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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 computationTue, 24 Nov 2009 09:42:45 -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/Nov/24/t12590810321dcnlt5kaerso15.htm/, Retrieved Thu, 25 Apr 2024 17:58:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59158, Retrieved Thu, 25 Apr 2024 17:58:38 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact220
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] [db49399df1e4a3dbe31268849cebfd7f] [Current]
-   P             [(Partial) Autocorrelation Function] [SHWWS9] [2009-12-01 19:06:31] [a66d3a79ef9e5308cd94a469bc5ca464]
-    D            [(Partial) Autocorrelation Function] [PAPER] [2009-12-13 09:34:23] [a66d3a79ef9e5308cd94a469bc5ca464]
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Dataseries X:
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




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=59158&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=59158&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59158&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
10.778076.02690
20.4800863.71870.000221
30.2682072.07750.02102
40.1546581.1980.117819
50.1201240.93050.177927
60.1051850.81480.209216
70.0887930.68780.247118
80.0981690.76040.224994
90.2064981.59950.057478
100.4136373.2040.001086
110.5849654.53111.4e-05
120.6415234.96923e-06
130.4315493.34280.000716
140.169971.31660.096493
15-0.009478-0.07340.47086
16-0.106195-0.82260.207001
17-0.136721-1.0590.146915
18-0.157948-1.22350.11297
19-0.184574-1.42970.078995
20-0.187027-1.44870.076313
21-0.108521-0.84060.201955
220.0508750.39410.34746
230.1729861.33990.092658
240.2036981.57780.05993
250.0359690.27860.390748
26-0.1446-1.12010.133574
27-0.246467-1.90910.030516
28-0.290821-2.25270.013974
29-0.311022-2.40920.009537
30-0.324202-2.51130.00737
31-0.335182-2.59630.005916
32-0.330237-2.5580.006535
33-0.25141-1.94740.028085
34-0.109512-0.84830.199827
35-0.017223-0.13340.447159
36-0.00018-0.00140.499447

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.77807 & 6.0269 & 0 \tabularnewline
2 & 0.480086 & 3.7187 & 0.000221 \tabularnewline
3 & 0.268207 & 2.0775 & 0.02102 \tabularnewline
4 & 0.154658 & 1.198 & 0.117819 \tabularnewline
5 & 0.120124 & 0.9305 & 0.177927 \tabularnewline
6 & 0.105185 & 0.8148 & 0.209216 \tabularnewline
7 & 0.088793 & 0.6878 & 0.247118 \tabularnewline
8 & 0.098169 & 0.7604 & 0.224994 \tabularnewline
9 & 0.206498 & 1.5995 & 0.057478 \tabularnewline
10 & 0.413637 & 3.204 & 0.001086 \tabularnewline
11 & 0.584965 & 4.5311 & 1.4e-05 \tabularnewline
12 & 0.641523 & 4.9692 & 3e-06 \tabularnewline
13 & 0.431549 & 3.3428 & 0.000716 \tabularnewline
14 & 0.16997 & 1.3166 & 0.096493 \tabularnewline
15 & -0.009478 & -0.0734 & 0.47086 \tabularnewline
16 & -0.106195 & -0.8226 & 0.207001 \tabularnewline
17 & -0.136721 & -1.059 & 0.146915 \tabularnewline
18 & -0.157948 & -1.2235 & 0.11297 \tabularnewline
19 & -0.184574 & -1.4297 & 0.078995 \tabularnewline
20 & -0.187027 & -1.4487 & 0.076313 \tabularnewline
21 & -0.108521 & -0.8406 & 0.201955 \tabularnewline
22 & 0.050875 & 0.3941 & 0.34746 \tabularnewline
23 & 0.172986 & 1.3399 & 0.092658 \tabularnewline
24 & 0.203698 & 1.5778 & 0.05993 \tabularnewline
25 & 0.035969 & 0.2786 & 0.390748 \tabularnewline
26 & -0.1446 & -1.1201 & 0.133574 \tabularnewline
27 & -0.246467 & -1.9091 & 0.030516 \tabularnewline
28 & -0.290821 & -2.2527 & 0.013974 \tabularnewline
29 & -0.311022 & -2.4092 & 0.009537 \tabularnewline
30 & -0.324202 & -2.5113 & 0.00737 \tabularnewline
31 & -0.335182 & -2.5963 & 0.005916 \tabularnewline
32 & -0.330237 & -2.558 & 0.006535 \tabularnewline
33 & -0.25141 & -1.9474 & 0.028085 \tabularnewline
34 & -0.109512 & -0.8483 & 0.199827 \tabularnewline
35 & -0.017223 & -0.1334 & 0.447159 \tabularnewline
36 & -0.00018 & -0.0014 & 0.499447 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59158&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]0.77807[/C][C]6.0269[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.480086[/C][C]3.7187[/C][C]0.000221[/C][/ROW]
[ROW][C]3[/C][C]0.268207[/C][C]2.0775[/C][C]0.02102[/C][/ROW]
[ROW][C]4[/C][C]0.154658[/C][C]1.198[/C][C]0.117819[/C][/ROW]
[ROW][C]5[/C][C]0.120124[/C][C]0.9305[/C][C]0.177927[/C][/ROW]
[ROW][C]6[/C][C]0.105185[/C][C]0.8148[/C][C]0.209216[/C][/ROW]
[ROW][C]7[/C][C]0.088793[/C][C]0.6878[/C][C]0.247118[/C][/ROW]
[ROW][C]8[/C][C]0.098169[/C][C]0.7604[/C][C]0.224994[/C][/ROW]
[ROW][C]9[/C][C]0.206498[/C][C]1.5995[/C][C]0.057478[/C][/ROW]
[ROW][C]10[/C][C]0.413637[/C][C]3.204[/C][C]0.001086[/C][/ROW]
[ROW][C]11[/C][C]0.584965[/C][C]4.5311[/C][C]1.4e-05[/C][/ROW]
[ROW][C]12[/C][C]0.641523[/C][C]4.9692[/C][C]3e-06[/C][/ROW]
[ROW][C]13[/C][C]0.431549[/C][C]3.3428[/C][C]0.000716[/C][/ROW]
[ROW][C]14[/C][C]0.16997[/C][C]1.3166[/C][C]0.096493[/C][/ROW]
[ROW][C]15[/C][C]-0.009478[/C][C]-0.0734[/C][C]0.47086[/C][/ROW]
[ROW][C]16[/C][C]-0.106195[/C][C]-0.8226[/C][C]0.207001[/C][/ROW]
[ROW][C]17[/C][C]-0.136721[/C][C]-1.059[/C][C]0.146915[/C][/ROW]
[ROW][C]18[/C][C]-0.157948[/C][C]-1.2235[/C][C]0.11297[/C][/ROW]
[ROW][C]19[/C][C]-0.184574[/C][C]-1.4297[/C][C]0.078995[/C][/ROW]
[ROW][C]20[/C][C]-0.187027[/C][C]-1.4487[/C][C]0.076313[/C][/ROW]
[ROW][C]21[/C][C]-0.108521[/C][C]-0.8406[/C][C]0.201955[/C][/ROW]
[ROW][C]22[/C][C]0.050875[/C][C]0.3941[/C][C]0.34746[/C][/ROW]
[ROW][C]23[/C][C]0.172986[/C][C]1.3399[/C][C]0.092658[/C][/ROW]
[ROW][C]24[/C][C]0.203698[/C][C]1.5778[/C][C]0.05993[/C][/ROW]
[ROW][C]25[/C][C]0.035969[/C][C]0.2786[/C][C]0.390748[/C][/ROW]
[ROW][C]26[/C][C]-0.1446[/C][C]-1.1201[/C][C]0.133574[/C][/ROW]
[ROW][C]27[/C][C]-0.246467[/C][C]-1.9091[/C][C]0.030516[/C][/ROW]
[ROW][C]28[/C][C]-0.290821[/C][C]-2.2527[/C][C]0.013974[/C][/ROW]
[ROW][C]29[/C][C]-0.311022[/C][C]-2.4092[/C][C]0.009537[/C][/ROW]
[ROW][C]30[/C][C]-0.324202[/C][C]-2.5113[/C][C]0.00737[/C][/ROW]
[ROW][C]31[/C][C]-0.335182[/C][C]-2.5963[/C][C]0.005916[/C][/ROW]
[ROW][C]32[/C][C]-0.330237[/C][C]-2.558[/C][C]0.006535[/C][/ROW]
[ROW][C]33[/C][C]-0.25141[/C][C]-1.9474[/C][C]0.028085[/C][/ROW]
[ROW][C]34[/C][C]-0.109512[/C][C]-0.8483[/C][C]0.199827[/C][/ROW]
[ROW][C]35[/C][C]-0.017223[/C][C]-0.1334[/C][C]0.447159[/C][/ROW]
[ROW][C]36[/C][C]-0.00018[/C][C]-0.0014[/C][C]0.499447[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59158&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59158&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
10.778076.02690
20.4800863.71870.000221
30.2682072.07750.02102
40.1546581.1980.117819
50.1201240.93050.177927
60.1051850.81480.209216
70.0887930.68780.247118
80.0981690.76040.224994
90.2064981.59950.057478
100.4136373.2040.001086
110.5849654.53111.4e-05
120.6415234.96923e-06
130.4315493.34280.000716
140.169971.31660.096493
15-0.009478-0.07340.47086
16-0.106195-0.82260.207001
17-0.136721-1.0590.146915
18-0.157948-1.22350.11297
19-0.184574-1.42970.078995
20-0.187027-1.44870.076313
21-0.108521-0.84060.201955
220.0508750.39410.34746
230.1729861.33990.092658
240.2036981.57780.05993
250.0359690.27860.390748
26-0.1446-1.12010.133574
27-0.246467-1.90910.030516
28-0.290821-2.25270.013974
29-0.311022-2.40920.009537
30-0.324202-2.51130.00737
31-0.335182-2.59630.005916
32-0.330237-2.5580.006535
33-0.25141-1.94740.028085
34-0.109512-0.84830.199827
35-0.017223-0.13340.447159
36-0.00018-0.00140.499447







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.778076.02690
2-0.317548-2.45970.008402
30.0651730.50480.307764
40.0225640.17480.430921
50.0618760.47930.316738
6-0.019723-0.15280.439546
70.0094410.07310.470972
80.0822860.63740.26315
90.2766862.14320.018081
100.3323572.57440.006263
110.1644471.27380.103823
120.1266170.98080.165321
13-0.478228-3.70430.000232
14-0.056326-0.43630.332093
15-0.163035-1.26290.105762
16-0.094941-0.73540.232476
17-0.045502-0.35250.362866
18-0.068552-0.5310.298688
19-0.101931-0.78960.216448
20-0.174252-1.34970.091084
21-0.145798-1.12930.131624
22-0.111617-0.86460.195356
230.0444940.34460.365783
240.0989370.76640.223233
25-0.081968-0.63490.263946
260.1719811.33220.093923
270.0065460.05070.479865
280.0604830.46850.320561
29-0.056669-0.4390.331135
300.0861870.66760.253475
310.0526840.40810.342331
320.0014160.0110.495644
330.0355140.27510.392096
34-0.085126-0.65940.256087
35-0.02587-0.20040.420928
36-0.108637-0.84150.201705

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.77807 & 6.0269 & 0 \tabularnewline
2 & -0.317548 & -2.4597 & 0.008402 \tabularnewline
3 & 0.065173 & 0.5048 & 0.307764 \tabularnewline
4 & 0.022564 & 0.1748 & 0.430921 \tabularnewline
5 & 0.061876 & 0.4793 & 0.316738 \tabularnewline
6 & -0.019723 & -0.1528 & 0.439546 \tabularnewline
7 & 0.009441 & 0.0731 & 0.470972 \tabularnewline
8 & 0.082286 & 0.6374 & 0.26315 \tabularnewline
9 & 0.276686 & 2.1432 & 0.018081 \tabularnewline
10 & 0.332357 & 2.5744 & 0.006263 \tabularnewline
11 & 0.164447 & 1.2738 & 0.103823 \tabularnewline
12 & 0.126617 & 0.9808 & 0.165321 \tabularnewline
13 & -0.478228 & -3.7043 & 0.000232 \tabularnewline
14 & -0.056326 & -0.4363 & 0.332093 \tabularnewline
15 & -0.163035 & -1.2629 & 0.105762 \tabularnewline
16 & -0.094941 & -0.7354 & 0.232476 \tabularnewline
17 & -0.045502 & -0.3525 & 0.362866 \tabularnewline
18 & -0.068552 & -0.531 & 0.298688 \tabularnewline
19 & -0.101931 & -0.7896 & 0.216448 \tabularnewline
20 & -0.174252 & -1.3497 & 0.091084 \tabularnewline
21 & -0.145798 & -1.1293 & 0.131624 \tabularnewline
22 & -0.111617 & -0.8646 & 0.195356 \tabularnewline
23 & 0.044494 & 0.3446 & 0.365783 \tabularnewline
24 & 0.098937 & 0.7664 & 0.223233 \tabularnewline
25 & -0.081968 & -0.6349 & 0.263946 \tabularnewline
26 & 0.171981 & 1.3322 & 0.093923 \tabularnewline
27 & 0.006546 & 0.0507 & 0.479865 \tabularnewline
28 & 0.060483 & 0.4685 & 0.320561 \tabularnewline
29 & -0.056669 & -0.439 & 0.331135 \tabularnewline
30 & 0.086187 & 0.6676 & 0.253475 \tabularnewline
31 & 0.052684 & 0.4081 & 0.342331 \tabularnewline
32 & 0.001416 & 0.011 & 0.495644 \tabularnewline
33 & 0.035514 & 0.2751 & 0.392096 \tabularnewline
34 & -0.085126 & -0.6594 & 0.256087 \tabularnewline
35 & -0.02587 & -0.2004 & 0.420928 \tabularnewline
36 & -0.108637 & -0.8415 & 0.201705 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59158&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]0.77807[/C][C]6.0269[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.317548[/C][C]-2.4597[/C][C]0.008402[/C][/ROW]
[ROW][C]3[/C][C]0.065173[/C][C]0.5048[/C][C]0.307764[/C][/ROW]
[ROW][C]4[/C][C]0.022564[/C][C]0.1748[/C][C]0.430921[/C][/ROW]
[ROW][C]5[/C][C]0.061876[/C][C]0.4793[/C][C]0.316738[/C][/ROW]
[ROW][C]6[/C][C]-0.019723[/C][C]-0.1528[/C][C]0.439546[/C][/ROW]
[ROW][C]7[/C][C]0.009441[/C][C]0.0731[/C][C]0.470972[/C][/ROW]
[ROW][C]8[/C][C]0.082286[/C][C]0.6374[/C][C]0.26315[/C][/ROW]
[ROW][C]9[/C][C]0.276686[/C][C]2.1432[/C][C]0.018081[/C][/ROW]
[ROW][C]10[/C][C]0.332357[/C][C]2.5744[/C][C]0.006263[/C][/ROW]
[ROW][C]11[/C][C]0.164447[/C][C]1.2738[/C][C]0.103823[/C][/ROW]
[ROW][C]12[/C][C]0.126617[/C][C]0.9808[/C][C]0.165321[/C][/ROW]
[ROW][C]13[/C][C]-0.478228[/C][C]-3.7043[/C][C]0.000232[/C][/ROW]
[ROW][C]14[/C][C]-0.056326[/C][C]-0.4363[/C][C]0.332093[/C][/ROW]
[ROW][C]15[/C][C]-0.163035[/C][C]-1.2629[/C][C]0.105762[/C][/ROW]
[ROW][C]16[/C][C]-0.094941[/C][C]-0.7354[/C][C]0.232476[/C][/ROW]
[ROW][C]17[/C][C]-0.045502[/C][C]-0.3525[/C][C]0.362866[/C][/ROW]
[ROW][C]18[/C][C]-0.068552[/C][C]-0.531[/C][C]0.298688[/C][/ROW]
[ROW][C]19[/C][C]-0.101931[/C][C]-0.7896[/C][C]0.216448[/C][/ROW]
[ROW][C]20[/C][C]-0.174252[/C][C]-1.3497[/C][C]0.091084[/C][/ROW]
[ROW][C]21[/C][C]-0.145798[/C][C]-1.1293[/C][C]0.131624[/C][/ROW]
[ROW][C]22[/C][C]-0.111617[/C][C]-0.8646[/C][C]0.195356[/C][/ROW]
[ROW][C]23[/C][C]0.044494[/C][C]0.3446[/C][C]0.365783[/C][/ROW]
[ROW][C]24[/C][C]0.098937[/C][C]0.7664[/C][C]0.223233[/C][/ROW]
[ROW][C]25[/C][C]-0.081968[/C][C]-0.6349[/C][C]0.263946[/C][/ROW]
[ROW][C]26[/C][C]0.171981[/C][C]1.3322[/C][C]0.093923[/C][/ROW]
[ROW][C]27[/C][C]0.006546[/C][C]0.0507[/C][C]0.479865[/C][/ROW]
[ROW][C]28[/C][C]0.060483[/C][C]0.4685[/C][C]0.320561[/C][/ROW]
[ROW][C]29[/C][C]-0.056669[/C][C]-0.439[/C][C]0.331135[/C][/ROW]
[ROW][C]30[/C][C]0.086187[/C][C]0.6676[/C][C]0.253475[/C][/ROW]
[ROW][C]31[/C][C]0.052684[/C][C]0.4081[/C][C]0.342331[/C][/ROW]
[ROW][C]32[/C][C]0.001416[/C][C]0.011[/C][C]0.495644[/C][/ROW]
[ROW][C]33[/C][C]0.035514[/C][C]0.2751[/C][C]0.392096[/C][/ROW]
[ROW][C]34[/C][C]-0.085126[/C][C]-0.6594[/C][C]0.256087[/C][/ROW]
[ROW][C]35[/C][C]-0.02587[/C][C]-0.2004[/C][C]0.420928[/C][/ROW]
[ROW][C]36[/C][C]-0.108637[/C][C]-0.8415[/C][C]0.201705[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59158&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59158&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
10.778076.02690
2-0.317548-2.45970.008402
30.0651730.50480.307764
40.0225640.17480.430921
50.0618760.47930.316738
6-0.019723-0.15280.439546
70.0094410.07310.470972
80.0822860.63740.26315
90.2766862.14320.018081
100.3323572.57440.006263
110.1644471.27380.103823
120.1266170.98080.165321
13-0.478228-3.70430.000232
14-0.056326-0.43630.332093
15-0.163035-1.26290.105762
16-0.094941-0.73540.232476
17-0.045502-0.35250.362866
18-0.068552-0.5310.298688
19-0.101931-0.78960.216448
20-0.174252-1.34970.091084
21-0.145798-1.12930.131624
22-0.111617-0.86460.195356
230.0444940.34460.365783
240.0989370.76640.223233
25-0.081968-0.63490.263946
260.1719811.33220.093923
270.0065460.05070.479865
280.0604830.46850.320561
29-0.056669-0.4390.331135
300.0861870.66760.253475
310.0526840.40810.342331
320.0014160.0110.495644
330.0355140.27510.392096
34-0.085126-0.65940.256087
35-0.02587-0.20040.420928
36-0.108637-0.84150.201705



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