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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, 01 Dec 2009 12:06:31 -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/01/t1259694444icv4s9043gpxn03.htm/, Retrieved Fri, 26 Apr 2024 23:59:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62197, Retrieved Fri, 26 Apr 2024 23:59:18 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact166

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]
-    D        [(Partial) Autocorrelation Function] [SHWWS8methode1a] [2009-11-24 16:42:45] [a66d3a79ef9e5308cd94a469bc5ca464]
-   P             [(Partial) Autocorrelation Function] [SHWWS9] [2009-12-01 19:06:31] [db49399df1e4a3dbe31268849cebfd7f] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
161
149
139
135
130
127
122
117
112
113
149
157
157
147
137
132
125
123
117
114
111
112
144
150
149
134
123
116
117
111
105
102
95
93
124
130
124
115
106
105
105
101
95
93
84
87
116
120
117
109
105
107
109
109
108
107
99
103
131
137

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=62197&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=62197&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62197&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
10.309332.3760.010383
2-0.12174-0.93510.176773
3-0.2552-1.96020.027348
4-0.222591-1.70980.046283
5-0.042904-0.32950.371454
60.0310890.23880.406044
7-0.045659-0.35070.363525
8-0.254355-1.95370.027739
9-0.290511-2.23150.014732
10-0.12641-0.9710.167763
110.2639352.02730.023577
120.7690415.90710
130.2195541.68640.048498
14-0.108686-0.83480.20359
15-0.207097-1.59070.058506
16-0.176355-1.35460.090353
17-0.022245-0.17090.432458
180.0354440.27220.393191
19-0.063693-0.48920.313244
20-0.219336-1.68480.04866
21-0.24596-1.88930.031888
22-0.110262-0.84690.200226
230.2057251.58020.059704
240.5691564.37182.5e-05
250.1426141.09540.138889
26-0.086595-0.66520.254273
27-0.132707-1.01930.156102
28-0.096129-0.73840.231606
290.0071260.05470.478266
300.0142460.10940.456617
31-0.043557-0.33460.369569
32-0.170522-1.30980.09767
33-0.189157-1.45290.075769
34-0.071257-0.54730.293106
350.1455571.1180.134039
360.3577222.74770.003974

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.30933 & 2.376 & 0.010383 \tabularnewline
2 & -0.12174 & -0.9351 & 0.176773 \tabularnewline
3 & -0.2552 & -1.9602 & 0.027348 \tabularnewline
4 & -0.222591 & -1.7098 & 0.046283 \tabularnewline
5 & -0.042904 & -0.3295 & 0.371454 \tabularnewline
6 & 0.031089 & 0.2388 & 0.406044 \tabularnewline
7 & -0.045659 & -0.3507 & 0.363525 \tabularnewline
8 & -0.254355 & -1.9537 & 0.027739 \tabularnewline
9 & -0.290511 & -2.2315 & 0.014732 \tabularnewline
10 & -0.12641 & -0.971 & 0.167763 \tabularnewline
11 & 0.263935 & 2.0273 & 0.023577 \tabularnewline
12 & 0.769041 & 5.9071 & 0 \tabularnewline
13 & 0.219554 & 1.6864 & 0.048498 \tabularnewline
14 & -0.108686 & -0.8348 & 0.20359 \tabularnewline
15 & -0.207097 & -1.5907 & 0.058506 \tabularnewline
16 & -0.176355 & -1.3546 & 0.090353 \tabularnewline
17 & -0.022245 & -0.1709 & 0.432458 \tabularnewline
18 & 0.035444 & 0.2722 & 0.393191 \tabularnewline
19 & -0.063693 & -0.4892 & 0.313244 \tabularnewline
20 & -0.219336 & -1.6848 & 0.04866 \tabularnewline
21 & -0.24596 & -1.8893 & 0.031888 \tabularnewline
22 & -0.110262 & -0.8469 & 0.200226 \tabularnewline
23 & 0.205725 & 1.5802 & 0.059704 \tabularnewline
24 & 0.569156 & 4.3718 & 2.5e-05 \tabularnewline
25 & 0.142614 & 1.0954 & 0.138889 \tabularnewline
26 & -0.086595 & -0.6652 & 0.254273 \tabularnewline
27 & -0.132707 & -1.0193 & 0.156102 \tabularnewline
28 & -0.096129 & -0.7384 & 0.231606 \tabularnewline
29 & 0.007126 & 0.0547 & 0.478266 \tabularnewline
30 & 0.014246 & 0.1094 & 0.456617 \tabularnewline
31 & -0.043557 & -0.3346 & 0.369569 \tabularnewline
32 & -0.170522 & -1.3098 & 0.09767 \tabularnewline
33 & -0.189157 & -1.4529 & 0.075769 \tabularnewline
34 & -0.071257 & -0.5473 & 0.293106 \tabularnewline
35 & 0.145557 & 1.118 & 0.134039 \tabularnewline
36 & 0.357722 & 2.7477 & 0.003974 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62197&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]0.30933[/C][C]2.376[/C][C]0.010383[/C][/ROW]
[ROW][C]2[/C][C]-0.12174[/C][C]-0.9351[/C][C]0.176773[/C][/ROW]
[ROW][C]3[/C][C]-0.2552[/C][C]-1.9602[/C][C]0.027348[/C][/ROW]
[ROW][C]4[/C][C]-0.222591[/C][C]-1.7098[/C][C]0.046283[/C][/ROW]
[ROW][C]5[/C][C]-0.042904[/C][C]-0.3295[/C][C]0.371454[/C][/ROW]
[ROW][C]6[/C][C]0.031089[/C][C]0.2388[/C][C]0.406044[/C][/ROW]
[ROW][C]7[/C][C]-0.045659[/C][C]-0.3507[/C][C]0.363525[/C][/ROW]
[ROW][C]8[/C][C]-0.254355[/C][C]-1.9537[/C][C]0.027739[/C][/ROW]
[ROW][C]9[/C][C]-0.290511[/C][C]-2.2315[/C][C]0.014732[/C][/ROW]
[ROW][C]10[/C][C]-0.12641[/C][C]-0.971[/C][C]0.167763[/C][/ROW]
[ROW][C]11[/C][C]0.263935[/C][C]2.0273[/C][C]0.023577[/C][/ROW]
[ROW][C]12[/C][C]0.769041[/C][C]5.9071[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.219554[/C][C]1.6864[/C][C]0.048498[/C][/ROW]
[ROW][C]14[/C][C]-0.108686[/C][C]-0.8348[/C][C]0.20359[/C][/ROW]
[ROW][C]15[/C][C]-0.207097[/C][C]-1.5907[/C][C]0.058506[/C][/ROW]
[ROW][C]16[/C][C]-0.176355[/C][C]-1.3546[/C][C]0.090353[/C][/ROW]
[ROW][C]17[/C][C]-0.022245[/C][C]-0.1709[/C][C]0.432458[/C][/ROW]
[ROW][C]18[/C][C]0.035444[/C][C]0.2722[/C][C]0.393191[/C][/ROW]
[ROW][C]19[/C][C]-0.063693[/C][C]-0.4892[/C][C]0.313244[/C][/ROW]
[ROW][C]20[/C][C]-0.219336[/C][C]-1.6848[/C][C]0.04866[/C][/ROW]
[ROW][C]21[/C][C]-0.24596[/C][C]-1.8893[/C][C]0.031888[/C][/ROW]
[ROW][C]22[/C][C]-0.110262[/C][C]-0.8469[/C][C]0.200226[/C][/ROW]
[ROW][C]23[/C][C]0.205725[/C][C]1.5802[/C][C]0.059704[/C][/ROW]
[ROW][C]24[/C][C]0.569156[/C][C]4.3718[/C][C]2.5e-05[/C][/ROW]
[ROW][C]25[/C][C]0.142614[/C][C]1.0954[/C][C]0.138889[/C][/ROW]
[ROW][C]26[/C][C]-0.086595[/C][C]-0.6652[/C][C]0.254273[/C][/ROW]
[ROW][C]27[/C][C]-0.132707[/C][C]-1.0193[/C][C]0.156102[/C][/ROW]
[ROW][C]28[/C][C]-0.096129[/C][C]-0.7384[/C][C]0.231606[/C][/ROW]
[ROW][C]29[/C][C]0.007126[/C][C]0.0547[/C][C]0.478266[/C][/ROW]
[ROW][C]30[/C][C]0.014246[/C][C]0.1094[/C][C]0.456617[/C][/ROW]
[ROW][C]31[/C][C]-0.043557[/C][C]-0.3346[/C][C]0.369569[/C][/ROW]
[ROW][C]32[/C][C]-0.170522[/C][C]-1.3098[/C][C]0.09767[/C][/ROW]
[ROW][C]33[/C][C]-0.189157[/C][C]-1.4529[/C][C]0.075769[/C][/ROW]
[ROW][C]34[/C][C]-0.071257[/C][C]-0.5473[/C][C]0.293106[/C][/ROW]
[ROW][C]35[/C][C]0.145557[/C][C]1.118[/C][C]0.134039[/C][/ROW]
[ROW][C]36[/C][C]0.357722[/C][C]2.7477[/C][C]0.003974[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62197&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62197&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
10.309332.3760.010383
2-0.12174-0.93510.176773
3-0.2552-1.96020.027348
4-0.222591-1.70980.046283
5-0.042904-0.32950.371454
60.0310890.23880.406044
7-0.045659-0.35070.363525
8-0.254355-1.95370.027739
9-0.290511-2.23150.014732
10-0.12641-0.9710.167763
110.2639352.02730.023577
120.7690415.90710
130.2195541.68640.048498
14-0.108686-0.83480.20359
15-0.207097-1.59070.058506
16-0.176355-1.35460.090353
17-0.022245-0.17090.432458
180.0354440.27220.393191
19-0.063693-0.48920.313244
20-0.219336-1.68480.04866
21-0.24596-1.88930.031888
22-0.110262-0.84690.200226
230.2057251.58020.059704
240.5691564.37182.5e-05
250.1426141.09540.138889
26-0.086595-0.66520.254273
27-0.132707-1.01930.156102
28-0.096129-0.73840.231606
290.0071260.05470.478266
300.0142460.10940.456617
31-0.043557-0.33460.369569
32-0.170522-1.30980.09767
33-0.189157-1.45290.075769
34-0.071257-0.54730.293106
350.1455571.1180.134039
360.3577222.74770.003974






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.309332.3760.010383
2-0.240431-1.84680.034897
3-0.157405-1.20910.115733
4-0.129439-0.99420.162083
50.0048730.03740.485135
6-0.056315-0.43260.333453
7-0.131604-1.01090.158104
8-0.295422-2.26920.013464
9-0.240339-1.84610.034949
10-0.183027-1.40590.082506
110.1337541.02740.154216
120.6530425.01613e-06
13-0.265082-2.03610.023117
140.0587310.45110.326777
15-0.026045-0.20010.421064
16-0.012721-0.09770.461245
17-0.026329-0.20220.420213
18-0.04229-0.32480.373226
19-0.075171-0.57740.282934
200.1194640.91760.181278
210.0133460.10250.459348
22-0.045375-0.34850.364341
23-0.062213-0.47790.317256
24-0.050834-0.39050.3488
25-0.031706-0.24350.404215
260.0093430.07180.471516
270.0260930.20040.420918
280.0473860.3640.358587
29-0.006159-0.04730.481213
30-0.067127-0.51560.304027
310.1001210.7690.222467
32-0.049631-0.38120.352202
330.0288710.22180.412632
340.026920.20680.418447
35-0.059622-0.4580.324331
36-0.113377-0.87090.193678

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.30933 & 2.376 & 0.010383 \tabularnewline
2 & -0.240431 & -1.8468 & 0.034897 \tabularnewline
3 & -0.157405 & -1.2091 & 0.115733 \tabularnewline
4 & -0.129439 & -0.9942 & 0.162083 \tabularnewline
5 & 0.004873 & 0.0374 & 0.485135 \tabularnewline
6 & -0.056315 & -0.4326 & 0.333453 \tabularnewline
7 & -0.131604 & -1.0109 & 0.158104 \tabularnewline
8 & -0.295422 & -2.2692 & 0.013464 \tabularnewline
9 & -0.240339 & -1.8461 & 0.034949 \tabularnewline
10 & -0.183027 & -1.4059 & 0.082506 \tabularnewline
11 & 0.133754 & 1.0274 & 0.154216 \tabularnewline
12 & 0.653042 & 5.0161 & 3e-06 \tabularnewline
13 & -0.265082 & -2.0361 & 0.023117 \tabularnewline
14 & 0.058731 & 0.4511 & 0.326777 \tabularnewline
15 & -0.026045 & -0.2001 & 0.421064 \tabularnewline
16 & -0.012721 & -0.0977 & 0.461245 \tabularnewline
17 & -0.026329 & -0.2022 & 0.420213 \tabularnewline
18 & -0.04229 & -0.3248 & 0.373226 \tabularnewline
19 & -0.075171 & -0.5774 & 0.282934 \tabularnewline
20 & 0.119464 & 0.9176 & 0.181278 \tabularnewline
21 & 0.013346 & 0.1025 & 0.459348 \tabularnewline
22 & -0.045375 & -0.3485 & 0.364341 \tabularnewline
23 & -0.062213 & -0.4779 & 0.317256 \tabularnewline
24 & -0.050834 & -0.3905 & 0.3488 \tabularnewline
25 & -0.031706 & -0.2435 & 0.404215 \tabularnewline
26 & 0.009343 & 0.0718 & 0.471516 \tabularnewline
27 & 0.026093 & 0.2004 & 0.420918 \tabularnewline
28 & 0.047386 & 0.364 & 0.358587 \tabularnewline
29 & -0.006159 & -0.0473 & 0.481213 \tabularnewline
30 & -0.067127 & -0.5156 & 0.304027 \tabularnewline
31 & 0.100121 & 0.769 & 0.222467 \tabularnewline
32 & -0.049631 & -0.3812 & 0.352202 \tabularnewline
33 & 0.028871 & 0.2218 & 0.412632 \tabularnewline
34 & 0.02692 & 0.2068 & 0.418447 \tabularnewline
35 & -0.059622 & -0.458 & 0.324331 \tabularnewline
36 & -0.113377 & -0.8709 & 0.193678 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62197&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]0.30933[/C][C]2.376[/C][C]0.010383[/C][/ROW]
[ROW][C]2[/C][C]-0.240431[/C][C]-1.8468[/C][C]0.034897[/C][/ROW]
[ROW][C]3[/C][C]-0.157405[/C][C]-1.2091[/C][C]0.115733[/C][/ROW]
[ROW][C]4[/C][C]-0.129439[/C][C]-0.9942[/C][C]0.162083[/C][/ROW]
[ROW][C]5[/C][C]0.004873[/C][C]0.0374[/C][C]0.485135[/C][/ROW]
[ROW][C]6[/C][C]-0.056315[/C][C]-0.4326[/C][C]0.333453[/C][/ROW]
[ROW][C]7[/C][C]-0.131604[/C][C]-1.0109[/C][C]0.158104[/C][/ROW]
[ROW][C]8[/C][C]-0.295422[/C][C]-2.2692[/C][C]0.013464[/C][/ROW]
[ROW][C]9[/C][C]-0.240339[/C][C]-1.8461[/C][C]0.034949[/C][/ROW]
[ROW][C]10[/C][C]-0.183027[/C][C]-1.4059[/C][C]0.082506[/C][/ROW]
[ROW][C]11[/C][C]0.133754[/C][C]1.0274[/C][C]0.154216[/C][/ROW]
[ROW][C]12[/C][C]0.653042[/C][C]5.0161[/C][C]3e-06[/C][/ROW]
[ROW][C]13[/C][C]-0.265082[/C][C]-2.0361[/C][C]0.023117[/C][/ROW]
[ROW][C]14[/C][C]0.058731[/C][C]0.4511[/C][C]0.326777[/C][/ROW]
[ROW][C]15[/C][C]-0.026045[/C][C]-0.2001[/C][C]0.421064[/C][/ROW]
[ROW][C]16[/C][C]-0.012721[/C][C]-0.0977[/C][C]0.461245[/C][/ROW]
[ROW][C]17[/C][C]-0.026329[/C][C]-0.2022[/C][C]0.420213[/C][/ROW]
[ROW][C]18[/C][C]-0.04229[/C][C]-0.3248[/C][C]0.373226[/C][/ROW]
[ROW][C]19[/C][C]-0.075171[/C][C]-0.5774[/C][C]0.282934[/C][/ROW]
[ROW][C]20[/C][C]0.119464[/C][C]0.9176[/C][C]0.181278[/C][/ROW]
[ROW][C]21[/C][C]0.013346[/C][C]0.1025[/C][C]0.459348[/C][/ROW]
[ROW][C]22[/C][C]-0.045375[/C][C]-0.3485[/C][C]0.364341[/C][/ROW]
[ROW][C]23[/C][C]-0.062213[/C][C]-0.4779[/C][C]0.317256[/C][/ROW]
[ROW][C]24[/C][C]-0.050834[/C][C]-0.3905[/C][C]0.3488[/C][/ROW]
[ROW][C]25[/C][C]-0.031706[/C][C]-0.2435[/C][C]0.404215[/C][/ROW]
[ROW][C]26[/C][C]0.009343[/C][C]0.0718[/C][C]0.471516[/C][/ROW]
[ROW][C]27[/C][C]0.026093[/C][C]0.2004[/C][C]0.420918[/C][/ROW]
[ROW][C]28[/C][C]0.047386[/C][C]0.364[/C][C]0.358587[/C][/ROW]
[ROW][C]29[/C][C]-0.006159[/C][C]-0.0473[/C][C]0.481213[/C][/ROW]
[ROW][C]30[/C][C]-0.067127[/C][C]-0.5156[/C][C]0.304027[/C][/ROW]
[ROW][C]31[/C][C]0.100121[/C][C]0.769[/C][C]0.222467[/C][/ROW]
[ROW][C]32[/C][C]-0.049631[/C][C]-0.3812[/C][C]0.352202[/C][/ROW]
[ROW][C]33[/C][C]0.028871[/C][C]0.2218[/C][C]0.412632[/C][/ROW]
[ROW][C]34[/C][C]0.02692[/C][C]0.2068[/C][C]0.418447[/C][/ROW]
[ROW][C]35[/C][C]-0.059622[/C][C]-0.458[/C][C]0.324331[/C][/ROW]
[ROW][C]36[/C][C]-0.113377[/C][C]-0.8709[/C][C]0.193678[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62197&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62197&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
10.309332.3760.010383
2-0.240431-1.84680.034897
3-0.157405-1.20910.115733
4-0.129439-0.99420.162083
50.0048730.03740.485135
6-0.056315-0.43260.333453
7-0.131604-1.01090.158104
8-0.295422-2.26920.013464
9-0.240339-1.84610.034949
10-0.183027-1.40590.082506
110.1337541.02740.154216
120.6530425.01613e-06
13-0.265082-2.03610.023117
140.0587310.45110.326777
15-0.026045-0.20010.421064
16-0.012721-0.09770.461245
17-0.026329-0.20220.420213
18-0.04229-0.32480.373226
19-0.075171-0.57740.282934
200.1194640.91760.181278
210.0133460.10250.459348
22-0.045375-0.34850.364341
23-0.062213-0.47790.317256
24-0.050834-0.39050.3488
25-0.031706-0.24350.404215
260.0093430.07180.471516
270.0260930.20040.420918
280.0473860.3640.358587
29-0.006159-0.04730.481213
30-0.067127-0.51560.304027
310.1001210.7690.222467
32-0.049631-0.38120.352202
330.0288710.22180.412632
340.026920.20680.418447
35-0.059622-0.4580.324331
36-0.113377-0.87090.193678


Figures (Output of Computation)

Input Parameters & R Code

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