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R Software Module

rwasp_autocorrelation.wasp

Title produced by software

(Partial) Autocorrelation Function

Date of computation

Fri, 05 Dec 2008 11:14:04 -0700

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Dec/05/t1228500930fn6i2deyn9pasje.htm/, Retrieved Fri, 01 Nov 2024 00:19:24 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=29376, Retrieved Fri, 01 Nov 2024 00:19:24 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

297

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   [Spectral Analysis] [ARMA - spectral a...] [2008-12-05 16:40:04] [5393e1e70f7d2761ff95f84c9c07decf]
F   P     [Spectral Analysis] [ARMA - spectral a...] [2008-12-05 16:46:36] [5393e1e70f7d2761ff95f84c9c07decf]
F RMP       [Standard Deviation-Mean Plot] [ARMA - standard d...] [2008-12-05 16:57:59] [5393e1e70f7d2761ff95f84c9c07decf]
F RM            [(Partial) Autocorrelation Function] [ARMA - (P)ACF] [2008-12-05 18:14:04] [ba53780e6ef414874481f097d8d35fc7] [Current]
- RMP             [ARIMA Backward Selection] [ARMA- backward se...] [2008-12-06 16:03:03] [5393e1e70f7d2761ff95f84c9c07decf] 
F   P               [ARIMA Backward Selection] [ARMA- backward se...] [2008-12-06 16:08:18] [5393e1e70f7d2761ff95f84c9c07decf] 
F   P                 [ARIMA Backward Selection] [ARMA Backward Sel...] [2008-12-07 23:19:17] [d32f94eec6fe2d8c421bd223368a5ced] 
-   P               [ARIMA Backward Selection] [ARMA Backward Sel...] [2008-12-07 23:17:15] [d32f94eec6fe2d8c421bd223368a5ced] 
- RMP               [Standard Deviation-Mean Plot] [Step 1 Standard D...] [2008-12-08 12:16:05] [82970caad4b026be9dd352fdec547fe4] 
F   P             [(Partial) Autocorrelation Function] [ARMA P(ACF)] [2008-12-07 23:00:55] [d32f94eec6fe2d8c421bd223368a5ced] 
F   P             [(Partial) Autocorrelation Function] [Step 2] [2008-12-08 11:59:04] [82970caad4b026be9dd352fdec547fe4] 
F                   [(Partial) Autocorrelation Function] [ARMA Step 3] [2008-12-08 23:14:21] [d32f94eec6fe2d8c421bd223368a5ced] 
- RM                  [Spectral Analysis] [Hercomputatie fee...] [2008-12-12 20:58:58] [deb3c14ac9e4607a6d84fc9d0e0e6cc2] 
F                   [(Partial) Autocorrelation Function] [ARMA - (P)ACF] [2008-12-09 06:50:57] [5393e1e70f7d2761ff95f84c9c07decf] 

Feedback Forum

2008-12-14 15:46:48 [Mehmet Yilmaz] [reply] 
De student maakt gebruik van de juiste software. 
 
De volgende gegevens zijn ingevoerd:  
time lags = 60 
Lambda = 0,5 
d = 1 
D = 1 
periode = 12.  
 
Deze waarden werden bekomen in voorgaande stappen.  
Nadien worden voor p, P, q en Q de juiste waarden bepaald. 
 
p = 3 
bij de partiele correlatie zien we dat de eerste 2 coefficienten significant zijn, de derde is een twijfelgeval waardoor we de waarde van p gelijkstellen aan 3. 
 
P = 0 
we kijken op de grafiek of de tabel van de autocorrelatie (want AR-model) naar de autocorrelatiewaarden van 12, 24, 36, 48 en 60. We zien dat enkel de lag van 12 significant verschilt van 0, de overige niet. Dit wil zeggen dat er geen saisonaal patroon aanwezig is, de waarde van P is dus 0. 
 
q = 0 
we moeten het typische patroon van een MA-model op de grafiek van de partiële autocorrelatie proberen te zoeken. In dit geval is er geen sprake van het typische patroon (negatieve, naar 0 convergerende waarden), waardoor we kunnen besluiten dat q = 0. 
 
Q = 1 
we moeten het typische patroon van een MA-model op de grafiek van de partiele autocorrelatie proberen te zoeken. Bij lags 12, 24, 36, enz. zien we een aflopend patroon indien we de lag van 24 een beetje verlengen. Enkel de lag van twaalf is significant, dus er is sprake van een eerste orde. Q is dus 1.
2008-12-15 19:43:24 [Jan Cavents] [reply] 
aan de uitgebreide feedback van Mehmet Yilmaz kan ik spijtig genoeg niets meer toevoegen.

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	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=29376&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=29376&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29376&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	0.210141	3.9816	4.1e-05
2	0.325131	6.1603	0
3	0.153275	2.9041	0.001955
4	0.167252	3.169	0.000831
5	0.099156	1.8787	0.030545
6	0.064513	1.2223	0.111191
7	-0.057203	-1.0838	0.13958
8	-0.023244	-0.4404	0.329956
9	-0.085115	-1.6127	0.053845
10	-0.168424	-3.1912	0.000771
11	-0.075939	-1.4388	0.075533
12	-0.475334	-9.0063	0
13	-0.179215	-3.3956	0.000381
14	-0.162819	-3.085	0.001097
15	-0.106644	-2.0206	0.02203
16	-0.147945	-2.8032	0.002668
17	-0.091478	-1.7333	0.041954
18	-0.089745	-1.7004	0.044958
19	0.027328	0.5178	0.302458
20	-0.012913	-0.2447	0.403425
21	0.024199	0.4585	0.323437
22	-0.018741	-0.3551	0.361367
23	0.009567	0.1813	0.42813
24	-0.022226	-0.4211	0.336957
25	0.091974	1.7427	0.041125
26	-0.045751	-0.8668	0.193302
27	-0.014979	-0.2838	0.388362
28	0.034483	0.6534	0.256968
29	0.081474	1.5437	0.061769
30	0.012117	0.2296	0.409275
31	0.025552	0.4841	0.31429
32	-0.054477	-1.0322	0.151339
33	0.008649	0.1639	0.434964
34	0.016116	0.3054	0.380134
35	-0.058412	-1.1067	0.134573
36	-0.022491	-0.4261	0.335132
37	-0.120582	-2.2847	0.011456
38	0.014974	0.2837	0.388394
39	-0.025852	-0.4898	0.312276
40	-0.027437	-0.5199	0.301741
41	-0.10329	-1.9571	0.025557
42	-0.019216	-0.3641	0.358002
43	-0.134731	-2.5528	0.00555
44	0.003017	0.0572	0.477223
45	-0.055783	-1.0569	0.145624
46	0.012286	0.2328	0.408029
47	0.020367	0.3859	0.3499
48	0.107896	2.0443	0.020825
49	0.132443	2.5094	0.006266
50	0.100776	1.9094	0.028501
51	0.074363	1.409	0.079853
52	0.099064	1.877	0.030665
53	0.119078	2.2562	0.01233
54	0.061026	1.1563	0.12417
55	0.137393	2.6032	0.004809
56	0.052891	1.0021	0.158474
57	0.042954	0.8139	0.208131
58	0.03993	0.7566	0.224901
59	0.067573	1.2803	0.100629
60	-0.029187	-0.553	0.2903

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.210141 & 3.9816 & 4.1e-05 \tabularnewline
2 & 0.325131 & 6.1603 & 0 \tabularnewline
3 & 0.153275 & 2.9041 & 0.001955 \tabularnewline
4 & 0.167252 & 3.169 & 0.000831 \tabularnewline
5 & 0.099156 & 1.8787 & 0.030545 \tabularnewline
6 & 0.064513 & 1.2223 & 0.111191 \tabularnewline
7 & -0.057203 & -1.0838 & 0.13958 \tabularnewline
8 & -0.023244 & -0.4404 & 0.329956 \tabularnewline
9 & -0.085115 & -1.6127 & 0.053845 \tabularnewline
10 & -0.168424 & -3.1912 & 0.000771 \tabularnewline
11 & -0.075939 & -1.4388 & 0.075533 \tabularnewline
12 & -0.475334 & -9.0063 & 0 \tabularnewline
13 & -0.179215 & -3.3956 & 0.000381 \tabularnewline
14 & -0.162819 & -3.085 & 0.001097 \tabularnewline
15 & -0.106644 & -2.0206 & 0.02203 \tabularnewline
16 & -0.147945 & -2.8032 & 0.002668 \tabularnewline
17 & -0.091478 & -1.7333 & 0.041954 \tabularnewline
18 & -0.089745 & -1.7004 & 0.044958 \tabularnewline
19 & 0.027328 & 0.5178 & 0.302458 \tabularnewline
20 & -0.012913 & -0.2447 & 0.403425 \tabularnewline
21 & 0.024199 & 0.4585 & 0.323437 \tabularnewline
22 & -0.018741 & -0.3551 & 0.361367 \tabularnewline
23 & 0.009567 & 0.1813 & 0.42813 \tabularnewline
24 & -0.022226 & -0.4211 & 0.336957 \tabularnewline
25 & 0.091974 & 1.7427 & 0.041125 \tabularnewline
26 & -0.045751 & -0.8668 & 0.193302 \tabularnewline
27 & -0.014979 & -0.2838 & 0.388362 \tabularnewline
28 & 0.034483 & 0.6534 & 0.256968 \tabularnewline
29 & 0.081474 & 1.5437 & 0.061769 \tabularnewline
30 & 0.012117 & 0.2296 & 0.409275 \tabularnewline
31 & 0.025552 & 0.4841 & 0.31429 \tabularnewline
32 & -0.054477 & -1.0322 & 0.151339 \tabularnewline
33 & 0.008649 & 0.1639 & 0.434964 \tabularnewline
34 & 0.016116 & 0.3054 & 0.380134 \tabularnewline
35 & -0.058412 & -1.1067 & 0.134573 \tabularnewline
36 & -0.022491 & -0.4261 & 0.335132 \tabularnewline
37 & -0.120582 & -2.2847 & 0.011456 \tabularnewline
38 & 0.014974 & 0.2837 & 0.388394 \tabularnewline
39 & -0.025852 & -0.4898 & 0.312276 \tabularnewline
40 & -0.027437 & -0.5199 & 0.301741 \tabularnewline
41 & -0.10329 & -1.9571 & 0.025557 \tabularnewline
42 & -0.019216 & -0.3641 & 0.358002 \tabularnewline
43 & -0.134731 & -2.5528 & 0.00555 \tabularnewline
44 & 0.003017 & 0.0572 & 0.477223 \tabularnewline
45 & -0.055783 & -1.0569 & 0.145624 \tabularnewline
46 & 0.012286 & 0.2328 & 0.408029 \tabularnewline
47 & 0.020367 & 0.3859 & 0.3499 \tabularnewline
48 & 0.107896 & 2.0443 & 0.020825 \tabularnewline
49 & 0.132443 & 2.5094 & 0.006266 \tabularnewline
50 & 0.100776 & 1.9094 & 0.028501 \tabularnewline
51 & 0.074363 & 1.409 & 0.079853 \tabularnewline
52 & 0.099064 & 1.877 & 0.030665 \tabularnewline
53 & 0.119078 & 2.2562 & 0.01233 \tabularnewline
54 & 0.061026 & 1.1563 & 0.12417 \tabularnewline
55 & 0.137393 & 2.6032 & 0.004809 \tabularnewline
56 & 0.052891 & 1.0021 & 0.158474 \tabularnewline
57 & 0.042954 & 0.8139 & 0.208131 \tabularnewline
58 & 0.03993 & 0.7566 & 0.224901 \tabularnewline
59 & 0.067573 & 1.2803 & 0.100629 \tabularnewline
60 & -0.029187 & -0.553 & 0.2903 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29376&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]0.210141[/C][C]3.9816[/C][C]4.1e-05[/C][/ROW]
[ROW][C]2[/C][C]0.325131[/C][C]6.1603[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.153275[/C][C]2.9041[/C][C]0.001955[/C][/ROW]
[ROW][C]4[/C][C]0.167252[/C][C]3.169[/C][C]0.000831[/C][/ROW]
[ROW][C]5[/C][C]0.099156[/C][C]1.8787[/C][C]0.030545[/C][/ROW]
[ROW][C]6[/C][C]0.064513[/C][C]1.2223[/C][C]0.111191[/C][/ROW]
[ROW][C]7[/C][C]-0.057203[/C][C]-1.0838[/C][C]0.13958[/C][/ROW]
[ROW][C]8[/C][C]-0.023244[/C][C]-0.4404[/C][C]0.329956[/C][/ROW]
[ROW][C]9[/C][C]-0.085115[/C][C]-1.6127[/C][C]0.053845[/C][/ROW]
[ROW][C]10[/C][C]-0.168424[/C][C]-3.1912[/C][C]0.000771[/C][/ROW]
[ROW][C]11[/C][C]-0.075939[/C][C]-1.4388[/C][C]0.075533[/C][/ROW]
[ROW][C]12[/C][C]-0.475334[/C][C]-9.0063[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.179215[/C][C]-3.3956[/C][C]0.000381[/C][/ROW]
[ROW][C]14[/C][C]-0.162819[/C][C]-3.085[/C][C]0.001097[/C][/ROW]
[ROW][C]15[/C][C]-0.106644[/C][C]-2.0206[/C][C]0.02203[/C][/ROW]
[ROW][C]16[/C][C]-0.147945[/C][C]-2.8032[/C][C]0.002668[/C][/ROW]
[ROW][C]17[/C][C]-0.091478[/C][C]-1.7333[/C][C]0.041954[/C][/ROW]
[ROW][C]18[/C][C]-0.089745[/C][C]-1.7004[/C][C]0.044958[/C][/ROW]
[ROW][C]19[/C][C]0.027328[/C][C]0.5178[/C][C]0.302458[/C][/ROW]
[ROW][C]20[/C][C]-0.012913[/C][C]-0.2447[/C][C]0.403425[/C][/ROW]
[ROW][C]21[/C][C]0.024199[/C][C]0.4585[/C][C]0.323437[/C][/ROW]
[ROW][C]22[/C][C]-0.018741[/C][C]-0.3551[/C][C]0.361367[/C][/ROW]
[ROW][C]23[/C][C]0.009567[/C][C]0.1813[/C][C]0.42813[/C][/ROW]
[ROW][C]24[/C][C]-0.022226[/C][C]-0.4211[/C][C]0.336957[/C][/ROW]
[ROW][C]25[/C][C]0.091974[/C][C]1.7427[/C][C]0.041125[/C][/ROW]
[ROW][C]26[/C][C]-0.045751[/C][C]-0.8668[/C][C]0.193302[/C][/ROW]
[ROW][C]27[/C][C]-0.014979[/C][C]-0.2838[/C][C]0.388362[/C][/ROW]
[ROW][C]28[/C][C]0.034483[/C][C]0.6534[/C][C]0.256968[/C][/ROW]
[ROW][C]29[/C][C]0.081474[/C][C]1.5437[/C][C]0.061769[/C][/ROW]
[ROW][C]30[/C][C]0.012117[/C][C]0.2296[/C][C]0.409275[/C][/ROW]
[ROW][C]31[/C][C]0.025552[/C][C]0.4841[/C][C]0.31429[/C][/ROW]
[ROW][C]32[/C][C]-0.054477[/C][C]-1.0322[/C][C]0.151339[/C][/ROW]
[ROW][C]33[/C][C]0.008649[/C][C]0.1639[/C][C]0.434964[/C][/ROW]
[ROW][C]34[/C][C]0.016116[/C][C]0.3054[/C][C]0.380134[/C][/ROW]
[ROW][C]35[/C][C]-0.058412[/C][C]-1.1067[/C][C]0.134573[/C][/ROW]
[ROW][C]36[/C][C]-0.022491[/C][C]-0.4261[/C][C]0.335132[/C][/ROW]
[ROW][C]37[/C][C]-0.120582[/C][C]-2.2847[/C][C]0.011456[/C][/ROW]
[ROW][C]38[/C][C]0.014974[/C][C]0.2837[/C][C]0.388394[/C][/ROW]
[ROW][C]39[/C][C]-0.025852[/C][C]-0.4898[/C][C]0.312276[/C][/ROW]
[ROW][C]40[/C][C]-0.027437[/C][C]-0.5199[/C][C]0.301741[/C][/ROW]
[ROW][C]41[/C][C]-0.10329[/C][C]-1.9571[/C][C]0.025557[/C][/ROW]
[ROW][C]42[/C][C]-0.019216[/C][C]-0.3641[/C][C]0.358002[/C][/ROW]
[ROW][C]43[/C][C]-0.134731[/C][C]-2.5528[/C][C]0.00555[/C][/ROW]
[ROW][C]44[/C][C]0.003017[/C][C]0.0572[/C][C]0.477223[/C][/ROW]
[ROW][C]45[/C][C]-0.055783[/C][C]-1.0569[/C][C]0.145624[/C][/ROW]
[ROW][C]46[/C][C]0.012286[/C][C]0.2328[/C][C]0.408029[/C][/ROW]
[ROW][C]47[/C][C]0.020367[/C][C]0.3859[/C][C]0.3499[/C][/ROW]
[ROW][C]48[/C][C]0.107896[/C][C]2.0443[/C][C]0.020825[/C][/ROW]
[ROW][C]49[/C][C]0.132443[/C][C]2.5094[/C][C]0.006266[/C][/ROW]
[ROW][C]50[/C][C]0.100776[/C][C]1.9094[/C][C]0.028501[/C][/ROW]
[ROW][C]51[/C][C]0.074363[/C][C]1.409[/C][C]0.079853[/C][/ROW]
[ROW][C]52[/C][C]0.099064[/C][C]1.877[/C][C]0.030665[/C][/ROW]
[ROW][C]53[/C][C]0.119078[/C][C]2.2562[/C][C]0.01233[/C][/ROW]
[ROW][C]54[/C][C]0.061026[/C][C]1.1563[/C][C]0.12417[/C][/ROW]
[ROW][C]55[/C][C]0.137393[/C][C]2.6032[/C][C]0.004809[/C][/ROW]
[ROW][C]56[/C][C]0.052891[/C][C]1.0021[/C][C]0.158474[/C][/ROW]
[ROW][C]57[/C][C]0.042954[/C][C]0.8139[/C][C]0.208131[/C][/ROW]
[ROW][C]58[/C][C]0.03993[/C][C]0.7566[/C][C]0.224901[/C][/ROW]
[ROW][C]59[/C][C]0.067573[/C][C]1.2803[/C][C]0.100629[/C][/ROW]
[ROW][C]60[/C][C]-0.029187[/C][C]-0.553[/C][C]0.2903[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29376&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29376&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	0.210141	3.9816	4.1e-05
2	0.325131	6.1603	0
3	0.153275	2.9041	0.001955
4	0.167252	3.169	0.000831
5	0.099156	1.8787	0.030545
6	0.064513	1.2223	0.111191
7	-0.057203	-1.0838	0.13958
8	-0.023244	-0.4404	0.329956
9	-0.085115	-1.6127	0.053845
10	-0.168424	-3.1912	0.000771
11	-0.075939	-1.4388	0.075533
12	-0.475334	-9.0063	0
13	-0.179215	-3.3956	0.000381
14	-0.162819	-3.085	0.001097
15	-0.106644	-2.0206	0.02203
16	-0.147945	-2.8032	0.002668
17	-0.091478	-1.7333	0.041954
18	-0.089745	-1.7004	0.044958
19	0.027328	0.5178	0.302458
20	-0.012913	-0.2447	0.403425
21	0.024199	0.4585	0.323437
22	-0.018741	-0.3551	0.361367
23	0.009567	0.1813	0.42813
24	-0.022226	-0.4211	0.336957
25	0.091974	1.7427	0.041125
26	-0.045751	-0.8668	0.193302
27	-0.014979	-0.2838	0.388362
28	0.034483	0.6534	0.256968
29	0.081474	1.5437	0.061769
30	0.012117	0.2296	0.409275
31	0.025552	0.4841	0.31429
32	-0.054477	-1.0322	0.151339
33	0.008649	0.1639	0.434964
34	0.016116	0.3054	0.380134
35	-0.058412	-1.1067	0.134573
36	-0.022491	-0.4261	0.335132
37	-0.120582	-2.2847	0.011456
38	0.014974	0.2837	0.388394
39	-0.025852	-0.4898	0.312276
40	-0.027437	-0.5199	0.301741
41	-0.10329	-1.9571	0.025557
42	-0.019216	-0.3641	0.358002
43	-0.134731	-2.5528	0.00555
44	0.003017	0.0572	0.477223
45	-0.055783	-1.0569	0.145624
46	0.012286	0.2328	0.408029
47	0.020367	0.3859	0.3499
48	0.107896	2.0443	0.020825
49	0.132443	2.5094	0.006266
50	0.100776	1.9094	0.028501
51	0.074363	1.409	0.079853
52	0.099064	1.877	0.030665
53	0.119078	2.2562	0.01233
54	0.061026	1.1563	0.12417
55	0.137393	2.6032	0.004809
56	0.052891	1.0021	0.158474
57	0.042954	0.8139	0.208131
58	0.03993	0.7566	0.224901
59	0.067573	1.2803	0.100629
60	-0.029187	-0.553	0.2903

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.210141	3.9816	4.1e-05
2	0.293952	5.5696	0
3	0.049544	0.9387	0.174253
4	0.049534	0.9385	0.174302
5	0.012741	0.2414	0.404686
6	-0.02095	-0.3969	0.34582
7	-0.124687	-2.3625	0.009343
8	-0.032709	-0.6197	0.267912
9	-0.045438	-0.8609	0.194928
10	-0.146092	-2.768	0.002966
11	0.023631	0.4477	0.327306
12	-0.42914	-8.131	0
13	-0.0237	-0.449	0.326836
14	0.150889	2.8589	0.002249
15	0.029791	0.5645	0.286395
16	-0.044612	-0.8453	0.199257
17	-0.012037	-0.2281	0.40986
18	0.004648	0.0881	0.464938
19	0.011303	0.2142	0.415271
20	0.009823	0.1861	0.426229
21	-0.009818	-0.186	0.426268
22	-0.15669	-2.9689	0.001595
23	0.012173	0.2306	0.408859
24	-0.273087	-5.1743	0
25	0.053216	1.0083	0.156993
26	-0.005528	-0.1047	0.458322
27	-0.053682	-1.0171	0.15489
28	0.046275	0.8768	0.190593
29	0.091076	1.7256	0.042637
30	-0.041044	-0.7777	0.218636
31	0.023452	0.4444	0.328528
32	-0.066214	-1.2546	0.105224
33	-0.006987	-0.1324	0.447376
34	-0.075688	-1.4341	0.076211
35	-0.076212	-1.444	0.074803
36	-0.234257	-4.4385	6e-06
37	-0.079056	-1.4979	0.06752
38	0.058053	1.0999	0.136046
39	-0.065149	-1.2344	0.108931
40	-0.007132	-0.1351	0.44629
41	0.026377	0.4998	0.308768
42	-0.0345	-0.6537	0.256866
43	-0.105199	-1.9932	0.023496
44	-0.043345	-0.8213	0.20602
45	0.008685	0.1646	0.434693
46	-0.002039	-0.0386	0.484604
47	-0.029957	-0.5676	0.285328
48	-0.043935	-0.8325	0.202852
49	0.020981	0.3975	0.345603
50	0.033518	0.6351	0.26289
51	-0.048425	-0.9175	0.17974
52	0.020257	0.3838	0.350674
53	0.017298	0.3277	0.371649
54	-0.079249	-1.5016	0.067046
55	0.003689	0.0699	0.472155
56	-0.027055	-0.5126	0.304266
57	-0.068417	-1.2963	0.097849
58	0.046652	0.8839	0.188663
59	0.041409	0.7846	0.216604
60	-0.038067	-0.7213	0.235608

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.210141 & 3.9816 & 4.1e-05 \tabularnewline
2 & 0.293952 & 5.5696 & 0 \tabularnewline
3 & 0.049544 & 0.9387 & 0.174253 \tabularnewline
4 & 0.049534 & 0.9385 & 0.174302 \tabularnewline
5 & 0.012741 & 0.2414 & 0.404686 \tabularnewline
6 & -0.02095 & -0.3969 & 0.34582 \tabularnewline
7 & -0.124687 & -2.3625 & 0.009343 \tabularnewline
8 & -0.032709 & -0.6197 & 0.267912 \tabularnewline
9 & -0.045438 & -0.8609 & 0.194928 \tabularnewline
10 & -0.146092 & -2.768 & 0.002966 \tabularnewline
11 & 0.023631 & 0.4477 & 0.327306 \tabularnewline
12 & -0.42914 & -8.131 & 0 \tabularnewline
13 & -0.0237 & -0.449 & 0.326836 \tabularnewline
14 & 0.150889 & 2.8589 & 0.002249 \tabularnewline
15 & 0.029791 & 0.5645 & 0.286395 \tabularnewline
16 & -0.044612 & -0.8453 & 0.199257 \tabularnewline
17 & -0.012037 & -0.2281 & 0.40986 \tabularnewline
18 & 0.004648 & 0.0881 & 0.464938 \tabularnewline
19 & 0.011303 & 0.2142 & 0.415271 \tabularnewline
20 & 0.009823 & 0.1861 & 0.426229 \tabularnewline
21 & -0.009818 & -0.186 & 0.426268 \tabularnewline
22 & -0.15669 & -2.9689 & 0.001595 \tabularnewline
23 & 0.012173 & 0.2306 & 0.408859 \tabularnewline
24 & -0.273087 & -5.1743 & 0 \tabularnewline
25 & 0.053216 & 1.0083 & 0.156993 \tabularnewline
26 & -0.005528 & -0.1047 & 0.458322 \tabularnewline
27 & -0.053682 & -1.0171 & 0.15489 \tabularnewline
28 & 0.046275 & 0.8768 & 0.190593 \tabularnewline
29 & 0.091076 & 1.7256 & 0.042637 \tabularnewline
30 & -0.041044 & -0.7777 & 0.218636 \tabularnewline
31 & 0.023452 & 0.4444 & 0.328528 \tabularnewline
32 & -0.066214 & -1.2546 & 0.105224 \tabularnewline
33 & -0.006987 & -0.1324 & 0.447376 \tabularnewline
34 & -0.075688 & -1.4341 & 0.076211 \tabularnewline
35 & -0.076212 & -1.444 & 0.074803 \tabularnewline
36 & -0.234257 & -4.4385 & 6e-06 \tabularnewline
37 & -0.079056 & -1.4979 & 0.06752 \tabularnewline
38 & 0.058053 & 1.0999 & 0.136046 \tabularnewline
39 & -0.065149 & -1.2344 & 0.108931 \tabularnewline
40 & -0.007132 & -0.1351 & 0.44629 \tabularnewline
41 & 0.026377 & 0.4998 & 0.308768 \tabularnewline
42 & -0.0345 & -0.6537 & 0.256866 \tabularnewline
43 & -0.105199 & -1.9932 & 0.023496 \tabularnewline
44 & -0.043345 & -0.8213 & 0.20602 \tabularnewline
45 & 0.008685 & 0.1646 & 0.434693 \tabularnewline
46 & -0.002039 & -0.0386 & 0.484604 \tabularnewline
47 & -0.029957 & -0.5676 & 0.285328 \tabularnewline
48 & -0.043935 & -0.8325 & 0.202852 \tabularnewline
49 & 0.020981 & 0.3975 & 0.345603 \tabularnewline
50 & 0.033518 & 0.6351 & 0.26289 \tabularnewline
51 & -0.048425 & -0.9175 & 0.17974 \tabularnewline
52 & 0.020257 & 0.3838 & 0.350674 \tabularnewline
53 & 0.017298 & 0.3277 & 0.371649 \tabularnewline
54 & -0.079249 & -1.5016 & 0.067046 \tabularnewline
55 & 0.003689 & 0.0699 & 0.472155 \tabularnewline
56 & -0.027055 & -0.5126 & 0.304266 \tabularnewline
57 & -0.068417 & -1.2963 & 0.097849 \tabularnewline
58 & 0.046652 & 0.8839 & 0.188663 \tabularnewline
59 & 0.041409 & 0.7846 & 0.216604 \tabularnewline
60 & -0.038067 & -0.7213 & 0.235608 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29376&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]0.210141[/C][C]3.9816[/C][C]4.1e-05[/C][/ROW]
[ROW][C]2[/C][C]0.293952[/C][C]5.5696[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.049544[/C][C]0.9387[/C][C]0.174253[/C][/ROW]
[ROW][C]4[/C][C]0.049534[/C][C]0.9385[/C][C]0.174302[/C][/ROW]
[ROW][C]5[/C][C]0.012741[/C][C]0.2414[/C][C]0.404686[/C][/ROW]
[ROW][C]6[/C][C]-0.02095[/C][C]-0.3969[/C][C]0.34582[/C][/ROW]
[ROW][C]7[/C][C]-0.124687[/C][C]-2.3625[/C][C]0.009343[/C][/ROW]
[ROW][C]8[/C][C]-0.032709[/C][C]-0.6197[/C][C]0.267912[/C][/ROW]
[ROW][C]9[/C][C]-0.045438[/C][C]-0.8609[/C][C]0.194928[/C][/ROW]
[ROW][C]10[/C][C]-0.146092[/C][C]-2.768[/C][C]0.002966[/C][/ROW]
[ROW][C]11[/C][C]0.023631[/C][C]0.4477[/C][C]0.327306[/C][/ROW]
[ROW][C]12[/C][C]-0.42914[/C][C]-8.131[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.0237[/C][C]-0.449[/C][C]0.326836[/C][/ROW]
[ROW][C]14[/C][C]0.150889[/C][C]2.8589[/C][C]0.002249[/C][/ROW]
[ROW][C]15[/C][C]0.029791[/C][C]0.5645[/C][C]0.286395[/C][/ROW]
[ROW][C]16[/C][C]-0.044612[/C][C]-0.8453[/C][C]0.199257[/C][/ROW]
[ROW][C]17[/C][C]-0.012037[/C][C]-0.2281[/C][C]0.40986[/C][/ROW]
[ROW][C]18[/C][C]0.004648[/C][C]0.0881[/C][C]0.464938[/C][/ROW]
[ROW][C]19[/C][C]0.011303[/C][C]0.2142[/C][C]0.415271[/C][/ROW]
[ROW][C]20[/C][C]0.009823[/C][C]0.1861[/C][C]0.426229[/C][/ROW]
[ROW][C]21[/C][C]-0.009818[/C][C]-0.186[/C][C]0.426268[/C][/ROW]
[ROW][C]22[/C][C]-0.15669[/C][C]-2.9689[/C][C]0.001595[/C][/ROW]
[ROW][C]23[/C][C]0.012173[/C][C]0.2306[/C][C]0.408859[/C][/ROW]
[ROW][C]24[/C][C]-0.273087[/C][C]-5.1743[/C][C]0[/C][/ROW]
[ROW][C]25[/C][C]0.053216[/C][C]1.0083[/C][C]0.156993[/C][/ROW]
[ROW][C]26[/C][C]-0.005528[/C][C]-0.1047[/C][C]0.458322[/C][/ROW]
[ROW][C]27[/C][C]-0.053682[/C][C]-1.0171[/C][C]0.15489[/C][/ROW]
[ROW][C]28[/C][C]0.046275[/C][C]0.8768[/C][C]0.190593[/C][/ROW]
[ROW][C]29[/C][C]0.091076[/C][C]1.7256[/C][C]0.042637[/C][/ROW]
[ROW][C]30[/C][C]-0.041044[/C][C]-0.7777[/C][C]0.218636[/C][/ROW]
[ROW][C]31[/C][C]0.023452[/C][C]0.4444[/C][C]0.328528[/C][/ROW]
[ROW][C]32[/C][C]-0.066214[/C][C]-1.2546[/C][C]0.105224[/C][/ROW]
[ROW][C]33[/C][C]-0.006987[/C][C]-0.1324[/C][C]0.447376[/C][/ROW]
[ROW][C]34[/C][C]-0.075688[/C][C]-1.4341[/C][C]0.076211[/C][/ROW]
[ROW][C]35[/C][C]-0.076212[/C][C]-1.444[/C][C]0.074803[/C][/ROW]
[ROW][C]36[/C][C]-0.234257[/C][C]-4.4385[/C][C]6e-06[/C][/ROW]
[ROW][C]37[/C][C]-0.079056[/C][C]-1.4979[/C][C]0.06752[/C][/ROW]
[ROW][C]38[/C][C]0.058053[/C][C]1.0999[/C][C]0.136046[/C][/ROW]
[ROW][C]39[/C][C]-0.065149[/C][C]-1.2344[/C][C]0.108931[/C][/ROW]
[ROW][C]40[/C][C]-0.007132[/C][C]-0.1351[/C][C]0.44629[/C][/ROW]
[ROW][C]41[/C][C]0.026377[/C][C]0.4998[/C][C]0.308768[/C][/ROW]
[ROW][C]42[/C][C]-0.0345[/C][C]-0.6537[/C][C]0.256866[/C][/ROW]
[ROW][C]43[/C][C]-0.105199[/C][C]-1.9932[/C][C]0.023496[/C][/ROW]
[ROW][C]44[/C][C]-0.043345[/C][C]-0.8213[/C][C]0.20602[/C][/ROW]
[ROW][C]45[/C][C]0.008685[/C][C]0.1646[/C][C]0.434693[/C][/ROW]
[ROW][C]46[/C][C]-0.002039[/C][C]-0.0386[/C][C]0.484604[/C][/ROW]
[ROW][C]47[/C][C]-0.029957[/C][C]-0.5676[/C][C]0.285328[/C][/ROW]
[ROW][C]48[/C][C]-0.043935[/C][C]-0.8325[/C][C]0.202852[/C][/ROW]
[ROW][C]49[/C][C]0.020981[/C][C]0.3975[/C][C]0.345603[/C][/ROW]
[ROW][C]50[/C][C]0.033518[/C][C]0.6351[/C][C]0.26289[/C][/ROW]
[ROW][C]51[/C][C]-0.048425[/C][C]-0.9175[/C][C]0.17974[/C][/ROW]
[ROW][C]52[/C][C]0.020257[/C][C]0.3838[/C][C]0.350674[/C][/ROW]
[ROW][C]53[/C][C]0.017298[/C][C]0.3277[/C][C]0.371649[/C][/ROW]
[ROW][C]54[/C][C]-0.079249[/C][C]-1.5016[/C][C]0.067046[/C][/ROW]
[ROW][C]55[/C][C]0.003689[/C][C]0.0699[/C][C]0.472155[/C][/ROW]
[ROW][C]56[/C][C]-0.027055[/C][C]-0.5126[/C][C]0.304266[/C][/ROW]
[ROW][C]57[/C][C]-0.068417[/C][C]-1.2963[/C][C]0.097849[/C][/ROW]
[ROW][C]58[/C][C]0.046652[/C][C]0.8839[/C][C]0.188663[/C][/ROW]
[ROW][C]59[/C][C]0.041409[/C][C]0.7846[/C][C]0.216604[/C][/ROW]
[ROW][C]60[/C][C]-0.038067[/C][C]-0.7213[/C][C]0.235608[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29376&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29376&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	0.210141	3.9816	4.1e-05
2	0.293952	5.5696	0
3	0.049544	0.9387	0.174253
4	0.049534	0.9385	0.174302
5	0.012741	0.2414	0.404686
6	-0.02095	-0.3969	0.34582
7	-0.124687	-2.3625	0.009343
8	-0.032709	-0.6197	0.267912
9	-0.045438	-0.8609	0.194928
10	-0.146092	-2.768	0.002966
11	0.023631	0.4477	0.327306
12	-0.42914	-8.131	0
13	-0.0237	-0.449	0.326836
14	0.150889	2.8589	0.002249
15	0.029791	0.5645	0.286395
16	-0.044612	-0.8453	0.199257
17	-0.012037	-0.2281	0.40986
18	0.004648	0.0881	0.464938
19	0.011303	0.2142	0.415271
20	0.009823	0.1861	0.426229
21	-0.009818	-0.186	0.426268
22	-0.15669	-2.9689	0.001595
23	0.012173	0.2306	0.408859
24	-0.273087	-5.1743	0
25	0.053216	1.0083	0.156993
26	-0.005528	-0.1047	0.458322
27	-0.053682	-1.0171	0.15489
28	0.046275	0.8768	0.190593
29	0.091076	1.7256	0.042637
30	-0.041044	-0.7777	0.218636
31	0.023452	0.4444	0.328528
32	-0.066214	-1.2546	0.105224
33	-0.006987	-0.1324	0.447376
34	-0.075688	-1.4341	0.076211
35	-0.076212	-1.444	0.074803
36	-0.234257	-4.4385	6e-06
37	-0.079056	-1.4979	0.06752
38	0.058053	1.0999	0.136046
39	-0.065149	-1.2344	0.108931
40	-0.007132	-0.1351	0.44629
41	0.026377	0.4998	0.308768
42	-0.0345	-0.6537	0.256866
43	-0.105199	-1.9932	0.023496
44	-0.043345	-0.8213	0.20602
45	0.008685	0.1646	0.434693
46	-0.002039	-0.0386	0.484604
47	-0.029957	-0.5676	0.285328
48	-0.043935	-0.8325	0.202852
49	0.020981	0.3975	0.345603
50	0.033518	0.6351	0.26289
51	-0.048425	-0.9175	0.17974
52	0.020257	0.3838	0.350674
53	0.017298	0.3277	0.371649
54	-0.079249	-1.5016	0.067046
55	0.003689	0.0699	0.472155
56	-0.027055	-0.5126	0.304266
57	-0.068417	-1.2963	0.097849
58	0.046652	0.8839	0.188663
59	0.041409	0.7846	0.216604
60	-0.038067	-0.7213	0.235608

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 12 ;

Parameters (R input):

par1 = 60 ; par2 = 1 ; par3 = 1 ; 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