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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, 18 Dec 2009 04:49:26 -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/18/t1261137013npoau8wx5bxq5ir.htm/, Retrieved Sat, 27 Apr 2024 12:10:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=69257, Retrieved Sat, 27 Apr 2024 12:10:00 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact127

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] [] [2009-11-24 09:58:46] [fef2f8976fa1eef1b54e2cee317fe737]
-    D            [(Partial) Autocorrelation Function] [] [2009-12-18 11:49:26] [2ffc7e281e02b99889abd2ccc65ed6c3] [Current]
-   P               [(Partial) Autocorrelation Function] [] [2009-12-18 11:51:01] [fef2f8976fa1eef1b54e2cee317fe737]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
120.9
119.6
125.9
116.1
107.5
116.7
112.5
113
126.4
114.1
112.5
112.4
113.1
116.3
111.7
118.8
116.5
125.1
113.1
119.6
114.4
114
117.8
117
120.9
115
117.3
119.4
114.9
125.8
117.6
117.6
114.9
121.9
117
106.4
110.5
113.6
114.2
125.4
124.6
120.2
120.8
111.4
124.1
120.2
125.5
116
117
105.7
102
106.4
96.9
107.6
98.8
101.1
105.7
104.6
103.2
101.6

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=69257&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=69257&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69257&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
10.5872024.06838.8e-05
20.5192513.59750.000379
30.2776581.92370.030169
40.2149961.48950.071444
50.1540811.06750.145543
60.2055711.42420.080423
70.2135171.47930.072798
80.0419120.29040.386389
9-0.022117-0.15320.439429
10-0.186799-1.29420.100897
11-0.144131-0.99860.161505
12-0.276323-1.91440.030769
13-0.094484-0.65460.257924
14-0.007794-0.0540.47858
150.0546710.37880.353263
160.0864510.59890.276012
170.0243150.16850.433466
18-0.012533-0.08680.465584
19-0.165528-1.14680.128572
20-0.035977-0.24930.402113
210.0407720.28250.389396
220.0518870.35950.360404
230.0811840.56250.288209
24-0.02713-0.1880.425849
25-0.093065-0.64480.261071
26-0.185314-1.28390.102672
27-0.121796-0.84380.201476
28-0.181579-1.2580.107236
29-0.074038-0.5130.305168
30-0.132312-0.91670.181945
31-0.052477-0.36360.358886
32-0.146285-1.01350.157953
33-0.215231-1.49120.071231
34-0.215466-1.49280.071018
35-0.245771-1.70280.047541
36-0.161189-1.11680.13483

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.587202 & 4.0683 & 8.8e-05 \tabularnewline
2 & 0.519251 & 3.5975 & 0.000379 \tabularnewline
3 & 0.277658 & 1.9237 & 0.030169 \tabularnewline
4 & 0.214996 & 1.4895 & 0.071444 \tabularnewline
5 & 0.154081 & 1.0675 & 0.145543 \tabularnewline
6 & 0.205571 & 1.4242 & 0.080423 \tabularnewline
7 & 0.213517 & 1.4793 & 0.072798 \tabularnewline
8 & 0.041912 & 0.2904 & 0.386389 \tabularnewline
9 & -0.022117 & -0.1532 & 0.439429 \tabularnewline
10 & -0.186799 & -1.2942 & 0.100897 \tabularnewline
11 & -0.144131 & -0.9986 & 0.161505 \tabularnewline
12 & -0.276323 & -1.9144 & 0.030769 \tabularnewline
13 & -0.094484 & -0.6546 & 0.257924 \tabularnewline
14 & -0.007794 & -0.054 & 0.47858 \tabularnewline
15 & 0.054671 & 0.3788 & 0.353263 \tabularnewline
16 & 0.086451 & 0.5989 & 0.276012 \tabularnewline
17 & 0.024315 & 0.1685 & 0.433466 \tabularnewline
18 & -0.012533 & -0.0868 & 0.465584 \tabularnewline
19 & -0.165528 & -1.1468 & 0.128572 \tabularnewline
20 & -0.035977 & -0.2493 & 0.402113 \tabularnewline
21 & 0.040772 & 0.2825 & 0.389396 \tabularnewline
22 & 0.051887 & 0.3595 & 0.360404 \tabularnewline
23 & 0.081184 & 0.5625 & 0.288209 \tabularnewline
24 & -0.02713 & -0.188 & 0.425849 \tabularnewline
25 & -0.093065 & -0.6448 & 0.261071 \tabularnewline
26 & -0.185314 & -1.2839 & 0.102672 \tabularnewline
27 & -0.121796 & -0.8438 & 0.201476 \tabularnewline
28 & -0.181579 & -1.258 & 0.107236 \tabularnewline
29 & -0.074038 & -0.513 & 0.305168 \tabularnewline
30 & -0.132312 & -0.9167 & 0.181945 \tabularnewline
31 & -0.052477 & -0.3636 & 0.358886 \tabularnewline
32 & -0.146285 & -1.0135 & 0.157953 \tabularnewline
33 & -0.215231 & -1.4912 & 0.071231 \tabularnewline
34 & -0.215466 & -1.4928 & 0.071018 \tabularnewline
35 & -0.245771 & -1.7028 & 0.047541 \tabularnewline
36 & -0.161189 & -1.1168 & 0.13483 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69257&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]0.587202[/C][C]4.0683[/C][C]8.8e-05[/C][/ROW]
[ROW][C]2[/C][C]0.519251[/C][C]3.5975[/C][C]0.000379[/C][/ROW]
[ROW][C]3[/C][C]0.277658[/C][C]1.9237[/C][C]0.030169[/C][/ROW]
[ROW][C]4[/C][C]0.214996[/C][C]1.4895[/C][C]0.071444[/C][/ROW]
[ROW][C]5[/C][C]0.154081[/C][C]1.0675[/C][C]0.145543[/C][/ROW]
[ROW][C]6[/C][C]0.205571[/C][C]1.4242[/C][C]0.080423[/C][/ROW]
[ROW][C]7[/C][C]0.213517[/C][C]1.4793[/C][C]0.072798[/C][/ROW]
[ROW][C]8[/C][C]0.041912[/C][C]0.2904[/C][C]0.386389[/C][/ROW]
[ROW][C]9[/C][C]-0.022117[/C][C]-0.1532[/C][C]0.439429[/C][/ROW]
[ROW][C]10[/C][C]-0.186799[/C][C]-1.2942[/C][C]0.100897[/C][/ROW]
[ROW][C]11[/C][C]-0.144131[/C][C]-0.9986[/C][C]0.161505[/C][/ROW]
[ROW][C]12[/C][C]-0.276323[/C][C]-1.9144[/C][C]0.030769[/C][/ROW]
[ROW][C]13[/C][C]-0.094484[/C][C]-0.6546[/C][C]0.257924[/C][/ROW]
[ROW][C]14[/C][C]-0.007794[/C][C]-0.054[/C][C]0.47858[/C][/ROW]
[ROW][C]15[/C][C]0.054671[/C][C]0.3788[/C][C]0.353263[/C][/ROW]
[ROW][C]16[/C][C]0.086451[/C][C]0.5989[/C][C]0.276012[/C][/ROW]
[ROW][C]17[/C][C]0.024315[/C][C]0.1685[/C][C]0.433466[/C][/ROW]
[ROW][C]18[/C][C]-0.012533[/C][C]-0.0868[/C][C]0.465584[/C][/ROW]
[ROW][C]19[/C][C]-0.165528[/C][C]-1.1468[/C][C]0.128572[/C][/ROW]
[ROW][C]20[/C][C]-0.035977[/C][C]-0.2493[/C][C]0.402113[/C][/ROW]
[ROW][C]21[/C][C]0.040772[/C][C]0.2825[/C][C]0.389396[/C][/ROW]
[ROW][C]22[/C][C]0.051887[/C][C]0.3595[/C][C]0.360404[/C][/ROW]
[ROW][C]23[/C][C]0.081184[/C][C]0.5625[/C][C]0.288209[/C][/ROW]
[ROW][C]24[/C][C]-0.02713[/C][C]-0.188[/C][C]0.425849[/C][/ROW]
[ROW][C]25[/C][C]-0.093065[/C][C]-0.6448[/C][C]0.261071[/C][/ROW]
[ROW][C]26[/C][C]-0.185314[/C][C]-1.2839[/C][C]0.102672[/C][/ROW]
[ROW][C]27[/C][C]-0.121796[/C][C]-0.8438[/C][C]0.201476[/C][/ROW]
[ROW][C]28[/C][C]-0.181579[/C][C]-1.258[/C][C]0.107236[/C][/ROW]
[ROW][C]29[/C][C]-0.074038[/C][C]-0.513[/C][C]0.305168[/C][/ROW]
[ROW][C]30[/C][C]-0.132312[/C][C]-0.9167[/C][C]0.181945[/C][/ROW]
[ROW][C]31[/C][C]-0.052477[/C][C]-0.3636[/C][C]0.358886[/C][/ROW]
[ROW][C]32[/C][C]-0.146285[/C][C]-1.0135[/C][C]0.157953[/C][/ROW]
[ROW][C]33[/C][C]-0.215231[/C][C]-1.4912[/C][C]0.071231[/C][/ROW]
[ROW][C]34[/C][C]-0.215466[/C][C]-1.4928[/C][C]0.071018[/C][/ROW]
[ROW][C]35[/C][C]-0.245771[/C][C]-1.7028[/C][C]0.047541[/C][/ROW]
[ROW][C]36[/C][C]-0.161189[/C][C]-1.1168[/C][C]0.13483[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69257&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69257&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
10.5872024.06838.8e-05
20.5192513.59750.000379
30.2776581.92370.030169
40.2149961.48950.071444
50.1540811.06750.145543
60.2055711.42420.080423
70.2135171.47930.072798
80.0419120.29040.386389
9-0.022117-0.15320.439429
10-0.186799-1.29420.100897
11-0.144131-0.99860.161505
12-0.276323-1.91440.030769
13-0.094484-0.65460.257924
14-0.007794-0.0540.47858
150.0546710.37880.353263
160.0864510.59890.276012
170.0243150.16850.433466
18-0.012533-0.08680.465584
19-0.165528-1.14680.128572
20-0.035977-0.24930.402113
210.0407720.28250.389396
220.0518870.35950.360404
230.0811840.56250.288209
24-0.02713-0.1880.425849
25-0.093065-0.64480.261071
26-0.185314-1.28390.102672
27-0.121796-0.84380.201476
28-0.181579-1.2580.107236
29-0.074038-0.5130.305168
30-0.132312-0.91670.181945
31-0.052477-0.36360.358886
32-0.146285-1.01350.157953
33-0.215231-1.49120.071231
34-0.215466-1.49280.071018
35-0.245771-1.70280.047541
36-0.161189-1.11680.13483






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.5872024.06838.8e-05
20.2662491.84460.035634
3-0.168228-1.16550.124784
40.0098470.06820.472947
50.0715830.49590.3111
60.1404360.9730.167723
70.0612360.42430.336638
8-0.310577-2.15170.018239
9-0.090114-0.62430.267684
10-0.097881-0.67810.250469
110.0975390.67580.251215
12-0.216096-1.49720.07045
130.1401160.97070.16827
140.2883071.99740.025731
150.0424920.29440.384864
160.0077990.0540.478566
17-0.129377-0.89630.18727
18-0.036226-0.2510.401451
19-0.192757-1.33550.094012
200.0031140.02160.491439
210.2021161.40030.083927
22-0.209246-1.44970.076822
230.1114230.7720.221961
24-0.135748-0.94050.175838
250.069530.48170.316098
260.0910510.63080.265576
27-0.132593-0.91860.18144
28-0.157324-1.090.140584
290.017720.12280.451401
300.0069540.04820.480886
310.0072120.050.480178
32-0.19356-1.3410.093112
330.0061340.04250.48314
34-0.040888-0.28330.389091
350.0718210.49760.310524
36-0.060876-0.42180.33754

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.587202 & 4.0683 & 8.8e-05 \tabularnewline
2 & 0.266249 & 1.8446 & 0.035634 \tabularnewline
3 & -0.168228 & -1.1655 & 0.124784 \tabularnewline
4 & 0.009847 & 0.0682 & 0.472947 \tabularnewline
5 & 0.071583 & 0.4959 & 0.3111 \tabularnewline
6 & 0.140436 & 0.973 & 0.167723 \tabularnewline
7 & 0.061236 & 0.4243 & 0.336638 \tabularnewline
8 & -0.310577 & -2.1517 & 0.018239 \tabularnewline
9 & -0.090114 & -0.6243 & 0.267684 \tabularnewline
10 & -0.097881 & -0.6781 & 0.250469 \tabularnewline
11 & 0.097539 & 0.6758 & 0.251215 \tabularnewline
12 & -0.216096 & -1.4972 & 0.07045 \tabularnewline
13 & 0.140116 & 0.9707 & 0.16827 \tabularnewline
14 & 0.288307 & 1.9974 & 0.025731 \tabularnewline
15 & 0.042492 & 0.2944 & 0.384864 \tabularnewline
16 & 0.007799 & 0.054 & 0.478566 \tabularnewline
17 & -0.129377 & -0.8963 & 0.18727 \tabularnewline
18 & -0.036226 & -0.251 & 0.401451 \tabularnewline
19 & -0.192757 & -1.3355 & 0.094012 \tabularnewline
20 & 0.003114 & 0.0216 & 0.491439 \tabularnewline
21 & 0.202116 & 1.4003 & 0.083927 \tabularnewline
22 & -0.209246 & -1.4497 & 0.076822 \tabularnewline
23 & 0.111423 & 0.772 & 0.221961 \tabularnewline
24 & -0.135748 & -0.9405 & 0.175838 \tabularnewline
25 & 0.06953 & 0.4817 & 0.316098 \tabularnewline
26 & 0.091051 & 0.6308 & 0.265576 \tabularnewline
27 & -0.132593 & -0.9186 & 0.18144 \tabularnewline
28 & -0.157324 & -1.09 & 0.140584 \tabularnewline
29 & 0.01772 & 0.1228 & 0.451401 \tabularnewline
30 & 0.006954 & 0.0482 & 0.480886 \tabularnewline
31 & 0.007212 & 0.05 & 0.480178 \tabularnewline
32 & -0.19356 & -1.341 & 0.093112 \tabularnewline
33 & 0.006134 & 0.0425 & 0.48314 \tabularnewline
34 & -0.040888 & -0.2833 & 0.389091 \tabularnewline
35 & 0.071821 & 0.4976 & 0.310524 \tabularnewline
36 & -0.060876 & -0.4218 & 0.33754 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69257&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]0.587202[/C][C]4.0683[/C][C]8.8e-05[/C][/ROW]
[ROW][C]2[/C][C]0.266249[/C][C]1.8446[/C][C]0.035634[/C][/ROW]
[ROW][C]3[/C][C]-0.168228[/C][C]-1.1655[/C][C]0.124784[/C][/ROW]
[ROW][C]4[/C][C]0.009847[/C][C]0.0682[/C][C]0.472947[/C][/ROW]
[ROW][C]5[/C][C]0.071583[/C][C]0.4959[/C][C]0.3111[/C][/ROW]
[ROW][C]6[/C][C]0.140436[/C][C]0.973[/C][C]0.167723[/C][/ROW]
[ROW][C]7[/C][C]0.061236[/C][C]0.4243[/C][C]0.336638[/C][/ROW]
[ROW][C]8[/C][C]-0.310577[/C][C]-2.1517[/C][C]0.018239[/C][/ROW]
[ROW][C]9[/C][C]-0.090114[/C][C]-0.6243[/C][C]0.267684[/C][/ROW]
[ROW][C]10[/C][C]-0.097881[/C][C]-0.6781[/C][C]0.250469[/C][/ROW]
[ROW][C]11[/C][C]0.097539[/C][C]0.6758[/C][C]0.251215[/C][/ROW]
[ROW][C]12[/C][C]-0.216096[/C][C]-1.4972[/C][C]0.07045[/C][/ROW]
[ROW][C]13[/C][C]0.140116[/C][C]0.9707[/C][C]0.16827[/C][/ROW]
[ROW][C]14[/C][C]0.288307[/C][C]1.9974[/C][C]0.025731[/C][/ROW]
[ROW][C]15[/C][C]0.042492[/C][C]0.2944[/C][C]0.384864[/C][/ROW]
[ROW][C]16[/C][C]0.007799[/C][C]0.054[/C][C]0.478566[/C][/ROW]
[ROW][C]17[/C][C]-0.129377[/C][C]-0.8963[/C][C]0.18727[/C][/ROW]
[ROW][C]18[/C][C]-0.036226[/C][C]-0.251[/C][C]0.401451[/C][/ROW]
[ROW][C]19[/C][C]-0.192757[/C][C]-1.3355[/C][C]0.094012[/C][/ROW]
[ROW][C]20[/C][C]0.003114[/C][C]0.0216[/C][C]0.491439[/C][/ROW]
[ROW][C]21[/C][C]0.202116[/C][C]1.4003[/C][C]0.083927[/C][/ROW]
[ROW][C]22[/C][C]-0.209246[/C][C]-1.4497[/C][C]0.076822[/C][/ROW]
[ROW][C]23[/C][C]0.111423[/C][C]0.772[/C][C]0.221961[/C][/ROW]
[ROW][C]24[/C][C]-0.135748[/C][C]-0.9405[/C][C]0.175838[/C][/ROW]
[ROW][C]25[/C][C]0.06953[/C][C]0.4817[/C][C]0.316098[/C][/ROW]
[ROW][C]26[/C][C]0.091051[/C][C]0.6308[/C][C]0.265576[/C][/ROW]
[ROW][C]27[/C][C]-0.132593[/C][C]-0.9186[/C][C]0.18144[/C][/ROW]
[ROW][C]28[/C][C]-0.157324[/C][C]-1.09[/C][C]0.140584[/C][/ROW]
[ROW][C]29[/C][C]0.01772[/C][C]0.1228[/C][C]0.451401[/C][/ROW]
[ROW][C]30[/C][C]0.006954[/C][C]0.0482[/C][C]0.480886[/C][/ROW]
[ROW][C]31[/C][C]0.007212[/C][C]0.05[/C][C]0.480178[/C][/ROW]
[ROW][C]32[/C][C]-0.19356[/C][C]-1.341[/C][C]0.093112[/C][/ROW]
[ROW][C]33[/C][C]0.006134[/C][C]0.0425[/C][C]0.48314[/C][/ROW]
[ROW][C]34[/C][C]-0.040888[/C][C]-0.2833[/C][C]0.389091[/C][/ROW]
[ROW][C]35[/C][C]0.071821[/C][C]0.4976[/C][C]0.310524[/C][/ROW]
[ROW][C]36[/C][C]-0.060876[/C][C]-0.4218[/C][C]0.33754[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69257&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69257&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
10.5872024.06838.8e-05
20.2662491.84460.035634
3-0.168228-1.16550.124784
40.0098470.06820.472947
50.0715830.49590.3111
60.1404360.9730.167723
70.0612360.42430.336638
8-0.310577-2.15170.018239
9-0.090114-0.62430.267684
10-0.097881-0.67810.250469
110.0975390.67580.251215
12-0.216096-1.49720.07045
130.1401160.97070.16827
140.2883071.99740.025731
150.0424920.29440.384864
160.0077990.0540.478566
17-0.129377-0.89630.18727
18-0.036226-0.2510.401451
19-0.192757-1.33550.094012
200.0031140.02160.491439
210.2021161.40030.083927
22-0.209246-1.44970.076822
230.1114230.7720.221961
24-0.135748-0.94050.175838
250.069530.48170.316098
260.0910510.63080.265576
27-0.132593-0.91860.18144
28-0.157324-1.090.140584
290.017720.12280.451401
300.0069540.04820.480886
310.0072120.050.480178
32-0.19356-1.3410.093112
330.0061340.04250.48314
34-0.040888-0.28330.389091
350.0718210.49760.310524
36-0.060876-0.42180.33754


Figures (Output of Computation)

Input Parameters & R Code

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