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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 computationThu, 03 Dec 2009 10:41:08 -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/03/t1259862148u36wj50sc3ksoe4.htm/, Retrieved Thu, 25 Apr 2024 10:13:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62971, Retrieved Thu, 25 Apr 2024 10:13:46 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact119

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]
-   PD        [(Partial) Autocorrelation Function] [ACF (d=0, D=1)] [2009-11-27 10:14:21] [f7fc9270f813d017f9fa5b506fdc7682]
-   P             [(Partial) Autocorrelation Function] [WS8 - review ] [2009-12-03 17:41:08] [d9efc2d105d810fc0b0ac636e31105d1] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
593530
610943
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 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=62971&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=62971&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62971&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
10.1431051.01190.158228
20.2596151.83580.036172
30.328122.32020.012227
40.1987341.40530.083063
50.1082010.76510.223905
60.1649671.16650.124474
70.0369570.26130.397457
80.1510031.06780.14538
90.047360.33490.369556
10-0.060647-0.42880.33494
110.3247592.29640.01294
12-0.050971-0.36040.360025
13-0.017444-0.12330.451164
140.181571.28390.102548
150.0517610.3660.357952
160.0074820.05290.47901
170.0676050.4780.317352
18-0.093383-0.66030.25604
190.0606210.42870.335007
20-0.053773-0.38020.352691
21-0.193404-1.36760.088781
22-0.026617-0.18820.425735
23-0.117442-0.83040.205119
24-0.217812-1.54020.064913
25-0.096153-0.67990.249851
26-0.189619-1.34080.093022
27-0.225935-1.59760.058217
28-0.162234-1.14720.128386
29-0.129118-0.9130.182812
30-0.105131-0.74340.230363
31-0.02787-0.19710.422286
32-0.156979-1.110.136152
330.0079510.05620.477695
34-0.042908-0.30340.381419
35-0.017695-0.12510.450465
36-0.031774-0.22470.411573

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.143105 & 1.0119 & 0.158228 \tabularnewline
2 & 0.259615 & 1.8358 & 0.036172 \tabularnewline
3 & 0.32812 & 2.3202 & 0.012227 \tabularnewline
4 & 0.198734 & 1.4053 & 0.083063 \tabularnewline
5 & 0.108201 & 0.7651 & 0.223905 \tabularnewline
6 & 0.164967 & 1.1665 & 0.124474 \tabularnewline
7 & 0.036957 & 0.2613 & 0.397457 \tabularnewline
8 & 0.151003 & 1.0678 & 0.14538 \tabularnewline
9 & 0.04736 & 0.3349 & 0.369556 \tabularnewline
10 & -0.060647 & -0.4288 & 0.33494 \tabularnewline
11 & 0.324759 & 2.2964 & 0.01294 \tabularnewline
12 & -0.050971 & -0.3604 & 0.360025 \tabularnewline
13 & -0.017444 & -0.1233 & 0.451164 \tabularnewline
14 & 0.18157 & 1.2839 & 0.102548 \tabularnewline
15 & 0.051761 & 0.366 & 0.357952 \tabularnewline
16 & 0.007482 & 0.0529 & 0.47901 \tabularnewline
17 & 0.067605 & 0.478 & 0.317352 \tabularnewline
18 & -0.093383 & -0.6603 & 0.25604 \tabularnewline
19 & 0.060621 & 0.4287 & 0.335007 \tabularnewline
20 & -0.053773 & -0.3802 & 0.352691 \tabularnewline
21 & -0.193404 & -1.3676 & 0.088781 \tabularnewline
22 & -0.026617 & -0.1882 & 0.425735 \tabularnewline
23 & -0.117442 & -0.8304 & 0.205119 \tabularnewline
24 & -0.217812 & -1.5402 & 0.064913 \tabularnewline
25 & -0.096153 & -0.6799 & 0.249851 \tabularnewline
26 & -0.189619 & -1.3408 & 0.093022 \tabularnewline
27 & -0.225935 & -1.5976 & 0.058217 \tabularnewline
28 & -0.162234 & -1.1472 & 0.128386 \tabularnewline
29 & -0.129118 & -0.913 & 0.182812 \tabularnewline
30 & -0.105131 & -0.7434 & 0.230363 \tabularnewline
31 & -0.02787 & -0.1971 & 0.422286 \tabularnewline
32 & -0.156979 & -1.11 & 0.136152 \tabularnewline
33 & 0.007951 & 0.0562 & 0.477695 \tabularnewline
34 & -0.042908 & -0.3034 & 0.381419 \tabularnewline
35 & -0.017695 & -0.1251 & 0.450465 \tabularnewline
36 & -0.031774 & -0.2247 & 0.411573 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62971&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]0.143105[/C][C]1.0119[/C][C]0.158228[/C][/ROW]
[ROW][C]2[/C][C]0.259615[/C][C]1.8358[/C][C]0.036172[/C][/ROW]
[ROW][C]3[/C][C]0.32812[/C][C]2.3202[/C][C]0.012227[/C][/ROW]
[ROW][C]4[/C][C]0.198734[/C][C]1.4053[/C][C]0.083063[/C][/ROW]
[ROW][C]5[/C][C]0.108201[/C][C]0.7651[/C][C]0.223905[/C][/ROW]
[ROW][C]6[/C][C]0.164967[/C][C]1.1665[/C][C]0.124474[/C][/ROW]
[ROW][C]7[/C][C]0.036957[/C][C]0.2613[/C][C]0.397457[/C][/ROW]
[ROW][C]8[/C][C]0.151003[/C][C]1.0678[/C][C]0.14538[/C][/ROW]
[ROW][C]9[/C][C]0.04736[/C][C]0.3349[/C][C]0.369556[/C][/ROW]
[ROW][C]10[/C][C]-0.060647[/C][C]-0.4288[/C][C]0.33494[/C][/ROW]
[ROW][C]11[/C][C]0.324759[/C][C]2.2964[/C][C]0.01294[/C][/ROW]
[ROW][C]12[/C][C]-0.050971[/C][C]-0.3604[/C][C]0.360025[/C][/ROW]
[ROW][C]13[/C][C]-0.017444[/C][C]-0.1233[/C][C]0.451164[/C][/ROW]
[ROW][C]14[/C][C]0.18157[/C][C]1.2839[/C][C]0.102548[/C][/ROW]
[ROW][C]15[/C][C]0.051761[/C][C]0.366[/C][C]0.357952[/C][/ROW]
[ROW][C]16[/C][C]0.007482[/C][C]0.0529[/C][C]0.47901[/C][/ROW]
[ROW][C]17[/C][C]0.067605[/C][C]0.478[/C][C]0.317352[/C][/ROW]
[ROW][C]18[/C][C]-0.093383[/C][C]-0.6603[/C][C]0.25604[/C][/ROW]
[ROW][C]19[/C][C]0.060621[/C][C]0.4287[/C][C]0.335007[/C][/ROW]
[ROW][C]20[/C][C]-0.053773[/C][C]-0.3802[/C][C]0.352691[/C][/ROW]
[ROW][C]21[/C][C]-0.193404[/C][C]-1.3676[/C][C]0.088781[/C][/ROW]
[ROW][C]22[/C][C]-0.026617[/C][C]-0.1882[/C][C]0.425735[/C][/ROW]
[ROW][C]23[/C][C]-0.117442[/C][C]-0.8304[/C][C]0.205119[/C][/ROW]
[ROW][C]24[/C][C]-0.217812[/C][C]-1.5402[/C][C]0.064913[/C][/ROW]
[ROW][C]25[/C][C]-0.096153[/C][C]-0.6799[/C][C]0.249851[/C][/ROW]
[ROW][C]26[/C][C]-0.189619[/C][C]-1.3408[/C][C]0.093022[/C][/ROW]
[ROW][C]27[/C][C]-0.225935[/C][C]-1.5976[/C][C]0.058217[/C][/ROW]
[ROW][C]28[/C][C]-0.162234[/C][C]-1.1472[/C][C]0.128386[/C][/ROW]
[ROW][C]29[/C][C]-0.129118[/C][C]-0.913[/C][C]0.182812[/C][/ROW]
[ROW][C]30[/C][C]-0.105131[/C][C]-0.7434[/C][C]0.230363[/C][/ROW]
[ROW][C]31[/C][C]-0.02787[/C][C]-0.1971[/C][C]0.422286[/C][/ROW]
[ROW][C]32[/C][C]-0.156979[/C][C]-1.11[/C][C]0.136152[/C][/ROW]
[ROW][C]33[/C][C]0.007951[/C][C]0.0562[/C][C]0.477695[/C][/ROW]
[ROW][C]34[/C][C]-0.042908[/C][C]-0.3034[/C][C]0.381419[/C][/ROW]
[ROW][C]35[/C][C]-0.017695[/C][C]-0.1251[/C][C]0.450465[/C][/ROW]
[ROW][C]36[/C][C]-0.031774[/C][C]-0.2247[/C][C]0.411573[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62971&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62971&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
10.1431051.01190.158228
20.2596151.83580.036172
30.328122.32020.012227
40.1987341.40530.083063
50.1082010.76510.223905
60.1649671.16650.124474
70.0369570.26130.397457
80.1510031.06780.14538
90.047360.33490.369556
10-0.060647-0.42880.33494
110.3247592.29640.01294
12-0.050971-0.36040.360025
13-0.017444-0.12330.451164
140.181571.28390.102548
150.0517610.3660.357952
160.0074820.05290.47901
170.0676050.4780.317352
18-0.093383-0.66030.25604
190.0606210.42870.335007
20-0.053773-0.38020.352691
21-0.193404-1.36760.088781
22-0.026617-0.18820.425735
23-0.117442-0.83040.205119
24-0.217812-1.54020.064913
25-0.096153-0.67990.249851
26-0.189619-1.34080.093022
27-0.225935-1.59760.058217
28-0.162234-1.14720.128386
29-0.129118-0.9130.182812
30-0.105131-0.74340.230363
31-0.02787-0.19710.422286
32-0.156979-1.110.136152
330.0079510.05620.477695
34-0.042908-0.30340.381419
35-0.017695-0.12510.450465
36-0.031774-0.22470.411573






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1431051.01190.158228
20.2441361.72630.045234
30.2877972.0350.023583
40.1063060.75170.227879
5-0.05339-0.37750.35369
60.0074620.05280.479065
7-0.080526-0.56940.285816
80.0976740.69070.246486
9-0.002333-0.01650.493451
10-0.135771-0.960.170827
110.3302262.33510.011798
12-0.108181-0.7650.223947
13-0.099663-0.70470.242126
140.099240.70170.243049
150.0147730.10450.458612
160.0142930.10110.459952
17-0.065149-0.46070.323514
18-0.136897-0.9680.16885
190.0385670.27270.393099
20-0.045188-0.31950.37533
21-0.114963-0.81290.210062
22-0.135633-0.95910.171069
230.0145410.10280.459258
24-0.023042-0.16290.435615
25-0.123278-0.87170.193767
26-0.095925-0.67830.250356
27-0.096184-0.68010.249781
28-0.062228-0.440.33091
290.1524911.07830.143043
30-0.029907-0.21150.416689
310.0968080.68450.248398
320.0222020.1570.437941
330.031130.22010.413337
34-0.02496-0.17650.430308
350.1109230.78430.218269
360.0220150.15570.438459

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.143105 & 1.0119 & 0.158228 \tabularnewline
2 & 0.244136 & 1.7263 & 0.045234 \tabularnewline
3 & 0.287797 & 2.035 & 0.023583 \tabularnewline
4 & 0.106306 & 0.7517 & 0.227879 \tabularnewline
5 & -0.05339 & -0.3775 & 0.35369 \tabularnewline
6 & 0.007462 & 0.0528 & 0.479065 \tabularnewline
7 & -0.080526 & -0.5694 & 0.285816 \tabularnewline
8 & 0.097674 & 0.6907 & 0.246486 \tabularnewline
9 & -0.002333 & -0.0165 & 0.493451 \tabularnewline
10 & -0.135771 & -0.96 & 0.170827 \tabularnewline
11 & 0.330226 & 2.3351 & 0.011798 \tabularnewline
12 & -0.108181 & -0.765 & 0.223947 \tabularnewline
13 & -0.099663 & -0.7047 & 0.242126 \tabularnewline
14 & 0.09924 & 0.7017 & 0.243049 \tabularnewline
15 & 0.014773 & 0.1045 & 0.458612 \tabularnewline
16 & 0.014293 & 0.1011 & 0.459952 \tabularnewline
17 & -0.065149 & -0.4607 & 0.323514 \tabularnewline
18 & -0.136897 & -0.968 & 0.16885 \tabularnewline
19 & 0.038567 & 0.2727 & 0.393099 \tabularnewline
20 & -0.045188 & -0.3195 & 0.37533 \tabularnewline
21 & -0.114963 & -0.8129 & 0.210062 \tabularnewline
22 & -0.135633 & -0.9591 & 0.171069 \tabularnewline
23 & 0.014541 & 0.1028 & 0.459258 \tabularnewline
24 & -0.023042 & -0.1629 & 0.435615 \tabularnewline
25 & -0.123278 & -0.8717 & 0.193767 \tabularnewline
26 & -0.095925 & -0.6783 & 0.250356 \tabularnewline
27 & -0.096184 & -0.6801 & 0.249781 \tabularnewline
28 & -0.062228 & -0.44 & 0.33091 \tabularnewline
29 & 0.152491 & 1.0783 & 0.143043 \tabularnewline
30 & -0.029907 & -0.2115 & 0.416689 \tabularnewline
31 & 0.096808 & 0.6845 & 0.248398 \tabularnewline
32 & 0.022202 & 0.157 & 0.437941 \tabularnewline
33 & 0.03113 & 0.2201 & 0.413337 \tabularnewline
34 & -0.02496 & -0.1765 & 0.430308 \tabularnewline
35 & 0.110923 & 0.7843 & 0.218269 \tabularnewline
36 & 0.022015 & 0.1557 & 0.438459 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62971&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]0.143105[/C][C]1.0119[/C][C]0.158228[/C][/ROW]
[ROW][C]2[/C][C]0.244136[/C][C]1.7263[/C][C]0.045234[/C][/ROW]
[ROW][C]3[/C][C]0.287797[/C][C]2.035[/C][C]0.023583[/C][/ROW]
[ROW][C]4[/C][C]0.106306[/C][C]0.7517[/C][C]0.227879[/C][/ROW]
[ROW][C]5[/C][C]-0.05339[/C][C]-0.3775[/C][C]0.35369[/C][/ROW]
[ROW][C]6[/C][C]0.007462[/C][C]0.0528[/C][C]0.479065[/C][/ROW]
[ROW][C]7[/C][C]-0.080526[/C][C]-0.5694[/C][C]0.285816[/C][/ROW]
[ROW][C]8[/C][C]0.097674[/C][C]0.6907[/C][C]0.246486[/C][/ROW]
[ROW][C]9[/C][C]-0.002333[/C][C]-0.0165[/C][C]0.493451[/C][/ROW]
[ROW][C]10[/C][C]-0.135771[/C][C]-0.96[/C][C]0.170827[/C][/ROW]
[ROW][C]11[/C][C]0.330226[/C][C]2.3351[/C][C]0.011798[/C][/ROW]
[ROW][C]12[/C][C]-0.108181[/C][C]-0.765[/C][C]0.223947[/C][/ROW]
[ROW][C]13[/C][C]-0.099663[/C][C]-0.7047[/C][C]0.242126[/C][/ROW]
[ROW][C]14[/C][C]0.09924[/C][C]0.7017[/C][C]0.243049[/C][/ROW]
[ROW][C]15[/C][C]0.014773[/C][C]0.1045[/C][C]0.458612[/C][/ROW]
[ROW][C]16[/C][C]0.014293[/C][C]0.1011[/C][C]0.459952[/C][/ROW]
[ROW][C]17[/C][C]-0.065149[/C][C]-0.4607[/C][C]0.323514[/C][/ROW]
[ROW][C]18[/C][C]-0.136897[/C][C]-0.968[/C][C]0.16885[/C][/ROW]
[ROW][C]19[/C][C]0.038567[/C][C]0.2727[/C][C]0.393099[/C][/ROW]
[ROW][C]20[/C][C]-0.045188[/C][C]-0.3195[/C][C]0.37533[/C][/ROW]
[ROW][C]21[/C][C]-0.114963[/C][C]-0.8129[/C][C]0.210062[/C][/ROW]
[ROW][C]22[/C][C]-0.135633[/C][C]-0.9591[/C][C]0.171069[/C][/ROW]
[ROW][C]23[/C][C]0.014541[/C][C]0.1028[/C][C]0.459258[/C][/ROW]
[ROW][C]24[/C][C]-0.023042[/C][C]-0.1629[/C][C]0.435615[/C][/ROW]
[ROW][C]25[/C][C]-0.123278[/C][C]-0.8717[/C][C]0.193767[/C][/ROW]
[ROW][C]26[/C][C]-0.095925[/C][C]-0.6783[/C][C]0.250356[/C][/ROW]
[ROW][C]27[/C][C]-0.096184[/C][C]-0.6801[/C][C]0.249781[/C][/ROW]
[ROW][C]28[/C][C]-0.062228[/C][C]-0.44[/C][C]0.33091[/C][/ROW]
[ROW][C]29[/C][C]0.152491[/C][C]1.0783[/C][C]0.143043[/C][/ROW]
[ROW][C]30[/C][C]-0.029907[/C][C]-0.2115[/C][C]0.416689[/C][/ROW]
[ROW][C]31[/C][C]0.096808[/C][C]0.6845[/C][C]0.248398[/C][/ROW]
[ROW][C]32[/C][C]0.022202[/C][C]0.157[/C][C]0.437941[/C][/ROW]
[ROW][C]33[/C][C]0.03113[/C][C]0.2201[/C][C]0.413337[/C][/ROW]
[ROW][C]34[/C][C]-0.02496[/C][C]-0.1765[/C][C]0.430308[/C][/ROW]
[ROW][C]35[/C][C]0.110923[/C][C]0.7843[/C][C]0.218269[/C][/ROW]
[ROW][C]36[/C][C]0.022015[/C][C]0.1557[/C][C]0.438459[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62971&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62971&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
10.1431051.01190.158228
20.2441361.72630.045234
30.2877972.0350.023583
40.1063060.75170.227879
5-0.05339-0.37750.35369
60.0074620.05280.479065
7-0.080526-0.56940.285816
80.0976740.69070.246486
9-0.002333-0.01650.493451
10-0.135771-0.960.170827
110.3302262.33510.011798
12-0.108181-0.7650.223947
13-0.099663-0.70470.242126
140.099240.70170.243049
150.0147730.10450.458612
160.0142930.10110.459952
17-0.065149-0.46070.323514
18-0.136897-0.9680.16885
190.0385670.27270.393099
20-0.045188-0.31950.37533
21-0.114963-0.81290.210062
22-0.135633-0.95910.171069
230.0145410.10280.459258
24-0.023042-0.16290.435615
25-0.123278-0.87170.193767
26-0.095925-0.67830.250356
27-0.096184-0.68010.249781
28-0.062228-0.440.33091
290.1524911.07830.143043
30-0.029907-0.21150.416689
310.0968080.68450.248398
320.0222020.1570.437941
330.031130.22010.413337
34-0.02496-0.17650.430308
350.1109230.78430.218269
360.0220150.15570.438459


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')