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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 computationMon, 14 Dec 2009 03:04:29 -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/14/t126078509293v1ostrhkzit2i.htm/, Retrieved Sun, 05 May 2024 10:29:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=67493, Retrieved Sun, 05 May 2024 10:29:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact133

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] [Ws 8 autocorrelat...] [2009-11-27 12:17:11] [12f02da0296cb21dc23d82ae014a8b71]
-   PD            [(Partial) Autocorrelation Function] [Paper Y3 autocor ...] [2009-12-14 10:04:29] [b653746fe14da1ddc21bd75262e8c46b] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
98.2
96.92
99.06
99.65
99.82
99.99
100.33
99.31
101.1
101.1
100.93
100.85
100.93
99.6
101.88
101.81
102.38
102.74
102.82
101.72
103.47
102.98
102.68
102.9
103.03
101.29
103.69
103.68
104.2
104.08
104.16
103.05
104.66
104.46
104.95
105.85
106.23
104.86
107.44
108.23
108.45
109.39
110.15
109.13
110.28
110.17
109.99
109.26
109.11
107.06
109.53
108.92
109.24
109.12
109
107.23
109.49
109.04
109.02
109.23

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=67493&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=67493&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67493&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
10.9219037.1410
20.8697256.73690
30.8247886.38880
40.7778866.02550
50.7372045.71040
60.7216275.58970
70.6462935.00623e-06
80.5956124.61361.1e-05
90.5543934.29433.3e-05
100.5083033.93730.000109
110.472163.65730.000269
120.4501223.48660.000461
130.3726022.88620.002706
140.311632.41390.009426
150.2617172.02720.023543
160.2062491.59760.057693
170.1604031.24250.109447
180.1373091.06360.145888
190.0700410.54250.294731
200.0254270.1970.422262
21-0.008337-0.06460.474362
22-0.043573-0.33750.368453
23-0.072594-0.56230.287999
24-0.084607-0.65540.25737
25-0.138422-1.07220.14396
26-0.180742-1.40.083328
27-0.208031-1.61140.056171
28-0.236853-1.83470.035758
29-0.25561-1.97990.026151
30-0.261996-2.02940.023429
31-0.302504-2.34320.011226
32-0.333943-2.58670.006066
33-0.354234-2.74390.003998
34-0.379381-2.93870.002336
35-0.389482-3.01690.001871
36-0.38699-2.99760.001977

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.921903 & 7.141 & 0 \tabularnewline
2 & 0.869725 & 6.7369 & 0 \tabularnewline
3 & 0.824788 & 6.3888 & 0 \tabularnewline
4 & 0.777886 & 6.0255 & 0 \tabularnewline
5 & 0.737204 & 5.7104 & 0 \tabularnewline
6 & 0.721627 & 5.5897 & 0 \tabularnewline
7 & 0.646293 & 5.0062 & 3e-06 \tabularnewline
8 & 0.595612 & 4.6136 & 1.1e-05 \tabularnewline
9 & 0.554393 & 4.2943 & 3.3e-05 \tabularnewline
10 & 0.508303 & 3.9373 & 0.000109 \tabularnewline
11 & 0.47216 & 3.6573 & 0.000269 \tabularnewline
12 & 0.450122 & 3.4866 & 0.000461 \tabularnewline
13 & 0.372602 & 2.8862 & 0.002706 \tabularnewline
14 & 0.31163 & 2.4139 & 0.009426 \tabularnewline
15 & 0.261717 & 2.0272 & 0.023543 \tabularnewline
16 & 0.206249 & 1.5976 & 0.057693 \tabularnewline
17 & 0.160403 & 1.2425 & 0.109447 \tabularnewline
18 & 0.137309 & 1.0636 & 0.145888 \tabularnewline
19 & 0.070041 & 0.5425 & 0.294731 \tabularnewline
20 & 0.025427 & 0.197 & 0.422262 \tabularnewline
21 & -0.008337 & -0.0646 & 0.474362 \tabularnewline
22 & -0.043573 & -0.3375 & 0.368453 \tabularnewline
23 & -0.072594 & -0.5623 & 0.287999 \tabularnewline
24 & -0.084607 & -0.6554 & 0.25737 \tabularnewline
25 & -0.138422 & -1.0722 & 0.14396 \tabularnewline
26 & -0.180742 & -1.4 & 0.083328 \tabularnewline
27 & -0.208031 & -1.6114 & 0.056171 \tabularnewline
28 & -0.236853 & -1.8347 & 0.035758 \tabularnewline
29 & -0.25561 & -1.9799 & 0.026151 \tabularnewline
30 & -0.261996 & -2.0294 & 0.023429 \tabularnewline
31 & -0.302504 & -2.3432 & 0.011226 \tabularnewline
32 & -0.333943 & -2.5867 & 0.006066 \tabularnewline
33 & -0.354234 & -2.7439 & 0.003998 \tabularnewline
34 & -0.379381 & -2.9387 & 0.002336 \tabularnewline
35 & -0.389482 & -3.0169 & 0.001871 \tabularnewline
36 & -0.38699 & -2.9976 & 0.001977 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67493&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]0.921903[/C][C]7.141[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.869725[/C][C]6.7369[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.824788[/C][C]6.3888[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.777886[/C][C]6.0255[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.737204[/C][C]5.7104[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.721627[/C][C]5.5897[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.646293[/C][C]5.0062[/C][C]3e-06[/C][/ROW]
[ROW][C]8[/C][C]0.595612[/C][C]4.6136[/C][C]1.1e-05[/C][/ROW]
[ROW][C]9[/C][C]0.554393[/C][C]4.2943[/C][C]3.3e-05[/C][/ROW]
[ROW][C]10[/C][C]0.508303[/C][C]3.9373[/C][C]0.000109[/C][/ROW]
[ROW][C]11[/C][C]0.47216[/C][C]3.6573[/C][C]0.000269[/C][/ROW]
[ROW][C]12[/C][C]0.450122[/C][C]3.4866[/C][C]0.000461[/C][/ROW]
[ROW][C]13[/C][C]0.372602[/C][C]2.8862[/C][C]0.002706[/C][/ROW]
[ROW][C]14[/C][C]0.31163[/C][C]2.4139[/C][C]0.009426[/C][/ROW]
[ROW][C]15[/C][C]0.261717[/C][C]2.0272[/C][C]0.023543[/C][/ROW]
[ROW][C]16[/C][C]0.206249[/C][C]1.5976[/C][C]0.057693[/C][/ROW]
[ROW][C]17[/C][C]0.160403[/C][C]1.2425[/C][C]0.109447[/C][/ROW]
[ROW][C]18[/C][C]0.137309[/C][C]1.0636[/C][C]0.145888[/C][/ROW]
[ROW][C]19[/C][C]0.070041[/C][C]0.5425[/C][C]0.294731[/C][/ROW]
[ROW][C]20[/C][C]0.025427[/C][C]0.197[/C][C]0.422262[/C][/ROW]
[ROW][C]21[/C][C]-0.008337[/C][C]-0.0646[/C][C]0.474362[/C][/ROW]
[ROW][C]22[/C][C]-0.043573[/C][C]-0.3375[/C][C]0.368453[/C][/ROW]
[ROW][C]23[/C][C]-0.072594[/C][C]-0.5623[/C][C]0.287999[/C][/ROW]
[ROW][C]24[/C][C]-0.084607[/C][C]-0.6554[/C][C]0.25737[/C][/ROW]
[ROW][C]25[/C][C]-0.138422[/C][C]-1.0722[/C][C]0.14396[/C][/ROW]
[ROW][C]26[/C][C]-0.180742[/C][C]-1.4[/C][C]0.083328[/C][/ROW]
[ROW][C]27[/C][C]-0.208031[/C][C]-1.6114[/C][C]0.056171[/C][/ROW]
[ROW][C]28[/C][C]-0.236853[/C][C]-1.8347[/C][C]0.035758[/C][/ROW]
[ROW][C]29[/C][C]-0.25561[/C][C]-1.9799[/C][C]0.026151[/C][/ROW]
[ROW][C]30[/C][C]-0.261996[/C][C]-2.0294[/C][C]0.023429[/C][/ROW]
[ROW][C]31[/C][C]-0.302504[/C][C]-2.3432[/C][C]0.011226[/C][/ROW]
[ROW][C]32[/C][C]-0.333943[/C][C]-2.5867[/C][C]0.006066[/C][/ROW]
[ROW][C]33[/C][C]-0.354234[/C][C]-2.7439[/C][C]0.003998[/C][/ROW]
[ROW][C]34[/C][C]-0.379381[/C][C]-2.9387[/C][C]0.002336[/C][/ROW]
[ROW][C]35[/C][C]-0.389482[/C][C]-3.0169[/C][C]0.001871[/C][/ROW]
[ROW][C]36[/C][C]-0.38699[/C][C]-2.9976[/C][C]0.001977[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67493&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67493&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
10.9219037.1410
20.8697256.73690
30.8247886.38880
40.7778866.02550
50.7372045.71040
60.7216275.58970
70.6462935.00623e-06
80.5956124.61361.1e-05
90.5543934.29433.3e-05
100.5083033.93730.000109
110.472163.65730.000269
120.4501223.48660.000461
130.3726022.88620.002706
140.311632.41390.009426
150.2617172.02720.023543
160.2062491.59760.057693
170.1604031.24250.109447
180.1373091.06360.145888
190.0700410.54250.294731
200.0254270.1970.422262
21-0.008337-0.06460.474362
22-0.043573-0.33750.368453
23-0.072594-0.56230.287999
24-0.084607-0.65540.25737
25-0.138422-1.07220.14396
26-0.180742-1.40.083328
27-0.208031-1.61140.056171
28-0.236853-1.83470.035758
29-0.25561-1.97990.026151
30-0.261996-2.02940.023429
31-0.302504-2.34320.011226
32-0.333943-2.58670.006066
33-0.354234-2.74390.003998
34-0.379381-2.93870.002336
35-0.389482-3.01690.001871
36-0.38699-2.99760.001977






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9219037.1410
20.1320421.02280.155257
30.0483270.37430.354736
4-0.017564-0.13610.446117
50.018590.1440.442992
60.1608381.24580.108833
7-0.362051-2.80440.003391
80.0488420.37830.35326
90.0344410.26680.395277
10-0.026215-0.20310.419886
110.0422630.32740.372266
12-0.007708-0.05970.476293
13-0.249149-1.92990.029176
14-0.055298-0.42830.334969
15-0.001091-0.00840.496644
16-0.034758-0.26920.394337
17-0.014631-0.11330.455073
180.0591710.45830.324183
19-0.122452-0.94850.173337
200.0247680.19180.424254
210.0023340.01810.492818
220.0121930.09440.462534
23-0.014473-0.11210.455555
24-0.00487-0.03770.485015
25-0.091396-0.7080.240859
26-0.077958-0.60390.274106
270.0241480.18710.426126
280.0020620.0160.493656
290.0145760.11290.455241
30-0.037569-0.2910.386026
31-0.071455-0.55350.290993
32-0.058039-0.44960.327321
33-0.049838-0.3860.350415
34-0.042736-0.3310.370886
350.0352140.27280.392985
36-0.002785-0.02160.491431

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.921903 & 7.141 & 0 \tabularnewline
2 & 0.132042 & 1.0228 & 0.155257 \tabularnewline
3 & 0.048327 & 0.3743 & 0.354736 \tabularnewline
4 & -0.017564 & -0.1361 & 0.446117 \tabularnewline
5 & 0.01859 & 0.144 & 0.442992 \tabularnewline
6 & 0.160838 & 1.2458 & 0.108833 \tabularnewline
7 & -0.362051 & -2.8044 & 0.003391 \tabularnewline
8 & 0.048842 & 0.3783 & 0.35326 \tabularnewline
9 & 0.034441 & 0.2668 & 0.395277 \tabularnewline
10 & -0.026215 & -0.2031 & 0.419886 \tabularnewline
11 & 0.042263 & 0.3274 & 0.372266 \tabularnewline
12 & -0.007708 & -0.0597 & 0.476293 \tabularnewline
13 & -0.249149 & -1.9299 & 0.029176 \tabularnewline
14 & -0.055298 & -0.4283 & 0.334969 \tabularnewline
15 & -0.001091 & -0.0084 & 0.496644 \tabularnewline
16 & -0.034758 & -0.2692 & 0.394337 \tabularnewline
17 & -0.014631 & -0.1133 & 0.455073 \tabularnewline
18 & 0.059171 & 0.4583 & 0.324183 \tabularnewline
19 & -0.122452 & -0.9485 & 0.173337 \tabularnewline
20 & 0.024768 & 0.1918 & 0.424254 \tabularnewline
21 & 0.002334 & 0.0181 & 0.492818 \tabularnewline
22 & 0.012193 & 0.0944 & 0.462534 \tabularnewline
23 & -0.014473 & -0.1121 & 0.455555 \tabularnewline
24 & -0.00487 & -0.0377 & 0.485015 \tabularnewline
25 & -0.091396 & -0.708 & 0.240859 \tabularnewline
26 & -0.077958 & -0.6039 & 0.274106 \tabularnewline
27 & 0.024148 & 0.1871 & 0.426126 \tabularnewline
28 & 0.002062 & 0.016 & 0.493656 \tabularnewline
29 & 0.014576 & 0.1129 & 0.455241 \tabularnewline
30 & -0.037569 & -0.291 & 0.386026 \tabularnewline
31 & -0.071455 & -0.5535 & 0.290993 \tabularnewline
32 & -0.058039 & -0.4496 & 0.327321 \tabularnewline
33 & -0.049838 & -0.386 & 0.350415 \tabularnewline
34 & -0.042736 & -0.331 & 0.370886 \tabularnewline
35 & 0.035214 & 0.2728 & 0.392985 \tabularnewline
36 & -0.002785 & -0.0216 & 0.491431 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67493&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]0.921903[/C][C]7.141[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.132042[/C][C]1.0228[/C][C]0.155257[/C][/ROW]
[ROW][C]3[/C][C]0.048327[/C][C]0.3743[/C][C]0.354736[/C][/ROW]
[ROW][C]4[/C][C]-0.017564[/C][C]-0.1361[/C][C]0.446117[/C][/ROW]
[ROW][C]5[/C][C]0.01859[/C][C]0.144[/C][C]0.442992[/C][/ROW]
[ROW][C]6[/C][C]0.160838[/C][C]1.2458[/C][C]0.108833[/C][/ROW]
[ROW][C]7[/C][C]-0.362051[/C][C]-2.8044[/C][C]0.003391[/C][/ROW]
[ROW][C]8[/C][C]0.048842[/C][C]0.3783[/C][C]0.35326[/C][/ROW]
[ROW][C]9[/C][C]0.034441[/C][C]0.2668[/C][C]0.395277[/C][/ROW]
[ROW][C]10[/C][C]-0.026215[/C][C]-0.2031[/C][C]0.419886[/C][/ROW]
[ROW][C]11[/C][C]0.042263[/C][C]0.3274[/C][C]0.372266[/C][/ROW]
[ROW][C]12[/C][C]-0.007708[/C][C]-0.0597[/C][C]0.476293[/C][/ROW]
[ROW][C]13[/C][C]-0.249149[/C][C]-1.9299[/C][C]0.029176[/C][/ROW]
[ROW][C]14[/C][C]-0.055298[/C][C]-0.4283[/C][C]0.334969[/C][/ROW]
[ROW][C]15[/C][C]-0.001091[/C][C]-0.0084[/C][C]0.496644[/C][/ROW]
[ROW][C]16[/C][C]-0.034758[/C][C]-0.2692[/C][C]0.394337[/C][/ROW]
[ROW][C]17[/C][C]-0.014631[/C][C]-0.1133[/C][C]0.455073[/C][/ROW]
[ROW][C]18[/C][C]0.059171[/C][C]0.4583[/C][C]0.324183[/C][/ROW]
[ROW][C]19[/C][C]-0.122452[/C][C]-0.9485[/C][C]0.173337[/C][/ROW]
[ROW][C]20[/C][C]0.024768[/C][C]0.1918[/C][C]0.424254[/C][/ROW]
[ROW][C]21[/C][C]0.002334[/C][C]0.0181[/C][C]0.492818[/C][/ROW]
[ROW][C]22[/C][C]0.012193[/C][C]0.0944[/C][C]0.462534[/C][/ROW]
[ROW][C]23[/C][C]-0.014473[/C][C]-0.1121[/C][C]0.455555[/C][/ROW]
[ROW][C]24[/C][C]-0.00487[/C][C]-0.0377[/C][C]0.485015[/C][/ROW]
[ROW][C]25[/C][C]-0.091396[/C][C]-0.708[/C][C]0.240859[/C][/ROW]
[ROW][C]26[/C][C]-0.077958[/C][C]-0.6039[/C][C]0.274106[/C][/ROW]
[ROW][C]27[/C][C]0.024148[/C][C]0.1871[/C][C]0.426126[/C][/ROW]
[ROW][C]28[/C][C]0.002062[/C][C]0.016[/C][C]0.493656[/C][/ROW]
[ROW][C]29[/C][C]0.014576[/C][C]0.1129[/C][C]0.455241[/C][/ROW]
[ROW][C]30[/C][C]-0.037569[/C][C]-0.291[/C][C]0.386026[/C][/ROW]
[ROW][C]31[/C][C]-0.071455[/C][C]-0.5535[/C][C]0.290993[/C][/ROW]
[ROW][C]32[/C][C]-0.058039[/C][C]-0.4496[/C][C]0.327321[/C][/ROW]
[ROW][C]33[/C][C]-0.049838[/C][C]-0.386[/C][C]0.350415[/C][/ROW]
[ROW][C]34[/C][C]-0.042736[/C][C]-0.331[/C][C]0.370886[/C][/ROW]
[ROW][C]35[/C][C]0.035214[/C][C]0.2728[/C][C]0.392985[/C][/ROW]
[ROW][C]36[/C][C]-0.002785[/C][C]-0.0216[/C][C]0.491431[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67493&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67493&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
10.9219037.1410
20.1320421.02280.155257
30.0483270.37430.354736
4-0.017564-0.13610.446117
50.018590.1440.442992
60.1608381.24580.108833
7-0.362051-2.80440.003391
80.0488420.37830.35326
90.0344410.26680.395277
10-0.026215-0.20310.419886
110.0422630.32740.372266
12-0.007708-0.05970.476293
13-0.249149-1.92990.029176
14-0.055298-0.42830.334969
15-0.001091-0.00840.496644
16-0.034758-0.26920.394337
17-0.014631-0.11330.455073
180.0591710.45830.324183
19-0.122452-0.94850.173337
200.0247680.19180.424254
210.0023340.01810.492818
220.0121930.09440.462534
23-0.014473-0.11210.455555
24-0.00487-0.03770.485015
25-0.091396-0.7080.240859
26-0.077958-0.60390.274106
270.0241480.18710.426126
280.0020620.0160.493656
290.0145760.11290.455241
30-0.037569-0.2910.386026
31-0.071455-0.55350.290993
32-0.058039-0.44960.327321
33-0.049838-0.3860.350415
34-0.042736-0.3310.370886
350.0352140.27280.392985
36-0.002785-0.02160.491431


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0 ; par2 = 36 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 0 ; 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')