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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 computationFri, 28 Nov 2008 03:12:46 -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/2008/Nov/28/t122786723755la004vk5bf541.htm/, Retrieved Tue, 28 May 2024 09:13:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=25978, Retrieved Tue, 28 May 2024 09:13:24 +0000
QR Codes:

Original text written by user:d=0 D=0
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact213
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Law of Averages] [Random Walk Simul...] [2008-11-25 18:40:39] [b98453cac15ba1066b407e146608df68]
F       [Law of Averages] [Random Walk Simul...] [2008-11-27 19:45:04] [58bf45a666dc5198906262e8815a9722]
F RMPD    [Standard Deviation-Mean Plot] [Standard Deviatio...] [2008-11-27 22:08:29] [58bf45a666dc5198906262e8815a9722]
- RMP       [(Partial) Autocorrelation Function] [(Partial) Autocor...] [2008-11-27 22:25:58] [58bf45a666dc5198906262e8815a9722]
F   P           [(Partial) Autocorrelation Function] [(Partial) Autocor...] [2008-11-28 10:12:46] [63db34dadd44fb018112addcdefe949f] [Current]
Feedback Forum
2008-12-04 15:31:34 [Matthieu Blondeau] [reply
Men moet de 'd' en 'D' veranderen om zo de reeks stationair te maken. Dit is correct.

Post a new message
Dataseries X:
106
82
114
118
105
105
103
107
123
112
104
122
108
94
120
118
117
113
106
108
122
115
110
120
104
96
121
111
120
114
107
108
127
105
119
121
106
97
119
122
121
106
114
112
127
109
118
123
115
105
116
131
121
104
127
126
124
132
117
123




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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 & 0 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=25978&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]0 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=25978&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=25978&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 time0 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.0952470.73780.231763
2-0.150608-1.16660.123993
30.1686791.30660.09817
40.1589391.23110.111538
50.105490.81710.208546
60.2669652.06790.021485
7-0.024652-0.1910.424604
80.1146060.88770.189114
90.0574140.44470.32906
10-0.210477-1.63030.054134
110.0391410.30320.381399
120.5284964.09376.4e-05
13-0.011068-0.08570.465982
14-0.171496-1.32840.094537
15-0.018534-0.14360.443163
160.0068620.05320.478893
170.0433670.33590.369051
180.1287130.9970.161383
19-0.037511-0.29060.386195
200.0317760.24610.403209
21-0.051618-0.39980.34535
22-0.191641-1.48440.071463
230.0984870.76290.224264
240.2735452.11890.019125
25-0.022418-0.17360.431363
26-0.110219-0.85380.198319
27-0.069911-0.54150.295075
280.0125980.09760.461295
29-0.007526-0.05830.476852
30-0.003139-0.02430.49034
31-0.017045-0.1320.447701
32-4e-05-3e-040.499876
33-0.095388-0.73890.231434
34-0.161032-1.24730.108558
350.0179510.1390.44494
360.1941561.50390.068923

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.095247 & 0.7378 & 0.231763 \tabularnewline
2 & -0.150608 & -1.1666 & 0.123993 \tabularnewline
3 & 0.168679 & 1.3066 & 0.09817 \tabularnewline
4 & 0.158939 & 1.2311 & 0.111538 \tabularnewline
5 & 0.10549 & 0.8171 & 0.208546 \tabularnewline
6 & 0.266965 & 2.0679 & 0.021485 \tabularnewline
7 & -0.024652 & -0.191 & 0.424604 \tabularnewline
8 & 0.114606 & 0.8877 & 0.189114 \tabularnewline
9 & 0.057414 & 0.4447 & 0.32906 \tabularnewline
10 & -0.210477 & -1.6303 & 0.054134 \tabularnewline
11 & 0.039141 & 0.3032 & 0.381399 \tabularnewline
12 & 0.528496 & 4.0937 & 6.4e-05 \tabularnewline
13 & -0.011068 & -0.0857 & 0.465982 \tabularnewline
14 & -0.171496 & -1.3284 & 0.094537 \tabularnewline
15 & -0.018534 & -0.1436 & 0.443163 \tabularnewline
16 & 0.006862 & 0.0532 & 0.478893 \tabularnewline
17 & 0.043367 & 0.3359 & 0.369051 \tabularnewline
18 & 0.128713 & 0.997 & 0.161383 \tabularnewline
19 & -0.037511 & -0.2906 & 0.386195 \tabularnewline
20 & 0.031776 & 0.2461 & 0.403209 \tabularnewline
21 & -0.051618 & -0.3998 & 0.34535 \tabularnewline
22 & -0.191641 & -1.4844 & 0.071463 \tabularnewline
23 & 0.098487 & 0.7629 & 0.224264 \tabularnewline
24 & 0.273545 & 2.1189 & 0.019125 \tabularnewline
25 & -0.022418 & -0.1736 & 0.431363 \tabularnewline
26 & -0.110219 & -0.8538 & 0.198319 \tabularnewline
27 & -0.069911 & -0.5415 & 0.295075 \tabularnewline
28 & 0.012598 & 0.0976 & 0.461295 \tabularnewline
29 & -0.007526 & -0.0583 & 0.476852 \tabularnewline
30 & -0.003139 & -0.0243 & 0.49034 \tabularnewline
31 & -0.017045 & -0.132 & 0.447701 \tabularnewline
32 & -4e-05 & -3e-04 & 0.499876 \tabularnewline
33 & -0.095388 & -0.7389 & 0.231434 \tabularnewline
34 & -0.161032 & -1.2473 & 0.108558 \tabularnewline
35 & 0.017951 & 0.139 & 0.44494 \tabularnewline
36 & 0.194156 & 1.5039 & 0.068923 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=25978&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]0.095247[/C][C]0.7378[/C][C]0.231763[/C][/ROW]
[ROW][C]2[/C][C]-0.150608[/C][C]-1.1666[/C][C]0.123993[/C][/ROW]
[ROW][C]3[/C][C]0.168679[/C][C]1.3066[/C][C]0.09817[/C][/ROW]
[ROW][C]4[/C][C]0.158939[/C][C]1.2311[/C][C]0.111538[/C][/ROW]
[ROW][C]5[/C][C]0.10549[/C][C]0.8171[/C][C]0.208546[/C][/ROW]
[ROW][C]6[/C][C]0.266965[/C][C]2.0679[/C][C]0.021485[/C][/ROW]
[ROW][C]7[/C][C]-0.024652[/C][C]-0.191[/C][C]0.424604[/C][/ROW]
[ROW][C]8[/C][C]0.114606[/C][C]0.8877[/C][C]0.189114[/C][/ROW]
[ROW][C]9[/C][C]0.057414[/C][C]0.4447[/C][C]0.32906[/C][/ROW]
[ROW][C]10[/C][C]-0.210477[/C][C]-1.6303[/C][C]0.054134[/C][/ROW]
[ROW][C]11[/C][C]0.039141[/C][C]0.3032[/C][C]0.381399[/C][/ROW]
[ROW][C]12[/C][C]0.528496[/C][C]4.0937[/C][C]6.4e-05[/C][/ROW]
[ROW][C]13[/C][C]-0.011068[/C][C]-0.0857[/C][C]0.465982[/C][/ROW]
[ROW][C]14[/C][C]-0.171496[/C][C]-1.3284[/C][C]0.094537[/C][/ROW]
[ROW][C]15[/C][C]-0.018534[/C][C]-0.1436[/C][C]0.443163[/C][/ROW]
[ROW][C]16[/C][C]0.006862[/C][C]0.0532[/C][C]0.478893[/C][/ROW]
[ROW][C]17[/C][C]0.043367[/C][C]0.3359[/C][C]0.369051[/C][/ROW]
[ROW][C]18[/C][C]0.128713[/C][C]0.997[/C][C]0.161383[/C][/ROW]
[ROW][C]19[/C][C]-0.037511[/C][C]-0.2906[/C][C]0.386195[/C][/ROW]
[ROW][C]20[/C][C]0.031776[/C][C]0.2461[/C][C]0.403209[/C][/ROW]
[ROW][C]21[/C][C]-0.051618[/C][C]-0.3998[/C][C]0.34535[/C][/ROW]
[ROW][C]22[/C][C]-0.191641[/C][C]-1.4844[/C][C]0.071463[/C][/ROW]
[ROW][C]23[/C][C]0.098487[/C][C]0.7629[/C][C]0.224264[/C][/ROW]
[ROW][C]24[/C][C]0.273545[/C][C]2.1189[/C][C]0.019125[/C][/ROW]
[ROW][C]25[/C][C]-0.022418[/C][C]-0.1736[/C][C]0.431363[/C][/ROW]
[ROW][C]26[/C][C]-0.110219[/C][C]-0.8538[/C][C]0.198319[/C][/ROW]
[ROW][C]27[/C][C]-0.069911[/C][C]-0.5415[/C][C]0.295075[/C][/ROW]
[ROW][C]28[/C][C]0.012598[/C][C]0.0976[/C][C]0.461295[/C][/ROW]
[ROW][C]29[/C][C]-0.007526[/C][C]-0.0583[/C][C]0.476852[/C][/ROW]
[ROW][C]30[/C][C]-0.003139[/C][C]-0.0243[/C][C]0.49034[/C][/ROW]
[ROW][C]31[/C][C]-0.017045[/C][C]-0.132[/C][C]0.447701[/C][/ROW]
[ROW][C]32[/C][C]-4e-05[/C][C]-3e-04[/C][C]0.499876[/C][/ROW]
[ROW][C]33[/C][C]-0.095388[/C][C]-0.7389[/C][C]0.231434[/C][/ROW]
[ROW][C]34[/C][C]-0.161032[/C][C]-1.2473[/C][C]0.108558[/C][/ROW]
[ROW][C]35[/C][C]0.017951[/C][C]0.139[/C][C]0.44494[/C][/ROW]
[ROW][C]36[/C][C]0.194156[/C][C]1.5039[/C][C]0.068923[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=25978&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=25978&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
10.0952470.73780.231763
2-0.150608-1.16660.123993
30.1686791.30660.09817
40.1589391.23110.111538
50.105490.81710.208546
60.2669652.06790.021485
7-0.024652-0.1910.424604
80.1146060.88770.189114
90.0574140.44470.32906
10-0.210477-1.63030.054134
110.0391410.30320.381399
120.5284964.09376.4e-05
13-0.011068-0.08570.465982
14-0.171496-1.32840.094537
15-0.018534-0.14360.443163
160.0068620.05320.478893
170.0433670.33590.369051
180.1287130.9970.161383
19-0.037511-0.29060.386195
200.0317760.24610.403209
21-0.051618-0.39980.34535
22-0.191641-1.48440.071463
230.0984870.76290.224264
240.2735452.11890.019125
25-0.022418-0.17360.431363
26-0.110219-0.85380.198319
27-0.069911-0.54150.295075
280.0125980.09760.461295
29-0.007526-0.05830.476852
30-0.003139-0.02430.49034
31-0.017045-0.1320.447701
32-4e-05-3e-040.499876
33-0.095388-0.73890.231434
34-0.161032-1.24730.108558
350.0179510.1390.44494
360.1941561.50390.068923







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.0952470.73780.231763
2-0.161142-1.24820.108404
30.207921.61050.056264
40.0943140.73060.233947
50.1465371.13510.130431
60.2757032.13560.018402
7-0.092425-0.71590.23841
80.2022961.5670.06119
9-0.146351-1.13360.130729
10-0.267591-2.07270.02125
11-0.007167-0.05550.477956
120.435083.37010.000659
130.0007120.00550.497808
14-0.0355-0.2750.392138
15-0.136098-1.05420.148007
16-0.109612-0.8490.199615
17-0.090598-0.70180.242769
18-0.011015-0.08530.466144
190.135841.05220.148461
200.025630.19850.421651
21-0.003099-0.0240.490465
22-0.030235-0.23420.407813
230.101680.78760.217012
24-0.08024-0.62150.2683
250.0254010.19680.422341
26-0.005431-0.04210.483291
27-0.028902-0.22390.411808
280.0530390.41080.341329
29-0.149702-1.15960.125406
30-0.065428-0.50680.307076
31-0.083996-0.65060.258884
320.0197310.15280.43952
330.0880560.68210.248906
340.0266280.20630.418644
35-0.028152-0.21810.414061
360.0811980.6290.265881

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.095247 & 0.7378 & 0.231763 \tabularnewline
2 & -0.161142 & -1.2482 & 0.108404 \tabularnewline
3 & 0.20792 & 1.6105 & 0.056264 \tabularnewline
4 & 0.094314 & 0.7306 & 0.233947 \tabularnewline
5 & 0.146537 & 1.1351 & 0.130431 \tabularnewline
6 & 0.275703 & 2.1356 & 0.018402 \tabularnewline
7 & -0.092425 & -0.7159 & 0.23841 \tabularnewline
8 & 0.202296 & 1.567 & 0.06119 \tabularnewline
9 & -0.146351 & -1.1336 & 0.130729 \tabularnewline
10 & -0.267591 & -2.0727 & 0.02125 \tabularnewline
11 & -0.007167 & -0.0555 & 0.477956 \tabularnewline
12 & 0.43508 & 3.3701 & 0.000659 \tabularnewline
13 & 0.000712 & 0.0055 & 0.497808 \tabularnewline
14 & -0.0355 & -0.275 & 0.392138 \tabularnewline
15 & -0.136098 & -1.0542 & 0.148007 \tabularnewline
16 & -0.109612 & -0.849 & 0.199615 \tabularnewline
17 & -0.090598 & -0.7018 & 0.242769 \tabularnewline
18 & -0.011015 & -0.0853 & 0.466144 \tabularnewline
19 & 0.13584 & 1.0522 & 0.148461 \tabularnewline
20 & 0.02563 & 0.1985 & 0.421651 \tabularnewline
21 & -0.003099 & -0.024 & 0.490465 \tabularnewline
22 & -0.030235 & -0.2342 & 0.407813 \tabularnewline
23 & 0.10168 & 0.7876 & 0.217012 \tabularnewline
24 & -0.08024 & -0.6215 & 0.2683 \tabularnewline
25 & 0.025401 & 0.1968 & 0.422341 \tabularnewline
26 & -0.005431 & -0.0421 & 0.483291 \tabularnewline
27 & -0.028902 & -0.2239 & 0.411808 \tabularnewline
28 & 0.053039 & 0.4108 & 0.341329 \tabularnewline
29 & -0.149702 & -1.1596 & 0.125406 \tabularnewline
30 & -0.065428 & -0.5068 & 0.307076 \tabularnewline
31 & -0.083996 & -0.6506 & 0.258884 \tabularnewline
32 & 0.019731 & 0.1528 & 0.43952 \tabularnewline
33 & 0.088056 & 0.6821 & 0.248906 \tabularnewline
34 & 0.026628 & 0.2063 & 0.418644 \tabularnewline
35 & -0.028152 & -0.2181 & 0.414061 \tabularnewline
36 & 0.081198 & 0.629 & 0.265881 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=25978&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]0.095247[/C][C]0.7378[/C][C]0.231763[/C][/ROW]
[ROW][C]2[/C][C]-0.161142[/C][C]-1.2482[/C][C]0.108404[/C][/ROW]
[ROW][C]3[/C][C]0.20792[/C][C]1.6105[/C][C]0.056264[/C][/ROW]
[ROW][C]4[/C][C]0.094314[/C][C]0.7306[/C][C]0.233947[/C][/ROW]
[ROW][C]5[/C][C]0.146537[/C][C]1.1351[/C][C]0.130431[/C][/ROW]
[ROW][C]6[/C][C]0.275703[/C][C]2.1356[/C][C]0.018402[/C][/ROW]
[ROW][C]7[/C][C]-0.092425[/C][C]-0.7159[/C][C]0.23841[/C][/ROW]
[ROW][C]8[/C][C]0.202296[/C][C]1.567[/C][C]0.06119[/C][/ROW]
[ROW][C]9[/C][C]-0.146351[/C][C]-1.1336[/C][C]0.130729[/C][/ROW]
[ROW][C]10[/C][C]-0.267591[/C][C]-2.0727[/C][C]0.02125[/C][/ROW]
[ROW][C]11[/C][C]-0.007167[/C][C]-0.0555[/C][C]0.477956[/C][/ROW]
[ROW][C]12[/C][C]0.43508[/C][C]3.3701[/C][C]0.000659[/C][/ROW]
[ROW][C]13[/C][C]0.000712[/C][C]0.0055[/C][C]0.497808[/C][/ROW]
[ROW][C]14[/C][C]-0.0355[/C][C]-0.275[/C][C]0.392138[/C][/ROW]
[ROW][C]15[/C][C]-0.136098[/C][C]-1.0542[/C][C]0.148007[/C][/ROW]
[ROW][C]16[/C][C]-0.109612[/C][C]-0.849[/C][C]0.199615[/C][/ROW]
[ROW][C]17[/C][C]-0.090598[/C][C]-0.7018[/C][C]0.242769[/C][/ROW]
[ROW][C]18[/C][C]-0.011015[/C][C]-0.0853[/C][C]0.466144[/C][/ROW]
[ROW][C]19[/C][C]0.13584[/C][C]1.0522[/C][C]0.148461[/C][/ROW]
[ROW][C]20[/C][C]0.02563[/C][C]0.1985[/C][C]0.421651[/C][/ROW]
[ROW][C]21[/C][C]-0.003099[/C][C]-0.024[/C][C]0.490465[/C][/ROW]
[ROW][C]22[/C][C]-0.030235[/C][C]-0.2342[/C][C]0.407813[/C][/ROW]
[ROW][C]23[/C][C]0.10168[/C][C]0.7876[/C][C]0.217012[/C][/ROW]
[ROW][C]24[/C][C]-0.08024[/C][C]-0.6215[/C][C]0.2683[/C][/ROW]
[ROW][C]25[/C][C]0.025401[/C][C]0.1968[/C][C]0.422341[/C][/ROW]
[ROW][C]26[/C][C]-0.005431[/C][C]-0.0421[/C][C]0.483291[/C][/ROW]
[ROW][C]27[/C][C]-0.028902[/C][C]-0.2239[/C][C]0.411808[/C][/ROW]
[ROW][C]28[/C][C]0.053039[/C][C]0.4108[/C][C]0.341329[/C][/ROW]
[ROW][C]29[/C][C]-0.149702[/C][C]-1.1596[/C][C]0.125406[/C][/ROW]
[ROW][C]30[/C][C]-0.065428[/C][C]-0.5068[/C][C]0.307076[/C][/ROW]
[ROW][C]31[/C][C]-0.083996[/C][C]-0.6506[/C][C]0.258884[/C][/ROW]
[ROW][C]32[/C][C]0.019731[/C][C]0.1528[/C][C]0.43952[/C][/ROW]
[ROW][C]33[/C][C]0.088056[/C][C]0.6821[/C][C]0.248906[/C][/ROW]
[ROW][C]34[/C][C]0.026628[/C][C]0.2063[/C][C]0.418644[/C][/ROW]
[ROW][C]35[/C][C]-0.028152[/C][C]-0.2181[/C][C]0.414061[/C][/ROW]
[ROW][C]36[/C][C]0.081198[/C][C]0.629[/C][C]0.265881[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=25978&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=25978&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
10.0952470.73780.231763
2-0.161142-1.24820.108404
30.207921.61050.056264
40.0943140.73060.233947
50.1465371.13510.130431
60.2757032.13560.018402
7-0.092425-0.71590.23841
80.2022961.5670.06119
9-0.146351-1.13360.130729
10-0.267591-2.07270.02125
11-0.007167-0.05550.477956
120.435083.37010.000659
130.0007120.00550.497808
14-0.0355-0.2750.392138
15-0.136098-1.05420.148007
16-0.109612-0.8490.199615
17-0.090598-0.70180.242769
18-0.011015-0.08530.466144
190.135841.05220.148461
200.025630.19850.421651
21-0.003099-0.0240.490465
22-0.030235-0.23420.407813
230.101680.78760.217012
24-0.08024-0.62150.2683
250.0254010.19680.422341
26-0.005431-0.04210.483291
27-0.028902-0.22390.411808
280.0530390.41080.341329
29-0.149702-1.15960.125406
30-0.065428-0.50680.307076
31-0.083996-0.65060.258884
320.0197310.15280.43952
330.0880560.68210.248906
340.0266280.20630.418644
35-0.028152-0.21810.414061
360.0811980.6290.265881



Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ;
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 (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='lags',ylab='ACF')
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')