]0.015324[/C][C]0.1187[/C][C]0.452954[/C][/ROW]
[ROW][C]30[/C][C]-0.050594[/C][C]-0.3919[/C][C]0.34826[/C][/ROW]
[ROW][C]31[/C][C]-0.008209[/C][C]-0.0636[/C][C]0.474754[/C][/ROW]
[ROW][C]32[/C][C]-0.006282[/C][C]-0.0487[/C][C]0.480676[/C][/ROW]
[ROW][C]33[/C][C]0.050686[/C][C]0.3926[/C][C]0.347997[/C][/ROW]
[ROW][C]34[/C][C]-0.094311[/C][C]-0.7305[/C][C]0.233955[/C][/ROW]
[ROW][C]35[/C][C]-0.012116[/C][C]-0.0939[/C][C]0.462769[/C][/ROW]
[ROW][C]36[/C][C]-0.054049[/C][C]-0.4187[/C][C]0.338478[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29938&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29938&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	0.509828	3.9491	0.000104
2	0.247071	1.9138	0.03021
3	0.316158	2.4489	0.008633
4	-0.156235	-1.2102	0.115476
5	-0.029783	-0.2307	0.409167
6	0.051135	0.3961	0.346721
7	-0.143959	-1.1151	0.134626
8	0.014565	0.1128	0.455275
9	-0.055794	-0.4322	0.33358
10	-0.180595	-1.3989	0.083498
11	-0.06095	-0.4721	0.319278
12	-0.043385	-0.3361	0.369
13	0.137855	1.0678	0.14494
14	0.118673	0.9192	0.180826
15	0.139918	1.0838	0.141394
16	-0.180441	-1.3977	0.083676
17	0.143562	1.112	0.135282
18	-0.045851	-0.3552	0.361858
19	-0.032126	-0.2488	0.402164
20	0.174033	1.3481	0.091354
21	-0.101783	-0.7884	0.216781
22	0.031536	0.2443	0.403926
23	-0.049606	-0.3842	0.351078
24	-0.098564	-0.7635	0.224086
25	-0.11675	-0.9043	0.184716
26	-0.100033	-0.7749	0.220735
27	-0.046265	-0.3584	0.360663
28	-0.017265	-0.1337	0.44703
29	0.015324	0.1187	0.452954
30	-0.050594	-0.3919	0.34826
31	-0.008209	-0.0636	0.474754
32	-0.006282	-0.0487	0.480676
33	0.050686	0.3926	0.347997
34	-0.094311	-0.7305	0.233955
35	-0.012116	-0.0939	0.462769
36	-0.054049	-0.4187	0.338478

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 36 ; par2 = -0.3 ; par3 = 0 ; par4 = 1 ; par5 = 12 ;

Parameters (R input):

par1 = 36 ; par2 = -0.3 ; 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