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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 computationTue, 29 Dec 2009 02:25:55 -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/29/t1262078796fslap8deo3wzijy.htm/, Retrieved Fri, 03 May 2024 04:34:29 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=71068, Retrieved Fri, 03 May 2024 04:34:29 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact151

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 12:16:10] [b98453cac15ba1066b407e146608df68]
- R  D        [(Partial) Autocorrelation Function] [] [2009-11-27 16:22:38] [9b30bff5dd5a100f8196daf92e735633]
-   PD            [(Partial) Autocorrelation Function] [] [2009-12-29 09:25:55] [54e293c1fb7c46e2abc5c1dda68d8adb] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
577992
565464
547344
554788
562325
560854
555332
543599
536662
542722
593530
610763
612613
611324
594167
595454
590865
589379
584428
573100
567456
569028
620735
628884
628232
612117
595404
597141
593408
590072
579799
574205
572775
572942
619567
625809
619916
587625
565742
557274
560576
548854
531673
525919
511038
498662
555362
564591
541657
527070
509846
514258
516922
507561
492622
490243
469357
477580
528379
533590
517945
506174
501866
516141
528222
532638
536322
536535
523597
536214
586570
596594
580523

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71068&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]2 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=71068&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71068&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.1529811.1850.120348
20.2317991.79550.038804
30.2704412.09480.020208
40.198941.5410.064289
50.1115970.86440.195398
60.1607231.2450.108994
70.0629060.48730.313923
80.1540711.19340.118699
90.1008180.78090.218955
10-0.064556-0.50010.309434
110.2827012.18980.016219
12-0.086675-0.67140.252278
13-0.004579-0.03550.485911
140.1864011.44390.076991
150.0457650.35450.362105
16-0.003032-0.02350.490671
170.0510520.39540.346957
18-0.03982-0.30840.379406
190.0701720.54350.294384
20-0.019994-0.15490.438722
21-0.125146-0.96940.168124
220.0110880.08590.46592
23-0.067788-0.52510.30073
24-0.231482-1.7930.039003
25-0.101582-0.78680.217234
26-0.165599-1.28270.10226
27-0.154178-1.19430.118538
28-0.150559-1.16620.12407
29-0.077059-0.59690.27641
30-0.122644-0.950.172963
31-0.078863-0.61090.271797
32-0.130361-1.00980.15833
330.0060870.04710.481277
34-0.077431-0.59980.275456
35-0.092288-0.71490.238734
36-0.024885-0.19280.4239

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.152981 & 1.185 & 0.120348 \tabularnewline
2 & 0.231799 & 1.7955 & 0.038804 \tabularnewline
3 & 0.270441 & 2.0948 & 0.020208 \tabularnewline
4 & 0.19894 & 1.541 & 0.064289 \tabularnewline
5 & 0.111597 & 0.8644 & 0.195398 \tabularnewline
6 & 0.160723 & 1.245 & 0.108994 \tabularnewline
7 & 0.062906 & 0.4873 & 0.313923 \tabularnewline
8 & 0.154071 & 1.1934 & 0.118699 \tabularnewline
9 & 0.100818 & 0.7809 & 0.218955 \tabularnewline
10 & -0.064556 & -0.5001 & 0.309434 \tabularnewline
11 & 0.282701 & 2.1898 & 0.016219 \tabularnewline
12 & -0.086675 & -0.6714 & 0.252278 \tabularnewline
13 & -0.004579 & -0.0355 & 0.485911 \tabularnewline
14 & 0.186401 & 1.4439 & 0.076991 \tabularnewline
15 & 0.045765 & 0.3545 & 0.362105 \tabularnewline
16 & -0.003032 & -0.0235 & 0.490671 \tabularnewline
17 & 0.051052 & 0.3954 & 0.346957 \tabularnewline
18 & -0.03982 & -0.3084 & 0.379406 \tabularnewline
19 & 0.070172 & 0.5435 & 0.294384 \tabularnewline
20 & -0.019994 & -0.1549 & 0.438722 \tabularnewline
21 & -0.125146 & -0.9694 & 0.168124 \tabularnewline
22 & 0.011088 & 0.0859 & 0.46592 \tabularnewline
23 & -0.067788 & -0.5251 & 0.30073 \tabularnewline
24 & -0.231482 & -1.793 & 0.039003 \tabularnewline
25 & -0.101582 & -0.7868 & 0.217234 \tabularnewline
26 & -0.165599 & -1.2827 & 0.10226 \tabularnewline
27 & -0.154178 & -1.1943 & 0.118538 \tabularnewline
28 & -0.150559 & -1.1662 & 0.12407 \tabularnewline
29 & -0.077059 & -0.5969 & 0.27641 \tabularnewline
30 & -0.122644 & -0.95 & 0.172963 \tabularnewline
31 & -0.078863 & -0.6109 & 0.271797 \tabularnewline
32 & -0.130361 & -1.0098 & 0.15833 \tabularnewline
33 & 0.006087 & 0.0471 & 0.481277 \tabularnewline
34 & -0.077431 & -0.5998 & 0.275456 \tabularnewline
35 & -0.092288 & -0.7149 & 0.238734 \tabularnewline
36 & -0.024885 & -0.1928 & 0.4239 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71068&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]0.152981[/C][C]1.185[/C][C]0.120348[/C][/ROW]
[ROW][C]2[/C][C]0.231799[/C][C]1.7955[/C][C]0.038804[/C][/ROW]
[ROW][C]3[/C][C]0.270441[/C][C]2.0948[/C][C]0.020208[/C][/ROW]
[ROW][C]4[/C][C]0.19894[/C][C]1.541[/C][C]0.064289[/C][/ROW]
[ROW][C]5[/C][C]0.111597[/C][C]0.8644[/C][C]0.195398[/C][/ROW]
[ROW][C]6[/C][C]0.160723[/C][C]1.245[/C][C]0.108994[/C][/ROW]
[ROW][C]7[/C][C]0.062906[/C][C]0.4873[/C][C]0.313923[/C][/ROW]
[ROW][C]8[/C][C]0.154071[/C][C]1.1934[/C][C]0.118699[/C][/ROW]
[ROW][C]9[/C][C]0.100818[/C][C]0.7809[/C][C]0.218955[/C][/ROW]
[ROW][C]10[/C][C]-0.064556[/C][C]-0.5001[/C][C]0.309434[/C][/ROW]
[ROW][C]11[/C][C]0.282701[/C][C]2.1898[/C][C]0.016219[/C][/ROW]
[ROW][C]12[/C][C]-0.086675[/C][C]-0.6714[/C][C]0.252278[/C][/ROW]
[ROW][C]13[/C][C]-0.004579[/C][C]-0.0355[/C][C]0.485911[/C][/ROW]
[ROW][C]14[/C][C]0.186401[/C][C]1.4439[/C][C]0.076991[/C][/ROW]
[ROW][C]15[/C][C]0.045765[/C][C]0.3545[/C][C]0.362105[/C][/ROW]
[ROW][C]16[/C][C]-0.003032[/C][C]-0.0235[/C][C]0.490671[/C][/ROW]
[ROW][C]17[/C][C]0.051052[/C][C]0.3954[/C][C]0.346957[/C][/ROW]
[ROW][C]18[/C][C]-0.03982[/C][C]-0.3084[/C][C]0.379406[/C][/ROW]
[ROW][C]19[/C][C]0.070172[/C][C]0.5435[/C][C]0.294384[/C][/ROW]
[ROW][C]20[/C][C]-0.019994[/C][C]-0.1549[/C][C]0.438722[/C][/ROW]
[ROW][C]21[/C][C]-0.125146[/C][C]-0.9694[/C][C]0.168124[/C][/ROW]
[ROW][C]22[/C][C]0.011088[/C][C]0.0859[/C][C]0.46592[/C][/ROW]
[ROW][C]23[/C][C]-0.067788[/C][C]-0.5251[/C][C]0.30073[/C][/ROW]
[ROW][C]24[/C][C]-0.231482[/C][C]-1.793[/C][C]0.039003[/C][/ROW]
[ROW][C]25[/C][C]-0.101582[/C][C]-0.7868[/C][C]0.217234[/C][/ROW]
[ROW][C]26[/C][C]-0.165599[/C][C]-1.2827[/C][C]0.10226[/C][/ROW]
[ROW][C]27[/C][C]-0.154178[/C][C]-1.1943[/C][C]0.118538[/C][/ROW]
[ROW][C]28[/C][C]-0.150559[/C][C]-1.1662[/C][C]0.12407[/C][/ROW]
[ROW][C]29[/C][C]-0.077059[/C][C]-0.5969[/C][C]0.27641[/C][/ROW]
[ROW][C]30[/C][C]-0.122644[/C][C]-0.95[/C][C]0.172963[/C][/ROW]
[ROW][C]31[/C][C]-0.078863[/C][C]-0.6109[/C][C]0.271797[/C][/ROW]
[ROW][C]32[/C][C]-0.130361[/C][C]-1.0098[/C][C]0.15833[/C][/ROW]
[ROW][C]33[/C][C]0.006087[/C][C]0.0471[/C][C]0.481277[/C][/ROW]
[ROW][C]34[/C][C]-0.077431[/C][C]-0.5998[/C][C]0.275456[/C][/ROW]
[ROW][C]35[/C][C]-0.092288[/C][C]-0.7149[/C][C]0.238734[/C][/ROW]
[ROW][C]36[/C][C]-0.024885[/C][C]-0.1928[/C][C]0.4239[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71068&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71068&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
10.1529811.1850.120348
20.2317991.79550.038804
30.2704412.09480.020208
40.198941.5410.064289
50.1115970.86440.195398
60.1607231.2450.108994
70.0629060.48730.313923
80.1540711.19340.118699
90.1008180.78090.218955
10-0.064556-0.50010.309434
110.2827012.18980.016219
12-0.086675-0.67140.252278
13-0.004579-0.03550.485911
140.1864011.44390.076991
150.0457650.35450.362105
16-0.003032-0.02350.490671
170.0510520.39540.346957
18-0.03982-0.30840.379406
190.0701720.54350.294384
20-0.019994-0.15490.438722
21-0.125146-0.96940.168124
220.0110880.08590.46592
23-0.067788-0.52510.30073
24-0.231482-1.7930.039003
25-0.101582-0.78680.217234
26-0.165599-1.28270.10226
27-0.154178-1.19430.118538
28-0.150559-1.16620.12407
29-0.077059-0.59690.27641
30-0.122644-0.950.172963
31-0.078863-0.61090.271797
32-0.130361-1.00980.15833
330.0060870.04710.481277
34-0.077431-0.59980.275456
35-0.092288-0.71490.238734
36-0.024885-0.19280.4239






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1529811.1850.120348
20.213391.65290.051786
30.2251861.74430.043115
40.1150020.89080.188297
5-0.011547-0.08940.464514
60.0434340.33640.368856
7-0.042877-0.33210.370476
80.0868450.67270.251861
90.0351650.27240.393131
10-0.159292-1.23390.111031
110.2610252.02190.023827
12-0.191462-1.48310.071647
13-0.037164-0.28790.387218
140.1876751.45370.075616
15-0.022338-0.1730.431604
16-0.002707-0.0210.49167
17-0.072617-0.56250.287939
18-0.057263-0.44360.32948
190.0726850.5630.287761
20-0.084321-0.65310.258079
21-0.033664-0.26080.397584
22-0.110362-0.85490.198015
230.0162130.12560.450241
24-0.162849-1.26140.10602
25-0.161016-1.24720.108582
260.0131160.10160.459708
27-0.01114-0.08630.465761
28-0.07251-0.56170.28822
290.1197810.92780.178609
30-0.097528-0.75540.226468
310.0556990.43140.333847
320.0125570.09730.461421
330.0584310.45260.326233
34-0.045205-0.35020.363723
350.0393430.30470.380807
360.0273040.21150.416609

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.152981 & 1.185 & 0.120348 \tabularnewline
2 & 0.21339 & 1.6529 & 0.051786 \tabularnewline
3 & 0.225186 & 1.7443 & 0.043115 \tabularnewline
4 & 0.115002 & 0.8908 & 0.188297 \tabularnewline
5 & -0.011547 & -0.0894 & 0.464514 \tabularnewline
6 & 0.043434 & 0.3364 & 0.368856 \tabularnewline
7 & -0.042877 & -0.3321 & 0.370476 \tabularnewline
8 & 0.086845 & 0.6727 & 0.251861 \tabularnewline
9 & 0.035165 & 0.2724 & 0.393131 \tabularnewline
10 & -0.159292 & -1.2339 & 0.111031 \tabularnewline
11 & 0.261025 & 2.0219 & 0.023827 \tabularnewline
12 & -0.191462 & -1.4831 & 0.071647 \tabularnewline
13 & -0.037164 & -0.2879 & 0.387218 \tabularnewline
14 & 0.187675 & 1.4537 & 0.075616 \tabularnewline
15 & -0.022338 & -0.173 & 0.431604 \tabularnewline
16 & -0.002707 & -0.021 & 0.49167 \tabularnewline
17 & -0.072617 & -0.5625 & 0.287939 \tabularnewline
18 & -0.057263 & -0.4436 & 0.32948 \tabularnewline
19 & 0.072685 & 0.563 & 0.287761 \tabularnewline
20 & -0.084321 & -0.6531 & 0.258079 \tabularnewline
21 & -0.033664 & -0.2608 & 0.397584 \tabularnewline
22 & -0.110362 & -0.8549 & 0.198015 \tabularnewline
23 & 0.016213 & 0.1256 & 0.450241 \tabularnewline
24 & -0.162849 & -1.2614 & 0.10602 \tabularnewline
25 & -0.161016 & -1.2472 & 0.108582 \tabularnewline
26 & 0.013116 & 0.1016 & 0.459708 \tabularnewline
27 & -0.01114 & -0.0863 & 0.465761 \tabularnewline
28 & -0.07251 & -0.5617 & 0.28822 \tabularnewline
29 & 0.119781 & 0.9278 & 0.178609 \tabularnewline
30 & -0.097528 & -0.7554 & 0.226468 \tabularnewline
31 & 0.055699 & 0.4314 & 0.333847 \tabularnewline
32 & 0.012557 & 0.0973 & 0.461421 \tabularnewline
33 & 0.058431 & 0.4526 & 0.326233 \tabularnewline
34 & -0.045205 & -0.3502 & 0.363723 \tabularnewline
35 & 0.039343 & 0.3047 & 0.380807 \tabularnewline
36 & 0.027304 & 0.2115 & 0.416609 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71068&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]0.152981[/C][C]1.185[/C][C]0.120348[/C][/ROW]
[ROW][C]2[/C][C]0.21339[/C][C]1.6529[/C][C]0.051786[/C][/ROW]
[ROW][C]3[/C][C]0.225186[/C][C]1.7443[/C][C]0.043115[/C][/ROW]
[ROW][C]4[/C][C]0.115002[/C][C]0.8908[/C][C]0.188297[/C][/ROW]
[ROW][C]5[/C][C]-0.011547[/C][C]-0.0894[/C][C]0.464514[/C][/ROW]
[ROW][C]6[/C][C]0.043434[/C][C]0.3364[/C][C]0.368856[/C][/ROW]
[ROW][C]7[/C][C]-0.042877[/C][C]-0.3321[/C][C]0.370476[/C][/ROW]
[ROW][C]8[/C][C]0.086845[/C][C]0.6727[/C][C]0.251861[/C][/ROW]
[ROW][C]9[/C][C]0.035165[/C][C]0.2724[/C][C]0.393131[/C][/ROW]
[ROW][C]10[/C][C]-0.159292[/C][C]-1.2339[/C][C]0.111031[/C][/ROW]
[ROW][C]11[/C][C]0.261025[/C][C]2.0219[/C][C]0.023827[/C][/ROW]
[ROW][C]12[/C][C]-0.191462[/C][C]-1.4831[/C][C]0.071647[/C][/ROW]
[ROW][C]13[/C][C]-0.037164[/C][C]-0.2879[/C][C]0.387218[/C][/ROW]
[ROW][C]14[/C][C]0.187675[/C][C]1.4537[/C][C]0.075616[/C][/ROW]
[ROW][C]15[/C][C]-0.022338[/C][C]-0.173[/C][C]0.431604[/C][/ROW]
[ROW][C]16[/C][C]-0.002707[/C][C]-0.021[/C][C]0.49167[/C][/ROW]
[ROW][C]17[/C][C]-0.072617[/C][C]-0.5625[/C][C]0.287939[/C][/ROW]
[ROW][C]18[/C][C]-0.057263[/C][C]-0.4436[/C][C]0.32948[/C][/ROW]
[ROW][C]19[/C][C]0.072685[/C][C]0.563[/C][C]0.287761[/C][/ROW]
[ROW][C]20[/C][C]-0.084321[/C][C]-0.6531[/C][C]0.258079[/C][/ROW]
[ROW][C]21[/C][C]-0.033664[/C][C]-0.2608[/C][C]0.397584[/C][/ROW]
[ROW][C]22[/C][C]-0.110362[/C][C]-0.8549[/C][C]0.198015[/C][/ROW]
[ROW][C]23[/C][C]0.016213[/C][C]0.1256[/C][C]0.450241[/C][/ROW]
[ROW][C]24[/C][C]-0.162849[/C][C]-1.2614[/C][C]0.10602[/C][/ROW]
[ROW][C]25[/C][C]-0.161016[/C][C]-1.2472[/C][C]0.108582[/C][/ROW]
[ROW][C]26[/C][C]0.013116[/C][C]0.1016[/C][C]0.459708[/C][/ROW]
[ROW][C]27[/C][C]-0.01114[/C][C]-0.0863[/C][C]0.465761[/C][/ROW]
[ROW][C]28[/C][C]-0.07251[/C][C]-0.5617[/C][C]0.28822[/C][/ROW]
[ROW][C]29[/C][C]0.119781[/C][C]0.9278[/C][C]0.178609[/C][/ROW]
[ROW][C]30[/C][C]-0.097528[/C][C]-0.7554[/C][C]0.226468[/C][/ROW]
[ROW][C]31[/C][C]0.055699[/C][C]0.4314[/C][C]0.333847[/C][/ROW]
[ROW][C]32[/C][C]0.012557[/C][C]0.0973[/C][C]0.461421[/C][/ROW]
[ROW][C]33[/C][C]0.058431[/C][C]0.4526[/C][C]0.326233[/C][/ROW]
[ROW][C]34[/C][C]-0.045205[/C][C]-0.3502[/C][C]0.363723[/C][/ROW]
[ROW][C]35[/C][C]0.039343[/C][C]0.3047[/C][C]0.380807[/C][/ROW]
[ROW][C]36[/C][C]0.027304[/C][C]0.2115[/C][C]0.416609[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71068&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71068&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
10.1529811.1850.120348
20.213391.65290.051786
30.2251861.74430.043115
40.1150020.89080.188297
5-0.011547-0.08940.464514
60.0434340.33640.368856
7-0.042877-0.33210.370476
80.0868450.67270.251861
90.0351650.27240.393131
10-0.159292-1.23390.111031
110.2610252.02190.023827
12-0.191462-1.48310.071647
13-0.037164-0.28790.387218
140.1876751.45370.075616
15-0.022338-0.1730.431604
16-0.002707-0.0210.49167
17-0.072617-0.56250.287939
18-0.057263-0.44360.32948
190.0726850.5630.287761
20-0.084321-0.65310.258079
21-0.033664-0.26080.397584
22-0.110362-0.85490.198015
230.0162130.12560.450241
24-0.162849-1.26140.10602
25-0.161016-1.24720.108582
260.0131160.10160.459708
27-0.01114-0.08630.465761
28-0.07251-0.56170.28822
290.1197810.92780.178609
30-0.097528-0.75540.226468
310.0556990.43140.333847
320.0125570.09730.461421
330.0584310.45260.326233
34-0.045205-0.35020.363723
350.0393430.30470.380807
360.0273040.21150.416609


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; 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')