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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationFri, 04 Dec 2009 05:13:18 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/04/t12599288582jbp6qlg0mpp3gr.htm/, Retrieved Sat, 27 Apr 2024 21:03:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63367, Retrieved Sat, 27 Apr 2024 21:03:33 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact124

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [(Partial) Autocorrelation Function] [Identifying Integ...] [2009-11-22 12:19:56] [b98453cac15ba1066b407e146608df68]
-    D        [(Partial) Autocorrelation Function] [] [2009-11-23 15:21:31] [5d885a68c2332cc44f6191ec94766bfa]
-   PD            [(Partial) Autocorrelation Function] [AC] [2009-12-04 12:13:18] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
564
581
597
587
536
524
537
536
533
528
516
502
506
518
534
528
478
469
490
493
508
517
514
510
527
542
565
555
499
511
526
532
549
561
557
566
588
620
626
620
573
573
574
580
590
593
597
595
612
628
629
621
569
567
573
584
589
591
595
594

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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=63367&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=63367&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63367&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.8905276.8980
20.7274375.63470
30.6186784.79236e-06
40.5755084.45791.8e-05
50.5761494.46281.8e-05
60.564024.36892.5e-05
70.5082623.9370.000109
80.4338573.36060.000678
90.3770912.92090.002456
100.3740522.89740.002623
110.4189093.24490.000962
120.42273.27420.000881
130.283492.19590.015988
140.1137650.88120.190859
15-0.003497-0.02710.489238
16-0.060835-0.47120.319595
17-0.073933-0.57270.284499
18-0.095085-0.73650.232141
19-0.148582-1.15090.127167
20-0.213378-1.65280.051796
21-0.25946-2.00980.024479
22-0.258604-2.00310.024843
23-0.220027-1.70430.046747
24-0.206544-1.59990.057439
25-0.289572-2.2430.014301
26-0.383031-2.96690.002157
27-0.433254-3.3560.000688
28-0.435794-3.37560.000648
29-0.40545-3.14060.001308
30-0.38224-2.96080.002195
31-0.373054-2.88970.00268
32-0.365992-2.8350.003119
33-0.353221-2.7360.004084
34-0.312569-2.42120.009256
35-0.247522-1.91730.029982
36-0.207444-1.60690.056669

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.890527 & 6.898 & 0 \tabularnewline
2 & 0.727437 & 5.6347 & 0 \tabularnewline
3 & 0.618678 & 4.7923 & 6e-06 \tabularnewline
4 & 0.575508 & 4.4579 & 1.8e-05 \tabularnewline
5 & 0.576149 & 4.4628 & 1.8e-05 \tabularnewline
6 & 0.56402 & 4.3689 & 2.5e-05 \tabularnewline
7 & 0.508262 & 3.937 & 0.000109 \tabularnewline
8 & 0.433857 & 3.3606 & 0.000678 \tabularnewline
9 & 0.377091 & 2.9209 & 0.002456 \tabularnewline
10 & 0.374052 & 2.8974 & 0.002623 \tabularnewline
11 & 0.418909 & 3.2449 & 0.000962 \tabularnewline
12 & 0.4227 & 3.2742 & 0.000881 \tabularnewline
13 & 0.28349 & 2.1959 & 0.015988 \tabularnewline
14 & 0.113765 & 0.8812 & 0.190859 \tabularnewline
15 & -0.003497 & -0.0271 & 0.489238 \tabularnewline
16 & -0.060835 & -0.4712 & 0.319595 \tabularnewline
17 & -0.073933 & -0.5727 & 0.284499 \tabularnewline
18 & -0.095085 & -0.7365 & 0.232141 \tabularnewline
19 & -0.148582 & -1.1509 & 0.127167 \tabularnewline
20 & -0.213378 & -1.6528 & 0.051796 \tabularnewline
21 & -0.25946 & -2.0098 & 0.024479 \tabularnewline
22 & -0.258604 & -2.0031 & 0.024843 \tabularnewline
23 & -0.220027 & -1.7043 & 0.046747 \tabularnewline
24 & -0.206544 & -1.5999 & 0.057439 \tabularnewline
25 & -0.289572 & -2.243 & 0.014301 \tabularnewline
26 & -0.383031 & -2.9669 & 0.002157 \tabularnewline
27 & -0.433254 & -3.356 & 0.000688 \tabularnewline
28 & -0.435794 & -3.3756 & 0.000648 \tabularnewline
29 & -0.40545 & -3.1406 & 0.001308 \tabularnewline
30 & -0.38224 & -2.9608 & 0.002195 \tabularnewline
31 & -0.373054 & -2.8897 & 0.00268 \tabularnewline
32 & -0.365992 & -2.835 & 0.003119 \tabularnewline
33 & -0.353221 & -2.736 & 0.004084 \tabularnewline
34 & -0.312569 & -2.4212 & 0.009256 \tabularnewline
35 & -0.247522 & -1.9173 & 0.029982 \tabularnewline
36 & -0.207444 & -1.6069 & 0.056669 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63367&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]0.890527[/C][C]6.898[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.727437[/C][C]5.6347[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.618678[/C][C]4.7923[/C][C]6e-06[/C][/ROW]
[ROW][C]4[/C][C]0.575508[/C][C]4.4579[/C][C]1.8e-05[/C][/ROW]
[ROW][C]5[/C][C]0.576149[/C][C]4.4628[/C][C]1.8e-05[/C][/ROW]
[ROW][C]6[/C][C]0.56402[/C][C]4.3689[/C][C]2.5e-05[/C][/ROW]
[ROW][C]7[/C][C]0.508262[/C][C]3.937[/C][C]0.000109[/C][/ROW]
[ROW][C]8[/C][C]0.433857[/C][C]3.3606[/C][C]0.000678[/C][/ROW]
[ROW][C]9[/C][C]0.377091[/C][C]2.9209[/C][C]0.002456[/C][/ROW]
[ROW][C]10[/C][C]0.374052[/C][C]2.8974[/C][C]0.002623[/C][/ROW]
[ROW][C]11[/C][C]0.418909[/C][C]3.2449[/C][C]0.000962[/C][/ROW]
[ROW][C]12[/C][C]0.4227[/C][C]3.2742[/C][C]0.000881[/C][/ROW]
[ROW][C]13[/C][C]0.28349[/C][C]2.1959[/C][C]0.015988[/C][/ROW]
[ROW][C]14[/C][C]0.113765[/C][C]0.8812[/C][C]0.190859[/C][/ROW]
[ROW][C]15[/C][C]-0.003497[/C][C]-0.0271[/C][C]0.489238[/C][/ROW]
[ROW][C]16[/C][C]-0.060835[/C][C]-0.4712[/C][C]0.319595[/C][/ROW]
[ROW][C]17[/C][C]-0.073933[/C][C]-0.5727[/C][C]0.284499[/C][/ROW]
[ROW][C]18[/C][C]-0.095085[/C][C]-0.7365[/C][C]0.232141[/C][/ROW]
[ROW][C]19[/C][C]-0.148582[/C][C]-1.1509[/C][C]0.127167[/C][/ROW]
[ROW][C]20[/C][C]-0.213378[/C][C]-1.6528[/C][C]0.051796[/C][/ROW]
[ROW][C]21[/C][C]-0.25946[/C][C]-2.0098[/C][C]0.024479[/C][/ROW]
[ROW][C]22[/C][C]-0.258604[/C][C]-2.0031[/C][C]0.024843[/C][/ROW]
[ROW][C]23[/C][C]-0.220027[/C][C]-1.7043[/C][C]0.046747[/C][/ROW]
[ROW][C]24[/C][C]-0.206544[/C][C]-1.5999[/C][C]0.057439[/C][/ROW]
[ROW][C]25[/C][C]-0.289572[/C][C]-2.243[/C][C]0.014301[/C][/ROW]
[ROW][C]26[/C][C]-0.383031[/C][C]-2.9669[/C][C]0.002157[/C][/ROW]
[ROW][C]27[/C][C]-0.433254[/C][C]-3.356[/C][C]0.000688[/C][/ROW]
[ROW][C]28[/C][C]-0.435794[/C][C]-3.3756[/C][C]0.000648[/C][/ROW]
[ROW][C]29[/C][C]-0.40545[/C][C]-3.1406[/C][C]0.001308[/C][/ROW]
[ROW][C]30[/C][C]-0.38224[/C][C]-2.9608[/C][C]0.002195[/C][/ROW]
[ROW][C]31[/C][C]-0.373054[/C][C]-2.8897[/C][C]0.00268[/C][/ROW]
[ROW][C]32[/C][C]-0.365992[/C][C]-2.835[/C][C]0.003119[/C][/ROW]
[ROW][C]33[/C][C]-0.353221[/C][C]-2.736[/C][C]0.004084[/C][/ROW]
[ROW][C]34[/C][C]-0.312569[/C][C]-2.4212[/C][C]0.009256[/C][/ROW]
[ROW][C]35[/C][C]-0.247522[/C][C]-1.9173[/C][C]0.029982[/C][/ROW]
[ROW][C]36[/C][C]-0.207444[/C][C]-1.6069[/C][C]0.056669[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63367&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63367&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.8905276.8980
20.7274375.63470
30.6186784.79236e-06
40.5755084.45791.8e-05
50.5761494.46281.8e-05
60.564024.36892.5e-05
70.5082623.9370.000109
80.4338573.36060.000678
90.3770912.92090.002456
100.3740522.89740.002623
110.4189093.24490.000962
120.42273.27420.000881
130.283492.19590.015988
140.1137650.88120.190859
15-0.003497-0.02710.489238
16-0.060835-0.47120.319595
17-0.073933-0.57270.284499
18-0.095085-0.73650.232141
19-0.148582-1.15090.127167
20-0.213378-1.65280.051796
21-0.25946-2.00980.024479
22-0.258604-2.00310.024843
23-0.220027-1.70430.046747
24-0.206544-1.59990.057439
25-0.289572-2.2430.014301
26-0.383031-2.96690.002157
27-0.433254-3.3560.000688
28-0.435794-3.37560.000648
29-0.40545-3.14060.001308
30-0.38224-2.96080.002195
31-0.373054-2.88970.00268
32-0.365992-2.8350.003119
33-0.353221-2.7360.004084
34-0.312569-2.42120.009256
35-0.247522-1.91730.029982
36-0.207444-1.60690.056669






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8905276.8980
2-0.316971-2.45530.008497
30.2568251.98940.025613
40.1180880.91470.182005
50.1448731.12220.133128
6-0.062562-0.48460.314862
7-0.078977-0.61180.271506
8-0.006678-0.05170.479458
90.0227280.17610.430424
100.1587191.22940.111854
110.1323751.02540.154652
12-0.203496-1.57630.06011
13-0.58464-4.52861.4e-05
140.107320.83130.204552
15-0.069475-0.53810.296233
16-0.095359-0.73870.2315
17-0.062921-0.48740.313882
18-0.031111-0.2410.405194
190.0045050.03490.48614
200.0086170.06670.473502
210.0649610.50320.308339
22-0.032871-0.25460.399944
23-0.020592-0.15950.436904
240.0715380.55410.290773
25-0.056733-0.43940.330958
260.0827220.64080.262059
27-0.068936-0.5340.297665
280.0115040.08910.464647
29-0.061511-0.47650.317737
300.0296820.22990.40947
310.105080.81390.209448
32-0.002725-0.02110.491616
33-0.050239-0.38910.349272
34-0.014635-0.11340.455062
350.0441730.34220.366713
36-0.061476-0.47620.317834

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.890527 & 6.898 & 0 \tabularnewline
2 & -0.316971 & -2.4553 & 0.008497 \tabularnewline
3 & 0.256825 & 1.9894 & 0.025613 \tabularnewline
4 & 0.118088 & 0.9147 & 0.182005 \tabularnewline
5 & 0.144873 & 1.1222 & 0.133128 \tabularnewline
6 & -0.062562 & -0.4846 & 0.314862 \tabularnewline
7 & -0.078977 & -0.6118 & 0.271506 \tabularnewline
8 & -0.006678 & -0.0517 & 0.479458 \tabularnewline
9 & 0.022728 & 0.1761 & 0.430424 \tabularnewline
10 & 0.158719 & 1.2294 & 0.111854 \tabularnewline
11 & 0.132375 & 1.0254 & 0.154652 \tabularnewline
12 & -0.203496 & -1.5763 & 0.06011 \tabularnewline
13 & -0.58464 & -4.5286 & 1.4e-05 \tabularnewline
14 & 0.10732 & 0.8313 & 0.204552 \tabularnewline
15 & -0.069475 & -0.5381 & 0.296233 \tabularnewline
16 & -0.095359 & -0.7387 & 0.2315 \tabularnewline
17 & -0.062921 & -0.4874 & 0.313882 \tabularnewline
18 & -0.031111 & -0.241 & 0.405194 \tabularnewline
19 & 0.004505 & 0.0349 & 0.48614 \tabularnewline
20 & 0.008617 & 0.0667 & 0.473502 \tabularnewline
21 & 0.064961 & 0.5032 & 0.308339 \tabularnewline
22 & -0.032871 & -0.2546 & 0.399944 \tabularnewline
23 & -0.020592 & -0.1595 & 0.436904 \tabularnewline
24 & 0.071538 & 0.5541 & 0.290773 \tabularnewline
25 & -0.056733 & -0.4394 & 0.330958 \tabularnewline
26 & 0.082722 & 0.6408 & 0.262059 \tabularnewline
27 & -0.068936 & -0.534 & 0.297665 \tabularnewline
28 & 0.011504 & 0.0891 & 0.464647 \tabularnewline
29 & -0.061511 & -0.4765 & 0.317737 \tabularnewline
30 & 0.029682 & 0.2299 & 0.40947 \tabularnewline
31 & 0.10508 & 0.8139 & 0.209448 \tabularnewline
32 & -0.002725 & -0.0211 & 0.491616 \tabularnewline
33 & -0.050239 & -0.3891 & 0.349272 \tabularnewline
34 & -0.014635 & -0.1134 & 0.455062 \tabularnewline
35 & 0.044173 & 0.3422 & 0.366713 \tabularnewline
36 & -0.061476 & -0.4762 & 0.317834 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63367&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]0.890527[/C][C]6.898[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.316971[/C][C]-2.4553[/C][C]0.008497[/C][/ROW]
[ROW][C]3[/C][C]0.256825[/C][C]1.9894[/C][C]0.025613[/C][/ROW]
[ROW][C]4[/C][C]0.118088[/C][C]0.9147[/C][C]0.182005[/C][/ROW]
[ROW][C]5[/C][C]0.144873[/C][C]1.1222[/C][C]0.133128[/C][/ROW]
[ROW][C]6[/C][C]-0.062562[/C][C]-0.4846[/C][C]0.314862[/C][/ROW]
[ROW][C]7[/C][C]-0.078977[/C][C]-0.6118[/C][C]0.271506[/C][/ROW]
[ROW][C]8[/C][C]-0.006678[/C][C]-0.0517[/C][C]0.479458[/C][/ROW]
[ROW][C]9[/C][C]0.022728[/C][C]0.1761[/C][C]0.430424[/C][/ROW]
[ROW][C]10[/C][C]0.158719[/C][C]1.2294[/C][C]0.111854[/C][/ROW]
[ROW][C]11[/C][C]0.132375[/C][C]1.0254[/C][C]0.154652[/C][/ROW]
[ROW][C]12[/C][C]-0.203496[/C][C]-1.5763[/C][C]0.06011[/C][/ROW]
[ROW][C]13[/C][C]-0.58464[/C][C]-4.5286[/C][C]1.4e-05[/C][/ROW]
[ROW][C]14[/C][C]0.10732[/C][C]0.8313[/C][C]0.204552[/C][/ROW]
[ROW][C]15[/C][C]-0.069475[/C][C]-0.5381[/C][C]0.296233[/C][/ROW]
[ROW][C]16[/C][C]-0.095359[/C][C]-0.7387[/C][C]0.2315[/C][/ROW]
[ROW][C]17[/C][C]-0.062921[/C][C]-0.4874[/C][C]0.313882[/C][/ROW]
[ROW][C]18[/C][C]-0.031111[/C][C]-0.241[/C][C]0.405194[/C][/ROW]
[ROW][C]19[/C][C]0.004505[/C][C]0.0349[/C][C]0.48614[/C][/ROW]
[ROW][C]20[/C][C]0.008617[/C][C]0.0667[/C][C]0.473502[/C][/ROW]
[ROW][C]21[/C][C]0.064961[/C][C]0.5032[/C][C]0.308339[/C][/ROW]
[ROW][C]22[/C][C]-0.032871[/C][C]-0.2546[/C][C]0.399944[/C][/ROW]
[ROW][C]23[/C][C]-0.020592[/C][C]-0.1595[/C][C]0.436904[/C][/ROW]
[ROW][C]24[/C][C]0.071538[/C][C]0.5541[/C][C]0.290773[/C][/ROW]
[ROW][C]25[/C][C]-0.056733[/C][C]-0.4394[/C][C]0.330958[/C][/ROW]
[ROW][C]26[/C][C]0.082722[/C][C]0.6408[/C][C]0.262059[/C][/ROW]
[ROW][C]27[/C][C]-0.068936[/C][C]-0.534[/C][C]0.297665[/C][/ROW]
[ROW][C]28[/C][C]0.011504[/C][C]0.0891[/C][C]0.464647[/C][/ROW]
[ROW][C]29[/C][C]-0.061511[/C][C]-0.4765[/C][C]0.317737[/C][/ROW]
[ROW][C]30[/C][C]0.029682[/C][C]0.2299[/C][C]0.40947[/C][/ROW]
[ROW][C]31[/C][C]0.10508[/C][C]0.8139[/C][C]0.209448[/C][/ROW]
[ROW][C]32[/C][C]-0.002725[/C][C]-0.0211[/C][C]0.491616[/C][/ROW]
[ROW][C]33[/C][C]-0.050239[/C][C]-0.3891[/C][C]0.349272[/C][/ROW]
[ROW][C]34[/C][C]-0.014635[/C][C]-0.1134[/C][C]0.455062[/C][/ROW]
[ROW][C]35[/C][C]0.044173[/C][C]0.3422[/C][C]0.366713[/C][/ROW]
[ROW][C]36[/C][C]-0.061476[/C][C]-0.4762[/C][C]0.317834[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63367&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63367&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8905276.8980
2-0.316971-2.45530.008497
30.2568251.98940.025613
40.1180880.91470.182005
50.1448731.12220.133128
6-0.062562-0.48460.314862
7-0.078977-0.61180.271506
8-0.006678-0.05170.479458
90.0227280.17610.430424
100.1587191.22940.111854
110.1323751.02540.154652
12-0.203496-1.57630.06011
13-0.58464-4.52861.4e-05
140.107320.83130.204552
15-0.069475-0.53810.296233
16-0.095359-0.73870.2315
17-0.062921-0.48740.313882
18-0.031111-0.2410.405194
190.0045050.03490.48614
200.0086170.06670.473502
210.0649610.50320.308339
22-0.032871-0.25460.399944
23-0.020592-0.15950.436904
240.0715380.55410.290773
25-0.056733-0.43940.330958
260.0827220.64080.262059
27-0.068936-0.5340.297665
280.0115040.08910.464647
29-0.061511-0.47650.317737
300.0296820.22990.40947
310.105080.81390.209448
32-0.002725-0.02110.491616
33-0.050239-0.38910.349272
34-0.014635-0.11340.455062
350.0441730.34220.366713
36-0.061476-0.47620.317834


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
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 (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='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
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')