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rwasp_autocorrelation.wasp

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(Partial) Autocorrelation Function

Date of computation

Thu, 22 Dec 2016 18:02:56 +0100

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Dec/22/t1482426205ocumm142ygi5vbb.htm/, Retrieved Mon, 29 Apr 2024 02:17:49 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=302573, Retrieved Mon, 29 Apr 2024 02:17:49 +0000

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-       [(Partial) Autocorrelation Function] [Autocorrelatie fu...] [2016-12-22 17:02:56] [0c0812954c36a879765e84a6a68f060c] [Current]

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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	Big Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302573&T=0

[TABLE]
[ROW]

Summary of computational transaction[/C][/ROW] [ROW]

Raw Input[/C]

view raw input (R code) [/C][/ROW] [ROW]

Raw Output[/C]

view raw output of R engine [/C][/ROW] [ROW]

Computing time[/C]

1 seconds[/C][/ROW] [ROW]

R Server[/C]

Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=302573&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302573&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	Big Analytics Cloud Computing Center

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	-0.517631	-3.3943	0.000744
2	0.138452	0.9079	0.184498
3	-0.49717	-3.2602	0.001091
4	0.831424	5.452	1e-06
5	-0.484495	-3.177	0.001377
6	0.157902	1.0354	0.153127
7	-0.435946	-2.8587	0.003268
8	0.712946	4.6751	1.5e-05
9	-0.399245	-2.618	0.006081
10	0.102762	0.6739	0.252004
11	-0.391223	-2.5654	0.006938
12	0.640282	4.1986	6.6e-05
13	-0.327724	-2.149	0.018652
14	0.053389	0.3501	0.363987
15	-0.31474	-2.0639	0.022548
16	0.543895	3.5666	0.000451
17	-0.279853	-1.8351	0.036705
18	0.029931	0.1963	0.422662
19	-0.25396	-1.6653	0.051559
20	0.426411	2.7962	0.00385
21	-0.209667	-1.3749	0.088145
22	0.000511	0.0034	0.49867
23	-0.174782	-1.1461	0.129042
24	0.315927	2.0717	0.022165
25	-0.151688	-0.9947	0.162727
26	-0.006589	-0.0432	0.482868
27	-0.111371	-0.7303	0.234581
28	0.252713	1.6572	0.052384
29	-0.124637	-0.8173	0.209131
30	0.006173	0.0405	0.483949
31	-0.086399	-0.5666	0.286981
32	0.152424	0.9995	0.16157
33	-0.080613	-0.5286	0.299894
34	0.011765	0.0771	0.469432
35	-0.074066	-0.4857	0.314828
36	0.102082	0.6694	0.253411

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.517631 & -3.3943 & 0.000744 \tabularnewline
2 & 0.138452 & 0.9079 & 0.184498 \tabularnewline
3 & -0.49717 & -3.2602 & 0.001091 \tabularnewline
4 & 0.831424 & 5.452 & 1e-06 \tabularnewline
5 & -0.484495 & -3.177 & 0.001377 \tabularnewline
6 & 0.157902 & 1.0354 & 0.153127 \tabularnewline
7 & -0.435946 & -2.8587 & 0.003268 \tabularnewline
8 & 0.712946 & 4.6751 & 1.5e-05 \tabularnewline
9 & -0.399245 & -2.618 & 0.006081 \tabularnewline
10 & 0.102762 & 0.6739 & 0.252004 \tabularnewline
11 & -0.391223 & -2.5654 & 0.006938 \tabularnewline
12 & 0.640282 & 4.1986 & 6.6e-05 \tabularnewline
13 & -0.327724 & -2.149 & 0.018652 \tabularnewline
14 & 0.053389 & 0.3501 & 0.363987 \tabularnewline
15 & -0.31474 & -2.0639 & 0.022548 \tabularnewline
16 & 0.543895 & 3.5666 & 0.000451 \tabularnewline
17 & -0.279853 & -1.8351 & 0.036705 \tabularnewline
18 & 0.029931 & 0.1963 & 0.422662 \tabularnewline
19 & -0.25396 & -1.6653 & 0.051559 \tabularnewline
20 & 0.426411 & 2.7962 & 0.00385 \tabularnewline
21 & -0.209667 & -1.3749 & 0.088145 \tabularnewline
22 & 0.000511 & 0.0034 & 0.49867 \tabularnewline
23 & -0.174782 & -1.1461 & 0.129042 \tabularnewline
24 & 0.315927 & 2.0717 & 0.022165 \tabularnewline
25 & -0.151688 & -0.9947 & 0.162727 \tabularnewline
26 & -0.006589 & -0.0432 & 0.482868 \tabularnewline
27 & -0.111371 & -0.7303 & 0.234581 \tabularnewline
28 & 0.252713 & 1.6572 & 0.052384 \tabularnewline
29 & -0.124637 & -0.8173 & 0.209131 \tabularnewline
30 & 0.006173 & 0.0405 & 0.483949 \tabularnewline
31 & -0.086399 & -0.5666 & 0.286981 \tabularnewline
32 & 0.152424 & 0.9995 & 0.16157 \tabularnewline
33 & -0.080613 & -0.5286 & 0.299894 \tabularnewline
34 & 0.011765 & 0.0771 & 0.469432 \tabularnewline
35 & -0.074066 & -0.4857 & 0.314828 \tabularnewline
36 & 0.102082 & 0.6694 & 0.253411 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302573&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]-0.517631[/C][C]-3.3943[/C][C]0.000744[/C][/ROW]
[ROW][C]2[/C][C]0.138452[/C][C]0.9079[/C][C]0.184498[/C][/ROW]
[ROW][C]3[/C][C]-0.49717[/C][C]-3.2602[/C][C]0.001091[/C][/ROW]
[ROW][C]4[/C][C]0.831424[/C][C]5.452[/C][C]1e-06[/C][/ROW]
[ROW][C]5[/C][C]-0.484495[/C][C]-3.177[/C][C]0.001377[/C][/ROW]
[ROW][C]6[/C][C]0.157902[/C][C]1.0354[/C][C]0.153127[/C][/ROW]
[ROW][C]7[/C][C]-0.435946[/C][C]-2.8587[/C][C]0.003268[/C][/ROW]
[ROW][C]8[/C][C]0.712946[/C][C]4.6751[/C][C]1.5e-05[/C][/ROW]
[ROW][C]9[/C][C]-0.399245[/C][C]-2.618[/C][C]0.006081[/C][/ROW]
[ROW][C]10[/C][C]0.102762[/C][C]0.6739[/C][C]0.252004[/C][/ROW]
[ROW][C]11[/C][C]-0.391223[/C][C]-2.5654[/C][C]0.006938[/C][/ROW]
[ROW][C]12[/C][C]0.640282[/C][C]4.1986[/C][C]6.6e-05[/C][/ROW]
[ROW][C]13[/C][C]-0.327724[/C][C]-2.149[/C][C]0.018652[/C][/ROW]
[ROW][C]14[/C][C]0.053389[/C][C]0.3501[/C][C]0.363987[/C][/ROW]
[ROW][C]15[/C][C]-0.31474[/C][C]-2.0639[/C][C]0.022548[/C][/ROW]
[ROW][C]16[/C][C]0.543895[/C][C]3.5666[/C][C]0.000451[/C][/ROW]
[ROW][C]17[/C][C]-0.279853[/C][C]-1.8351[/C][C]0.036705[/C][/ROW]
[ROW][C]18[/C][C]0.029931[/C][C]0.1963[/C][C]0.422662[/C][/ROW]
[ROW][C]19[/C][C]-0.25396[/C][C]-1.6653[/C][C]0.051559[/C][/ROW]
[ROW][C]20[/C][C]0.426411[/C][C]2.7962[/C][C]0.00385[/C][/ROW]
[ROW][C]21[/C][C]-0.209667[/C][C]-1.3749[/C][C]0.088145[/C][/ROW]
[ROW][C]22[/C][C]0.000511[/C][C]0.0034[/C][C]0.49867[/C][/ROW]
[ROW][C]23[/C][C]-0.174782[/C][C]-1.1461[/C][C]0.129042[/C][/ROW]
[ROW][C]24[/C][C]0.315927[/C][C]2.0717[/C][C]0.022165[/C][/ROW]
[ROW][C]25[/C][C]-0.151688[/C][C]-0.9947[/C][C]0.162727[/C][/ROW]
[ROW][C]26[/C][C]-0.006589[/C][C]-0.0432[/C][C]0.482868[/C][/ROW]
[ROW][C]27[/C][C]-0.111371[/C][C]-0.7303[/C][C]0.234581[/C][/ROW]
[ROW][C]28[/C][C]0.252713[/C][C]1.6572[/C][C]0.052384[/C][/ROW]
[ROW][C]29[/C][C]-0.124637[/C][C]-0.8173[/C][C]0.209131[/C][/ROW]
[ROW][C]30[/C][C]0.006173[/C][C]0.0405[/C][C]0.483949[/C][/ROW]
[ROW][C]31[/C][C]-0.086399[/C][C]-0.5666[/C][C]0.286981[/C][/ROW]
[ROW][C]32[/C][C]0.152424[/C][C]0.9995[/C][C]0.16157[/C][/ROW]
[ROW][C]33[/C][C]-0.080613[/C][C]-0.5286[/C][C]0.299894[/C][/ROW]
[ROW][C]34[/C][C]0.011765[/C][C]0.0771[/C][C]0.469432[/C][/ROW]
[ROW][C]35[/C][C]-0.074066[/C][C]-0.4857[/C][C]0.314828[/C][/ROW]
[ROW][C]36[/C][C]0.102082[/C][C]0.6694[/C][C]0.253411[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=302573&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302573&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	-0.517631	-3.3943	0.000744
2	0.138452	0.9079	0.184498
3	-0.49717	-3.2602	0.001091
4	0.831424	5.452	1e-06
5	-0.484495	-3.177	0.001377
6	0.157902	1.0354	0.153127
7	-0.435946	-2.8587	0.003268
8	0.712946	4.6751	1.5e-05
9	-0.399245	-2.618	0.006081
10	0.102762	0.6739	0.252004
11	-0.391223	-2.5654	0.006938
12	0.640282	4.1986	6.6e-05
13	-0.327724	-2.149	0.018652
14	0.053389	0.3501	0.363987
15	-0.31474	-2.0639	0.022548
16	0.543895	3.5666	0.000451
17	-0.279853	-1.8351	0.036705
18	0.029931	0.1963	0.422662
19	-0.25396	-1.6653	0.051559
20	0.426411	2.7962	0.00385
21	-0.209667	-1.3749	0.088145
22	0.000511	0.0034	0.49867
23	-0.174782	-1.1461	0.129042
24	0.315927	2.0717	0.022165
25	-0.151688	-0.9947	0.162727
26	-0.006589	-0.0432	0.482868
27	-0.111371	-0.7303	0.234581
28	0.252713	1.6572	0.052384
29	-0.124637	-0.8173	0.209131
30	0.006173	0.0405	0.483949
31	-0.086399	-0.5666	0.286981
32	0.152424	0.9995	0.16157
33	-0.080613	-0.5286	0.299894
34	0.011765	0.0771	0.469432
35	-0.074066	-0.4857	0.314828
36	0.102082	0.6694	0.253411

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	-0.517631	-3.3943	0.000744
2	-0.176884	-1.1599	0.126243
3	-0.711252	-4.664	1.5e-05
4	0.520299	3.4118	0.000708
5	-0.045978	-0.3015	0.382244
6	-0.05913	-0.3877	0.350061
7	0.019165	0.1257	0.450288
8	0.018988	0.1245	0.450744
9	0.177229	1.1622	0.125789
10	-0.148009	-0.9706	0.168597
11	-0.092147	-0.6042	0.274427
12	0.080742	0.5295	0.299606
13	0.000232	0.0015	0.499396
14	-0.051332	-0.3366	0.369025
15	0.0529	0.3469	0.365183
16	-0.035563	-0.2332	0.408355
17	-0.024828	-0.1628	0.435717
18	0.004081	0.0268	0.489388
19	-0.024005	-0.1574	0.437829
20	-0.134903	-0.8846	0.190641
21	-0.041495	-0.2721	0.393422
22	-0.079173	-0.5192	0.303151
23	0.063561	0.4168	0.339449
24	-0.104435	-0.6848	0.248564
25	-0.103849	-0.681	0.249767
26	0.106547	0.6987	0.244258
27	-0.00584	-0.0383	0.484815
28	0.105666	0.6929	0.24605
29	-0.015917	-0.1044	0.45868
30	0.115931	0.7602	0.225639
31	0.061937	0.4062	0.343323
32	-0.188531	-1.2363	0.111532
33	0.052698	0.3456	0.365678
34	-0.050497	-0.3311	0.371078
35	-0.133036	-0.8724	0.193924
36	7e-05	5e-04	0.499819

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.517631 & -3.3943 & 0.000744 \tabularnewline
2 & -0.176884 & -1.1599 & 0.126243 \tabularnewline
3 & -0.711252 & -4.664 & 1.5e-05 \tabularnewline
4 & 0.520299 & 3.4118 & 0.000708 \tabularnewline
5 & -0.045978 & -0.3015 & 0.382244 \tabularnewline
6 & -0.05913 & -0.3877 & 0.350061 \tabularnewline
7 & 0.019165 & 0.1257 & 0.450288 \tabularnewline
8 & 0.018988 & 0.1245 & 0.450744 \tabularnewline
9 & 0.177229 & 1.1622 & 0.125789 \tabularnewline
10 & -0.148009 & -0.9706 & 0.168597 \tabularnewline
11 & -0.092147 & -0.6042 & 0.274427 \tabularnewline
12 & 0.080742 & 0.5295 & 0.299606 \tabularnewline
13 & 0.000232 & 0.0015 & 0.499396 \tabularnewline
14 & -0.051332 & -0.3366 & 0.369025 \tabularnewline
15 & 0.0529 & 0.3469 & 0.365183 \tabularnewline
16 & -0.035563 & -0.2332 & 0.408355 \tabularnewline
17 & -0.024828 & -0.1628 & 0.435717 \tabularnewline
18 & 0.004081 & 0.0268 & 0.489388 \tabularnewline
19 & -0.024005 & -0.1574 & 0.437829 \tabularnewline
20 & -0.134903 & -0.8846 & 0.190641 \tabularnewline
21 & -0.041495 & -0.2721 & 0.393422 \tabularnewline
22 & -0.079173 & -0.5192 & 0.303151 \tabularnewline
23 & 0.063561 & 0.4168 & 0.339449 \tabularnewline
24 & -0.104435 & -0.6848 & 0.248564 \tabularnewline
25 & -0.103849 & -0.681 & 0.249767 \tabularnewline
26 & 0.106547 & 0.6987 & 0.244258 \tabularnewline
27 & -0.00584 & -0.0383 & 0.484815 \tabularnewline
28 & 0.105666 & 0.6929 & 0.24605 \tabularnewline
29 & -0.015917 & -0.1044 & 0.45868 \tabularnewline
30 & 0.115931 & 0.7602 & 0.225639 \tabularnewline
31 & 0.061937 & 0.4062 & 0.343323 \tabularnewline
32 & -0.188531 & -1.2363 & 0.111532 \tabularnewline
33 & 0.052698 & 0.3456 & 0.365678 \tabularnewline
34 & -0.050497 & -0.3311 & 0.371078 \tabularnewline
35 & -0.133036 & -0.8724 & 0.193924 \tabularnewline
36 & 7e-05 & 5e-04 & 0.499819 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302573&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]-0.517631[/C][C]-3.3943[/C][C]0.000744[/C][/ROW]
[ROW][C]2[/C][C]-0.176884[/C][C]-1.1599[/C][C]0.126243[/C][/ROW]
[ROW][C]3[/C][C]-0.711252[/C][C]-4.664[/C][C]1.5e-05[/C][/ROW]
[ROW][C]4[/C][C]0.520299[/C][C]3.4118[/C][C]0.000708[/C][/ROW]
[ROW][C]5[/C][C]-0.045978[/C][C]-0.3015[/C][C]0.382244[/C][/ROW]
[ROW][C]6[/C][C]-0.05913[/C][C]-0.3877[/C][C]0.350061[/C][/ROW]
[ROW][C]7[/C][C]0.019165[/C][C]0.1257[/C][C]0.450288[/C][/ROW]
[ROW][C]8[/C][C]0.018988[/C][C]0.1245[/C][C]0.450744[/C][/ROW]
[ROW][C]9[/C][C]0.177229[/C][C]1.1622[/C][C]0.125789[/C][/ROW]
[ROW][C]10[/C][C]-0.148009[/C][C]-0.9706[/C][C]0.168597[/C][/ROW]
[ROW][C]11[/C][C]-0.092147[/C][C]-0.6042[/C][C]0.274427[/C][/ROW]
[ROW][C]12[/C][C]0.080742[/C][C]0.5295[/C][C]0.299606[/C][/ROW]
[ROW][C]13[/C][C]0.000232[/C][C]0.0015[/C][C]0.499396[/C][/ROW]
[ROW][C]14[/C][C]-0.051332[/C][C]-0.3366[/C][C]0.369025[/C][/ROW]
[ROW][C]15[/C][C]0.0529[/C][C]0.3469[/C][C]0.365183[/C][/ROW]
[ROW][C]16[/C][C]-0.035563[/C][C]-0.2332[/C][C]0.408355[/C][/ROW]
[ROW][C]17[/C][C]-0.024828[/C][C]-0.1628[/C][C]0.435717[/C][/ROW]
[ROW][C]18[/C][C]0.004081[/C][C]0.0268[/C][C]0.489388[/C][/ROW]
[ROW][C]19[/C][C]-0.024005[/C][C]-0.1574[/C][C]0.437829[/C][/ROW]
[ROW][C]20[/C][C]-0.134903[/C][C]-0.8846[/C][C]0.190641[/C][/ROW]
[ROW][C]21[/C][C]-0.041495[/C][C]-0.2721[/C][C]0.393422[/C][/ROW]
[ROW][C]22[/C][C]-0.079173[/C][C]-0.5192[/C][C]0.303151[/C][/ROW]
[ROW][C]23[/C][C]0.063561[/C][C]0.4168[/C][C]0.339449[/C][/ROW]
[ROW][C]24[/C][C]-0.104435[/C][C]-0.6848[/C][C]0.248564[/C][/ROW]
[ROW][C]25[/C][C]-0.103849[/C][C]-0.681[/C][C]0.249767[/C][/ROW]
[ROW][C]26[/C][C]0.106547[/C][C]0.6987[/C][C]0.244258[/C][/ROW]
[ROW][C]27[/C][C]-0.00584[/C][C]-0.0383[/C][C]0.484815[/C][/ROW]
[ROW][C]28[/C][C]0.105666[/C][C]0.6929[/C][C]0.24605[/C][/ROW]
[ROW][C]29[/C][C]-0.015917[/C][C]-0.1044[/C][C]0.45868[/C][/ROW]
[ROW][C]30[/C][C]0.115931[/C][C]0.7602[/C][C]0.225639[/C][/ROW]
[ROW][C]31[/C][C]0.061937[/C][C]0.4062[/C][C]0.343323[/C][/ROW]
[ROW][C]32[/C][C]-0.188531[/C][C]-1.2363[/C][C]0.111532[/C][/ROW]
[ROW][C]33[/C][C]0.052698[/C][C]0.3456[/C][C]0.365678[/C][/ROW]
[ROW][C]34[/C][C]-0.050497[/C][C]-0.3311[/C][C]0.371078[/C][/ROW]
[ROW][C]35[/C][C]-0.133036[/C][C]-0.8724[/C][C]0.193924[/C][/ROW]
[ROW][C]36[/C][C]7e-05[/C][C]5e-04[/C][C]0.499819[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=302573&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302573&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	-0.517631	-3.3943	0.000744
2	-0.176884	-1.1599	0.126243
3	-0.711252	-4.664	1.5e-05
4	0.520299	3.4118	0.000708
5	-0.045978	-0.3015	0.382244
6	-0.05913	-0.3877	0.350061
7	0.019165	0.1257	0.450288
8	0.018988	0.1245	0.450744
9	0.177229	1.1622	0.125789
10	-0.148009	-0.9706	0.168597
11	-0.092147	-0.6042	0.274427
12	0.080742	0.5295	0.299606
13	0.000232	0.0015	0.499396
14	-0.051332	-0.3366	0.369025
15	0.0529	0.3469	0.365183
16	-0.035563	-0.2332	0.408355
17	-0.024828	-0.1628	0.435717
18	0.004081	0.0268	0.489388
19	-0.024005	-0.1574	0.437829
20	-0.134903	-0.8846	0.190641
21	-0.041495	-0.2721	0.393422
22	-0.079173	-0.5192	0.303151
23	0.063561	0.4168	0.339449
24	-0.104435	-0.6848	0.248564
25	-0.103849	-0.681	0.249767
26	0.106547	0.6987	0.244258
27	-0.00584	-0.0383	0.484815
28	0.105666	0.6929	0.24605
29	-0.015917	-0.1044	0.45868
30	0.115931	0.7602	0.225639
31	0.061937	0.4062	0.343323
32	-0.188531	-1.2363	0.111532
33	0.052698	0.3456	0.365678
34	-0.050497	-0.3311	0.371078
35	-0.133036	-0.8724	0.193924
36	7e-05	5e-04	0.499819

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Figure 3

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 2 ; par5 = 6 ; par6 = White Noise ; par7 = 0.95 ;

Parameters (R input):

par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ; par8 = ;

R code (references can be found in the software module):

if (par1 == 'Default') {
par1 = 10*log10(length(x))
} else {
par1 <- as.numeric(par1)
}
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
par5 <- as.numeric(par5)
if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
par7 <- as.numeric(par7)
if (par8 != '') par8 <- as.numeric(par8)
x <- na.omit(x)
ox <- x
if (par8 == '') {
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
} else {
x <- log(x,base=par8)
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='picts.png')
op <- par(mfrow=c(2,1))
plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')
if (par8=='') {
mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
} else {
mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
}
plot(x,type='l', main=mytitle,xlab='time',ylab='value')
par(op)
dev.off()
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)
dev.off()
(myacf <- c(racf$acf))
(mypacf <- c(rpacf$acf))
lengthx <- length(x)
sqrtn <- sqrt(lengthx)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,'ACF(k)',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,'PACF(k)',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