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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 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 Wed, 24 Apr 2024 03:01:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59248, Retrieved Wed, 24 Apr 2024 03:01:37 +0000
QR Codes:

Original text written by user:WS 8 Identifying Integration Processes
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact185

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]
-    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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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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

Tables (Output of Computation)





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:  
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:  
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:  
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


Figures (Output of Computation)

Input Parameters & R Code

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')