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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 12:34:58 -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/t1259091352fc1qceidj6v5iqi.htm/, Retrieved Thu, 25 Apr 2024 07:03:25 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59249, Retrieved Thu, 25 Apr 2024 07:03:25 +0000
QR Codes:

Original text written by user:WS 8 Identifying Integration Processes
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact157

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] [101f710c1bf3d900563184d79f7da6e1]
-   P               [(Partial) Autocorrelation Function] [WS 8 Identifying ...] [2009-11-24 19:34:58] [9b6f46453e60f88d91cef176fe926003] [Current]
-   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 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=59249&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=59249&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59249&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
1-0.49091-3.95789.5e-05
20.0467480.37690.353739
30.4051183.26620.000871
4-0.339655-2.73840.003979
50.101690.81990.207648
60.2324921.87440.032684
7-0.378405-3.05080.001651
80.2247691.81210.037291
90.0437870.3530.362608
10-0.245842-1.9820.025853
110.2220331.79010.039049
12-0.120575-0.97210.167301
13-0.142678-1.15030.127116
140.1871961.50920.068044
15-0.06159-0.49660.31059
16-0.163193-1.31570.096448
170.2059291.66030.05084
18-0.117582-0.9480.173326
19-0.090606-0.73050.233858
200.1536871.23910.109889
21-0.096185-0.77550.220437
22-0.112996-0.9110.182829
230.3011812.42820.008975
24-0.289965-2.33780.011244
250.1481231.19420.118368
260.0701430.56550.286836
27-0.165111-1.33120.093892
280.0902640.72770.234697
290.0914960.73770.231686
30-0.190364-1.53480.064848
310.1547761.24780.108283
32-0.007932-0.06390.474604
33-0.07239-0.58360.280744
340.0399060.32170.374344
350.0111020.08950.464478
36-0.067925-0.54760.29291

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.49091 & -3.9578 & 9.5e-05 \tabularnewline
2 & 0.046748 & 0.3769 & 0.353739 \tabularnewline
3 & 0.405118 & 3.2662 & 0.000871 \tabularnewline
4 & -0.339655 & -2.7384 & 0.003979 \tabularnewline
5 & 0.10169 & 0.8199 & 0.207648 \tabularnewline
6 & 0.232492 & 1.8744 & 0.032684 \tabularnewline
7 & -0.378405 & -3.0508 & 0.001651 \tabularnewline
8 & 0.224769 & 1.8121 & 0.037291 \tabularnewline
9 & 0.043787 & 0.353 & 0.362608 \tabularnewline
10 & -0.245842 & -1.982 & 0.025853 \tabularnewline
11 & 0.222033 & 1.7901 & 0.039049 \tabularnewline
12 & -0.120575 & -0.9721 & 0.167301 \tabularnewline
13 & -0.142678 & -1.1503 & 0.127116 \tabularnewline
14 & 0.187196 & 1.5092 & 0.068044 \tabularnewline
15 & -0.06159 & -0.4966 & 0.31059 \tabularnewline
16 & -0.163193 & -1.3157 & 0.096448 \tabularnewline
17 & 0.205929 & 1.6603 & 0.05084 \tabularnewline
18 & -0.117582 & -0.948 & 0.173326 \tabularnewline
19 & -0.090606 & -0.7305 & 0.233858 \tabularnewline
20 & 0.153687 & 1.2391 & 0.109889 \tabularnewline
21 & -0.096185 & -0.7755 & 0.220437 \tabularnewline
22 & -0.112996 & -0.911 & 0.182829 \tabularnewline
23 & 0.301181 & 2.4282 & 0.008975 \tabularnewline
24 & -0.289965 & -2.3378 & 0.011244 \tabularnewline
25 & 0.148123 & 1.1942 & 0.118368 \tabularnewline
26 & 0.070143 & 0.5655 & 0.286836 \tabularnewline
27 & -0.165111 & -1.3312 & 0.093892 \tabularnewline
28 & 0.090264 & 0.7277 & 0.234697 \tabularnewline
29 & 0.091496 & 0.7377 & 0.231686 \tabularnewline
30 & -0.190364 & -1.5348 & 0.064848 \tabularnewline
31 & 0.154776 & 1.2478 & 0.108283 \tabularnewline
32 & -0.007932 & -0.0639 & 0.474604 \tabularnewline
33 & -0.07239 & -0.5836 & 0.280744 \tabularnewline
34 & 0.039906 & 0.3217 & 0.374344 \tabularnewline
35 & 0.011102 & 0.0895 & 0.464478 \tabularnewline
36 & -0.067925 & -0.5476 & 0.29291 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59249&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]-0.49091[/C][C]-3.9578[/C][C]9.5e-05[/C][/ROW]
[ROW][C]2[/C][C]0.046748[/C][C]0.3769[/C][C]0.353739[/C][/ROW]
[ROW][C]3[/C][C]0.405118[/C][C]3.2662[/C][C]0.000871[/C][/ROW]
[ROW][C]4[/C][C]-0.339655[/C][C]-2.7384[/C][C]0.003979[/C][/ROW]
[ROW][C]5[/C][C]0.10169[/C][C]0.8199[/C][C]0.207648[/C][/ROW]
[ROW][C]6[/C][C]0.232492[/C][C]1.8744[/C][C]0.032684[/C][/ROW]
[ROW][C]7[/C][C]-0.378405[/C][C]-3.0508[/C][C]0.001651[/C][/ROW]
[ROW][C]8[/C][C]0.224769[/C][C]1.8121[/C][C]0.037291[/C][/ROW]
[ROW][C]9[/C][C]0.043787[/C][C]0.353[/C][C]0.362608[/C][/ROW]
[ROW][C]10[/C][C]-0.245842[/C][C]-1.982[/C][C]0.025853[/C][/ROW]
[ROW][C]11[/C][C]0.222033[/C][C]1.7901[/C][C]0.039049[/C][/ROW]
[ROW][C]12[/C][C]-0.120575[/C][C]-0.9721[/C][C]0.167301[/C][/ROW]
[ROW][C]13[/C][C]-0.142678[/C][C]-1.1503[/C][C]0.127116[/C][/ROW]
[ROW][C]14[/C][C]0.187196[/C][C]1.5092[/C][C]0.068044[/C][/ROW]
[ROW][C]15[/C][C]-0.06159[/C][C]-0.4966[/C][C]0.31059[/C][/ROW]
[ROW][C]16[/C][C]-0.163193[/C][C]-1.3157[/C][C]0.096448[/C][/ROW]
[ROW][C]17[/C][C]0.205929[/C][C]1.6603[/C][C]0.05084[/C][/ROW]
[ROW][C]18[/C][C]-0.117582[/C][C]-0.948[/C][C]0.173326[/C][/ROW]
[ROW][C]19[/C][C]-0.090606[/C][C]-0.7305[/C][C]0.233858[/C][/ROW]
[ROW][C]20[/C][C]0.153687[/C][C]1.2391[/C][C]0.109889[/C][/ROW]
[ROW][C]21[/C][C]-0.096185[/C][C]-0.7755[/C][C]0.220437[/C][/ROW]
[ROW][C]22[/C][C]-0.112996[/C][C]-0.911[/C][C]0.182829[/C][/ROW]
[ROW][C]23[/C][C]0.301181[/C][C]2.4282[/C][C]0.008975[/C][/ROW]
[ROW][C]24[/C][C]-0.289965[/C][C]-2.3378[/C][C]0.011244[/C][/ROW]
[ROW][C]25[/C][C]0.148123[/C][C]1.1942[/C][C]0.118368[/C][/ROW]
[ROW][C]26[/C][C]0.070143[/C][C]0.5655[/C][C]0.286836[/C][/ROW]
[ROW][C]27[/C][C]-0.165111[/C][C]-1.3312[/C][C]0.093892[/C][/ROW]
[ROW][C]28[/C][C]0.090264[/C][C]0.7277[/C][C]0.234697[/C][/ROW]
[ROW][C]29[/C][C]0.091496[/C][C]0.7377[/C][C]0.231686[/C][/ROW]
[ROW][C]30[/C][C]-0.190364[/C][C]-1.5348[/C][C]0.064848[/C][/ROW]
[ROW][C]31[/C][C]0.154776[/C][C]1.2478[/C][C]0.108283[/C][/ROW]
[ROW][C]32[/C][C]-0.007932[/C][C]-0.0639[/C][C]0.474604[/C][/ROW]
[ROW][C]33[/C][C]-0.07239[/C][C]-0.5836[/C][C]0.280744[/C][/ROW]
[ROW][C]34[/C][C]0.039906[/C][C]0.3217[/C][C]0.374344[/C][/ROW]
[ROW][C]35[/C][C]0.011102[/C][C]0.0895[/C][C]0.464478[/C][/ROW]
[ROW][C]36[/C][C]-0.067925[/C][C]-0.5476[/C][C]0.29291[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59249&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59249&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
1-0.49091-3.95789.5e-05
20.0467480.37690.353739
30.4051183.26620.000871
4-0.339655-2.73840.003979
50.101690.81990.207648
60.2324921.87440.032684
7-0.378405-3.05080.001651
80.2247691.81210.037291
90.0437870.3530.362608
10-0.245842-1.9820.025853
110.2220331.79010.039049
12-0.120575-0.97210.167301
13-0.142678-1.15030.127116
140.1871961.50920.068044
15-0.06159-0.49660.31059
16-0.163193-1.31570.096448
170.2059291.66030.05084
18-0.117582-0.9480.173326
19-0.090606-0.73050.233858
200.1536871.23910.109889
21-0.096185-0.77550.220437
22-0.112996-0.9110.182829
230.3011812.42820.008975
24-0.289965-2.33780.011244
250.1481231.19420.118368
260.0701430.56550.286836
27-0.165111-1.33120.093892
280.0902640.72770.234697
290.0914960.73770.231686
30-0.190364-1.53480.064848
310.1547761.24780.108283
32-0.007932-0.06390.474604
33-0.07239-0.58360.280744
340.0399060.32170.374344
350.0111020.08950.464478
36-0.067925-0.54760.29291






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.49091-3.95789.5e-05
2-0.255919-2.06330.021542
30.4346663.50440.000417
40.1353591.09130.139585
5-0.090694-0.73120.233643
60.0982170.79180.215665
7-0.152539-1.22980.1116
8-0.084485-0.68110.249102
90.0393080.31690.376164
100.0128790.10380.458809
110.0057140.04610.481699
12-0.114478-0.9230.179722
13-0.155611-1.25460.107063
14-0.069021-0.55650.289901
150.2000531.61290.055808
16-0.007651-0.06170.475502
17-0.071944-0.580.281951
18-0.019066-0.15370.439155
19-0.105557-0.8510.19894
20-0.089594-0.72230.236341
210.0896110.72250.2363
22-0.035353-0.2850.388265
230.1774461.43060.078665
24-0.078671-0.63430.264067
250.0168480.13580.446187
26-0.068077-0.54890.292493
270.0491590.39630.346578
28-0.063803-0.51440.30436
290.0284010.2290.409802
300.0530450.42770.335156
31-0.042104-0.33950.36768
32-0.053137-0.42840.334887
330.0965330.77830.219616
34-0.120448-0.97110.167554
35-0.016085-0.12970.448611
360.0145040.11690.453637

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.49091 & -3.9578 & 9.5e-05 \tabularnewline
2 & -0.255919 & -2.0633 & 0.021542 \tabularnewline
3 & 0.434666 & 3.5044 & 0.000417 \tabularnewline
4 & 0.135359 & 1.0913 & 0.139585 \tabularnewline
5 & -0.090694 & -0.7312 & 0.233643 \tabularnewline
6 & 0.098217 & 0.7918 & 0.215665 \tabularnewline
7 & -0.152539 & -1.2298 & 0.1116 \tabularnewline
8 & -0.084485 & -0.6811 & 0.249102 \tabularnewline
9 & 0.039308 & 0.3169 & 0.376164 \tabularnewline
10 & 0.012879 & 0.1038 & 0.458809 \tabularnewline
11 & 0.005714 & 0.0461 & 0.481699 \tabularnewline
12 & -0.114478 & -0.923 & 0.179722 \tabularnewline
13 & -0.155611 & -1.2546 & 0.107063 \tabularnewline
14 & -0.069021 & -0.5565 & 0.289901 \tabularnewline
15 & 0.200053 & 1.6129 & 0.055808 \tabularnewline
16 & -0.007651 & -0.0617 & 0.475502 \tabularnewline
17 & -0.071944 & -0.58 & 0.281951 \tabularnewline
18 & -0.019066 & -0.1537 & 0.439155 \tabularnewline
19 & -0.105557 & -0.851 & 0.19894 \tabularnewline
20 & -0.089594 & -0.7223 & 0.236341 \tabularnewline
21 & 0.089611 & 0.7225 & 0.2363 \tabularnewline
22 & -0.035353 & -0.285 & 0.388265 \tabularnewline
23 & 0.177446 & 1.4306 & 0.078665 \tabularnewline
24 & -0.078671 & -0.6343 & 0.264067 \tabularnewline
25 & 0.016848 & 0.1358 & 0.446187 \tabularnewline
26 & -0.068077 & -0.5489 & 0.292493 \tabularnewline
27 & 0.049159 & 0.3963 & 0.346578 \tabularnewline
28 & -0.063803 & -0.5144 & 0.30436 \tabularnewline
29 & 0.028401 & 0.229 & 0.409802 \tabularnewline
30 & 0.053045 & 0.4277 & 0.335156 \tabularnewline
31 & -0.042104 & -0.3395 & 0.36768 \tabularnewline
32 & -0.053137 & -0.4284 & 0.334887 \tabularnewline
33 & 0.096533 & 0.7783 & 0.219616 \tabularnewline
34 & -0.120448 & -0.9711 & 0.167554 \tabularnewline
35 & -0.016085 & -0.1297 & 0.448611 \tabularnewline
36 & 0.014504 & 0.1169 & 0.453637 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59249&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]-0.49091[/C][C]-3.9578[/C][C]9.5e-05[/C][/ROW]
[ROW][C]2[/C][C]-0.255919[/C][C]-2.0633[/C][C]0.021542[/C][/ROW]
[ROW][C]3[/C][C]0.434666[/C][C]3.5044[/C][C]0.000417[/C][/ROW]
[ROW][C]4[/C][C]0.135359[/C][C]1.0913[/C][C]0.139585[/C][/ROW]
[ROW][C]5[/C][C]-0.090694[/C][C]-0.7312[/C][C]0.233643[/C][/ROW]
[ROW][C]6[/C][C]0.098217[/C][C]0.7918[/C][C]0.215665[/C][/ROW]
[ROW][C]7[/C][C]-0.152539[/C][C]-1.2298[/C][C]0.1116[/C][/ROW]
[ROW][C]8[/C][C]-0.084485[/C][C]-0.6811[/C][C]0.249102[/C][/ROW]
[ROW][C]9[/C][C]0.039308[/C][C]0.3169[/C][C]0.376164[/C][/ROW]
[ROW][C]10[/C][C]0.012879[/C][C]0.1038[/C][C]0.458809[/C][/ROW]
[ROW][C]11[/C][C]0.005714[/C][C]0.0461[/C][C]0.481699[/C][/ROW]
[ROW][C]12[/C][C]-0.114478[/C][C]-0.923[/C][C]0.179722[/C][/ROW]
[ROW][C]13[/C][C]-0.155611[/C][C]-1.2546[/C][C]0.107063[/C][/ROW]
[ROW][C]14[/C][C]-0.069021[/C][C]-0.5565[/C][C]0.289901[/C][/ROW]
[ROW][C]15[/C][C]0.200053[/C][C]1.6129[/C][C]0.055808[/C][/ROW]
[ROW][C]16[/C][C]-0.007651[/C][C]-0.0617[/C][C]0.475502[/C][/ROW]
[ROW][C]17[/C][C]-0.071944[/C][C]-0.58[/C][C]0.281951[/C][/ROW]
[ROW][C]18[/C][C]-0.019066[/C][C]-0.1537[/C][C]0.439155[/C][/ROW]
[ROW][C]19[/C][C]-0.105557[/C][C]-0.851[/C][C]0.19894[/C][/ROW]
[ROW][C]20[/C][C]-0.089594[/C][C]-0.7223[/C][C]0.236341[/C][/ROW]
[ROW][C]21[/C][C]0.089611[/C][C]0.7225[/C][C]0.2363[/C][/ROW]
[ROW][C]22[/C][C]-0.035353[/C][C]-0.285[/C][C]0.388265[/C][/ROW]
[ROW][C]23[/C][C]0.177446[/C][C]1.4306[/C][C]0.078665[/C][/ROW]
[ROW][C]24[/C][C]-0.078671[/C][C]-0.6343[/C][C]0.264067[/C][/ROW]
[ROW][C]25[/C][C]0.016848[/C][C]0.1358[/C][C]0.446187[/C][/ROW]
[ROW][C]26[/C][C]-0.068077[/C][C]-0.5489[/C][C]0.292493[/C][/ROW]
[ROW][C]27[/C][C]0.049159[/C][C]0.3963[/C][C]0.346578[/C][/ROW]
[ROW][C]28[/C][C]-0.063803[/C][C]-0.5144[/C][C]0.30436[/C][/ROW]
[ROW][C]29[/C][C]0.028401[/C][C]0.229[/C][C]0.409802[/C][/ROW]
[ROW][C]30[/C][C]0.053045[/C][C]0.4277[/C][C]0.335156[/C][/ROW]
[ROW][C]31[/C][C]-0.042104[/C][C]-0.3395[/C][C]0.36768[/C][/ROW]
[ROW][C]32[/C][C]-0.053137[/C][C]-0.4284[/C][C]0.334887[/C][/ROW]
[ROW][C]33[/C][C]0.096533[/C][C]0.7783[/C][C]0.219616[/C][/ROW]
[ROW][C]34[/C][C]-0.120448[/C][C]-0.9711[/C][C]0.167554[/C][/ROW]
[ROW][C]35[/C][C]-0.016085[/C][C]-0.1297[/C][C]0.448611[/C][/ROW]
[ROW][C]36[/C][C]0.014504[/C][C]0.1169[/C][C]0.453637[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59249&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59249&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
1-0.49091-3.95789.5e-05
2-0.255919-2.06330.021542
30.4346663.50440.000417
40.1353591.09130.139585
5-0.090694-0.73120.233643
60.0982170.79180.215665
7-0.152539-1.22980.1116
8-0.084485-0.68110.249102
90.0393080.31690.376164
100.0128790.10380.458809
110.0057140.04610.481699
12-0.114478-0.9230.179722
13-0.155611-1.25460.107063
14-0.069021-0.55650.289901
150.2000531.61290.055808
16-0.007651-0.06170.475502
17-0.071944-0.580.281951
18-0.019066-0.15370.439155
19-0.105557-0.8510.19894
20-0.089594-0.72230.236341
210.0896110.72250.2363
22-0.035353-0.2850.388265
230.1774461.43060.078665
24-0.078671-0.63430.264067
250.0168480.13580.446187
26-0.068077-0.54890.292493
270.0491590.39630.346578
28-0.063803-0.51440.30436
290.0284010.2290.409802
300.0530450.42770.335156
31-0.042104-0.33950.36768
32-0.053137-0.42840.334887
330.0965330.77830.219616
34-0.120448-0.97110.167554
35-0.016085-0.12970.448611
360.0145040.11690.453637


Figures (Output of Computation)

Input Parameters & R Code

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