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rwasp_autocorrelation.wasp

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(Partial) Autocorrelation Function

Date of computation

Sat, 19 Dec 2009 09:33:09 -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/2009/Dec/19/t12612406078a23nw57dsnmyzl.htm/, Retrieved Fri, 03 May 2024 15:59:22 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=69688, Retrieved Fri, 03 May 2024 15:59:22 +0000

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105

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

-     [(Partial) Autocorrelation Function] [(Partial) Autocor...] [2008-12-21 16:05:06] [005278dde49cfd8c32bf201feaeb19d6]
-  MPD    [(Partial) Autocorrelation Function] [autocorrelatie (d=2)] [2009-12-19 16:33:09] [986e3c28a4248c495afaef9fd432264f] [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	'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=69688&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=69688&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69688&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	-0.372854	-4.612	4e-06
2	-0.11203	-1.3857	0.083922
3	0.018984	0.2348	0.407331
4	-0.040083	-0.4958	0.310374
5	0.070132	0.8675	0.193518
6	0.008939	0.1106	0.456054
7	-0.039906	-0.4936	0.311143
8	0.008742	0.1081	0.457015
9	-0.14165	-1.7521	0.040879
10	0.125624	1.5539	0.061139
11	0.123768	1.5309	0.063926
12	-0.010032	-0.1241	0.450705
13	-0.181875	-2.2497	0.012948
14	0.08962	1.1085	0.134685
15	-0.003877	-0.048	0.480906
16	-0.049769	-0.6156	0.269532
17	0.049826	0.6163	0.269302
18	-0.020025	-0.2477	0.402353
19	-0.019529	-0.2416	0.404721
20	0.067131	0.8304	0.203813
21	-0.137921	-1.706	0.04502
22	0.182534	2.2578	0.012686
23	-0.137393	-1.6995	0.045633
24	-0.055077	-0.6813	0.248368
25	0.204627	2.5311	0.00619
26	-0.081436	-1.0073	0.157687
27	-0.067372	-0.8333	0.202974
28	0.094183	1.165	0.12292
29	-0.102319	-1.2656	0.103787
30	0.072184	0.8929	0.186666
31	0.012946	0.1601	0.436494
32	-0.044362	-0.5487	0.291995
33	0.017324	0.2143	0.415305
34	-0.128645	-1.5913	0.056808
35	0.097038	1.2003	0.115941
36	0.100089	1.238	0.1088

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.372854 & -4.612 & 4e-06 \tabularnewline
2 & -0.11203 & -1.3857 & 0.083922 \tabularnewline
3 & 0.018984 & 0.2348 & 0.407331 \tabularnewline
4 & -0.040083 & -0.4958 & 0.310374 \tabularnewline
5 & 0.070132 & 0.8675 & 0.193518 \tabularnewline
6 & 0.008939 & 0.1106 & 0.456054 \tabularnewline
7 & -0.039906 & -0.4936 & 0.311143 \tabularnewline
8 & 0.008742 & 0.1081 & 0.457015 \tabularnewline
9 & -0.14165 & -1.7521 & 0.040879 \tabularnewline
10 & 0.125624 & 1.5539 & 0.061139 \tabularnewline
11 & 0.123768 & 1.5309 & 0.063926 \tabularnewline
12 & -0.010032 & -0.1241 & 0.450705 \tabularnewline
13 & -0.181875 & -2.2497 & 0.012948 \tabularnewline
14 & 0.08962 & 1.1085 & 0.134685 \tabularnewline
15 & -0.003877 & -0.048 & 0.480906 \tabularnewline
16 & -0.049769 & -0.6156 & 0.269532 \tabularnewline
17 & 0.049826 & 0.6163 & 0.269302 \tabularnewline
18 & -0.020025 & -0.2477 & 0.402353 \tabularnewline
19 & -0.019529 & -0.2416 & 0.404721 \tabularnewline
20 & 0.067131 & 0.8304 & 0.203813 \tabularnewline
21 & -0.137921 & -1.706 & 0.04502 \tabularnewline
22 & 0.182534 & 2.2578 & 0.012686 \tabularnewline
23 & -0.137393 & -1.6995 & 0.045633 \tabularnewline
24 & -0.055077 & -0.6813 & 0.248368 \tabularnewline
25 & 0.204627 & 2.5311 & 0.00619 \tabularnewline
26 & -0.081436 & -1.0073 & 0.157687 \tabularnewline
27 & -0.067372 & -0.8333 & 0.202974 \tabularnewline
28 & 0.094183 & 1.165 & 0.12292 \tabularnewline
29 & -0.102319 & -1.2656 & 0.103787 \tabularnewline
30 & 0.072184 & 0.8929 & 0.186666 \tabularnewline
31 & 0.012946 & 0.1601 & 0.436494 \tabularnewline
32 & -0.044362 & -0.5487 & 0.291995 \tabularnewline
33 & 0.017324 & 0.2143 & 0.415305 \tabularnewline
34 & -0.128645 & -1.5913 & 0.056808 \tabularnewline
35 & 0.097038 & 1.2003 & 0.115941 \tabularnewline
36 & 0.100089 & 1.238 & 0.1088 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69688&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]-0.372854[/C][C]-4.612[/C][C]4e-06[/C][/ROW]
[ROW][C]2[/C][C]-0.11203[/C][C]-1.3857[/C][C]0.083922[/C][/ROW]
[ROW][C]3[/C][C]0.018984[/C][C]0.2348[/C][C]0.407331[/C][/ROW]
[ROW][C]4[/C][C]-0.040083[/C][C]-0.4958[/C][C]0.310374[/C][/ROW]
[ROW][C]5[/C][C]0.070132[/C][C]0.8675[/C][C]0.193518[/C][/ROW]
[ROW][C]6[/C][C]0.008939[/C][C]0.1106[/C][C]0.456054[/C][/ROW]
[ROW][C]7[/C][C]-0.039906[/C][C]-0.4936[/C][C]0.311143[/C][/ROW]
[ROW][C]8[/C][C]0.008742[/C][C]0.1081[/C][C]0.457015[/C][/ROW]
[ROW][C]9[/C][C]-0.14165[/C][C]-1.7521[/C][C]0.040879[/C][/ROW]
[ROW][C]10[/C][C]0.125624[/C][C]1.5539[/C][C]0.061139[/C][/ROW]
[ROW][C]11[/C][C]0.123768[/C][C]1.5309[/C][C]0.063926[/C][/ROW]
[ROW][C]12[/C][C]-0.010032[/C][C]-0.1241[/C][C]0.450705[/C][/ROW]
[ROW][C]13[/C][C]-0.181875[/C][C]-2.2497[/C][C]0.012948[/C][/ROW]
[ROW][C]14[/C][C]0.08962[/C][C]1.1085[/C][C]0.134685[/C][/ROW]
[ROW][C]15[/C][C]-0.003877[/C][C]-0.048[/C][C]0.480906[/C][/ROW]
[ROW][C]16[/C][C]-0.049769[/C][C]-0.6156[/C][C]0.269532[/C][/ROW]
[ROW][C]17[/C][C]0.049826[/C][C]0.6163[/C][C]0.269302[/C][/ROW]
[ROW][C]18[/C][C]-0.020025[/C][C]-0.2477[/C][C]0.402353[/C][/ROW]
[ROW][C]19[/C][C]-0.019529[/C][C]-0.2416[/C][C]0.404721[/C][/ROW]
[ROW][C]20[/C][C]0.067131[/C][C]0.8304[/C][C]0.203813[/C][/ROW]
[ROW][C]21[/C][C]-0.137921[/C][C]-1.706[/C][C]0.04502[/C][/ROW]
[ROW][C]22[/C][C]0.182534[/C][C]2.2578[/C][C]0.012686[/C][/ROW]
[ROW][C]23[/C][C]-0.137393[/C][C]-1.6995[/C][C]0.045633[/C][/ROW]
[ROW][C]24[/C][C]-0.055077[/C][C]-0.6813[/C][C]0.248368[/C][/ROW]
[ROW][C]25[/C][C]0.204627[/C][C]2.5311[/C][C]0.00619[/C][/ROW]
[ROW][C]26[/C][C]-0.081436[/C][C]-1.0073[/C][C]0.157687[/C][/ROW]
[ROW][C]27[/C][C]-0.067372[/C][C]-0.8333[/C][C]0.202974[/C][/ROW]
[ROW][C]28[/C][C]0.094183[/C][C]1.165[/C][C]0.12292[/C][/ROW]
[ROW][C]29[/C][C]-0.102319[/C][C]-1.2656[/C][C]0.103787[/C][/ROW]
[ROW][C]30[/C][C]0.072184[/C][C]0.8929[/C][C]0.186666[/C][/ROW]
[ROW][C]31[/C][C]0.012946[/C][C]0.1601[/C][C]0.436494[/C][/ROW]
[ROW][C]32[/C][C]-0.044362[/C][C]-0.5487[/C][C]0.291995[/C][/ROW]
[ROW][C]33[/C][C]0.017324[/C][C]0.2143[/C][C]0.415305[/C][/ROW]
[ROW][C]34[/C][C]-0.128645[/C][C]-1.5913[/C][C]0.056808[/C][/ROW]
[ROW][C]35[/C][C]0.097038[/C][C]1.2003[/C][C]0.115941[/C][/ROW]
[ROW][C]36[/C][C]0.100089[/C][C]1.238[/C][C]0.1088[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69688&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69688&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	-0.372854	-4.612	4e-06
2	-0.11203	-1.3857	0.083922
3	0.018984	0.2348	0.407331
4	-0.040083	-0.4958	0.310374
5	0.070132	0.8675	0.193518
6	0.008939	0.1106	0.456054
7	-0.039906	-0.4936	0.311143
8	0.008742	0.1081	0.457015
9	-0.14165	-1.7521	0.040879
10	0.125624	1.5539	0.061139
11	0.123768	1.5309	0.063926
12	-0.010032	-0.1241	0.450705
13	-0.181875	-2.2497	0.012948
14	0.08962	1.1085	0.134685
15	-0.003877	-0.048	0.480906
16	-0.049769	-0.6156	0.269532
17	0.049826	0.6163	0.269302
18	-0.020025	-0.2477	0.402353
19	-0.019529	-0.2416	0.404721
20	0.067131	0.8304	0.203813
21	-0.137921	-1.706	0.04502
22	0.182534	2.2578	0.012686
23	-0.137393	-1.6995	0.045633
24	-0.055077	-0.6813	0.248368
25	0.204627	2.5311	0.00619
26	-0.081436	-1.0073	0.157687
27	-0.067372	-0.8333	0.202974
28	0.094183	1.165	0.12292
29	-0.102319	-1.2656	0.103787
30	0.072184	0.8929	0.186666
31	0.012946	0.1601	0.436494
32	-0.044362	-0.5487	0.291995
33	0.017324	0.2143	0.415305
34	-0.128645	-1.5913	0.056808
35	0.097038	1.2003	0.115941
36	0.100089	1.238	0.1088

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	-0.372854	-4.612	4e-06
2	-0.291587	-3.6067	0.00021
3	-0.182395	-2.2561	0.012741
4	-0.184415	-2.2811	0.011962
5	-0.060301	-0.7459	0.228442
6	-0.013978	-0.1729	0.431482
7	-0.031277	-0.3869	0.349695
8	-0.014913	-0.1845	0.426946
9	-0.203048	-2.5116	0.006529
10	-0.066134	-0.818	0.207304
11	0.110097	1.3618	0.087628
12	0.176998	2.1893	0.015043
13	-0.058175	-0.7196	0.236438
14	0.036444	0.4508	0.32639
15	0.002923	0.0362	0.485601
16	-0.095492	-1.1812	0.119683
17	-0.05442	-0.6731	0.250939
18	-0.041665	-0.5154	0.30352
19	-0.012549	-0.1552	0.438426
20	0.093877	1.1612	0.123686
21	-0.126377	-1.5632	0.060036
22	0.016051	0.1985	0.421442
23	-0.108492	-1.342	0.090796
24	-0.141258	-1.7473	0.041298
25	0.102538	1.2683	0.103304
26	0.075291	0.9313	0.176582
27	0.009452	0.1169	0.453538
28	0.092689	1.1465	0.126688
29	-0.06028	-0.7456	0.228522
30	-0.049101	-0.6073	0.272261
31	0.028822	0.3565	0.360978
32	-0.013196	-0.1632	0.435277
33	0.032805	0.4058	0.342739
34	-0.1414	-1.749	0.041146
35	-0.03244	-0.4013	0.344395
36	-0.01029	-0.1273	0.449442

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.372854 & -4.612 & 4e-06 \tabularnewline
2 & -0.291587 & -3.6067 & 0.00021 \tabularnewline
3 & -0.182395 & -2.2561 & 0.012741 \tabularnewline
4 & -0.184415 & -2.2811 & 0.011962 \tabularnewline
5 & -0.060301 & -0.7459 & 0.228442 \tabularnewline
6 & -0.013978 & -0.1729 & 0.431482 \tabularnewline
7 & -0.031277 & -0.3869 & 0.349695 \tabularnewline
8 & -0.014913 & -0.1845 & 0.426946 \tabularnewline
9 & -0.203048 & -2.5116 & 0.006529 \tabularnewline
10 & -0.066134 & -0.818 & 0.207304 \tabularnewline
11 & 0.110097 & 1.3618 & 0.087628 \tabularnewline
12 & 0.176998 & 2.1893 & 0.015043 \tabularnewline
13 & -0.058175 & -0.7196 & 0.236438 \tabularnewline
14 & 0.036444 & 0.4508 & 0.32639 \tabularnewline
15 & 0.002923 & 0.0362 & 0.485601 \tabularnewline
16 & -0.095492 & -1.1812 & 0.119683 \tabularnewline
17 & -0.05442 & -0.6731 & 0.250939 \tabularnewline
18 & -0.041665 & -0.5154 & 0.30352 \tabularnewline
19 & -0.012549 & -0.1552 & 0.438426 \tabularnewline
20 & 0.093877 & 1.1612 & 0.123686 \tabularnewline
21 & -0.126377 & -1.5632 & 0.060036 \tabularnewline
22 & 0.016051 & 0.1985 & 0.421442 \tabularnewline
23 & -0.108492 & -1.342 & 0.090796 \tabularnewline
24 & -0.141258 & -1.7473 & 0.041298 \tabularnewline
25 & 0.102538 & 1.2683 & 0.103304 \tabularnewline
26 & 0.075291 & 0.9313 & 0.176582 \tabularnewline
27 & 0.009452 & 0.1169 & 0.453538 \tabularnewline
28 & 0.092689 & 1.1465 & 0.126688 \tabularnewline
29 & -0.06028 & -0.7456 & 0.228522 \tabularnewline
30 & -0.049101 & -0.6073 & 0.272261 \tabularnewline
31 & 0.028822 & 0.3565 & 0.360978 \tabularnewline
32 & -0.013196 & -0.1632 & 0.435277 \tabularnewline
33 & 0.032805 & 0.4058 & 0.342739 \tabularnewline
34 & -0.1414 & -1.749 & 0.041146 \tabularnewline
35 & -0.03244 & -0.4013 & 0.344395 \tabularnewline
36 & -0.01029 & -0.1273 & 0.449442 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69688&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]-0.372854[/C][C]-4.612[/C][C]4e-06[/C][/ROW]
[ROW][C]2[/C][C]-0.291587[/C][C]-3.6067[/C][C]0.00021[/C][/ROW]
[ROW][C]3[/C][C]-0.182395[/C][C]-2.2561[/C][C]0.012741[/C][/ROW]
[ROW][C]4[/C][C]-0.184415[/C][C]-2.2811[/C][C]0.011962[/C][/ROW]
[ROW][C]5[/C][C]-0.060301[/C][C]-0.7459[/C][C]0.228442[/C][/ROW]
[ROW][C]6[/C][C]-0.013978[/C][C]-0.1729[/C][C]0.431482[/C][/ROW]
[ROW][C]7[/C][C]-0.031277[/C][C]-0.3869[/C][C]0.349695[/C][/ROW]
[ROW][C]8[/C][C]-0.014913[/C][C]-0.1845[/C][C]0.426946[/C][/ROW]
[ROW][C]9[/C][C]-0.203048[/C][C]-2.5116[/C][C]0.006529[/C][/ROW]
[ROW][C]10[/C][C]-0.066134[/C][C]-0.818[/C][C]0.207304[/C][/ROW]
[ROW][C]11[/C][C]0.110097[/C][C]1.3618[/C][C]0.087628[/C][/ROW]
[ROW][C]12[/C][C]0.176998[/C][C]2.1893[/C][C]0.015043[/C][/ROW]
[ROW][C]13[/C][C]-0.058175[/C][C]-0.7196[/C][C]0.236438[/C][/ROW]
[ROW][C]14[/C][C]0.036444[/C][C]0.4508[/C][C]0.32639[/C][/ROW]
[ROW][C]15[/C][C]0.002923[/C][C]0.0362[/C][C]0.485601[/C][/ROW]
[ROW][C]16[/C][C]-0.095492[/C][C]-1.1812[/C][C]0.119683[/C][/ROW]
[ROW][C]17[/C][C]-0.05442[/C][C]-0.6731[/C][C]0.250939[/C][/ROW]
[ROW][C]18[/C][C]-0.041665[/C][C]-0.5154[/C][C]0.30352[/C][/ROW]
[ROW][C]19[/C][C]-0.012549[/C][C]-0.1552[/C][C]0.438426[/C][/ROW]
[ROW][C]20[/C][C]0.093877[/C][C]1.1612[/C][C]0.123686[/C][/ROW]
[ROW][C]21[/C][C]-0.126377[/C][C]-1.5632[/C][C]0.060036[/C][/ROW]
[ROW][C]22[/C][C]0.016051[/C][C]0.1985[/C][C]0.421442[/C][/ROW]
[ROW][C]23[/C][C]-0.108492[/C][C]-1.342[/C][C]0.090796[/C][/ROW]
[ROW][C]24[/C][C]-0.141258[/C][C]-1.7473[/C][C]0.041298[/C][/ROW]
[ROW][C]25[/C][C]0.102538[/C][C]1.2683[/C][C]0.103304[/C][/ROW]
[ROW][C]26[/C][C]0.075291[/C][C]0.9313[/C][C]0.176582[/C][/ROW]
[ROW][C]27[/C][C]0.009452[/C][C]0.1169[/C][C]0.453538[/C][/ROW]
[ROW][C]28[/C][C]0.092689[/C][C]1.1465[/C][C]0.126688[/C][/ROW]
[ROW][C]29[/C][C]-0.06028[/C][C]-0.7456[/C][C]0.228522[/C][/ROW]
[ROW][C]30[/C][C]-0.049101[/C][C]-0.6073[/C][C]0.272261[/C][/ROW]
[ROW][C]31[/C][C]0.028822[/C][C]0.3565[/C][C]0.360978[/C][/ROW]
[ROW][C]32[/C][C]-0.013196[/C][C]-0.1632[/C][C]0.435277[/C][/ROW]
[ROW][C]33[/C][C]0.032805[/C][C]0.4058[/C][C]0.342739[/C][/ROW]
[ROW][C]34[/C][C]-0.1414[/C][C]-1.749[/C][C]0.041146[/C][/ROW]
[ROW][C]35[/C][C]-0.03244[/C][C]-0.4013[/C][C]0.344395[/C][/ROW]
[ROW][C]36[/C][C]-0.01029[/C][C]-0.1273[/C][C]0.449442[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69688&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69688&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	-0.372854	-4.612	4e-06
2	-0.291587	-3.6067	0.00021
3	-0.182395	-2.2561	0.012741
4	-0.184415	-2.2811	0.011962
5	-0.060301	-0.7459	0.228442
6	-0.013978	-0.1729	0.431482
7	-0.031277	-0.3869	0.349695
8	-0.014913	-0.1845	0.426946
9	-0.203048	-2.5116	0.006529
10	-0.066134	-0.818	0.207304
11	0.110097	1.3618	0.087628
12	0.176998	2.1893	0.015043
13	-0.058175	-0.7196	0.236438
14	0.036444	0.4508	0.32639
15	0.002923	0.0362	0.485601
16	-0.095492	-1.1812	0.119683
17	-0.05442	-0.6731	0.250939
18	-0.041665	-0.5154	0.30352
19	-0.012549	-0.1552	0.438426
20	0.093877	1.1612	0.123686
21	-0.126377	-1.5632	0.060036
22	0.016051	0.1985	0.421442
23	-0.108492	-1.342	0.090796
24	-0.141258	-1.7473	0.041298
25	0.102538	1.2683	0.103304
26	0.075291	0.9313	0.176582
27	0.009452	0.1169	0.453538
28	0.092689	1.1465	0.126688
29	-0.06028	-0.7456	0.228522
30	-0.049101	-0.6073	0.272261
31	0.028822	0.3565	0.360978
32	-0.013196	-0.1632	0.435277
33	0.032805	0.4058	0.342739
34	-0.1414	-1.749	0.041146
35	-0.03244	-0.4013	0.344395
36	-0.01029	-0.1273	0.449442

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 36 ; par2 = -0.1 ; par3 = 2 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ;

Parameters (R input):

par1 = 36 ; par2 = -0.1 ; par3 = 2 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = ;

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