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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 08:59:07 -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/t1261065723j8ivob8g3axylcd.htm/, Retrieved Tue, 30 Apr 2024 04:07:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=68964, Retrieved Tue, 30 Apr 2024 04:07:36 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsws 8 d=1 en D=1
Estimated Impact142
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]
-    D        [(Partial) Autocorrelation Function] [Ws8 method 1 link 3] [2009-11-25 11:51:12] [616e2df490b611f6cb7080068870ecbd]
-   P           [(Partial) Autocorrelation Function] [Ws8 method 1 3de ...] [2009-11-25 11:56:04] [616e2df490b611f6cb7080068870ecbd]
-   P               [(Partial) Autocorrelation Function] [ws 8 d=1 en D=1] [2009-12-17 15:59:07] [88e98f4c87ea17c4967db8279bda8533] [Current]
-   P                 [(Partial) Autocorrelation Function] [ws 8 d=1 en D=0] [2009-12-17 18:57:18] [616e2df490b611f6cb7080068870ecbd]
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Dataseries X:
8.2
8.0
7.5
6.8
6.5
6.6
7.6
8.0
8.1
7.7
7.5
7.6
7.8
7.8
7.8
7.5
7.5
7.1
7.5
7.5
7.6
7.7
7.7
7.9
8.1
8.2
8.2
8.2
7.9
7.3
6.9
6.6
6.7
6.9
7.0
7.1
7.2
7.1
6.9
7.0
6.8
6.4
6.7
6.6
6.4
6.3
6.2
6.5
6.8
6.8
6.4
6.1
5.8
6.1
7.2
7.3
6.9
6.1
5.8
6.2
7.1
7.7
7.9
7.7
7.4
7.5
8.0
8.1




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=68964&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=68964&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68964&T=0

As an alternative you can also use a 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
10.5243513.88870.000137
2-0.04633-0.34360.366231
3-0.517702-3.83940.00016
4-0.506856-3.75890.000207
5-0.148877-1.10410.137178
60.1889591.40140.083362
70.2593761.92360.029795
80.1000640.74210.230595
9-0.090615-0.6720.252193
10-0.127753-0.94740.17378
110.0342750.25420.400148
120.0663780.49230.312244
130.1199960.88990.188694
140.0183360.1360.446164
15-0.091256-0.67680.250695
16-0.183816-1.36320.089184
17-0.162938-1.20840.116035
18-0.009284-0.06880.47268
190.1311760.97280.167449
200.2557711.89690.031552
210.1967551.45920.075103
22-0.016062-0.11910.452808
23-0.296822-2.20130.015965
24-0.376551-2.79260.00359
25-0.177013-1.31280.097357
260.1139030.84470.200961
270.258771.91910.030084
280.1794821.33110.094328
29-0.006427-0.04770.481078
30-0.201694-1.49580.070211
31-0.140454-1.04160.151069
32-0.027706-0.20550.418981
330.0964490.71530.23873
340.0176530.13090.448159
35-0.074156-0.550.292289
36-0.136335-1.01110.158201

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.524351 & 3.8887 & 0.000137 \tabularnewline
2 & -0.04633 & -0.3436 & 0.366231 \tabularnewline
3 & -0.517702 & -3.8394 & 0.00016 \tabularnewline
4 & -0.506856 & -3.7589 & 0.000207 \tabularnewline
5 & -0.148877 & -1.1041 & 0.137178 \tabularnewline
6 & 0.188959 & 1.4014 & 0.083362 \tabularnewline
7 & 0.259376 & 1.9236 & 0.029795 \tabularnewline
8 & 0.100064 & 0.7421 & 0.230595 \tabularnewline
9 & -0.090615 & -0.672 & 0.252193 \tabularnewline
10 & -0.127753 & -0.9474 & 0.17378 \tabularnewline
11 & 0.034275 & 0.2542 & 0.400148 \tabularnewline
12 & 0.066378 & 0.4923 & 0.312244 \tabularnewline
13 & 0.119996 & 0.8899 & 0.188694 \tabularnewline
14 & 0.018336 & 0.136 & 0.446164 \tabularnewline
15 & -0.091256 & -0.6768 & 0.250695 \tabularnewline
16 & -0.183816 & -1.3632 & 0.089184 \tabularnewline
17 & -0.162938 & -1.2084 & 0.116035 \tabularnewline
18 & -0.009284 & -0.0688 & 0.47268 \tabularnewline
19 & 0.131176 & 0.9728 & 0.167449 \tabularnewline
20 & 0.255771 & 1.8969 & 0.031552 \tabularnewline
21 & 0.196755 & 1.4592 & 0.075103 \tabularnewline
22 & -0.016062 & -0.1191 & 0.452808 \tabularnewline
23 & -0.296822 & -2.2013 & 0.015965 \tabularnewline
24 & -0.376551 & -2.7926 & 0.00359 \tabularnewline
25 & -0.177013 & -1.3128 & 0.097357 \tabularnewline
26 & 0.113903 & 0.8447 & 0.200961 \tabularnewline
27 & 0.25877 & 1.9191 & 0.030084 \tabularnewline
28 & 0.179482 & 1.3311 & 0.094328 \tabularnewline
29 & -0.006427 & -0.0477 & 0.481078 \tabularnewline
30 & -0.201694 & -1.4958 & 0.070211 \tabularnewline
31 & -0.140454 & -1.0416 & 0.151069 \tabularnewline
32 & -0.027706 & -0.2055 & 0.418981 \tabularnewline
33 & 0.096449 & 0.7153 & 0.23873 \tabularnewline
34 & 0.017653 & 0.1309 & 0.448159 \tabularnewline
35 & -0.074156 & -0.55 & 0.292289 \tabularnewline
36 & -0.136335 & -1.0111 & 0.158201 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68964&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]0.524351[/C][C]3.8887[/C][C]0.000137[/C][/ROW]
[ROW][C]2[/C][C]-0.04633[/C][C]-0.3436[/C][C]0.366231[/C][/ROW]
[ROW][C]3[/C][C]-0.517702[/C][C]-3.8394[/C][C]0.00016[/C][/ROW]
[ROW][C]4[/C][C]-0.506856[/C][C]-3.7589[/C][C]0.000207[/C][/ROW]
[ROW][C]5[/C][C]-0.148877[/C][C]-1.1041[/C][C]0.137178[/C][/ROW]
[ROW][C]6[/C][C]0.188959[/C][C]1.4014[/C][C]0.083362[/C][/ROW]
[ROW][C]7[/C][C]0.259376[/C][C]1.9236[/C][C]0.029795[/C][/ROW]
[ROW][C]8[/C][C]0.100064[/C][C]0.7421[/C][C]0.230595[/C][/ROW]
[ROW][C]9[/C][C]-0.090615[/C][C]-0.672[/C][C]0.252193[/C][/ROW]
[ROW][C]10[/C][C]-0.127753[/C][C]-0.9474[/C][C]0.17378[/C][/ROW]
[ROW][C]11[/C][C]0.034275[/C][C]0.2542[/C][C]0.400148[/C][/ROW]
[ROW][C]12[/C][C]0.066378[/C][C]0.4923[/C][C]0.312244[/C][/ROW]
[ROW][C]13[/C][C]0.119996[/C][C]0.8899[/C][C]0.188694[/C][/ROW]
[ROW][C]14[/C][C]0.018336[/C][C]0.136[/C][C]0.446164[/C][/ROW]
[ROW][C]15[/C][C]-0.091256[/C][C]-0.6768[/C][C]0.250695[/C][/ROW]
[ROW][C]16[/C][C]-0.183816[/C][C]-1.3632[/C][C]0.089184[/C][/ROW]
[ROW][C]17[/C][C]-0.162938[/C][C]-1.2084[/C][C]0.116035[/C][/ROW]
[ROW][C]18[/C][C]-0.009284[/C][C]-0.0688[/C][C]0.47268[/C][/ROW]
[ROW][C]19[/C][C]0.131176[/C][C]0.9728[/C][C]0.167449[/C][/ROW]
[ROW][C]20[/C][C]0.255771[/C][C]1.8969[/C][C]0.031552[/C][/ROW]
[ROW][C]21[/C][C]0.196755[/C][C]1.4592[/C][C]0.075103[/C][/ROW]
[ROW][C]22[/C][C]-0.016062[/C][C]-0.1191[/C][C]0.452808[/C][/ROW]
[ROW][C]23[/C][C]-0.296822[/C][C]-2.2013[/C][C]0.015965[/C][/ROW]
[ROW][C]24[/C][C]-0.376551[/C][C]-2.7926[/C][C]0.00359[/C][/ROW]
[ROW][C]25[/C][C]-0.177013[/C][C]-1.3128[/C][C]0.097357[/C][/ROW]
[ROW][C]26[/C][C]0.113903[/C][C]0.8447[/C][C]0.200961[/C][/ROW]
[ROW][C]27[/C][C]0.25877[/C][C]1.9191[/C][C]0.030084[/C][/ROW]
[ROW][C]28[/C][C]0.179482[/C][C]1.3311[/C][C]0.094328[/C][/ROW]
[ROW][C]29[/C][C]-0.006427[/C][C]-0.0477[/C][C]0.481078[/C][/ROW]
[ROW][C]30[/C][C]-0.201694[/C][C]-1.4958[/C][C]0.070211[/C][/ROW]
[ROW][C]31[/C][C]-0.140454[/C][C]-1.0416[/C][C]0.151069[/C][/ROW]
[ROW][C]32[/C][C]-0.027706[/C][C]-0.2055[/C][C]0.418981[/C][/ROW]
[ROW][C]33[/C][C]0.096449[/C][C]0.7153[/C][C]0.23873[/C][/ROW]
[ROW][C]34[/C][C]0.017653[/C][C]0.1309[/C][C]0.448159[/C][/ROW]
[ROW][C]35[/C][C]-0.074156[/C][C]-0.55[/C][C]0.292289[/C][/ROW]
[ROW][C]36[/C][C]-0.136335[/C][C]-1.0111[/C][C]0.158201[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68964&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68964&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.5243513.88870.000137
2-0.04633-0.34360.366231
3-0.517702-3.83940.00016
4-0.506856-3.75890.000207
5-0.148877-1.10410.137178
60.1889591.40140.083362
70.2593761.92360.029795
80.1000640.74210.230595
9-0.090615-0.6720.252193
10-0.127753-0.94740.17378
110.0342750.25420.400148
120.0663780.49230.312244
130.1199960.88990.188694
140.0183360.1360.446164
15-0.091256-0.67680.250695
16-0.183816-1.36320.089184
17-0.162938-1.20840.116035
18-0.009284-0.06880.47268
190.1311760.97280.167449
200.2557711.89690.031552
210.1967551.45920.075103
22-0.016062-0.11910.452808
23-0.296822-2.20130.015965
24-0.376551-2.79260.00359
25-0.177013-1.31280.097357
260.1139030.84470.200961
270.258771.91910.030084
280.1794821.33110.094328
29-0.006427-0.04770.481078
30-0.201694-1.49580.070211
31-0.140454-1.04160.151069
32-0.027706-0.20550.418981
330.0964490.71530.23873
340.0176530.13090.448159
35-0.074156-0.550.292289
36-0.136335-1.01110.158201







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.5243513.88870.000137
2-0.443104-3.28610.000886
3-0.429557-3.18570.00119
40.0128710.09550.46215
50.1129530.83770.202918
6-0.087713-0.65050.259039
7-0.152186-1.12860.131974
8-0.031331-0.23240.40856
90.028380.21050.417039
100.0331950.24620.403231
110.1325450.9830.164961
12-0.207881-1.54170.064442
130.1645181.22010.113817
140.0511930.37970.352832
15-0.11138-0.8260.206182
16-0.170882-1.26730.105195
17-0.010029-0.07440.470491
180.1302820.96620.169088
19-0.048817-0.3620.359357
200.1255130.93080.178005
210.0034820.02580.489746
22-0.149483-1.10860.136215
23-0.129278-0.95870.170941
24-0.091558-0.6790.249988
250.104750.77680.220289
26-0.095431-0.70770.241049
27-0.127032-0.94210.175133
28-0.044007-0.32640.372695
290.068060.50470.307876
30-0.106516-0.78990.216476
31-0.05331-0.39540.347053
32-0.092992-0.68960.246657
33-0.007888-0.05850.476781
34-0.142056-1.05350.148356
35-0.016582-0.1230.451286
36-0.121532-0.90130.185678

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.524351 & 3.8887 & 0.000137 \tabularnewline
2 & -0.443104 & -3.2861 & 0.000886 \tabularnewline
3 & -0.429557 & -3.1857 & 0.00119 \tabularnewline
4 & 0.012871 & 0.0955 & 0.46215 \tabularnewline
5 & 0.112953 & 0.8377 & 0.202918 \tabularnewline
6 & -0.087713 & -0.6505 & 0.259039 \tabularnewline
7 & -0.152186 & -1.1286 & 0.131974 \tabularnewline
8 & -0.031331 & -0.2324 & 0.40856 \tabularnewline
9 & 0.02838 & 0.2105 & 0.417039 \tabularnewline
10 & 0.033195 & 0.2462 & 0.403231 \tabularnewline
11 & 0.132545 & 0.983 & 0.164961 \tabularnewline
12 & -0.207881 & -1.5417 & 0.064442 \tabularnewline
13 & 0.164518 & 1.2201 & 0.113817 \tabularnewline
14 & 0.051193 & 0.3797 & 0.352832 \tabularnewline
15 & -0.11138 & -0.826 & 0.206182 \tabularnewline
16 & -0.170882 & -1.2673 & 0.105195 \tabularnewline
17 & -0.010029 & -0.0744 & 0.470491 \tabularnewline
18 & 0.130282 & 0.9662 & 0.169088 \tabularnewline
19 & -0.048817 & -0.362 & 0.359357 \tabularnewline
20 & 0.125513 & 0.9308 & 0.178005 \tabularnewline
21 & 0.003482 & 0.0258 & 0.489746 \tabularnewline
22 & -0.149483 & -1.1086 & 0.136215 \tabularnewline
23 & -0.129278 & -0.9587 & 0.170941 \tabularnewline
24 & -0.091558 & -0.679 & 0.249988 \tabularnewline
25 & 0.10475 & 0.7768 & 0.220289 \tabularnewline
26 & -0.095431 & -0.7077 & 0.241049 \tabularnewline
27 & -0.127032 & -0.9421 & 0.175133 \tabularnewline
28 & -0.044007 & -0.3264 & 0.372695 \tabularnewline
29 & 0.06806 & 0.5047 & 0.307876 \tabularnewline
30 & -0.106516 & -0.7899 & 0.216476 \tabularnewline
31 & -0.05331 & -0.3954 & 0.347053 \tabularnewline
32 & -0.092992 & -0.6896 & 0.246657 \tabularnewline
33 & -0.007888 & -0.0585 & 0.476781 \tabularnewline
34 & -0.142056 & -1.0535 & 0.148356 \tabularnewline
35 & -0.016582 & -0.123 & 0.451286 \tabularnewline
36 & -0.121532 & -0.9013 & 0.185678 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68964&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]0.524351[/C][C]3.8887[/C][C]0.000137[/C][/ROW]
[ROW][C]2[/C][C]-0.443104[/C][C]-3.2861[/C][C]0.000886[/C][/ROW]
[ROW][C]3[/C][C]-0.429557[/C][C]-3.1857[/C][C]0.00119[/C][/ROW]
[ROW][C]4[/C][C]0.012871[/C][C]0.0955[/C][C]0.46215[/C][/ROW]
[ROW][C]5[/C][C]0.112953[/C][C]0.8377[/C][C]0.202918[/C][/ROW]
[ROW][C]6[/C][C]-0.087713[/C][C]-0.6505[/C][C]0.259039[/C][/ROW]
[ROW][C]7[/C][C]-0.152186[/C][C]-1.1286[/C][C]0.131974[/C][/ROW]
[ROW][C]8[/C][C]-0.031331[/C][C]-0.2324[/C][C]0.40856[/C][/ROW]
[ROW][C]9[/C][C]0.02838[/C][C]0.2105[/C][C]0.417039[/C][/ROW]
[ROW][C]10[/C][C]0.033195[/C][C]0.2462[/C][C]0.403231[/C][/ROW]
[ROW][C]11[/C][C]0.132545[/C][C]0.983[/C][C]0.164961[/C][/ROW]
[ROW][C]12[/C][C]-0.207881[/C][C]-1.5417[/C][C]0.064442[/C][/ROW]
[ROW][C]13[/C][C]0.164518[/C][C]1.2201[/C][C]0.113817[/C][/ROW]
[ROW][C]14[/C][C]0.051193[/C][C]0.3797[/C][C]0.352832[/C][/ROW]
[ROW][C]15[/C][C]-0.11138[/C][C]-0.826[/C][C]0.206182[/C][/ROW]
[ROW][C]16[/C][C]-0.170882[/C][C]-1.2673[/C][C]0.105195[/C][/ROW]
[ROW][C]17[/C][C]-0.010029[/C][C]-0.0744[/C][C]0.470491[/C][/ROW]
[ROW][C]18[/C][C]0.130282[/C][C]0.9662[/C][C]0.169088[/C][/ROW]
[ROW][C]19[/C][C]-0.048817[/C][C]-0.362[/C][C]0.359357[/C][/ROW]
[ROW][C]20[/C][C]0.125513[/C][C]0.9308[/C][C]0.178005[/C][/ROW]
[ROW][C]21[/C][C]0.003482[/C][C]0.0258[/C][C]0.489746[/C][/ROW]
[ROW][C]22[/C][C]-0.149483[/C][C]-1.1086[/C][C]0.136215[/C][/ROW]
[ROW][C]23[/C][C]-0.129278[/C][C]-0.9587[/C][C]0.170941[/C][/ROW]
[ROW][C]24[/C][C]-0.091558[/C][C]-0.679[/C][C]0.249988[/C][/ROW]
[ROW][C]25[/C][C]0.10475[/C][C]0.7768[/C][C]0.220289[/C][/ROW]
[ROW][C]26[/C][C]-0.095431[/C][C]-0.7077[/C][C]0.241049[/C][/ROW]
[ROW][C]27[/C][C]-0.127032[/C][C]-0.9421[/C][C]0.175133[/C][/ROW]
[ROW][C]28[/C][C]-0.044007[/C][C]-0.3264[/C][C]0.372695[/C][/ROW]
[ROW][C]29[/C][C]0.06806[/C][C]0.5047[/C][C]0.307876[/C][/ROW]
[ROW][C]30[/C][C]-0.106516[/C][C]-0.7899[/C][C]0.216476[/C][/ROW]
[ROW][C]31[/C][C]-0.05331[/C][C]-0.3954[/C][C]0.347053[/C][/ROW]
[ROW][C]32[/C][C]-0.092992[/C][C]-0.6896[/C][C]0.246657[/C][/ROW]
[ROW][C]33[/C][C]-0.007888[/C][C]-0.0585[/C][C]0.476781[/C][/ROW]
[ROW][C]34[/C][C]-0.142056[/C][C]-1.0535[/C][C]0.148356[/C][/ROW]
[ROW][C]35[/C][C]-0.016582[/C][C]-0.123[/C][C]0.451286[/C][/ROW]
[ROW][C]36[/C][C]-0.121532[/C][C]-0.9013[/C][C]0.185678[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68964&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68964&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.5243513.88870.000137
2-0.443104-3.28610.000886
3-0.429557-3.18570.00119
40.0128710.09550.46215
50.1129530.83770.202918
6-0.087713-0.65050.259039
7-0.152186-1.12860.131974
8-0.031331-0.23240.40856
90.028380.21050.417039
100.0331950.24620.403231
110.1325450.9830.164961
12-0.207881-1.54170.064442
130.1645181.22010.113817
140.0511930.37970.352832
15-0.11138-0.8260.206182
16-0.170882-1.26730.105195
17-0.010029-0.07440.470491
180.1302820.96620.169088
19-0.048817-0.3620.359357
200.1255130.93080.178005
210.0034820.02580.489746
22-0.149483-1.10860.136215
23-0.129278-0.95870.170941
24-0.091558-0.6790.249988
250.104750.77680.220289
26-0.095431-0.70770.241049
27-0.127032-0.94210.175133
28-0.044007-0.32640.372695
290.068060.50470.307876
30-0.106516-0.78990.216476
31-0.05331-0.39540.347053
32-0.092992-0.68960.246657
33-0.007888-0.05850.476781
34-0.142056-1.05350.148356
35-0.016582-0.1230.451286
36-0.121532-0.90130.185678



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')