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rwasp_autocorrelation.wasp

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(Partial) Autocorrelation Function

Date of computation

Tue, 09 Dec 2008 04:32:38 -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/09/t1228822411x3clsxuewzfmdxg.htm/, Retrieved Sun, 19 May 2024 08:44:48 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=31307, Retrieved Sun, 19 May 2024 08:44:48 +0000

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194

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

F       [(Partial) Autocorrelation Function] [Stefan Temmerman] [2008-12-09 11:32:38] [30f7cb12a8cb61e43b87da59ece37a2f] [Current]

Feedback Forum

2008-12-15 17:09:30 [Gert-Jan Geudens] [reply] 
We bekomen een inderdaad een stationaire reeks door enkel niet-seizonaal te differentiëren.
2008-12-15 17:32:48 [Gert-Jan Geudens] [reply] 
STAP 4 
 
Een AR-proces kunnen we afleiden uit de autocorrelatie. We herkennen hier -mits een beetje goede wil- het typische patroon voor een AR-proces. Om parameter p te bepalen moeten we naar het aantal significante coëfficiënten in de partiële autocorrelatie kijken. We zien dat er geen significante partiële autocorrelatiecoëfficiënt is en dus is volgens ons p gelijk aan 0. Als p gelijk is aan nul, is er dus toch geen AR-proces. Dit lijkt ons een beetje vreemd. Daarom lijkt het ons beter om ons te baseren op het software model dat we zullen vinden in stap 5. 
Een seizonaal AR-proces (seizonaliteit in de ACF) is er ook niet en een MA proces (PACF) en SMA (seizonaliteit in PCF) zijn er ook niet.

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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	1 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31307&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31307&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31307&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	1 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	-0.009762	-0.075	0.470241
2	-0.057552	-0.4421	0.33003
3	0.231455	1.7778	0.040292
4	0.125147	0.9613	0.170169
5	-0.178089	-1.3679	0.088261
6	-0.029416	-0.226	0.41101
7	0.009211	0.0707	0.471919
8	-0.137825	-1.0587	0.147037
9	-0.019731	-0.1516	0.440026
10	0.002515	0.0193	0.492327
11	0.024064	0.1848	0.426995
12	-0.117236	-0.9005	0.185757
13	-0.037451	-0.2877	0.387304
14	-0.00349	-0.0268	0.489353
15	-0.121418	-0.9326	0.177406
16	-0.205124	-1.5756	0.060234
17	-0.052062	-0.3999	0.345339
18	0.020936	0.1608	0.436395
19	-0.132357	-1.0167	0.156735
20	0.075144	0.5772	0.283003
21	0.0243	0.1866	0.426288
22	0.09992	0.7675	0.222922
23	-0.052606	-0.4041	0.34381
24	-0.042718	-0.3281	0.371991
25	0.085214	0.6545	0.257652
26	0.022265	0.171	0.432397
27	-0.02879	-0.2211	0.412875
28	0.003745	0.0288	0.488575
29	0.047091	0.3617	0.35943
30	-0.060748	-0.4666	0.321248
31	0.034501	0.265	0.395965
32	-0.001593	-0.0122	0.495138
33	-0.066304	-0.5093	0.306223
34	-0.013949	-0.1071	0.45752
35	-0.027749	-0.2131	0.415974
36	-0.014854	-0.1141	0.454775

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.009762 & -0.075 & 0.470241 \tabularnewline
2 & -0.057552 & -0.4421 & 0.33003 \tabularnewline
3 & 0.231455 & 1.7778 & 0.040292 \tabularnewline
4 & 0.125147 & 0.9613 & 0.170169 \tabularnewline
5 & -0.178089 & -1.3679 & 0.088261 \tabularnewline
6 & -0.029416 & -0.226 & 0.41101 \tabularnewline
7 & 0.009211 & 0.0707 & 0.471919 \tabularnewline
8 & -0.137825 & -1.0587 & 0.147037 \tabularnewline
9 & -0.019731 & -0.1516 & 0.440026 \tabularnewline
10 & 0.002515 & 0.0193 & 0.492327 \tabularnewline
11 & 0.024064 & 0.1848 & 0.426995 \tabularnewline
12 & -0.117236 & -0.9005 & 0.185757 \tabularnewline
13 & -0.037451 & -0.2877 & 0.387304 \tabularnewline
14 & -0.00349 & -0.0268 & 0.489353 \tabularnewline
15 & -0.121418 & -0.9326 & 0.177406 \tabularnewline
16 & -0.205124 & -1.5756 & 0.060234 \tabularnewline
17 & -0.052062 & -0.3999 & 0.345339 \tabularnewline
18 & 0.020936 & 0.1608 & 0.436395 \tabularnewline
19 & -0.132357 & -1.0167 & 0.156735 \tabularnewline
20 & 0.075144 & 0.5772 & 0.283003 \tabularnewline
21 & 0.0243 & 0.1866 & 0.426288 \tabularnewline
22 & 0.09992 & 0.7675 & 0.222922 \tabularnewline
23 & -0.052606 & -0.4041 & 0.34381 \tabularnewline
24 & -0.042718 & -0.3281 & 0.371991 \tabularnewline
25 & 0.085214 & 0.6545 & 0.257652 \tabularnewline
26 & 0.022265 & 0.171 & 0.432397 \tabularnewline
27 & -0.02879 & -0.2211 & 0.412875 \tabularnewline
28 & 0.003745 & 0.0288 & 0.488575 \tabularnewline
29 & 0.047091 & 0.3617 & 0.35943 \tabularnewline
30 & -0.060748 & -0.4666 & 0.321248 \tabularnewline
31 & 0.034501 & 0.265 & 0.395965 \tabularnewline
32 & -0.001593 & -0.0122 & 0.495138 \tabularnewline
33 & -0.066304 & -0.5093 & 0.306223 \tabularnewline
34 & -0.013949 & -0.1071 & 0.45752 \tabularnewline
35 & -0.027749 & -0.2131 & 0.415974 \tabularnewline
36 & -0.014854 & -0.1141 & 0.454775 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31307&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]-0.009762[/C][C]-0.075[/C][C]0.470241[/C][/ROW]
[ROW][C]2[/C][C]-0.057552[/C][C]-0.4421[/C][C]0.33003[/C][/ROW]
[ROW][C]3[/C][C]0.231455[/C][C]1.7778[/C][C]0.040292[/C][/ROW]
[ROW][C]4[/C][C]0.125147[/C][C]0.9613[/C][C]0.170169[/C][/ROW]
[ROW][C]5[/C][C]-0.178089[/C][C]-1.3679[/C][C]0.088261[/C][/ROW]
[ROW][C]6[/C][C]-0.029416[/C][C]-0.226[/C][C]0.41101[/C][/ROW]
[ROW][C]7[/C][C]0.009211[/C][C]0.0707[/C][C]0.471919[/C][/ROW]
[ROW][C]8[/C][C]-0.137825[/C][C]-1.0587[/C][C]0.147037[/C][/ROW]
[ROW][C]9[/C][C]-0.019731[/C][C]-0.1516[/C][C]0.440026[/C][/ROW]
[ROW][C]10[/C][C]0.002515[/C][C]0.0193[/C][C]0.492327[/C][/ROW]
[ROW][C]11[/C][C]0.024064[/C][C]0.1848[/C][C]0.426995[/C][/ROW]
[ROW][C]12[/C][C]-0.117236[/C][C]-0.9005[/C][C]0.185757[/C][/ROW]
[ROW][C]13[/C][C]-0.037451[/C][C]-0.2877[/C][C]0.387304[/C][/ROW]
[ROW][C]14[/C][C]-0.00349[/C][C]-0.0268[/C][C]0.489353[/C][/ROW]
[ROW][C]15[/C][C]-0.121418[/C][C]-0.9326[/C][C]0.177406[/C][/ROW]
[ROW][C]16[/C][C]-0.205124[/C][C]-1.5756[/C][C]0.060234[/C][/ROW]
[ROW][C]17[/C][C]-0.052062[/C][C]-0.3999[/C][C]0.345339[/C][/ROW]
[ROW][C]18[/C][C]0.020936[/C][C]0.1608[/C][C]0.436395[/C][/ROW]
[ROW][C]19[/C][C]-0.132357[/C][C]-1.0167[/C][C]0.156735[/C][/ROW]
[ROW][C]20[/C][C]0.075144[/C][C]0.5772[/C][C]0.283003[/C][/ROW]
[ROW][C]21[/C][C]0.0243[/C][C]0.1866[/C][C]0.426288[/C][/ROW]
[ROW][C]22[/C][C]0.09992[/C][C]0.7675[/C][C]0.222922[/C][/ROW]
[ROW][C]23[/C][C]-0.052606[/C][C]-0.4041[/C][C]0.34381[/C][/ROW]
[ROW][C]24[/C][C]-0.042718[/C][C]-0.3281[/C][C]0.371991[/C][/ROW]
[ROW][C]25[/C][C]0.085214[/C][C]0.6545[/C][C]0.257652[/C][/ROW]
[ROW][C]26[/C][C]0.022265[/C][C]0.171[/C][C]0.432397[/C][/ROW]
[ROW][C]27[/C][C]-0.02879[/C][C]-0.2211[/C][C]0.412875[/C][/ROW]
[ROW][C]28[/C][C]0.003745[/C][C]0.0288[/C][C]0.488575[/C][/ROW]
[ROW][C]29[/C][C]0.047091[/C][C]0.3617[/C][C]0.35943[/C][/ROW]
[ROW][C]30[/C][C]-0.060748[/C][C]-0.4666[/C][C]0.321248[/C][/ROW]
[ROW][C]31[/C][C]0.034501[/C][C]0.265[/C][C]0.395965[/C][/ROW]
[ROW][C]32[/C][C]-0.001593[/C][C]-0.0122[/C][C]0.495138[/C][/ROW]
[ROW][C]33[/C][C]-0.066304[/C][C]-0.5093[/C][C]0.306223[/C][/ROW]
[ROW][C]34[/C][C]-0.013949[/C][C]-0.1071[/C][C]0.45752[/C][/ROW]
[ROW][C]35[/C][C]-0.027749[/C][C]-0.2131[/C][C]0.415974[/C][/ROW]
[ROW][C]36[/C][C]-0.014854[/C][C]-0.1141[/C][C]0.454775[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31307&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31307&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	-0.009762	-0.075	0.470241
2	-0.057552	-0.4421	0.33003
3	0.231455	1.7778	0.040292
4	0.125147	0.9613	0.170169
5	-0.178089	-1.3679	0.088261
6	-0.029416	-0.226	0.41101
7	0.009211	0.0707	0.471919
8	-0.137825	-1.0587	0.147037
9	-0.019731	-0.1516	0.440026
10	0.002515	0.0193	0.492327
11	0.024064	0.1848	0.426995
12	-0.117236	-0.9005	0.185757
13	-0.037451	-0.2877	0.387304
14	-0.00349	-0.0268	0.489353
15	-0.121418	-0.9326	0.177406
16	-0.205124	-1.5756	0.060234
17	-0.052062	-0.3999	0.345339
18	0.020936	0.1608	0.436395
19	-0.132357	-1.0167	0.156735
20	0.075144	0.5772	0.283003
21	0.0243	0.1866	0.426288
22	0.09992	0.7675	0.222922
23	-0.052606	-0.4041	0.34381
24	-0.042718	-0.3281	0.371991
25	0.085214	0.6545	0.257652
26	0.022265	0.171	0.432397
27	-0.02879	-0.2211	0.412875
28	0.003745	0.0288	0.488575
29	0.047091	0.3617	0.35943
30	-0.060748	-0.4666	0.321248
31	0.034501	0.265	0.395965
32	-0.001593	-0.0122	0.495138
33	-0.066304	-0.5093	0.306223
34	-0.013949	-0.1071	0.45752
35	-0.027749	-0.2131	0.415974
36	-0.014854	-0.1141	0.454775

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	-0.009762	-0.075	0.470241
2	-0.057652	-0.4428	0.329752
3	0.231088	1.775	0.040526
4	0.130945	1.0058	0.159308
5	-0.160707	-1.2344	0.110971
6	-0.083086	-0.6382	0.262908
7	-0.067825	-0.521	0.302167
8	-0.088895	-0.6828	0.248698
9	0.048412	0.3719	0.355664
10	-0.000155	-0.0012	0.499526
11	0.074116	0.5693	0.285657
12	-0.115937	-0.8905	0.188399
13	-0.093693	-0.7197	0.237286
14	-0.049035	-0.3766	0.353894
15	-0.108592	-0.8341	0.203791
16	-0.175083	-1.3448	0.091913
17	-0.081679	-0.6274	0.266413
18	0.039379	0.3025	0.381677
19	-0.034627	-0.266	0.395593
20	0.100547	0.7723	0.221505
21	-0.060164	-0.4621	0.322844
22	0.085175	0.6542	0.257748
23	-0.125158	-0.9614	0.170148
24	-0.173453	-1.3323	0.09394
25	0.033121	0.2544	0.400033
26	0.041279	0.3171	0.376154
27	0.070644	0.5426	0.294716
28	-0.01749	-0.1343	0.446795
29	-0.063734	-0.4895	0.313134
30	-0.090422	-0.6945	0.245032
31	-0.080686	-0.6198	0.2689
32	-0.08691	-0.6676	0.253506
33	-0.076797	-0.5899	0.278759
34	0.014885	0.1143	0.454681
35	-0.052173	-0.4008	0.345025
36	0.018295	0.1405	0.444362

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.009762 & -0.075 & 0.470241 \tabularnewline
2 & -0.057652 & -0.4428 & 0.329752 \tabularnewline
3 & 0.231088 & 1.775 & 0.040526 \tabularnewline
4 & 0.130945 & 1.0058 & 0.159308 \tabularnewline
5 & -0.160707 & -1.2344 & 0.110971 \tabularnewline
6 & -0.083086 & -0.6382 & 0.262908 \tabularnewline
7 & -0.067825 & -0.521 & 0.302167 \tabularnewline
8 & -0.088895 & -0.6828 & 0.248698 \tabularnewline
9 & 0.048412 & 0.3719 & 0.355664 \tabularnewline
10 & -0.000155 & -0.0012 & 0.499526 \tabularnewline
11 & 0.074116 & 0.5693 & 0.285657 \tabularnewline
12 & -0.115937 & -0.8905 & 0.188399 \tabularnewline
13 & -0.093693 & -0.7197 & 0.237286 \tabularnewline
14 & -0.049035 & -0.3766 & 0.353894 \tabularnewline
15 & -0.108592 & -0.8341 & 0.203791 \tabularnewline
16 & -0.175083 & -1.3448 & 0.091913 \tabularnewline
17 & -0.081679 & -0.6274 & 0.266413 \tabularnewline
18 & 0.039379 & 0.3025 & 0.381677 \tabularnewline
19 & -0.034627 & -0.266 & 0.395593 \tabularnewline
20 & 0.100547 & 0.7723 & 0.221505 \tabularnewline
21 & -0.060164 & -0.4621 & 0.322844 \tabularnewline
22 & 0.085175 & 0.6542 & 0.257748 \tabularnewline
23 & -0.125158 & -0.9614 & 0.170148 \tabularnewline
24 & -0.173453 & -1.3323 & 0.09394 \tabularnewline
25 & 0.033121 & 0.2544 & 0.400033 \tabularnewline
26 & 0.041279 & 0.3171 & 0.376154 \tabularnewline
27 & 0.070644 & 0.5426 & 0.294716 \tabularnewline
28 & -0.01749 & -0.1343 & 0.446795 \tabularnewline
29 & -0.063734 & -0.4895 & 0.313134 \tabularnewline
30 & -0.090422 & -0.6945 & 0.245032 \tabularnewline
31 & -0.080686 & -0.6198 & 0.2689 \tabularnewline
32 & -0.08691 & -0.6676 & 0.253506 \tabularnewline
33 & -0.076797 & -0.5899 & 0.278759 \tabularnewline
34 & 0.014885 & 0.1143 & 0.454681 \tabularnewline
35 & -0.052173 & -0.4008 & 0.345025 \tabularnewline
36 & 0.018295 & 0.1405 & 0.444362 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31307&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]-0.009762[/C][C]-0.075[/C][C]0.470241[/C][/ROW]
[ROW][C]2[/C][C]-0.057652[/C][C]-0.4428[/C][C]0.329752[/C][/ROW]
[ROW][C]3[/C][C]0.231088[/C][C]1.775[/C][C]0.040526[/C][/ROW]
[ROW][C]4[/C][C]0.130945[/C][C]1.0058[/C][C]0.159308[/C][/ROW]
[ROW][C]5[/C][C]-0.160707[/C][C]-1.2344[/C][C]0.110971[/C][/ROW]
[ROW][C]6[/C][C]-0.083086[/C][C]-0.6382[/C][C]0.262908[/C][/ROW]
[ROW][C]7[/C][C]-0.067825[/C][C]-0.521[/C][C]0.302167[/C][/ROW]
[ROW][C]8[/C][C]-0.088895[/C][C]-0.6828[/C][C]0.248698[/C][/ROW]
[ROW][C]9[/C][C]0.048412[/C][C]0.3719[/C][C]0.355664[/C][/ROW]
[ROW][C]10[/C][C]-0.000155[/C][C]-0.0012[/C][C]0.499526[/C][/ROW]
[ROW][C]11[/C][C]0.074116[/C][C]0.5693[/C][C]0.285657[/C][/ROW]
[ROW][C]12[/C][C]-0.115937[/C][C]-0.8905[/C][C]0.188399[/C][/ROW]
[ROW][C]13[/C][C]-0.093693[/C][C]-0.7197[/C][C]0.237286[/C][/ROW]
[ROW][C]14[/C][C]-0.049035[/C][C]-0.3766[/C][C]0.353894[/C][/ROW]
[ROW][C]15[/C][C]-0.108592[/C][C]-0.8341[/C][C]0.203791[/C][/ROW]
[ROW][C]16[/C][C]-0.175083[/C][C]-1.3448[/C][C]0.091913[/C][/ROW]
[ROW][C]17[/C][C]-0.081679[/C][C]-0.6274[/C][C]0.266413[/C][/ROW]
[ROW][C]18[/C][C]0.039379[/C][C]0.3025[/C][C]0.381677[/C][/ROW]
[ROW][C]19[/C][C]-0.034627[/C][C]-0.266[/C][C]0.395593[/C][/ROW]
[ROW][C]20[/C][C]0.100547[/C][C]0.7723[/C][C]0.221505[/C][/ROW]
[ROW][C]21[/C][C]-0.060164[/C][C]-0.4621[/C][C]0.322844[/C][/ROW]
[ROW][C]22[/C][C]0.085175[/C][C]0.6542[/C][C]0.257748[/C][/ROW]
[ROW][C]23[/C][C]-0.125158[/C][C]-0.9614[/C][C]0.170148[/C][/ROW]
[ROW][C]24[/C][C]-0.173453[/C][C]-1.3323[/C][C]0.09394[/C][/ROW]
[ROW][C]25[/C][C]0.033121[/C][C]0.2544[/C][C]0.400033[/C][/ROW]
[ROW][C]26[/C][C]0.041279[/C][C]0.3171[/C][C]0.376154[/C][/ROW]
[ROW][C]27[/C][C]0.070644[/C][C]0.5426[/C][C]0.294716[/C][/ROW]
[ROW][C]28[/C][C]-0.01749[/C][C]-0.1343[/C][C]0.446795[/C][/ROW]
[ROW][C]29[/C][C]-0.063734[/C][C]-0.4895[/C][C]0.313134[/C][/ROW]
[ROW][C]30[/C][C]-0.090422[/C][C]-0.6945[/C][C]0.245032[/C][/ROW]
[ROW][C]31[/C][C]-0.080686[/C][C]-0.6198[/C][C]0.2689[/C][/ROW]
[ROW][C]32[/C][C]-0.08691[/C][C]-0.6676[/C][C]0.253506[/C][/ROW]
[ROW][C]33[/C][C]-0.076797[/C][C]-0.5899[/C][C]0.278759[/C][/ROW]
[ROW][C]34[/C][C]0.014885[/C][C]0.1143[/C][C]0.454681[/C][/ROW]
[ROW][C]35[/C][C]-0.052173[/C][C]-0.4008[/C][C]0.345025[/C][/ROW]
[ROW][C]36[/C][C]0.018295[/C][C]0.1405[/C][C]0.444362[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31307&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31307&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	-0.009762	-0.075	0.470241
2	-0.057652	-0.4428	0.329752
3	0.231088	1.775	0.040526
4	0.130945	1.0058	0.159308
5	-0.160707	-1.2344	0.110971
6	-0.083086	-0.6382	0.262908
7	-0.067825	-0.521	0.302167
8	-0.088895	-0.6828	0.248698
9	0.048412	0.3719	0.355664
10	-0.000155	-0.0012	0.499526
11	0.074116	0.5693	0.285657
12	-0.115937	-0.8905	0.188399
13	-0.093693	-0.7197	0.237286
14	-0.049035	-0.3766	0.353894
15	-0.108592	-0.8341	0.203791
16	-0.175083	-1.3448	0.091913
17	-0.081679	-0.6274	0.266413
18	0.039379	0.3025	0.381677
19	-0.034627	-0.266	0.395593
20	0.100547	0.7723	0.221505
21	-0.060164	-0.4621	0.322844
22	0.085175	0.6542	0.257748
23	-0.125158	-0.9614	0.170148
24	-0.173453	-1.3323	0.09394
25	0.033121	0.2544	0.400033
26	0.041279	0.3171	0.376154
27	0.070644	0.5426	0.294716
28	-0.01749	-0.1343	0.446795
29	-0.063734	-0.4895	0.313134
30	-0.090422	-0.6945	0.245032
31	-0.080686	-0.6198	0.2689
32	-0.08691	-0.6676	0.253506
33	-0.076797	-0.5899	0.278759
34	0.014885	0.1143	0.454681
35	-0.052173	-0.4008	0.345025
36	0.018295	0.1405	0.444362

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 36 ; par2 = -0.7 ; par3 = 1 ; par4 = 0 ; par5 = 12 ;

Parameters (R input):

par1 = 36 ; par2 = -0.7 ; par3 = 1 ; par4 = 0 ; 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