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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 computationMon, 23 Nov 2009 08:32:19 -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/23/t12589904028n02f8qm207ixos.htm/, Retrieved Wed, 05 Feb 2025 06:05:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=58797, Retrieved Wed, 05 Feb 2025 06:05:07 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact267

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 12:26:39] [b98453cac15ba1066b407e146608df68]
-    D          [(Partial) Autocorrelation Function] [] [2009-11-23 15:32:19] [2b679e8ec54382eeb0ec0b6bb527570a] [Current]
-    D            [(Partial) Autocorrelation Function] [AC d=1 D=1] [2009-12-04 12:17:39] [74be16979710d4c4e7c6647856088456]
- R PD            [(Partial) Autocorrelation Function] [AutoCF d=1,D=1] [2009-12-04 15:19:19] [fa71ec4c741ffec745cb91dcbd756720]
-    D            [(Partial) Autocorrelation Function] [] [2009-12-20 08:24:43] [5d885a68c2332cc44f6191ec94766bfa]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
100.03
100.25
99.6
100.16
100.49
99.72
100.14
98.48
100.38
101.45
98.42
98.6
100.06
98.62
100.84
100.02
97.95
98.32
98.27
97.22
99.28
100.38
99.02
100.32
99.81
100.6
101.19
100.47
101.77
102.32
102.39
101.16
100.63
101.48
101.44
100.09
100.7
100.78
99.81
98.45
98.49
97.48
97.91
96.94
98.53
96.82
95.76
95.27
97.32
96.68
97.87
97.42
97.94
99.52
100.99
99.92
101.97
101.58
99.54
100.83

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=58797&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=58797&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=58797&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
1-0.186791-1.28060.103314
2-0.036465-0.250.401841
30.318762.18530.016942
4-0.176154-1.20770.116611
50.0649710.44540.32903
60.274381.88110.033084
7-0.205514-1.40890.082718
80.177531.21710.114824
90.0202130.13860.44519
10-0.241558-1.6560.052188
110.1795721.23110.112208
12-0.354602-2.4310.009462
13-0.129596-0.88850.189408
140.1436680.98490.16485
15-0.167392-1.14760.128475
16-0.019763-0.13550.446403
170.0328830.22540.411309
18-0.357404-2.45020.009027
190.1134850.7780.220229
200.0175540.12030.452361
21-0.176274-1.20850.116455
220.1182170.81050.210881
230.0583780.40020.345404
24-0.141441-0.96970.168587
250.2127091.45830.07571
26-0.000649-0.00450.498233
27-0.08702-0.59660.276826
280.0407720.27950.390537
290.0483610.33150.370854
300.0779660.53450.297754
310.0096090.06590.473877
320.0023290.0160.493665
33-0.016086-0.11030.45633
340.0737910.50590.307651
35-0.123054-0.84360.20158
360.06360.4360.332409

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.186791 & -1.2806 & 0.103314 \tabularnewline
2 & -0.036465 & -0.25 & 0.401841 \tabularnewline
3 & 0.31876 & 2.1853 & 0.016942 \tabularnewline
4 & -0.176154 & -1.2077 & 0.116611 \tabularnewline
5 & 0.064971 & 0.4454 & 0.32903 \tabularnewline
6 & 0.27438 & 1.8811 & 0.033084 \tabularnewline
7 & -0.205514 & -1.4089 & 0.082718 \tabularnewline
8 & 0.17753 & 1.2171 & 0.114824 \tabularnewline
9 & 0.020213 & 0.1386 & 0.44519 \tabularnewline
10 & -0.241558 & -1.656 & 0.052188 \tabularnewline
11 & 0.179572 & 1.2311 & 0.112208 \tabularnewline
12 & -0.354602 & -2.431 & 0.009462 \tabularnewline
13 & -0.129596 & -0.8885 & 0.189408 \tabularnewline
14 & 0.143668 & 0.9849 & 0.16485 \tabularnewline
15 & -0.167392 & -1.1476 & 0.128475 \tabularnewline
16 & -0.019763 & -0.1355 & 0.446403 \tabularnewline
17 & 0.032883 & 0.2254 & 0.411309 \tabularnewline
18 & -0.357404 & -2.4502 & 0.009027 \tabularnewline
19 & 0.113485 & 0.778 & 0.220229 \tabularnewline
20 & 0.017554 & 0.1203 & 0.452361 \tabularnewline
21 & -0.176274 & -1.2085 & 0.116455 \tabularnewline
22 & 0.118217 & 0.8105 & 0.210881 \tabularnewline
23 & 0.058378 & 0.4002 & 0.345404 \tabularnewline
24 & -0.141441 & -0.9697 & 0.168587 \tabularnewline
25 & 0.212709 & 1.4583 & 0.07571 \tabularnewline
26 & -0.000649 & -0.0045 & 0.498233 \tabularnewline
27 & -0.08702 & -0.5966 & 0.276826 \tabularnewline
28 & 0.040772 & 0.2795 & 0.390537 \tabularnewline
29 & 0.048361 & 0.3315 & 0.370854 \tabularnewline
30 & 0.077966 & 0.5345 & 0.297754 \tabularnewline
31 & 0.009609 & 0.0659 & 0.473877 \tabularnewline
32 & 0.002329 & 0.016 & 0.493665 \tabularnewline
33 & -0.016086 & -0.1103 & 0.45633 \tabularnewline
34 & 0.073791 & 0.5059 & 0.307651 \tabularnewline
35 & -0.123054 & -0.8436 & 0.20158 \tabularnewline
36 & 0.0636 & 0.436 & 0.332409 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=58797&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]-0.186791[/C][C]-1.2806[/C][C]0.103314[/C][/ROW]
[ROW][C]2[/C][C]-0.036465[/C][C]-0.25[/C][C]0.401841[/C][/ROW]
[ROW][C]3[/C][C]0.31876[/C][C]2.1853[/C][C]0.016942[/C][/ROW]
[ROW][C]4[/C][C]-0.176154[/C][C]-1.2077[/C][C]0.116611[/C][/ROW]
[ROW][C]5[/C][C]0.064971[/C][C]0.4454[/C][C]0.32903[/C][/ROW]
[ROW][C]6[/C][C]0.27438[/C][C]1.8811[/C][C]0.033084[/C][/ROW]
[ROW][C]7[/C][C]-0.205514[/C][C]-1.4089[/C][C]0.082718[/C][/ROW]
[ROW][C]8[/C][C]0.17753[/C][C]1.2171[/C][C]0.114824[/C][/ROW]
[ROW][C]9[/C][C]0.020213[/C][C]0.1386[/C][C]0.44519[/C][/ROW]
[ROW][C]10[/C][C]-0.241558[/C][C]-1.656[/C][C]0.052188[/C][/ROW]
[ROW][C]11[/C][C]0.179572[/C][C]1.2311[/C][C]0.112208[/C][/ROW]
[ROW][C]12[/C][C]-0.354602[/C][C]-2.431[/C][C]0.009462[/C][/ROW]
[ROW][C]13[/C][C]-0.129596[/C][C]-0.8885[/C][C]0.189408[/C][/ROW]
[ROW][C]14[/C][C]0.143668[/C][C]0.9849[/C][C]0.16485[/C][/ROW]
[ROW][C]15[/C][C]-0.167392[/C][C]-1.1476[/C][C]0.128475[/C][/ROW]
[ROW][C]16[/C][C]-0.019763[/C][C]-0.1355[/C][C]0.446403[/C][/ROW]
[ROW][C]17[/C][C]0.032883[/C][C]0.2254[/C][C]0.411309[/C][/ROW]
[ROW][C]18[/C][C]-0.357404[/C][C]-2.4502[/C][C]0.009027[/C][/ROW]
[ROW][C]19[/C][C]0.113485[/C][C]0.778[/C][C]0.220229[/C][/ROW]
[ROW][C]20[/C][C]0.017554[/C][C]0.1203[/C][C]0.452361[/C][/ROW]
[ROW][C]21[/C][C]-0.176274[/C][C]-1.2085[/C][C]0.116455[/C][/ROW]
[ROW][C]22[/C][C]0.118217[/C][C]0.8105[/C][C]0.210881[/C][/ROW]
[ROW][C]23[/C][C]0.058378[/C][C]0.4002[/C][C]0.345404[/C][/ROW]
[ROW][C]24[/C][C]-0.141441[/C][C]-0.9697[/C][C]0.168587[/C][/ROW]
[ROW][C]25[/C][C]0.212709[/C][C]1.4583[/C][C]0.07571[/C][/ROW]
[ROW][C]26[/C][C]-0.000649[/C][C]-0.0045[/C][C]0.498233[/C][/ROW]
[ROW][C]27[/C][C]-0.08702[/C][C]-0.5966[/C][C]0.276826[/C][/ROW]
[ROW][C]28[/C][C]0.040772[/C][C]0.2795[/C][C]0.390537[/C][/ROW]
[ROW][C]29[/C][C]0.048361[/C][C]0.3315[/C][C]0.370854[/C][/ROW]
[ROW][C]30[/C][C]0.077966[/C][C]0.5345[/C][C]0.297754[/C][/ROW]
[ROW][C]31[/C][C]0.009609[/C][C]0.0659[/C][C]0.473877[/C][/ROW]
[ROW][C]32[/C][C]0.002329[/C][C]0.016[/C][C]0.493665[/C][/ROW]
[ROW][C]33[/C][C]-0.016086[/C][C]-0.1103[/C][C]0.45633[/C][/ROW]
[ROW][C]34[/C][C]0.073791[/C][C]0.5059[/C][C]0.307651[/C][/ROW]
[ROW][C]35[/C][C]-0.123054[/C][C]-0.8436[/C][C]0.20158[/C][/ROW]
[ROW][C]36[/C][C]0.0636[/C][C]0.436[/C][C]0.332409[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=58797&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=58797&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
1-0.186791-1.28060.103314
2-0.036465-0.250.401841
30.318762.18530.016942
4-0.176154-1.20770.116611
50.0649710.44540.32903
60.274381.88110.033084
7-0.205514-1.40890.082718
80.177531.21710.114824
90.0202130.13860.44519
10-0.241558-1.6560.052188
110.1795721.23110.112208
12-0.354602-2.4310.009462
13-0.129596-0.88850.189408
140.1436680.98490.16485
15-0.167392-1.14760.128475
16-0.019763-0.13550.446403
170.0328830.22540.411309
18-0.357404-2.45020.009027
190.1134850.7780.220229
200.0175540.12030.452361
21-0.176274-1.20850.116455
220.1182170.81050.210881
230.0583780.40020.345404
24-0.141441-0.96970.168587
250.2127091.45830.07571
26-0.000649-0.00450.498233
27-0.08702-0.59660.276826
280.0407720.27950.390537
290.0483610.33150.370854
300.0779660.53450.297754
310.0096090.06590.473877
320.0023290.0160.493665
33-0.016086-0.11030.45633
340.0737910.50590.307651
35-0.123054-0.84360.20158
360.06360.4360.332409






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.186791-1.28060.103314
2-0.073936-0.50690.307305
30.310092.12590.019399
4-0.071495-0.49010.313156
50.0452730.31040.378824
60.2215361.51880.067759
7-0.068849-0.4720.319554
80.1184960.81240.210339
9-0.07106-0.48720.314204
10-0.163584-1.12150.133892
110.0089960.06170.475543
12-0.441736-3.02840.001992
13-0.160155-1.0980.138905
14-0.099289-0.68070.249704
150.0649450.44520.329094
160.1005920.68960.24691
17-0.00974-0.06680.473524
18-0.090831-0.62270.268244
190.0459860.31530.376979
200.0906930.62180.268551
210.0251140.17220.43202
22-0.133462-0.9150.18244
230.1172120.80360.212848
24-0.173584-1.190.120005
250.0540270.37040.356377
260.0653650.44810.328063
27-0.030555-0.20950.417491
28-0.167353-1.14730.12853
29-0.021395-0.14670.442008
30-0.013092-0.08980.464433
31-0.090061-0.61740.269967
320.0393590.26980.394237
33-0.044193-0.3030.381624
340.0763670.52350.301527
35-0.058555-0.40140.344961
36-0.037005-0.25370.40042

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.186791 & -1.2806 & 0.103314 \tabularnewline
2 & -0.073936 & -0.5069 & 0.307305 \tabularnewline
3 & 0.31009 & 2.1259 & 0.019399 \tabularnewline
4 & -0.071495 & -0.4901 & 0.313156 \tabularnewline
5 & 0.045273 & 0.3104 & 0.378824 \tabularnewline
6 & 0.221536 & 1.5188 & 0.067759 \tabularnewline
7 & -0.068849 & -0.472 & 0.319554 \tabularnewline
8 & 0.118496 & 0.8124 & 0.210339 \tabularnewline
9 & -0.07106 & -0.4872 & 0.314204 \tabularnewline
10 & -0.163584 & -1.1215 & 0.133892 \tabularnewline
11 & 0.008996 & 0.0617 & 0.475543 \tabularnewline
12 & -0.441736 & -3.0284 & 0.001992 \tabularnewline
13 & -0.160155 & -1.098 & 0.138905 \tabularnewline
14 & -0.099289 & -0.6807 & 0.249704 \tabularnewline
15 & 0.064945 & 0.4452 & 0.329094 \tabularnewline
16 & 0.100592 & 0.6896 & 0.24691 \tabularnewline
17 & -0.00974 & -0.0668 & 0.473524 \tabularnewline
18 & -0.090831 & -0.6227 & 0.268244 \tabularnewline
19 & 0.045986 & 0.3153 & 0.376979 \tabularnewline
20 & 0.090693 & 0.6218 & 0.268551 \tabularnewline
21 & 0.025114 & 0.1722 & 0.43202 \tabularnewline
22 & -0.133462 & -0.915 & 0.18244 \tabularnewline
23 & 0.117212 & 0.8036 & 0.212848 \tabularnewline
24 & -0.173584 & -1.19 & 0.120005 \tabularnewline
25 & 0.054027 & 0.3704 & 0.356377 \tabularnewline
26 & 0.065365 & 0.4481 & 0.328063 \tabularnewline
27 & -0.030555 & -0.2095 & 0.417491 \tabularnewline
28 & -0.167353 & -1.1473 & 0.12853 \tabularnewline
29 & -0.021395 & -0.1467 & 0.442008 \tabularnewline
30 & -0.013092 & -0.0898 & 0.464433 \tabularnewline
31 & -0.090061 & -0.6174 & 0.269967 \tabularnewline
32 & 0.039359 & 0.2698 & 0.394237 \tabularnewline
33 & -0.044193 & -0.303 & 0.381624 \tabularnewline
34 & 0.076367 & 0.5235 & 0.301527 \tabularnewline
35 & -0.058555 & -0.4014 & 0.344961 \tabularnewline
36 & -0.037005 & -0.2537 & 0.40042 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=58797&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]-0.186791[/C][C]-1.2806[/C][C]0.103314[/C][/ROW]
[ROW][C]2[/C][C]-0.073936[/C][C]-0.5069[/C][C]0.307305[/C][/ROW]
[ROW][C]3[/C][C]0.31009[/C][C]2.1259[/C][C]0.019399[/C][/ROW]
[ROW][C]4[/C][C]-0.071495[/C][C]-0.4901[/C][C]0.313156[/C][/ROW]
[ROW][C]5[/C][C]0.045273[/C][C]0.3104[/C][C]0.378824[/C][/ROW]
[ROW][C]6[/C][C]0.221536[/C][C]1.5188[/C][C]0.067759[/C][/ROW]
[ROW][C]7[/C][C]-0.068849[/C][C]-0.472[/C][C]0.319554[/C][/ROW]
[ROW][C]8[/C][C]0.118496[/C][C]0.8124[/C][C]0.210339[/C][/ROW]
[ROW][C]9[/C][C]-0.07106[/C][C]-0.4872[/C][C]0.314204[/C][/ROW]
[ROW][C]10[/C][C]-0.163584[/C][C]-1.1215[/C][C]0.133892[/C][/ROW]
[ROW][C]11[/C][C]0.008996[/C][C]0.0617[/C][C]0.475543[/C][/ROW]
[ROW][C]12[/C][C]-0.441736[/C][C]-3.0284[/C][C]0.001992[/C][/ROW]
[ROW][C]13[/C][C]-0.160155[/C][C]-1.098[/C][C]0.138905[/C][/ROW]
[ROW][C]14[/C][C]-0.099289[/C][C]-0.6807[/C][C]0.249704[/C][/ROW]
[ROW][C]15[/C][C]0.064945[/C][C]0.4452[/C][C]0.329094[/C][/ROW]
[ROW][C]16[/C][C]0.100592[/C][C]0.6896[/C][C]0.24691[/C][/ROW]
[ROW][C]17[/C][C]-0.00974[/C][C]-0.0668[/C][C]0.473524[/C][/ROW]
[ROW][C]18[/C][C]-0.090831[/C][C]-0.6227[/C][C]0.268244[/C][/ROW]
[ROW][C]19[/C][C]0.045986[/C][C]0.3153[/C][C]0.376979[/C][/ROW]
[ROW][C]20[/C][C]0.090693[/C][C]0.6218[/C][C]0.268551[/C][/ROW]
[ROW][C]21[/C][C]0.025114[/C][C]0.1722[/C][C]0.43202[/C][/ROW]
[ROW][C]22[/C][C]-0.133462[/C][C]-0.915[/C][C]0.18244[/C][/ROW]
[ROW][C]23[/C][C]0.117212[/C][C]0.8036[/C][C]0.212848[/C][/ROW]
[ROW][C]24[/C][C]-0.173584[/C][C]-1.19[/C][C]0.120005[/C][/ROW]
[ROW][C]25[/C][C]0.054027[/C][C]0.3704[/C][C]0.356377[/C][/ROW]
[ROW][C]26[/C][C]0.065365[/C][C]0.4481[/C][C]0.328063[/C][/ROW]
[ROW][C]27[/C][C]-0.030555[/C][C]-0.2095[/C][C]0.417491[/C][/ROW]
[ROW][C]28[/C][C]-0.167353[/C][C]-1.1473[/C][C]0.12853[/C][/ROW]
[ROW][C]29[/C][C]-0.021395[/C][C]-0.1467[/C][C]0.442008[/C][/ROW]
[ROW][C]30[/C][C]-0.013092[/C][C]-0.0898[/C][C]0.464433[/C][/ROW]
[ROW][C]31[/C][C]-0.090061[/C][C]-0.6174[/C][C]0.269967[/C][/ROW]
[ROW][C]32[/C][C]0.039359[/C][C]0.2698[/C][C]0.394237[/C][/ROW]
[ROW][C]33[/C][C]-0.044193[/C][C]-0.303[/C][C]0.381624[/C][/ROW]
[ROW][C]34[/C][C]0.076367[/C][C]0.5235[/C][C]0.301527[/C][/ROW]
[ROW][C]35[/C][C]-0.058555[/C][C]-0.4014[/C][C]0.344961[/C][/ROW]
[ROW][C]36[/C][C]-0.037005[/C][C]-0.2537[/C][C]0.40042[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=58797&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=58797&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
1-0.186791-1.28060.103314
2-0.073936-0.50690.307305
30.310092.12590.019399
4-0.071495-0.49010.313156
50.0452730.31040.378824
60.2215361.51880.067759
7-0.068849-0.4720.319554
80.1184960.81240.210339
9-0.07106-0.48720.314204
10-0.163584-1.12150.133892
110.0089960.06170.475543
12-0.441736-3.02840.001992
13-0.160155-1.0980.138905
14-0.099289-0.68070.249704
150.0649450.44520.329094
160.1005920.68960.24691
17-0.00974-0.06680.473524
18-0.090831-0.62270.268244
190.0459860.31530.376979
200.0906930.62180.268551
210.0251140.17220.43202
22-0.133462-0.9150.18244
230.1172120.80360.212848
24-0.173584-1.190.120005
250.0540270.37040.356377
260.0653650.44810.328063
27-0.030555-0.20950.417491
28-0.167353-1.14730.12853
29-0.021395-0.14670.442008
30-0.013092-0.08980.464433
31-0.090061-0.61740.269967
320.0393590.26980.394237
33-0.044193-0.3030.381624
340.0763670.52350.301527
35-0.058555-0.40140.344961
36-0.037005-0.25370.40042


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')