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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 computationThu, 03 Dec 2009 05:09:45 -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/Dec/03/t12598422262i82nnexjzpl027.htm/, Retrieved Fri, 19 Apr 2024 08:15:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62687, Retrieved Fri, 19 Apr 2024 08:15:14 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact147

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [(Partial) Autocorrelation Function] [] [2009-11-27 14:46:03] [b98453cac15ba1066b407e146608df68]
-    D      [(Partial) Autocorrelation Function] [] [2009-12-03 12:09:45] [8551abdd6804649d94d88b1829ac2b1a] [Current]
-   PD        [(Partial) Autocorrelation Function] [] [2009-12-03 12:13:55] [875a981b2b01315c1c471abd4dd66675]
-   P           [(Partial) Autocorrelation Function] [] [2009-12-03 12:15:21] [875a981b2b01315c1c471abd4dd66675]
- RMP           [ARIMA Backward Selection] [] [2009-12-11 17:32:13] [875a981b2b01315c1c471abd4dd66675]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
128,7
136,9
156,9
109,1
122,3
123,9
90,9
77,9
120,3
118,9
125,5
98,9
102,9
105,9
117,6
113,6
115,9
118,9
77,6
81,2
123,1
136,6
112,1
95,1
96,3
105,7
115,8
105,7
105,7
111,1
82,4
60
107,3
99,3
113,5
108,9
100,2
103,9
138,7
120,2
100,2
143,2
70,9
85,2
133
136,6
117,9
106,3
122,3
125,5
148,4
126,3
99,6
140,4
80,3
92,6
138,5
110,9
119,6
105
109
129,4
148,6
101,4
134,8
143,7
81,6
90,3
141,5
140,7
140,2
100,2
125,7
119,6
134,7
109
116,3
146,9
97,4
89,4
132,1
139,8
129
112,5
121,9
121,7
123,1
131,6
119,3
132,5
98,3
85,1
131,7
129,3
90,7
78,6
68,9
79,1
83,5
74,1
59,7
93,3
61,3
56,6
98,5

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=62687&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=62687&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62687&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
10.3546513.63410.000217
20.0566220.58020.281512
30.2317182.37440.009697
40.2106672.15870.016576
50.2016832.06660.020614
60.2036632.08690.019658
70.1176091.20510.11543
80.0855010.87610.191481
90.0206430.21150.416445
10-0.212085-2.17320.016005
110.0217020.22240.412227
120.4339354.44651.1e-05
13-0.007654-0.07840.46882
14-0.252051-2.58270.005589
15-0.060961-0.62470.266773
16-0.066993-0.68650.246963
17-0.046119-0.47260.318748
18-0.034282-0.35130.363038
19-0.010939-0.11210.455483
20-0.02138-0.21910.413505
21-0.063604-0.65170.257994
22-0.258555-2.64940.004655
23-0.022629-0.23190.408543
240.3462543.5480.000291
25-0.036339-0.37240.355188
26-0.268179-2.7480.003529
27-0.107669-1.10330.136215
28-0.086305-0.88440.18926
29-0.094194-0.96520.168332
30-0.098093-1.00520.158567
31-0.084658-0.86750.193826
32-0.113274-1.16070.124195
33-0.11113-1.13870.128701
34-0.221666-2.27140.012581
35-0.076188-0.78070.218369
360.2538872.60160.00531

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.354651 & 3.6341 & 0.000217 \tabularnewline
2 & 0.056622 & 0.5802 & 0.281512 \tabularnewline
3 & 0.231718 & 2.3744 & 0.009697 \tabularnewline
4 & 0.210667 & 2.1587 & 0.016576 \tabularnewline
5 & 0.201683 & 2.0666 & 0.020614 \tabularnewline
6 & 0.203663 & 2.0869 & 0.019658 \tabularnewline
7 & 0.117609 & 1.2051 & 0.11543 \tabularnewline
8 & 0.085501 & 0.8761 & 0.191481 \tabularnewline
9 & 0.020643 & 0.2115 & 0.416445 \tabularnewline
10 & -0.212085 & -2.1732 & 0.016005 \tabularnewline
11 & 0.021702 & 0.2224 & 0.412227 \tabularnewline
12 & 0.433935 & 4.4465 & 1.1e-05 \tabularnewline
13 & -0.007654 & -0.0784 & 0.46882 \tabularnewline
14 & -0.252051 & -2.5827 & 0.005589 \tabularnewline
15 & -0.060961 & -0.6247 & 0.266773 \tabularnewline
16 & -0.066993 & -0.6865 & 0.246963 \tabularnewline
17 & -0.046119 & -0.4726 & 0.318748 \tabularnewline
18 & -0.034282 & -0.3513 & 0.363038 \tabularnewline
19 & -0.010939 & -0.1121 & 0.455483 \tabularnewline
20 & -0.02138 & -0.2191 & 0.413505 \tabularnewline
21 & -0.063604 & -0.6517 & 0.257994 \tabularnewline
22 & -0.258555 & -2.6494 & 0.004655 \tabularnewline
23 & -0.022629 & -0.2319 & 0.408543 \tabularnewline
24 & 0.346254 & 3.548 & 0.000291 \tabularnewline
25 & -0.036339 & -0.3724 & 0.355188 \tabularnewline
26 & -0.268179 & -2.748 & 0.003529 \tabularnewline
27 & -0.107669 & -1.1033 & 0.136215 \tabularnewline
28 & -0.086305 & -0.8844 & 0.18926 \tabularnewline
29 & -0.094194 & -0.9652 & 0.168332 \tabularnewline
30 & -0.098093 & -1.0052 & 0.158567 \tabularnewline
31 & -0.084658 & -0.8675 & 0.193826 \tabularnewline
32 & -0.113274 & -1.1607 & 0.124195 \tabularnewline
33 & -0.11113 & -1.1387 & 0.128701 \tabularnewline
34 & -0.221666 & -2.2714 & 0.012581 \tabularnewline
35 & -0.076188 & -0.7807 & 0.218369 \tabularnewline
36 & 0.253887 & 2.6016 & 0.00531 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62687&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]0.354651[/C][C]3.6341[/C][C]0.000217[/C][/ROW]
[ROW][C]2[/C][C]0.056622[/C][C]0.5802[/C][C]0.281512[/C][/ROW]
[ROW][C]3[/C][C]0.231718[/C][C]2.3744[/C][C]0.009697[/C][/ROW]
[ROW][C]4[/C][C]0.210667[/C][C]2.1587[/C][C]0.016576[/C][/ROW]
[ROW][C]5[/C][C]0.201683[/C][C]2.0666[/C][C]0.020614[/C][/ROW]
[ROW][C]6[/C][C]0.203663[/C][C]2.0869[/C][C]0.019658[/C][/ROW]
[ROW][C]7[/C][C]0.117609[/C][C]1.2051[/C][C]0.11543[/C][/ROW]
[ROW][C]8[/C][C]0.085501[/C][C]0.8761[/C][C]0.191481[/C][/ROW]
[ROW][C]9[/C][C]0.020643[/C][C]0.2115[/C][C]0.416445[/C][/ROW]
[ROW][C]10[/C][C]-0.212085[/C][C]-2.1732[/C][C]0.016005[/C][/ROW]
[ROW][C]11[/C][C]0.021702[/C][C]0.2224[/C][C]0.412227[/C][/ROW]
[ROW][C]12[/C][C]0.433935[/C][C]4.4465[/C][C]1.1e-05[/C][/ROW]
[ROW][C]13[/C][C]-0.007654[/C][C]-0.0784[/C][C]0.46882[/C][/ROW]
[ROW][C]14[/C][C]-0.252051[/C][C]-2.5827[/C][C]0.005589[/C][/ROW]
[ROW][C]15[/C][C]-0.060961[/C][C]-0.6247[/C][C]0.266773[/C][/ROW]
[ROW][C]16[/C][C]-0.066993[/C][C]-0.6865[/C][C]0.246963[/C][/ROW]
[ROW][C]17[/C][C]-0.046119[/C][C]-0.4726[/C][C]0.318748[/C][/ROW]
[ROW][C]18[/C][C]-0.034282[/C][C]-0.3513[/C][C]0.363038[/C][/ROW]
[ROW][C]19[/C][C]-0.010939[/C][C]-0.1121[/C][C]0.455483[/C][/ROW]
[ROW][C]20[/C][C]-0.02138[/C][C]-0.2191[/C][C]0.413505[/C][/ROW]
[ROW][C]21[/C][C]-0.063604[/C][C]-0.6517[/C][C]0.257994[/C][/ROW]
[ROW][C]22[/C][C]-0.258555[/C][C]-2.6494[/C][C]0.004655[/C][/ROW]
[ROW][C]23[/C][C]-0.022629[/C][C]-0.2319[/C][C]0.408543[/C][/ROW]
[ROW][C]24[/C][C]0.346254[/C][C]3.548[/C][C]0.000291[/C][/ROW]
[ROW][C]25[/C][C]-0.036339[/C][C]-0.3724[/C][C]0.355188[/C][/ROW]
[ROW][C]26[/C][C]-0.268179[/C][C]-2.748[/C][C]0.003529[/C][/ROW]
[ROW][C]27[/C][C]-0.107669[/C][C]-1.1033[/C][C]0.136215[/C][/ROW]
[ROW][C]28[/C][C]-0.086305[/C][C]-0.8844[/C][C]0.18926[/C][/ROW]
[ROW][C]29[/C][C]-0.094194[/C][C]-0.9652[/C][C]0.168332[/C][/ROW]
[ROW][C]30[/C][C]-0.098093[/C][C]-1.0052[/C][C]0.158567[/C][/ROW]
[ROW][C]31[/C][C]-0.084658[/C][C]-0.8675[/C][C]0.193826[/C][/ROW]
[ROW][C]32[/C][C]-0.113274[/C][C]-1.1607[/C][C]0.124195[/C][/ROW]
[ROW][C]33[/C][C]-0.11113[/C][C]-1.1387[/C][C]0.128701[/C][/ROW]
[ROW][C]34[/C][C]-0.221666[/C][C]-2.2714[/C][C]0.012581[/C][/ROW]
[ROW][C]35[/C][C]-0.076188[/C][C]-0.7807[/C][C]0.218369[/C][/ROW]
[ROW][C]36[/C][C]0.253887[/C][C]2.6016[/C][C]0.00531[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62687&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62687&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
10.3546513.63410.000217
20.0566220.58020.281512
30.2317182.37440.009697
40.2106672.15870.016576
50.2016832.06660.020614
60.2036632.08690.019658
70.1176091.20510.11543
80.0855010.87610.191481
90.0206430.21150.416445
10-0.212085-2.17320.016005
110.0217020.22240.412227
120.4339354.44651.1e-05
13-0.007654-0.07840.46882
14-0.252051-2.58270.005589
15-0.060961-0.62470.266773
16-0.066993-0.68650.246963
17-0.046119-0.47260.318748
18-0.034282-0.35130.363038
19-0.010939-0.11210.455483
20-0.02138-0.21910.413505
21-0.063604-0.65170.257994
22-0.258555-2.64940.004655
23-0.022629-0.23190.408543
240.3462543.5480.000291
25-0.036339-0.37240.355188
26-0.268179-2.7480.003529
27-0.107669-1.10330.136215
28-0.086305-0.88440.18926
29-0.094194-0.96520.168332
30-0.098093-1.00520.158567
31-0.084658-0.86750.193826
32-0.113274-1.16070.124195
33-0.11113-1.13870.128701
34-0.221666-2.27140.012581
35-0.076188-0.78070.218369
360.2538872.60160.00531






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3546513.63410.000217
2-0.079105-0.81060.209717
30.2740752.80840.002969
40.0375610.38490.350551
50.164161.68210.047757
60.0618340.63360.263856
70.0012620.01290.494855
8-0.003254-0.03330.486731
9-0.104332-1.06910.14374
10-0.313663-3.21410.000869
110.1744441.78750.03837
120.4378094.48629e-06
13-0.30305-3.10530.001222
14-0.176162-1.80510.036961
15-0.015773-0.16160.435954
16-0.053613-0.54940.291961
17-0.008047-0.08250.467221
18-0.044404-0.4550.325023
190.159381.63320.052716
20-0.050575-0.51820.302692
210.0419590.430.334055
22-0.059493-0.60960.271716
230.0586280.60080.274649
240.099491.01950.155163
25-0.152561-1.56330.060497
26-0.12744-1.30590.097225
27-0.093585-0.9590.169891
28-0.001214-0.01240.495049
29-0.046894-0.48050.315929
30-0.052925-0.54230.294373
31-0.017959-0.1840.427176
32-0.091258-0.93510.175937
330.1276671.30820.096832
340.1113621.14110.128207
35-0.07876-0.80710.210731
360.0110890.11360.454876

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.354651 & 3.6341 & 0.000217 \tabularnewline
2 & -0.079105 & -0.8106 & 0.209717 \tabularnewline
3 & 0.274075 & 2.8084 & 0.002969 \tabularnewline
4 & 0.037561 & 0.3849 & 0.350551 \tabularnewline
5 & 0.16416 & 1.6821 & 0.047757 \tabularnewline
6 & 0.061834 & 0.6336 & 0.263856 \tabularnewline
7 & 0.001262 & 0.0129 & 0.494855 \tabularnewline
8 & -0.003254 & -0.0333 & 0.486731 \tabularnewline
9 & -0.104332 & -1.0691 & 0.14374 \tabularnewline
10 & -0.313663 & -3.2141 & 0.000869 \tabularnewline
11 & 0.174444 & 1.7875 & 0.03837 \tabularnewline
12 & 0.437809 & 4.4862 & 9e-06 \tabularnewline
13 & -0.30305 & -3.1053 & 0.001222 \tabularnewline
14 & -0.176162 & -1.8051 & 0.036961 \tabularnewline
15 & -0.015773 & -0.1616 & 0.435954 \tabularnewline
16 & -0.053613 & -0.5494 & 0.291961 \tabularnewline
17 & -0.008047 & -0.0825 & 0.467221 \tabularnewline
18 & -0.044404 & -0.455 & 0.325023 \tabularnewline
19 & 0.15938 & 1.6332 & 0.052716 \tabularnewline
20 & -0.050575 & -0.5182 & 0.302692 \tabularnewline
21 & 0.041959 & 0.43 & 0.334055 \tabularnewline
22 & -0.059493 & -0.6096 & 0.271716 \tabularnewline
23 & 0.058628 & 0.6008 & 0.274649 \tabularnewline
24 & 0.09949 & 1.0195 & 0.155163 \tabularnewline
25 & -0.152561 & -1.5633 & 0.060497 \tabularnewline
26 & -0.12744 & -1.3059 & 0.097225 \tabularnewline
27 & -0.093585 & -0.959 & 0.169891 \tabularnewline
28 & -0.001214 & -0.0124 & 0.495049 \tabularnewline
29 & -0.046894 & -0.4805 & 0.315929 \tabularnewline
30 & -0.052925 & -0.5423 & 0.294373 \tabularnewline
31 & -0.017959 & -0.184 & 0.427176 \tabularnewline
32 & -0.091258 & -0.9351 & 0.175937 \tabularnewline
33 & 0.127667 & 1.3082 & 0.096832 \tabularnewline
34 & 0.111362 & 1.1411 & 0.128207 \tabularnewline
35 & -0.07876 & -0.8071 & 0.210731 \tabularnewline
36 & 0.011089 & 0.1136 & 0.454876 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62687&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]0.354651[/C][C]3.6341[/C][C]0.000217[/C][/ROW]
[ROW][C]2[/C][C]-0.079105[/C][C]-0.8106[/C][C]0.209717[/C][/ROW]
[ROW][C]3[/C][C]0.274075[/C][C]2.8084[/C][C]0.002969[/C][/ROW]
[ROW][C]4[/C][C]0.037561[/C][C]0.3849[/C][C]0.350551[/C][/ROW]
[ROW][C]5[/C][C]0.16416[/C][C]1.6821[/C][C]0.047757[/C][/ROW]
[ROW][C]6[/C][C]0.061834[/C][C]0.6336[/C][C]0.263856[/C][/ROW]
[ROW][C]7[/C][C]0.001262[/C][C]0.0129[/C][C]0.494855[/C][/ROW]
[ROW][C]8[/C][C]-0.003254[/C][C]-0.0333[/C][C]0.486731[/C][/ROW]
[ROW][C]9[/C][C]-0.104332[/C][C]-1.0691[/C][C]0.14374[/C][/ROW]
[ROW][C]10[/C][C]-0.313663[/C][C]-3.2141[/C][C]0.000869[/C][/ROW]
[ROW][C]11[/C][C]0.174444[/C][C]1.7875[/C][C]0.03837[/C][/ROW]
[ROW][C]12[/C][C]0.437809[/C][C]4.4862[/C][C]9e-06[/C][/ROW]
[ROW][C]13[/C][C]-0.30305[/C][C]-3.1053[/C][C]0.001222[/C][/ROW]
[ROW][C]14[/C][C]-0.176162[/C][C]-1.8051[/C][C]0.036961[/C][/ROW]
[ROW][C]15[/C][C]-0.015773[/C][C]-0.1616[/C][C]0.435954[/C][/ROW]
[ROW][C]16[/C][C]-0.053613[/C][C]-0.5494[/C][C]0.291961[/C][/ROW]
[ROW][C]17[/C][C]-0.008047[/C][C]-0.0825[/C][C]0.467221[/C][/ROW]
[ROW][C]18[/C][C]-0.044404[/C][C]-0.455[/C][C]0.325023[/C][/ROW]
[ROW][C]19[/C][C]0.15938[/C][C]1.6332[/C][C]0.052716[/C][/ROW]
[ROW][C]20[/C][C]-0.050575[/C][C]-0.5182[/C][C]0.302692[/C][/ROW]
[ROW][C]21[/C][C]0.041959[/C][C]0.43[/C][C]0.334055[/C][/ROW]
[ROW][C]22[/C][C]-0.059493[/C][C]-0.6096[/C][C]0.271716[/C][/ROW]
[ROW][C]23[/C][C]0.058628[/C][C]0.6008[/C][C]0.274649[/C][/ROW]
[ROW][C]24[/C][C]0.09949[/C][C]1.0195[/C][C]0.155163[/C][/ROW]
[ROW][C]25[/C][C]-0.152561[/C][C]-1.5633[/C][C]0.060497[/C][/ROW]
[ROW][C]26[/C][C]-0.12744[/C][C]-1.3059[/C][C]0.097225[/C][/ROW]
[ROW][C]27[/C][C]-0.093585[/C][C]-0.959[/C][C]0.169891[/C][/ROW]
[ROW][C]28[/C][C]-0.001214[/C][C]-0.0124[/C][C]0.495049[/C][/ROW]
[ROW][C]29[/C][C]-0.046894[/C][C]-0.4805[/C][C]0.315929[/C][/ROW]
[ROW][C]30[/C][C]-0.052925[/C][C]-0.5423[/C][C]0.294373[/C][/ROW]
[ROW][C]31[/C][C]-0.017959[/C][C]-0.184[/C][C]0.427176[/C][/ROW]
[ROW][C]32[/C][C]-0.091258[/C][C]-0.9351[/C][C]0.175937[/C][/ROW]
[ROW][C]33[/C][C]0.127667[/C][C]1.3082[/C][C]0.096832[/C][/ROW]
[ROW][C]34[/C][C]0.111362[/C][C]1.1411[/C][C]0.128207[/C][/ROW]
[ROW][C]35[/C][C]-0.07876[/C][C]-0.8071[/C][C]0.210731[/C][/ROW]
[ROW][C]36[/C][C]0.011089[/C][C]0.1136[/C][C]0.454876[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62687&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62687&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
10.3546513.63410.000217
2-0.079105-0.81060.209717
30.2740752.80840.002969
40.0375610.38490.350551
50.164161.68210.047757
60.0618340.63360.263856
70.0012620.01290.494855
8-0.003254-0.03330.486731
9-0.104332-1.06910.14374
10-0.313663-3.21410.000869
110.1744441.78750.03837
120.4378094.48629e-06
13-0.30305-3.10530.001222
14-0.176162-1.80510.036961
15-0.015773-0.16160.435954
16-0.053613-0.54940.291961
17-0.008047-0.08250.467221
18-0.044404-0.4550.325023
190.159381.63320.052716
20-0.050575-0.51820.302692
210.0419590.430.334055
22-0.059493-0.60960.271716
230.0586280.60080.274649
240.099491.01950.155163
25-0.152561-1.56330.060497
26-0.12744-1.30590.097225
27-0.093585-0.9590.169891
28-0.001214-0.01240.495049
29-0.046894-0.48050.315929
30-0.052925-0.54230.294373
31-0.017959-0.1840.427176
32-0.091258-0.93510.175937
330.1276671.30820.096832
340.1113621.14110.128207
35-0.07876-0.80710.210731
360.0110890.11360.454876


Figures (Output of Computation)

Input Parameters & R Code

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')