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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, 17 Dec 2009 07:53:39 -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/17/t1261061672xevxhmf7elv0iye.htm/, Retrieved Mon, 12 May 2025 18:23:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=68928, Retrieved Mon, 12 May 2025 18:23:41 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact186

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 12:26:39] [b98453cac15ba1066b407e146608df68]
-   PD        [(Partial) Autocorrelation Function] [ACF2] [2009-11-25 16:43:12] [3b0db66ac8145b1be856a517e2900332]
-   P             [(Partial) Autocorrelation Function] [ACF (3)] [2009-12-17 14:53:39] [2ecea65fec1cd5f6b1ab182881aa2a91] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
21
19
25
21
23
23
19
18
19
19
22
23
20
14
14
14
15
11
17
16
20
24
23
20
21
19
23
23
23
23
27
26
17
24
26
24
27
27
26
24
23
23
24
17
21
19
22
22
18
16
14
12
14
16
8
3
0
5
1
1
3

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=68928&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=68928&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68928&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
1-0.541715-4.1615.2e-05
20.0055370.04250.483109
30.0405130.31120.378377
40.0216690.16640.434188
5-0.075724-0.58160.28151
60.0864970.66440.254514
7-0.056721-0.43570.332328
80.0688710.5290.299393
9-0.062635-0.48110.316109
10-0.018995-0.14590.442248
110.1015450.780.21926
12-0.107278-0.8240.206624
130.1305271.00260.160075
14-0.175071-1.34470.091927
150.0111680.08580.465963
160.2047041.57240.060607
17-0.178722-1.37280.087506
180.0183420.14090.444221
190.0783280.60170.274856
200.0531170.4080.342376
21-0.197711-1.51860.067096
220.082380.63280.264663
23-2.3e-05-2e-040.499929
240.1062680.81630.208817
25-0.264643-2.03280.023292
260.3040812.33570.011463
27-0.138323-1.06250.146174
28-0.008941-0.06870.472738
290.0783420.60180.274822
30-0.187517-1.44030.077528
310.1602781.23110.111582
320.0155980.11980.452519
33-0.070835-0.54410.294215
340.0076590.05880.476642
350.0068840.05290.479004
36-0.01554-0.11940.452695

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.541715 & -4.161 & 5.2e-05 \tabularnewline
2 & 0.005537 & 0.0425 & 0.483109 \tabularnewline
3 & 0.040513 & 0.3112 & 0.378377 \tabularnewline
4 & 0.021669 & 0.1664 & 0.434188 \tabularnewline
5 & -0.075724 & -0.5816 & 0.28151 \tabularnewline
6 & 0.086497 & 0.6644 & 0.254514 \tabularnewline
7 & -0.056721 & -0.4357 & 0.332328 \tabularnewline
8 & 0.068871 & 0.529 & 0.299393 \tabularnewline
9 & -0.062635 & -0.4811 & 0.316109 \tabularnewline
10 & -0.018995 & -0.1459 & 0.442248 \tabularnewline
11 & 0.101545 & 0.78 & 0.21926 \tabularnewline
12 & -0.107278 & -0.824 & 0.206624 \tabularnewline
13 & 0.130527 & 1.0026 & 0.160075 \tabularnewline
14 & -0.175071 & -1.3447 & 0.091927 \tabularnewline
15 & 0.011168 & 0.0858 & 0.465963 \tabularnewline
16 & 0.204704 & 1.5724 & 0.060607 \tabularnewline
17 & -0.178722 & -1.3728 & 0.087506 \tabularnewline
18 & 0.018342 & 0.1409 & 0.444221 \tabularnewline
19 & 0.078328 & 0.6017 & 0.274856 \tabularnewline
20 & 0.053117 & 0.408 & 0.342376 \tabularnewline
21 & -0.197711 & -1.5186 & 0.067096 \tabularnewline
22 & 0.08238 & 0.6328 & 0.264663 \tabularnewline
23 & -2.3e-05 & -2e-04 & 0.499929 \tabularnewline
24 & 0.106268 & 0.8163 & 0.208817 \tabularnewline
25 & -0.264643 & -2.0328 & 0.023292 \tabularnewline
26 & 0.304081 & 2.3357 & 0.011463 \tabularnewline
27 & -0.138323 & -1.0625 & 0.146174 \tabularnewline
28 & -0.008941 & -0.0687 & 0.472738 \tabularnewline
29 & 0.078342 & 0.6018 & 0.274822 \tabularnewline
30 & -0.187517 & -1.4403 & 0.077528 \tabularnewline
31 & 0.160278 & 1.2311 & 0.111582 \tabularnewline
32 & 0.015598 & 0.1198 & 0.452519 \tabularnewline
33 & -0.070835 & -0.5441 & 0.294215 \tabularnewline
34 & 0.007659 & 0.0588 & 0.476642 \tabularnewline
35 & 0.006884 & 0.0529 & 0.479004 \tabularnewline
36 & -0.01554 & -0.1194 & 0.452695 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68928&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]-0.541715[/C][C]-4.161[/C][C]5.2e-05[/C][/ROW]
[ROW][C]2[/C][C]0.005537[/C][C]0.0425[/C][C]0.483109[/C][/ROW]
[ROW][C]3[/C][C]0.040513[/C][C]0.3112[/C][C]0.378377[/C][/ROW]
[ROW][C]4[/C][C]0.021669[/C][C]0.1664[/C][C]0.434188[/C][/ROW]
[ROW][C]5[/C][C]-0.075724[/C][C]-0.5816[/C][C]0.28151[/C][/ROW]
[ROW][C]6[/C][C]0.086497[/C][C]0.6644[/C][C]0.254514[/C][/ROW]
[ROW][C]7[/C][C]-0.056721[/C][C]-0.4357[/C][C]0.332328[/C][/ROW]
[ROW][C]8[/C][C]0.068871[/C][C]0.529[/C][C]0.299393[/C][/ROW]
[ROW][C]9[/C][C]-0.062635[/C][C]-0.4811[/C][C]0.316109[/C][/ROW]
[ROW][C]10[/C][C]-0.018995[/C][C]-0.1459[/C][C]0.442248[/C][/ROW]
[ROW][C]11[/C][C]0.101545[/C][C]0.78[/C][C]0.21926[/C][/ROW]
[ROW][C]12[/C][C]-0.107278[/C][C]-0.824[/C][C]0.206624[/C][/ROW]
[ROW][C]13[/C][C]0.130527[/C][C]1.0026[/C][C]0.160075[/C][/ROW]
[ROW][C]14[/C][C]-0.175071[/C][C]-1.3447[/C][C]0.091927[/C][/ROW]
[ROW][C]15[/C][C]0.011168[/C][C]0.0858[/C][C]0.465963[/C][/ROW]
[ROW][C]16[/C][C]0.204704[/C][C]1.5724[/C][C]0.060607[/C][/ROW]
[ROW][C]17[/C][C]-0.178722[/C][C]-1.3728[/C][C]0.087506[/C][/ROW]
[ROW][C]18[/C][C]0.018342[/C][C]0.1409[/C][C]0.444221[/C][/ROW]
[ROW][C]19[/C][C]0.078328[/C][C]0.6017[/C][C]0.274856[/C][/ROW]
[ROW][C]20[/C][C]0.053117[/C][C]0.408[/C][C]0.342376[/C][/ROW]
[ROW][C]21[/C][C]-0.197711[/C][C]-1.5186[/C][C]0.067096[/C][/ROW]
[ROW][C]22[/C][C]0.08238[/C][C]0.6328[/C][C]0.264663[/C][/ROW]
[ROW][C]23[/C][C]-2.3e-05[/C][C]-2e-04[/C][C]0.499929[/C][/ROW]
[ROW][C]24[/C][C]0.106268[/C][C]0.8163[/C][C]0.208817[/C][/ROW]
[ROW][C]25[/C][C]-0.264643[/C][C]-2.0328[/C][C]0.023292[/C][/ROW]
[ROW][C]26[/C][C]0.304081[/C][C]2.3357[/C][C]0.011463[/C][/ROW]
[ROW][C]27[/C][C]-0.138323[/C][C]-1.0625[/C][C]0.146174[/C][/ROW]
[ROW][C]28[/C][C]-0.008941[/C][C]-0.0687[/C][C]0.472738[/C][/ROW]
[ROW][C]29[/C][C]0.078342[/C][C]0.6018[/C][C]0.274822[/C][/ROW]
[ROW][C]30[/C][C]-0.187517[/C][C]-1.4403[/C][C]0.077528[/C][/ROW]
[ROW][C]31[/C][C]0.160278[/C][C]1.2311[/C][C]0.111582[/C][/ROW]
[ROW][C]32[/C][C]0.015598[/C][C]0.1198[/C][C]0.452519[/C][/ROW]
[ROW][C]33[/C][C]-0.070835[/C][C]-0.5441[/C][C]0.294215[/C][/ROW]
[ROW][C]34[/C][C]0.007659[/C][C]0.0588[/C][C]0.476642[/C][/ROW]
[ROW][C]35[/C][C]0.006884[/C][C]0.0529[/C][C]0.479004[/C][/ROW]
[ROW][C]36[/C][C]-0.01554[/C][C]-0.1194[/C][C]0.452695[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68928&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68928&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
1-0.541715-4.1615.2e-05
20.0055370.04250.483109
30.0405130.31120.378377
40.0216690.16640.434188
5-0.075724-0.58160.28151
60.0864970.66440.254514
7-0.056721-0.43570.332328
80.0688710.5290.299393
9-0.062635-0.48110.316109
10-0.018995-0.14590.442248
110.1015450.780.21926
12-0.107278-0.8240.206624
130.1305271.00260.160075
14-0.175071-1.34470.091927
150.0111680.08580.465963
160.2047041.57240.060607
17-0.178722-1.37280.087506
180.0183420.14090.444221
190.0783280.60170.274856
200.0531170.4080.342376
21-0.197711-1.51860.067096
220.082380.63280.264663
23-2.3e-05-2e-040.499929
240.1062680.81630.208817
25-0.264643-2.03280.023292
260.3040812.33570.011463
27-0.138323-1.06250.146174
28-0.008941-0.06870.472738
290.0783420.60180.274822
30-0.187517-1.44030.077528
310.1602781.23110.111582
320.0155980.11980.452519
33-0.070835-0.54410.294215
340.0076590.05880.476642
350.0068840.05290.479004
36-0.01554-0.11940.452695






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.541715-4.1615.2e-05
2-0.407501-3.13010.001358
3-0.298724-2.29450.012667
4-0.187863-1.4430.077154
5-0.239465-1.83940.035447
6-0.144734-1.11170.135383
7-0.161287-1.23890.11015
8-0.037222-0.28590.387974
9-0.039568-0.30390.381127
10-0.109858-0.84380.201085
110.0322870.2480.402497
12-0.043306-0.33260.370293
130.1667541.28090.102627
14-0.027748-0.21310.415978
15-0.225545-1.73240.04421
160.0347040.26660.395366
17-0.056663-0.43520.33249
18-0.065889-0.50610.307335
19-0.039725-0.30510.380668
200.2458511.88840.031945
210.1047140.80430.212221
22-0.019441-0.14930.440901
23-0.073805-0.56690.286464
240.0586970.45090.326873
25-0.248976-1.91240.030341
26-0.044047-0.33830.368158
27-0.020662-0.15870.43722
28-0.009092-0.06980.47228
290.1427761.09670.138618
30-0.141643-1.0880.140515
31-0.044164-0.33920.367822
32-0.010771-0.08270.467172
330.0815620.62650.266704
340.1164650.89460.187323
35-0.124167-0.95370.172052
36-0.137032-1.05260.148417

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.541715 & -4.161 & 5.2e-05 \tabularnewline
2 & -0.407501 & -3.1301 & 0.001358 \tabularnewline
3 & -0.298724 & -2.2945 & 0.012667 \tabularnewline
4 & -0.187863 & -1.443 & 0.077154 \tabularnewline
5 & -0.239465 & -1.8394 & 0.035447 \tabularnewline
6 & -0.144734 & -1.1117 & 0.135383 \tabularnewline
7 & -0.161287 & -1.2389 & 0.11015 \tabularnewline
8 & -0.037222 & -0.2859 & 0.387974 \tabularnewline
9 & -0.039568 & -0.3039 & 0.381127 \tabularnewline
10 & -0.109858 & -0.8438 & 0.201085 \tabularnewline
11 & 0.032287 & 0.248 & 0.402497 \tabularnewline
12 & -0.043306 & -0.3326 & 0.370293 \tabularnewline
13 & 0.166754 & 1.2809 & 0.102627 \tabularnewline
14 & -0.027748 & -0.2131 & 0.415978 \tabularnewline
15 & -0.225545 & -1.7324 & 0.04421 \tabularnewline
16 & 0.034704 & 0.2666 & 0.395366 \tabularnewline
17 & -0.056663 & -0.4352 & 0.33249 \tabularnewline
18 & -0.065889 & -0.5061 & 0.307335 \tabularnewline
19 & -0.039725 & -0.3051 & 0.380668 \tabularnewline
20 & 0.245851 & 1.8884 & 0.031945 \tabularnewline
21 & 0.104714 & 0.8043 & 0.212221 \tabularnewline
22 & -0.019441 & -0.1493 & 0.440901 \tabularnewline
23 & -0.073805 & -0.5669 & 0.286464 \tabularnewline
24 & 0.058697 & 0.4509 & 0.326873 \tabularnewline
25 & -0.248976 & -1.9124 & 0.030341 \tabularnewline
26 & -0.044047 & -0.3383 & 0.368158 \tabularnewline
27 & -0.020662 & -0.1587 & 0.43722 \tabularnewline
28 & -0.009092 & -0.0698 & 0.47228 \tabularnewline
29 & 0.142776 & 1.0967 & 0.138618 \tabularnewline
30 & -0.141643 & -1.088 & 0.140515 \tabularnewline
31 & -0.044164 & -0.3392 & 0.367822 \tabularnewline
32 & -0.010771 & -0.0827 & 0.467172 \tabularnewline
33 & 0.081562 & 0.6265 & 0.266704 \tabularnewline
34 & 0.116465 & 0.8946 & 0.187323 \tabularnewline
35 & -0.124167 & -0.9537 & 0.172052 \tabularnewline
36 & -0.137032 & -1.0526 & 0.148417 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68928&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]-0.541715[/C][C]-4.161[/C][C]5.2e-05[/C][/ROW]
[ROW][C]2[/C][C]-0.407501[/C][C]-3.1301[/C][C]0.001358[/C][/ROW]
[ROW][C]3[/C][C]-0.298724[/C][C]-2.2945[/C][C]0.012667[/C][/ROW]
[ROW][C]4[/C][C]-0.187863[/C][C]-1.443[/C][C]0.077154[/C][/ROW]
[ROW][C]5[/C][C]-0.239465[/C][C]-1.8394[/C][C]0.035447[/C][/ROW]
[ROW][C]6[/C][C]-0.144734[/C][C]-1.1117[/C][C]0.135383[/C][/ROW]
[ROW][C]7[/C][C]-0.161287[/C][C]-1.2389[/C][C]0.11015[/C][/ROW]
[ROW][C]8[/C][C]-0.037222[/C][C]-0.2859[/C][C]0.387974[/C][/ROW]
[ROW][C]9[/C][C]-0.039568[/C][C]-0.3039[/C][C]0.381127[/C][/ROW]
[ROW][C]10[/C][C]-0.109858[/C][C]-0.8438[/C][C]0.201085[/C][/ROW]
[ROW][C]11[/C][C]0.032287[/C][C]0.248[/C][C]0.402497[/C][/ROW]
[ROW][C]12[/C][C]-0.043306[/C][C]-0.3326[/C][C]0.370293[/C][/ROW]
[ROW][C]13[/C][C]0.166754[/C][C]1.2809[/C][C]0.102627[/C][/ROW]
[ROW][C]14[/C][C]-0.027748[/C][C]-0.2131[/C][C]0.415978[/C][/ROW]
[ROW][C]15[/C][C]-0.225545[/C][C]-1.7324[/C][C]0.04421[/C][/ROW]
[ROW][C]16[/C][C]0.034704[/C][C]0.2666[/C][C]0.395366[/C][/ROW]
[ROW][C]17[/C][C]-0.056663[/C][C]-0.4352[/C][C]0.33249[/C][/ROW]
[ROW][C]18[/C][C]-0.065889[/C][C]-0.5061[/C][C]0.307335[/C][/ROW]
[ROW][C]19[/C][C]-0.039725[/C][C]-0.3051[/C][C]0.380668[/C][/ROW]
[ROW][C]20[/C][C]0.245851[/C][C]1.8884[/C][C]0.031945[/C][/ROW]
[ROW][C]21[/C][C]0.104714[/C][C]0.8043[/C][C]0.212221[/C][/ROW]
[ROW][C]22[/C][C]-0.019441[/C][C]-0.1493[/C][C]0.440901[/C][/ROW]
[ROW][C]23[/C][C]-0.073805[/C][C]-0.5669[/C][C]0.286464[/C][/ROW]
[ROW][C]24[/C][C]0.058697[/C][C]0.4509[/C][C]0.326873[/C][/ROW]
[ROW][C]25[/C][C]-0.248976[/C][C]-1.9124[/C][C]0.030341[/C][/ROW]
[ROW][C]26[/C][C]-0.044047[/C][C]-0.3383[/C][C]0.368158[/C][/ROW]
[ROW][C]27[/C][C]-0.020662[/C][C]-0.1587[/C][C]0.43722[/C][/ROW]
[ROW][C]28[/C][C]-0.009092[/C][C]-0.0698[/C][C]0.47228[/C][/ROW]
[ROW][C]29[/C][C]0.142776[/C][C]1.0967[/C][C]0.138618[/C][/ROW]
[ROW][C]30[/C][C]-0.141643[/C][C]-1.088[/C][C]0.140515[/C][/ROW]
[ROW][C]31[/C][C]-0.044164[/C][C]-0.3392[/C][C]0.367822[/C][/ROW]
[ROW][C]32[/C][C]-0.010771[/C][C]-0.0827[/C][C]0.467172[/C][/ROW]
[ROW][C]33[/C][C]0.081562[/C][C]0.6265[/C][C]0.266704[/C][/ROW]
[ROW][C]34[/C][C]0.116465[/C][C]0.8946[/C][C]0.187323[/C][/ROW]
[ROW][C]35[/C][C]-0.124167[/C][C]-0.9537[/C][C]0.172052[/C][/ROW]
[ROW][C]36[/C][C]-0.137032[/C][C]-1.0526[/C][C]0.148417[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68928&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68928&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
1-0.541715-4.1615.2e-05
2-0.407501-3.13010.001358
3-0.298724-2.29450.012667
4-0.187863-1.4430.077154
5-0.239465-1.83940.035447
6-0.144734-1.11170.135383
7-0.161287-1.23890.11015
8-0.037222-0.28590.387974
9-0.039568-0.30390.381127
10-0.109858-0.84380.201085
110.0322870.2480.402497
12-0.043306-0.33260.370293
130.1667541.28090.102627
14-0.027748-0.21310.415978
15-0.225545-1.73240.04421
160.0347040.26660.395366
17-0.056663-0.43520.33249
18-0.065889-0.50610.307335
19-0.039725-0.30510.380668
200.2458511.88840.031945
210.1047140.80430.212221
22-0.019441-0.14930.440901
23-0.073805-0.56690.286464
240.0586970.45090.326873
25-0.248976-1.91240.030341
26-0.044047-0.33830.368158
27-0.020662-0.15870.43722
28-0.009092-0.06980.47228
290.1427761.09670.138618
30-0.141643-1.0880.140515
31-0.044164-0.33920.367822
32-0.010771-0.08270.467172
330.0815620.62650.266704
340.1164650.89460.187323
35-0.124167-0.95370.172052
36-0.137032-1.05260.148417


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 2 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 2 ; 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')