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rwasp_autocorrelation.wasp

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(Partial) Autocorrelation Function

Date of computation

Thu, 22 Dec 2011 09:03:03 -0500

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/22/t13245626522gmx1425f7cdlev.htm/, Retrieved Fri, 03 May 2024 11:58:59 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=159471, Retrieved Fri, 03 May 2024 11:58:59 +0000

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-     [Multiple Regression] [montly  dummies] [2011-12-22 13:26:17] [a2638725f7f7c6bd63902ba17eba666b]
- RMPD    [(Partial) Autocorrelation Function] [acf] [2011-12-22 14:03:03] [1e640daebbc6b5a89eef23229b5a56d5] [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	'Herman Ole Andreas Wold' @ wold.wessa.net

\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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=159471&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=159471&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=159471&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	'Herman Ole Andreas Wold' @ wold.wessa.net

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.253408	2.0897	0.020196
2	-0.195884	-1.6153	0.055438
3	-0.275046	-2.2681	0.013252
4	-0.255988	-2.1109	0.019229
5	0.041332	0.3408	0.367141
6	0.16977	1.4	0.083035
7	0.047298	0.39	0.348867
8	-0.244007	-2.0121	0.024085
9	-0.272283	-2.2453	0.014002
10	-0.148535	-1.2248	0.112429
11	0.250157	2.0628	0.021475
12	0.748754	6.1744	0
13	0.172675	1.4239	0.079522
14	-0.153451	-1.2654	0.105026
15	-0.218898	-1.8051	0.037744
16	-0.211745	-1.7461	0.042655
17	0.015498	0.1278	0.449342
18	0.098522	0.8124	0.209689
19	0.02396	0.1976	0.421983
20	-0.233227	-1.9232	0.029319
21	-0.2187	-1.8034	0.037874
22	-0.081476	-0.6719	0.251971
23	0.18332	1.5117	0.067622
24	0.548563	4.5236	1.3e-05
25	0.128741	1.0616	0.146081
26	-0.156409	-1.2898	0.100749
27	-0.225932	-1.8631	0.033385
28	-0.159365	-1.3142	0.096605
29	0.020368	0.168	0.433558
30	0.066579	0.549	0.292393
31	0.004629	0.0382	0.484832
32	-0.191386	-1.5782	0.05958
33	-0.14138	-1.1658	0.123874
34	-0.058442	-0.4819	0.315703
35	0.127911	1.0548	0.147628
36	0.419888	3.4625	0.000465

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.253408 & 2.0897 & 0.020196 \tabularnewline
2 & -0.195884 & -1.6153 & 0.055438 \tabularnewline
3 & -0.275046 & -2.2681 & 0.013252 \tabularnewline
4 & -0.255988 & -2.1109 & 0.019229 \tabularnewline
5 & 0.041332 & 0.3408 & 0.367141 \tabularnewline
6 & 0.16977 & 1.4 & 0.083035 \tabularnewline
7 & 0.047298 & 0.39 & 0.348867 \tabularnewline
8 & -0.244007 & -2.0121 & 0.024085 \tabularnewline
9 & -0.272283 & -2.2453 & 0.014002 \tabularnewline
10 & -0.148535 & -1.2248 & 0.112429 \tabularnewline
11 & 0.250157 & 2.0628 & 0.021475 \tabularnewline
12 & 0.748754 & 6.1744 & 0 \tabularnewline
13 & 0.172675 & 1.4239 & 0.079522 \tabularnewline
14 & -0.153451 & -1.2654 & 0.105026 \tabularnewline
15 & -0.218898 & -1.8051 & 0.037744 \tabularnewline
16 & -0.211745 & -1.7461 & 0.042655 \tabularnewline
17 & 0.015498 & 0.1278 & 0.449342 \tabularnewline
18 & 0.098522 & 0.8124 & 0.209689 \tabularnewline
19 & 0.02396 & 0.1976 & 0.421983 \tabularnewline
20 & -0.233227 & -1.9232 & 0.029319 \tabularnewline
21 & -0.2187 & -1.8034 & 0.037874 \tabularnewline
22 & -0.081476 & -0.6719 & 0.251971 \tabularnewline
23 & 0.18332 & 1.5117 & 0.067622 \tabularnewline
24 & 0.548563 & 4.5236 & 1.3e-05 \tabularnewline
25 & 0.128741 & 1.0616 & 0.146081 \tabularnewline
26 & -0.156409 & -1.2898 & 0.100749 \tabularnewline
27 & -0.225932 & -1.8631 & 0.033385 \tabularnewline
28 & -0.159365 & -1.3142 & 0.096605 \tabularnewline
29 & 0.020368 & 0.168 & 0.433558 \tabularnewline
30 & 0.066579 & 0.549 & 0.292393 \tabularnewline
31 & 0.004629 & 0.0382 & 0.484832 \tabularnewline
32 & -0.191386 & -1.5782 & 0.05958 \tabularnewline
33 & -0.14138 & -1.1658 & 0.123874 \tabularnewline
34 & -0.058442 & -0.4819 & 0.315703 \tabularnewline
35 & 0.127911 & 1.0548 & 0.147628 \tabularnewline
36 & 0.419888 & 3.4625 & 0.000465 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=159471&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]0.253408[/C][C]2.0897[/C][C]0.020196[/C][/ROW]
[ROW][C]2[/C][C]-0.195884[/C][C]-1.6153[/C][C]0.055438[/C][/ROW]
[ROW][C]3[/C][C]-0.275046[/C][C]-2.2681[/C][C]0.013252[/C][/ROW]
[ROW][C]4[/C][C]-0.255988[/C][C]-2.1109[/C][C]0.019229[/C][/ROW]
[ROW][C]5[/C][C]0.041332[/C][C]0.3408[/C][C]0.367141[/C][/ROW]
[ROW][C]6[/C][C]0.16977[/C][C]1.4[/C][C]0.083035[/C][/ROW]
[ROW][C]7[/C][C]0.047298[/C][C]0.39[/C][C]0.348867[/C][/ROW]
[ROW][C]8[/C][C]-0.244007[/C][C]-2.0121[/C][C]0.024085[/C][/ROW]
[ROW][C]9[/C][C]-0.272283[/C][C]-2.2453[/C][C]0.014002[/C][/ROW]
[ROW][C]10[/C][C]-0.148535[/C][C]-1.2248[/C][C]0.112429[/C][/ROW]
[ROW][C]11[/C][C]0.250157[/C][C]2.0628[/C][C]0.021475[/C][/ROW]
[ROW][C]12[/C][C]0.748754[/C][C]6.1744[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.172675[/C][C]1.4239[/C][C]0.079522[/C][/ROW]
[ROW][C]14[/C][C]-0.153451[/C][C]-1.2654[/C][C]0.105026[/C][/ROW]
[ROW][C]15[/C][C]-0.218898[/C][C]-1.8051[/C][C]0.037744[/C][/ROW]
[ROW][C]16[/C][C]-0.211745[/C][C]-1.7461[/C][C]0.042655[/C][/ROW]
[ROW][C]17[/C][C]0.015498[/C][C]0.1278[/C][C]0.449342[/C][/ROW]
[ROW][C]18[/C][C]0.098522[/C][C]0.8124[/C][C]0.209689[/C][/ROW]
[ROW][C]19[/C][C]0.02396[/C][C]0.1976[/C][C]0.421983[/C][/ROW]
[ROW][C]20[/C][C]-0.233227[/C][C]-1.9232[/C][C]0.029319[/C][/ROW]
[ROW][C]21[/C][C]-0.2187[/C][C]-1.8034[/C][C]0.037874[/C][/ROW]
[ROW][C]22[/C][C]-0.081476[/C][C]-0.6719[/C][C]0.251971[/C][/ROW]
[ROW][C]23[/C][C]0.18332[/C][C]1.5117[/C][C]0.067622[/C][/ROW]
[ROW][C]24[/C][C]0.548563[/C][C]4.5236[/C][C]1.3e-05[/C][/ROW]
[ROW][C]25[/C][C]0.128741[/C][C]1.0616[/C][C]0.146081[/C][/ROW]
[ROW][C]26[/C][C]-0.156409[/C][C]-1.2898[/C][C]0.100749[/C][/ROW]
[ROW][C]27[/C][C]-0.225932[/C][C]-1.8631[/C][C]0.033385[/C][/ROW]
[ROW][C]28[/C][C]-0.159365[/C][C]-1.3142[/C][C]0.096605[/C][/ROW]
[ROW][C]29[/C][C]0.020368[/C][C]0.168[/C][C]0.433558[/C][/ROW]
[ROW][C]30[/C][C]0.066579[/C][C]0.549[/C][C]0.292393[/C][/ROW]
[ROW][C]31[/C][C]0.004629[/C][C]0.0382[/C][C]0.484832[/C][/ROW]
[ROW][C]32[/C][C]-0.191386[/C][C]-1.5782[/C][C]0.05958[/C][/ROW]
[ROW][C]33[/C][C]-0.14138[/C][C]-1.1658[/C][C]0.123874[/C][/ROW]
[ROW][C]34[/C][C]-0.058442[/C][C]-0.4819[/C][C]0.315703[/C][/ROW]
[ROW][C]35[/C][C]0.127911[/C][C]1.0548[/C][C]0.147628[/C][/ROW]
[ROW][C]36[/C][C]0.419888[/C][C]3.4625[/C][C]0.000465[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=159471&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=159471&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	0.253408	2.0897	0.020196
2	-0.195884	-1.6153	0.055438
3	-0.275046	-2.2681	0.013252
4	-0.255988	-2.1109	0.019229
5	0.041332	0.3408	0.367141
6	0.16977	1.4	0.083035
7	0.047298	0.39	0.348867
8	-0.244007	-2.0121	0.024085
9	-0.272283	-2.2453	0.014002
10	-0.148535	-1.2248	0.112429
11	0.250157	2.0628	0.021475
12	0.748754	6.1744	0
13	0.172675	1.4239	0.079522
14	-0.153451	-1.2654	0.105026
15	-0.218898	-1.8051	0.037744
16	-0.211745	-1.7461	0.042655
17	0.015498	0.1278	0.449342
18	0.098522	0.8124	0.209689
19	0.02396	0.1976	0.421983
20	-0.233227	-1.9232	0.029319
21	-0.2187	-1.8034	0.037874
22	-0.081476	-0.6719	0.251971
23	0.18332	1.5117	0.067622
24	0.548563	4.5236	1.3e-05
25	0.128741	1.0616	0.146081
26	-0.156409	-1.2898	0.100749
27	-0.225932	-1.8631	0.033385
28	-0.159365	-1.3142	0.096605
29	0.020368	0.168	0.433558
30	0.066579	0.549	0.292393
31	0.004629	0.0382	0.484832
32	-0.191386	-1.5782	0.05958
33	-0.14138	-1.1658	0.123874
34	-0.058442	-0.4819	0.315703
35	0.127911	1.0548	0.147628
36	0.419888	3.4625	0.000465

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.253408	2.0897	0.020196
2	-0.277948	-2.292	0.012503
3	-0.163495	-1.3482	0.091031
4	-0.216631	-1.7864	0.039247
5	0.078559	0.6478	0.259643
6	0.003112	0.0257	0.489801
7	-0.071432	-0.589	0.278892
8	-0.292071	-2.4085	0.009368
9	-0.148571	-1.2251	0.112374
10	-0.195557	-1.6126	0.055731
11	0.181556	1.4972	0.069491
12	0.623205	5.1391	1e-06
13	-0.144886	-1.1948	0.118165
14	0.152188	1.255	0.106892
15	0.047882	0.3948	0.347095
16	0.060671	0.5003	0.309238
17	-0.080375	-0.6628	0.254853
18	-0.105224	-0.8677	0.194305
19	-0.010438	-0.0861	0.46583
20	-0.075509	-0.6227	0.267794
21	0.041465	0.3419	0.366729
22	-0.020809	-0.1716	0.432133
23	-0.117529	-0.9692	0.167948
24	0.027358	0.2256	0.411094
25	-0.013701	-0.113	0.455189
26	-0.13084	-1.0789	0.142214
27	-0.152821	-1.2602	0.105954
28	0.021851	0.1802	0.428771
29	-0.027496	-0.2267	0.410653
30	-0.027115	-0.2236	0.41187
31	-0.05274	-0.4349	0.332506
32	0.063146	0.5207	0.302129
33	0.060259	0.4969	0.310427
34	-0.066144	-0.5454	0.293618
35	-0.022997	-0.1896	0.425079
36	-0.010415	-0.0859	0.465905

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.253408 & 2.0897 & 0.020196 \tabularnewline
2 & -0.277948 & -2.292 & 0.012503 \tabularnewline
3 & -0.163495 & -1.3482 & 0.091031 \tabularnewline
4 & -0.216631 & -1.7864 & 0.039247 \tabularnewline
5 & 0.078559 & 0.6478 & 0.259643 \tabularnewline
6 & 0.003112 & 0.0257 & 0.489801 \tabularnewline
7 & -0.071432 & -0.589 & 0.278892 \tabularnewline
8 & -0.292071 & -2.4085 & 0.009368 \tabularnewline
9 & -0.148571 & -1.2251 & 0.112374 \tabularnewline
10 & -0.195557 & -1.6126 & 0.055731 \tabularnewline
11 & 0.181556 & 1.4972 & 0.069491 \tabularnewline
12 & 0.623205 & 5.1391 & 1e-06 \tabularnewline
13 & -0.144886 & -1.1948 & 0.118165 \tabularnewline
14 & 0.152188 & 1.255 & 0.106892 \tabularnewline
15 & 0.047882 & 0.3948 & 0.347095 \tabularnewline
16 & 0.060671 & 0.5003 & 0.309238 \tabularnewline
17 & -0.080375 & -0.6628 & 0.254853 \tabularnewline
18 & -0.105224 & -0.8677 & 0.194305 \tabularnewline
19 & -0.010438 & -0.0861 & 0.46583 \tabularnewline
20 & -0.075509 & -0.6227 & 0.267794 \tabularnewline
21 & 0.041465 & 0.3419 & 0.366729 \tabularnewline
22 & -0.020809 & -0.1716 & 0.432133 \tabularnewline
23 & -0.117529 & -0.9692 & 0.167948 \tabularnewline
24 & 0.027358 & 0.2256 & 0.411094 \tabularnewline
25 & -0.013701 & -0.113 & 0.455189 \tabularnewline
26 & -0.13084 & -1.0789 & 0.142214 \tabularnewline
27 & -0.152821 & -1.2602 & 0.105954 \tabularnewline
28 & 0.021851 & 0.1802 & 0.428771 \tabularnewline
29 & -0.027496 & -0.2267 & 0.410653 \tabularnewline
30 & -0.027115 & -0.2236 & 0.41187 \tabularnewline
31 & -0.05274 & -0.4349 & 0.332506 \tabularnewline
32 & 0.063146 & 0.5207 & 0.302129 \tabularnewline
33 & 0.060259 & 0.4969 & 0.310427 \tabularnewline
34 & -0.066144 & -0.5454 & 0.293618 \tabularnewline
35 & -0.022997 & -0.1896 & 0.425079 \tabularnewline
36 & -0.010415 & -0.0859 & 0.465905 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=159471&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]0.253408[/C][C]2.0897[/C][C]0.020196[/C][/ROW]
[ROW][C]2[/C][C]-0.277948[/C][C]-2.292[/C][C]0.012503[/C][/ROW]
[ROW][C]3[/C][C]-0.163495[/C][C]-1.3482[/C][C]0.091031[/C][/ROW]
[ROW][C]4[/C][C]-0.216631[/C][C]-1.7864[/C][C]0.039247[/C][/ROW]
[ROW][C]5[/C][C]0.078559[/C][C]0.6478[/C][C]0.259643[/C][/ROW]
[ROW][C]6[/C][C]0.003112[/C][C]0.0257[/C][C]0.489801[/C][/ROW]
[ROW][C]7[/C][C]-0.071432[/C][C]-0.589[/C][C]0.278892[/C][/ROW]
[ROW][C]8[/C][C]-0.292071[/C][C]-2.4085[/C][C]0.009368[/C][/ROW]
[ROW][C]9[/C][C]-0.148571[/C][C]-1.2251[/C][C]0.112374[/C][/ROW]
[ROW][C]10[/C][C]-0.195557[/C][C]-1.6126[/C][C]0.055731[/C][/ROW]
[ROW][C]11[/C][C]0.181556[/C][C]1.4972[/C][C]0.069491[/C][/ROW]
[ROW][C]12[/C][C]0.623205[/C][C]5.1391[/C][C]1e-06[/C][/ROW]
[ROW][C]13[/C][C]-0.144886[/C][C]-1.1948[/C][C]0.118165[/C][/ROW]
[ROW][C]14[/C][C]0.152188[/C][C]1.255[/C][C]0.106892[/C][/ROW]
[ROW][C]15[/C][C]0.047882[/C][C]0.3948[/C][C]0.347095[/C][/ROW]
[ROW][C]16[/C][C]0.060671[/C][C]0.5003[/C][C]0.309238[/C][/ROW]
[ROW][C]17[/C][C]-0.080375[/C][C]-0.6628[/C][C]0.254853[/C][/ROW]
[ROW][C]18[/C][C]-0.105224[/C][C]-0.8677[/C][C]0.194305[/C][/ROW]
[ROW][C]19[/C][C]-0.010438[/C][C]-0.0861[/C][C]0.46583[/C][/ROW]
[ROW][C]20[/C][C]-0.075509[/C][C]-0.6227[/C][C]0.267794[/C][/ROW]
[ROW][C]21[/C][C]0.041465[/C][C]0.3419[/C][C]0.366729[/C][/ROW]
[ROW][C]22[/C][C]-0.020809[/C][C]-0.1716[/C][C]0.432133[/C][/ROW]
[ROW][C]23[/C][C]-0.117529[/C][C]-0.9692[/C][C]0.167948[/C][/ROW]
[ROW][C]24[/C][C]0.027358[/C][C]0.2256[/C][C]0.411094[/C][/ROW]
[ROW][C]25[/C][C]-0.013701[/C][C]-0.113[/C][C]0.455189[/C][/ROW]
[ROW][C]26[/C][C]-0.13084[/C][C]-1.0789[/C][C]0.142214[/C][/ROW]
[ROW][C]27[/C][C]-0.152821[/C][C]-1.2602[/C][C]0.105954[/C][/ROW]
[ROW][C]28[/C][C]0.021851[/C][C]0.1802[/C][C]0.428771[/C][/ROW]
[ROW][C]29[/C][C]-0.027496[/C][C]-0.2267[/C][C]0.410653[/C][/ROW]
[ROW][C]30[/C][C]-0.027115[/C][C]-0.2236[/C][C]0.41187[/C][/ROW]
[ROW][C]31[/C][C]-0.05274[/C][C]-0.4349[/C][C]0.332506[/C][/ROW]
[ROW][C]32[/C][C]0.063146[/C][C]0.5207[/C][C]0.302129[/C][/ROW]
[ROW][C]33[/C][C]0.060259[/C][C]0.4969[/C][C]0.310427[/C][/ROW]
[ROW][C]34[/C][C]-0.066144[/C][C]-0.5454[/C][C]0.293618[/C][/ROW]
[ROW][C]35[/C][C]-0.022997[/C][C]-0.1896[/C][C]0.425079[/C][/ROW]
[ROW][C]36[/C][C]-0.010415[/C][C]-0.0859[/C][C]0.465905[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=159471&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=159471&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	0.253408	2.0897	0.020196
2	-0.277948	-2.292	0.012503
3	-0.163495	-1.3482	0.091031
4	-0.216631	-1.7864	0.039247
5	0.078559	0.6478	0.259643
6	0.003112	0.0257	0.489801
7	-0.071432	-0.589	0.278892
8	-0.292071	-2.4085	0.009368
9	-0.148571	-1.2251	0.112374
10	-0.195557	-1.6126	0.055731
11	0.181556	1.4972	0.069491
12	0.623205	5.1391	1e-06
13	-0.144886	-1.1948	0.118165
14	0.152188	1.255	0.106892
15	0.047882	0.3948	0.347095
16	0.060671	0.5003	0.309238
17	-0.080375	-0.6628	0.254853
18	-0.105224	-0.8677	0.194305
19	-0.010438	-0.0861	0.46583
20	-0.075509	-0.6227	0.267794
21	0.041465	0.3419	0.366729
22	-0.020809	-0.1716	0.432133
23	-0.117529	-0.9692	0.167948
24	0.027358	0.2256	0.411094
25	-0.013701	-0.113	0.455189
26	-0.13084	-1.0789	0.142214
27	-0.152821	-1.2602	0.105954
28	0.021851	0.1802	0.428771
29	-0.027496	-0.2267	0.410653
30	-0.027115	-0.2236	0.41187
31	-0.05274	-0.4349	0.332506
32	0.063146	0.5207	0.302129
33	0.060259	0.4969	0.310427
34	-0.066144	-0.5454	0.293618
35	-0.022997	-0.1896	0.425079
36	-0.010415	-0.0859	0.465905

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 = 1 ; par4 = 0 ; par5 = 12 ; 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)
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,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