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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 12:25:42 -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/t1259090804agfmko3uyihisff.htm/, Retrieved Sun, 21 Jul 2024 10:52:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59248, Retrieved Sun, 21 Jul 2024 10:52:53 +0000
QR Codes:

Original text written by user:WS 8 Identifying Integration Processes
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] [WS 8 Identifying ...] [2009-11-24 19:14:07] [101f710c1bf3d900563184d79f7da6e1]
-   PD            [(Partial) Autocorrelation Function] [WS 8 Identifying ...] [2009-11-24 19:25:42] [9b6f46453e60f88d91cef176fe926003] [Current]
-   P               [(Partial) Autocorrelation Function] [WS 8 Identifying ...] [2009-11-24 19:34:58] [101f710c1bf3d900563184d79f7da6e1]
-   P                 [(Partial) Autocorrelation Function] [WS 9 Estimation o...] [2009-12-02 21:09:56] [101f710c1bf3d900563184d79f7da6e1]
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Dataseries X:
14.5
14.3
15.3
14.4
13.7
14.2
13.5
11.9
14.6
15.6
14.1
14.9
14.2
14.6
17.2
15.4
14.3
17.5
14.5
14.4
16.6
16.7
16.6
16.9
15.7
16.4
18.4
16.9
16.5
18.3
15.1
15.7
18.1
16.8
18.9
19
18.1
17.8
21.5
17.1
18.7
19
16.4
16.9
18.6
19.3
19.4
17.6
18.6
18.1
20.4
18.1
19.6
19.9
19.2
17.8
19.2
22
21.1
19.5
22.2
20.9
22.2
23.5
21.5
24.3
22.8
20.3
23.7
23.3
19.6
18
17.3
16.8
18.2
16.5
16
18.4




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=59248&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=59248&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59248&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
10.7033745.71420
20.6414495.21121e-06
30.5332654.33232.6e-05
40.2894192.35120.010853
50.1980681.60910.056183
60.0517820.42070.337679
7-0.147113-1.19520.118152
8-0.167415-1.36010.089215
9-0.241581-1.96260.026954
10-0.278996-2.26660.01335
11-0.235556-1.91370.030001
12-0.275748-2.24020.014226
13-0.246638-2.00370.024605
14-0.197235-1.60230.056928
15-0.17067-1.38650.085126
16-0.181639-1.47560.072397
17-0.096594-0.78470.217708
18-0.096105-0.78080.218867
19-0.073546-0.59750.276112
20-0.010842-0.08810.46504
21-3.8e-05-3e-040.499879
220.0113480.09220.463412
230.0869350.70630.241255
240.0577010.46880.32039
250.12731.03420.15241
260.1245881.01220.15758
270.0959090.77920.219332
280.0941650.7650.223499
290.0822540.66820.253158
300.0262330.21310.415947
310.0236340.1920.424165
32-0.016339-0.13270.447401
33-0.018057-0.14670.441908
34-0.017978-0.14610.442161
35-0.030451-0.24740.402689
36-0.052518-0.42670.335508

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.703374 & 5.7142 & 0 \tabularnewline
2 & 0.641449 & 5.2112 & 1e-06 \tabularnewline
3 & 0.533265 & 4.3323 & 2.6e-05 \tabularnewline
4 & 0.289419 & 2.3512 & 0.010853 \tabularnewline
5 & 0.198068 & 1.6091 & 0.056183 \tabularnewline
6 & 0.051782 & 0.4207 & 0.337679 \tabularnewline
7 & -0.147113 & -1.1952 & 0.118152 \tabularnewline
8 & -0.167415 & -1.3601 & 0.089215 \tabularnewline
9 & -0.241581 & -1.9626 & 0.026954 \tabularnewline
10 & -0.278996 & -2.2666 & 0.01335 \tabularnewline
11 & -0.235556 & -1.9137 & 0.030001 \tabularnewline
12 & -0.275748 & -2.2402 & 0.014226 \tabularnewline
13 & -0.246638 & -2.0037 & 0.024605 \tabularnewline
14 & -0.197235 & -1.6023 & 0.056928 \tabularnewline
15 & -0.17067 & -1.3865 & 0.085126 \tabularnewline
16 & -0.181639 & -1.4756 & 0.072397 \tabularnewline
17 & -0.096594 & -0.7847 & 0.217708 \tabularnewline
18 & -0.096105 & -0.7808 & 0.218867 \tabularnewline
19 & -0.073546 & -0.5975 & 0.276112 \tabularnewline
20 & -0.010842 & -0.0881 & 0.46504 \tabularnewline
21 & -3.8e-05 & -3e-04 & 0.499879 \tabularnewline
22 & 0.011348 & 0.0922 & 0.463412 \tabularnewline
23 & 0.086935 & 0.7063 & 0.241255 \tabularnewline
24 & 0.057701 & 0.4688 & 0.32039 \tabularnewline
25 & 0.1273 & 1.0342 & 0.15241 \tabularnewline
26 & 0.124588 & 1.0122 & 0.15758 \tabularnewline
27 & 0.095909 & 0.7792 & 0.219332 \tabularnewline
28 & 0.094165 & 0.765 & 0.223499 \tabularnewline
29 & 0.082254 & 0.6682 & 0.253158 \tabularnewline
30 & 0.026233 & 0.2131 & 0.415947 \tabularnewline
31 & 0.023634 & 0.192 & 0.424165 \tabularnewline
32 & -0.016339 & -0.1327 & 0.447401 \tabularnewline
33 & -0.018057 & -0.1467 & 0.441908 \tabularnewline
34 & -0.017978 & -0.1461 & 0.442161 \tabularnewline
35 & -0.030451 & -0.2474 & 0.402689 \tabularnewline
36 & -0.052518 & -0.4267 & 0.335508 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59248&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]0.703374[/C][C]5.7142[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.641449[/C][C]5.2112[/C][C]1e-06[/C][/ROW]
[ROW][C]3[/C][C]0.533265[/C][C]4.3323[/C][C]2.6e-05[/C][/ROW]
[ROW][C]4[/C][C]0.289419[/C][C]2.3512[/C][C]0.010853[/C][/ROW]
[ROW][C]5[/C][C]0.198068[/C][C]1.6091[/C][C]0.056183[/C][/ROW]
[ROW][C]6[/C][C]0.051782[/C][C]0.4207[/C][C]0.337679[/C][/ROW]
[ROW][C]7[/C][C]-0.147113[/C][C]-1.1952[/C][C]0.118152[/C][/ROW]
[ROW][C]8[/C][C]-0.167415[/C][C]-1.3601[/C][C]0.089215[/C][/ROW]
[ROW][C]9[/C][C]-0.241581[/C][C]-1.9626[/C][C]0.026954[/C][/ROW]
[ROW][C]10[/C][C]-0.278996[/C][C]-2.2666[/C][C]0.01335[/C][/ROW]
[ROW][C]11[/C][C]-0.235556[/C][C]-1.9137[/C][C]0.030001[/C][/ROW]
[ROW][C]12[/C][C]-0.275748[/C][C]-2.2402[/C][C]0.014226[/C][/ROW]
[ROW][C]13[/C][C]-0.246638[/C][C]-2.0037[/C][C]0.024605[/C][/ROW]
[ROW][C]14[/C][C]-0.197235[/C][C]-1.6023[/C][C]0.056928[/C][/ROW]
[ROW][C]15[/C][C]-0.17067[/C][C]-1.3865[/C][C]0.085126[/C][/ROW]
[ROW][C]16[/C][C]-0.181639[/C][C]-1.4756[/C][C]0.072397[/C][/ROW]
[ROW][C]17[/C][C]-0.096594[/C][C]-0.7847[/C][C]0.217708[/C][/ROW]
[ROW][C]18[/C][C]-0.096105[/C][C]-0.7808[/C][C]0.218867[/C][/ROW]
[ROW][C]19[/C][C]-0.073546[/C][C]-0.5975[/C][C]0.276112[/C][/ROW]
[ROW][C]20[/C][C]-0.010842[/C][C]-0.0881[/C][C]0.46504[/C][/ROW]
[ROW][C]21[/C][C]-3.8e-05[/C][C]-3e-04[/C][C]0.499879[/C][/ROW]
[ROW][C]22[/C][C]0.011348[/C][C]0.0922[/C][C]0.463412[/C][/ROW]
[ROW][C]23[/C][C]0.086935[/C][C]0.7063[/C][C]0.241255[/C][/ROW]
[ROW][C]24[/C][C]0.057701[/C][C]0.4688[/C][C]0.32039[/C][/ROW]
[ROW][C]25[/C][C]0.1273[/C][C]1.0342[/C][C]0.15241[/C][/ROW]
[ROW][C]26[/C][C]0.124588[/C][C]1.0122[/C][C]0.15758[/C][/ROW]
[ROW][C]27[/C][C]0.095909[/C][C]0.7792[/C][C]0.219332[/C][/ROW]
[ROW][C]28[/C][C]0.094165[/C][C]0.765[/C][C]0.223499[/C][/ROW]
[ROW][C]29[/C][C]0.082254[/C][C]0.6682[/C][C]0.253158[/C][/ROW]
[ROW][C]30[/C][C]0.026233[/C][C]0.2131[/C][C]0.415947[/C][/ROW]
[ROW][C]31[/C][C]0.023634[/C][C]0.192[/C][C]0.424165[/C][/ROW]
[ROW][C]32[/C][C]-0.016339[/C][C]-0.1327[/C][C]0.447401[/C][/ROW]
[ROW][C]33[/C][C]-0.018057[/C][C]-0.1467[/C][C]0.441908[/C][/ROW]
[ROW][C]34[/C][C]-0.017978[/C][C]-0.1461[/C][C]0.442161[/C][/ROW]
[ROW][C]35[/C][C]-0.030451[/C][C]-0.2474[/C][C]0.402689[/C][/ROW]
[ROW][C]36[/C][C]-0.052518[/C][C]-0.4267[/C][C]0.335508[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59248&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59248&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
10.7033745.71420
20.6414495.21121e-06
30.5332654.33232.6e-05
40.2894192.35120.010853
50.1980681.60910.056183
60.0517820.42070.337679
7-0.147113-1.19520.118152
8-0.167415-1.36010.089215
9-0.241581-1.96260.026954
10-0.278996-2.26660.01335
11-0.235556-1.91370.030001
12-0.275748-2.24020.014226
13-0.246638-2.00370.024605
14-0.197235-1.60230.056928
15-0.17067-1.38650.085126
16-0.181639-1.47560.072397
17-0.096594-0.78470.217708
18-0.096105-0.78080.218867
19-0.073546-0.59750.276112
20-0.010842-0.08810.46504
21-3.8e-05-3e-040.499879
220.0113480.09220.463412
230.0869350.70630.241255
240.0577010.46880.32039
250.12731.03420.15241
260.1245881.01220.15758
270.0959090.77920.219332
280.0941650.7650.223499
290.0822540.66820.253158
300.0262330.21310.415947
310.0236340.1920.424165
32-0.016339-0.13270.447401
33-0.018057-0.14670.441908
34-0.017978-0.14610.442161
35-0.030451-0.24740.402689
36-0.052518-0.42670.335508







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.7033745.71420
20.290372.3590.010647
30.0191420.15550.438447
4-0.36191-2.94020.002259
5-0.057314-0.46560.321511
6-0.050689-0.41180.340912
7-0.223719-1.81750.03684
80.0523970.42570.335864
90.0621050.50450.30778
100.0058680.04770.481062
11-0.012661-0.10290.459194
12-0.105547-0.85750.197145
13-0.04691-0.38110.352178
14-0.022701-0.18440.427122
150.0507810.41250.340638
16-0.173481-1.40940.081711
170.0983330.79890.213618
180.0225460.18320.427615
19-0.062123-0.50470.30773
20-0.00035-0.00280.49887
210.0517250.42020.337845
22-0.044929-0.3650.358139
230.0510770.4150.339762
24-0.029274-0.23780.406377
250.1075620.87380.192688
26-0.074521-0.60540.273491
27-0.014416-0.11710.453562
28-0.102258-0.83070.204555
290.0730170.59320.277541
30-0.038544-0.31310.377582
31-0.002161-0.01760.493023
32-0.014032-0.1140.454793
330.1358611.10370.136858
34-0.040469-0.32880.371684
35-0.035115-0.28530.388163
36-0.110112-0.89460.187137

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.703374 & 5.7142 & 0 \tabularnewline
2 & 0.29037 & 2.359 & 0.010647 \tabularnewline
3 & 0.019142 & 0.1555 & 0.438447 \tabularnewline
4 & -0.36191 & -2.9402 & 0.002259 \tabularnewline
5 & -0.057314 & -0.4656 & 0.321511 \tabularnewline
6 & -0.050689 & -0.4118 & 0.340912 \tabularnewline
7 & -0.223719 & -1.8175 & 0.03684 \tabularnewline
8 & 0.052397 & 0.4257 & 0.335864 \tabularnewline
9 & 0.062105 & 0.5045 & 0.30778 \tabularnewline
10 & 0.005868 & 0.0477 & 0.481062 \tabularnewline
11 & -0.012661 & -0.1029 & 0.459194 \tabularnewline
12 & -0.105547 & -0.8575 & 0.197145 \tabularnewline
13 & -0.04691 & -0.3811 & 0.352178 \tabularnewline
14 & -0.022701 & -0.1844 & 0.427122 \tabularnewline
15 & 0.050781 & 0.4125 & 0.340638 \tabularnewline
16 & -0.173481 & -1.4094 & 0.081711 \tabularnewline
17 & 0.098333 & 0.7989 & 0.213618 \tabularnewline
18 & 0.022546 & 0.1832 & 0.427615 \tabularnewline
19 & -0.062123 & -0.5047 & 0.30773 \tabularnewline
20 & -0.00035 & -0.0028 & 0.49887 \tabularnewline
21 & 0.051725 & 0.4202 & 0.337845 \tabularnewline
22 & -0.044929 & -0.365 & 0.358139 \tabularnewline
23 & 0.051077 & 0.415 & 0.339762 \tabularnewline
24 & -0.029274 & -0.2378 & 0.406377 \tabularnewline
25 & 0.107562 & 0.8738 & 0.192688 \tabularnewline
26 & -0.074521 & -0.6054 & 0.273491 \tabularnewline
27 & -0.014416 & -0.1171 & 0.453562 \tabularnewline
28 & -0.102258 & -0.8307 & 0.204555 \tabularnewline
29 & 0.073017 & 0.5932 & 0.277541 \tabularnewline
30 & -0.038544 & -0.3131 & 0.377582 \tabularnewline
31 & -0.002161 & -0.0176 & 0.493023 \tabularnewline
32 & -0.014032 & -0.114 & 0.454793 \tabularnewline
33 & 0.135861 & 1.1037 & 0.136858 \tabularnewline
34 & -0.040469 & -0.3288 & 0.371684 \tabularnewline
35 & -0.035115 & -0.2853 & 0.388163 \tabularnewline
36 & -0.110112 & -0.8946 & 0.187137 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59248&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]0.703374[/C][C]5.7142[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.29037[/C][C]2.359[/C][C]0.010647[/C][/ROW]
[ROW][C]3[/C][C]0.019142[/C][C]0.1555[/C][C]0.438447[/C][/ROW]
[ROW][C]4[/C][C]-0.36191[/C][C]-2.9402[/C][C]0.002259[/C][/ROW]
[ROW][C]5[/C][C]-0.057314[/C][C]-0.4656[/C][C]0.321511[/C][/ROW]
[ROW][C]6[/C][C]-0.050689[/C][C]-0.4118[/C][C]0.340912[/C][/ROW]
[ROW][C]7[/C][C]-0.223719[/C][C]-1.8175[/C][C]0.03684[/C][/ROW]
[ROW][C]8[/C][C]0.052397[/C][C]0.4257[/C][C]0.335864[/C][/ROW]
[ROW][C]9[/C][C]0.062105[/C][C]0.5045[/C][C]0.30778[/C][/ROW]
[ROW][C]10[/C][C]0.005868[/C][C]0.0477[/C][C]0.481062[/C][/ROW]
[ROW][C]11[/C][C]-0.012661[/C][C]-0.1029[/C][C]0.459194[/C][/ROW]
[ROW][C]12[/C][C]-0.105547[/C][C]-0.8575[/C][C]0.197145[/C][/ROW]
[ROW][C]13[/C][C]-0.04691[/C][C]-0.3811[/C][C]0.352178[/C][/ROW]
[ROW][C]14[/C][C]-0.022701[/C][C]-0.1844[/C][C]0.427122[/C][/ROW]
[ROW][C]15[/C][C]0.050781[/C][C]0.4125[/C][C]0.340638[/C][/ROW]
[ROW][C]16[/C][C]-0.173481[/C][C]-1.4094[/C][C]0.081711[/C][/ROW]
[ROW][C]17[/C][C]0.098333[/C][C]0.7989[/C][C]0.213618[/C][/ROW]
[ROW][C]18[/C][C]0.022546[/C][C]0.1832[/C][C]0.427615[/C][/ROW]
[ROW][C]19[/C][C]-0.062123[/C][C]-0.5047[/C][C]0.30773[/C][/ROW]
[ROW][C]20[/C][C]-0.00035[/C][C]-0.0028[/C][C]0.49887[/C][/ROW]
[ROW][C]21[/C][C]0.051725[/C][C]0.4202[/C][C]0.337845[/C][/ROW]
[ROW][C]22[/C][C]-0.044929[/C][C]-0.365[/C][C]0.358139[/C][/ROW]
[ROW][C]23[/C][C]0.051077[/C][C]0.415[/C][C]0.339762[/C][/ROW]
[ROW][C]24[/C][C]-0.029274[/C][C]-0.2378[/C][C]0.406377[/C][/ROW]
[ROW][C]25[/C][C]0.107562[/C][C]0.8738[/C][C]0.192688[/C][/ROW]
[ROW][C]26[/C][C]-0.074521[/C][C]-0.6054[/C][C]0.273491[/C][/ROW]
[ROW][C]27[/C][C]-0.014416[/C][C]-0.1171[/C][C]0.453562[/C][/ROW]
[ROW][C]28[/C][C]-0.102258[/C][C]-0.8307[/C][C]0.204555[/C][/ROW]
[ROW][C]29[/C][C]0.073017[/C][C]0.5932[/C][C]0.277541[/C][/ROW]
[ROW][C]30[/C][C]-0.038544[/C][C]-0.3131[/C][C]0.377582[/C][/ROW]
[ROW][C]31[/C][C]-0.002161[/C][C]-0.0176[/C][C]0.493023[/C][/ROW]
[ROW][C]32[/C][C]-0.014032[/C][C]-0.114[/C][C]0.454793[/C][/ROW]
[ROW][C]33[/C][C]0.135861[/C][C]1.1037[/C][C]0.136858[/C][/ROW]
[ROW][C]34[/C][C]-0.040469[/C][C]-0.3288[/C][C]0.371684[/C][/ROW]
[ROW][C]35[/C][C]-0.035115[/C][C]-0.2853[/C][C]0.388163[/C][/ROW]
[ROW][C]36[/C][C]-0.110112[/C][C]-0.8946[/C][C]0.187137[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59248&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59248&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
10.7033745.71420
20.290372.3590.010647
30.0191420.15550.438447
4-0.36191-2.94020.002259
5-0.057314-0.46560.321511
6-0.050689-0.41180.340912
7-0.223719-1.81750.03684
80.0523970.42570.335864
90.0621050.50450.30778
100.0058680.04770.481062
11-0.012661-0.10290.459194
12-0.105547-0.85750.197145
13-0.04691-0.38110.352178
14-0.022701-0.18440.427122
150.0507810.41250.340638
16-0.173481-1.40940.081711
170.0983330.79890.213618
180.0225460.18320.427615
19-0.062123-0.50470.30773
20-0.00035-0.00280.49887
210.0517250.42020.337845
22-0.044929-0.3650.358139
230.0510770.4150.339762
24-0.029274-0.23780.406377
250.1075620.87380.192688
26-0.074521-0.60540.273491
27-0.014416-0.11710.453562
28-0.102258-0.83070.204555
290.0730170.59320.277541
30-0.038544-0.31310.377582
31-0.002161-0.01760.493023
32-0.014032-0.1140.454793
330.1358611.10370.136858
34-0.040469-0.32880.371684
35-0.035115-0.28530.388163
36-0.110112-0.89460.187137



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