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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 computationWed, 02 Dec 2009 03:04:22 -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/02/t1259748311g91v6ozqruq6vz2.htm/, Retrieved Sat, 27 Apr 2024 15:49:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62311, Retrieved Sat, 27 Apr 2024 15:49:33 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordscvm
Estimated Impact153

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] [BBWS8-ACF1] [2009-11-28 15:24:25] [408e92805dcb18620260f240a7fb9d53]
-    D          [(Partial) Autocorrelation Function] [W8: d,D=0, Lamda 1] [2009-12-01 14:27:42] [03d5b865e91ca35b5a5d21b8d6da5aba]
-   PD              [(Partial) Autocorrelation Function] [W9: Autocorrelati...] [2009-12-02 10:04:22] [a5ada8bd39e806b5b90f09589c89554a] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
114.1
110.3
103.9
101.6
94.6
95.9
104.7
102.8
98.1
113.9
80.9
95.7
113.2
105.9
108.8
102.3
99
100.7
115.5
100.7
109.9
114.6
85.4
100.5
114.8
116.5
112.9
102
106
105.3
118.8
106.1
109.3
117.2
92.5
104.2
112.5
122.4
113.3
100
110.7
112.8
109.8
117.3
109.1
115.9
96
99.8
116.8
115.7
99.4
94.3
91
93.2
103.1
94.1
91.8
102.7
82.6
89.1

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=62311&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=62311&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62311&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
1-0.357051-2.74260.00403
2-0.225365-1.73110.044334
30.1394381.0710.144255
4-0.203067-1.55980.062079
50.1529251.17460.122429
60.0836110.64220.261607
70.0342280.26290.396768
8-0.065305-0.50160.308901
90.0719880.5530.291192
10-0.262886-2.01930.024005
11-0.119196-0.91560.181812
120.5853664.49631.6e-05
13-0.190604-1.46410.074244
14-0.146274-1.12360.132877
15-0.023322-0.17910.429221
16-0.049822-0.38270.351662
170.1307891.00460.159594
18-0.033582-0.25790.398673
190.1192270.91580.18175
20-0.096522-0.74140.230696
210.0070570.05420.478476
22-0.107377-0.82480.206409
23-0.123917-0.95180.172534
240.3873462.97530.002119
25-0.079855-0.61340.270993
26-0.156496-1.20210.11707
27-0.006751-0.05190.47941
28-0.011467-0.08810.465056
290.073670.56590.286815
30-0.025261-0.1940.423408
310.1046160.80360.212436
32-0.098824-0.75910.225413
33-0.018598-0.14290.443447
340.0220780.16960.432958
35-0.167487-1.28650.101648
360.2671252.05180.022316

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.357051 & -2.7426 & 0.00403 \tabularnewline
2 & -0.225365 & -1.7311 & 0.044334 \tabularnewline
3 & 0.139438 & 1.071 & 0.144255 \tabularnewline
4 & -0.203067 & -1.5598 & 0.062079 \tabularnewline
5 & 0.152925 & 1.1746 & 0.122429 \tabularnewline
6 & 0.083611 & 0.6422 & 0.261607 \tabularnewline
7 & 0.034228 & 0.2629 & 0.396768 \tabularnewline
8 & -0.065305 & -0.5016 & 0.308901 \tabularnewline
9 & 0.071988 & 0.553 & 0.291192 \tabularnewline
10 & -0.262886 & -2.0193 & 0.024005 \tabularnewline
11 & -0.119196 & -0.9156 & 0.181812 \tabularnewline
12 & 0.585366 & 4.4963 & 1.6e-05 \tabularnewline
13 & -0.190604 & -1.4641 & 0.074244 \tabularnewline
14 & -0.146274 & -1.1236 & 0.132877 \tabularnewline
15 & -0.023322 & -0.1791 & 0.429221 \tabularnewline
16 & -0.049822 & -0.3827 & 0.351662 \tabularnewline
17 & 0.130789 & 1.0046 & 0.159594 \tabularnewline
18 & -0.033582 & -0.2579 & 0.398673 \tabularnewline
19 & 0.119227 & 0.9158 & 0.18175 \tabularnewline
20 & -0.096522 & -0.7414 & 0.230696 \tabularnewline
21 & 0.007057 & 0.0542 & 0.478476 \tabularnewline
22 & -0.107377 & -0.8248 & 0.206409 \tabularnewline
23 & -0.123917 & -0.9518 & 0.172534 \tabularnewline
24 & 0.387346 & 2.9753 & 0.002119 \tabularnewline
25 & -0.079855 & -0.6134 & 0.270993 \tabularnewline
26 & -0.156496 & -1.2021 & 0.11707 \tabularnewline
27 & -0.006751 & -0.0519 & 0.47941 \tabularnewline
28 & -0.011467 & -0.0881 & 0.465056 \tabularnewline
29 & 0.07367 & 0.5659 & 0.286815 \tabularnewline
30 & -0.025261 & -0.194 & 0.423408 \tabularnewline
31 & 0.104616 & 0.8036 & 0.212436 \tabularnewline
32 & -0.098824 & -0.7591 & 0.225413 \tabularnewline
33 & -0.018598 & -0.1429 & 0.443447 \tabularnewline
34 & 0.022078 & 0.1696 & 0.432958 \tabularnewline
35 & -0.167487 & -1.2865 & 0.101648 \tabularnewline
36 & 0.267125 & 2.0518 & 0.022316 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62311&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]-0.357051[/C][C]-2.7426[/C][C]0.00403[/C][/ROW]
[ROW][C]2[/C][C]-0.225365[/C][C]-1.7311[/C][C]0.044334[/C][/ROW]
[ROW][C]3[/C][C]0.139438[/C][C]1.071[/C][C]0.144255[/C][/ROW]
[ROW][C]4[/C][C]-0.203067[/C][C]-1.5598[/C][C]0.062079[/C][/ROW]
[ROW][C]5[/C][C]0.152925[/C][C]1.1746[/C][C]0.122429[/C][/ROW]
[ROW][C]6[/C][C]0.083611[/C][C]0.6422[/C][C]0.261607[/C][/ROW]
[ROW][C]7[/C][C]0.034228[/C][C]0.2629[/C][C]0.396768[/C][/ROW]
[ROW][C]8[/C][C]-0.065305[/C][C]-0.5016[/C][C]0.308901[/C][/ROW]
[ROW][C]9[/C][C]0.071988[/C][C]0.553[/C][C]0.291192[/C][/ROW]
[ROW][C]10[/C][C]-0.262886[/C][C]-2.0193[/C][C]0.024005[/C][/ROW]
[ROW][C]11[/C][C]-0.119196[/C][C]-0.9156[/C][C]0.181812[/C][/ROW]
[ROW][C]12[/C][C]0.585366[/C][C]4.4963[/C][C]1.6e-05[/C][/ROW]
[ROW][C]13[/C][C]-0.190604[/C][C]-1.4641[/C][C]0.074244[/C][/ROW]
[ROW][C]14[/C][C]-0.146274[/C][C]-1.1236[/C][C]0.132877[/C][/ROW]
[ROW][C]15[/C][C]-0.023322[/C][C]-0.1791[/C][C]0.429221[/C][/ROW]
[ROW][C]16[/C][C]-0.049822[/C][C]-0.3827[/C][C]0.351662[/C][/ROW]
[ROW][C]17[/C][C]0.130789[/C][C]1.0046[/C][C]0.159594[/C][/ROW]
[ROW][C]18[/C][C]-0.033582[/C][C]-0.2579[/C][C]0.398673[/C][/ROW]
[ROW][C]19[/C][C]0.119227[/C][C]0.9158[/C][C]0.18175[/C][/ROW]
[ROW][C]20[/C][C]-0.096522[/C][C]-0.7414[/C][C]0.230696[/C][/ROW]
[ROW][C]21[/C][C]0.007057[/C][C]0.0542[/C][C]0.478476[/C][/ROW]
[ROW][C]22[/C][C]-0.107377[/C][C]-0.8248[/C][C]0.206409[/C][/ROW]
[ROW][C]23[/C][C]-0.123917[/C][C]-0.9518[/C][C]0.172534[/C][/ROW]
[ROW][C]24[/C][C]0.387346[/C][C]2.9753[/C][C]0.002119[/C][/ROW]
[ROW][C]25[/C][C]-0.079855[/C][C]-0.6134[/C][C]0.270993[/C][/ROW]
[ROW][C]26[/C][C]-0.156496[/C][C]-1.2021[/C][C]0.11707[/C][/ROW]
[ROW][C]27[/C][C]-0.006751[/C][C]-0.0519[/C][C]0.47941[/C][/ROW]
[ROW][C]28[/C][C]-0.011467[/C][C]-0.0881[/C][C]0.465056[/C][/ROW]
[ROW][C]29[/C][C]0.07367[/C][C]0.5659[/C][C]0.286815[/C][/ROW]
[ROW][C]30[/C][C]-0.025261[/C][C]-0.194[/C][C]0.423408[/C][/ROW]
[ROW][C]31[/C][C]0.104616[/C][C]0.8036[/C][C]0.212436[/C][/ROW]
[ROW][C]32[/C][C]-0.098824[/C][C]-0.7591[/C][C]0.225413[/C][/ROW]
[ROW][C]33[/C][C]-0.018598[/C][C]-0.1429[/C][C]0.443447[/C][/ROW]
[ROW][C]34[/C][C]0.022078[/C][C]0.1696[/C][C]0.432958[/C][/ROW]
[ROW][C]35[/C][C]-0.167487[/C][C]-1.2865[/C][C]0.101648[/C][/ROW]
[ROW][C]36[/C][C]0.267125[/C][C]2.0518[/C][C]0.022316[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62311&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62311&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
1-0.357051-2.74260.00403
2-0.225365-1.73110.044334
30.1394381.0710.144255
4-0.203067-1.55980.062079
50.1529251.17460.122429
60.0836110.64220.261607
70.0342280.26290.396768
8-0.065305-0.50160.308901
90.0719880.5530.291192
10-0.262886-2.01930.024005
11-0.119196-0.91560.181812
120.5853664.49631.6e-05
13-0.190604-1.46410.074244
14-0.146274-1.12360.132877
15-0.023322-0.17910.429221
16-0.049822-0.38270.351662
170.1307891.00460.159594
18-0.033582-0.25790.398673
190.1192270.91580.18175
20-0.096522-0.74140.230696
210.0070570.05420.478476
22-0.107377-0.82480.206409
23-0.123917-0.95180.172534
240.3873462.97530.002119
25-0.079855-0.61340.270993
26-0.156496-1.20210.11707
27-0.006751-0.05190.47941
28-0.011467-0.08810.465056
290.073670.56590.286815
30-0.025261-0.1940.423408
310.1046160.80360.212436
32-0.098824-0.75910.225413
33-0.018598-0.14290.443447
340.0220780.16960.432958
35-0.167487-1.28650.101648
360.2671252.05180.022316






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.357051-2.74260.00403
2-0.404406-3.10630.001456
3-0.161632-1.24150.109663
4-0.409633-3.14640.001295
5-0.194783-1.49620.069971
6-0.137201-1.05390.148121
70.1358371.04340.150513
80.1031790.79250.215614
90.4073833.12920.001362
10-0.019783-0.1520.43987
11-0.411002-3.1570.001256
120.1199810.92160.180247
130.1255880.96470.169326
140.0529230.40650.34292
15-0.224485-1.72430.044945
160.0123250.09470.462448
170.0763520.58650.279899
18-0.087552-0.67250.251946
190.0650380.49960.309618
20-0.007289-0.0560.47777
21-0.050963-0.39150.348437
220.0340960.26190.397158
23-0.003329-0.02560.489844
24-0.040904-0.31420.377243
25-0.12515-0.96130.170163
26-0.098412-0.75590.226354
270.004730.03630.485569
28-0.039155-0.30080.38233
29-0.014277-0.10970.456523
30-0.017925-0.13770.445479
310.0480440.3690.356712
320.0207340.15930.437004
33-0.082723-0.63540.263809
340.109450.84070.201955
35-0.054506-0.41870.338489
36-0.107033-0.82210.207154

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.357051 & -2.7426 & 0.00403 \tabularnewline
2 & -0.404406 & -3.1063 & 0.001456 \tabularnewline
3 & -0.161632 & -1.2415 & 0.109663 \tabularnewline
4 & -0.409633 & -3.1464 & 0.001295 \tabularnewline
5 & -0.194783 & -1.4962 & 0.069971 \tabularnewline
6 & -0.137201 & -1.0539 & 0.148121 \tabularnewline
7 & 0.135837 & 1.0434 & 0.150513 \tabularnewline
8 & 0.103179 & 0.7925 & 0.215614 \tabularnewline
9 & 0.407383 & 3.1292 & 0.001362 \tabularnewline
10 & -0.019783 & -0.152 & 0.43987 \tabularnewline
11 & -0.411002 & -3.157 & 0.001256 \tabularnewline
12 & 0.119981 & 0.9216 & 0.180247 \tabularnewline
13 & 0.125588 & 0.9647 & 0.169326 \tabularnewline
14 & 0.052923 & 0.4065 & 0.34292 \tabularnewline
15 & -0.224485 & -1.7243 & 0.044945 \tabularnewline
16 & 0.012325 & 0.0947 & 0.462448 \tabularnewline
17 & 0.076352 & 0.5865 & 0.279899 \tabularnewline
18 & -0.087552 & -0.6725 & 0.251946 \tabularnewline
19 & 0.065038 & 0.4996 & 0.309618 \tabularnewline
20 & -0.007289 & -0.056 & 0.47777 \tabularnewline
21 & -0.050963 & -0.3915 & 0.348437 \tabularnewline
22 & 0.034096 & 0.2619 & 0.397158 \tabularnewline
23 & -0.003329 & -0.0256 & 0.489844 \tabularnewline
24 & -0.040904 & -0.3142 & 0.377243 \tabularnewline
25 & -0.12515 & -0.9613 & 0.170163 \tabularnewline
26 & -0.098412 & -0.7559 & 0.226354 \tabularnewline
27 & 0.00473 & 0.0363 & 0.485569 \tabularnewline
28 & -0.039155 & -0.3008 & 0.38233 \tabularnewline
29 & -0.014277 & -0.1097 & 0.456523 \tabularnewline
30 & -0.017925 & -0.1377 & 0.445479 \tabularnewline
31 & 0.048044 & 0.369 & 0.356712 \tabularnewline
32 & 0.020734 & 0.1593 & 0.437004 \tabularnewline
33 & -0.082723 & -0.6354 & 0.263809 \tabularnewline
34 & 0.10945 & 0.8407 & 0.201955 \tabularnewline
35 & -0.054506 & -0.4187 & 0.338489 \tabularnewline
36 & -0.107033 & -0.8221 & 0.207154 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62311&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]-0.357051[/C][C]-2.7426[/C][C]0.00403[/C][/ROW]
[ROW][C]2[/C][C]-0.404406[/C][C]-3.1063[/C][C]0.001456[/C][/ROW]
[ROW][C]3[/C][C]-0.161632[/C][C]-1.2415[/C][C]0.109663[/C][/ROW]
[ROW][C]4[/C][C]-0.409633[/C][C]-3.1464[/C][C]0.001295[/C][/ROW]
[ROW][C]5[/C][C]-0.194783[/C][C]-1.4962[/C][C]0.069971[/C][/ROW]
[ROW][C]6[/C][C]-0.137201[/C][C]-1.0539[/C][C]0.148121[/C][/ROW]
[ROW][C]7[/C][C]0.135837[/C][C]1.0434[/C][C]0.150513[/C][/ROW]
[ROW][C]8[/C][C]0.103179[/C][C]0.7925[/C][C]0.215614[/C][/ROW]
[ROW][C]9[/C][C]0.407383[/C][C]3.1292[/C][C]0.001362[/C][/ROW]
[ROW][C]10[/C][C]-0.019783[/C][C]-0.152[/C][C]0.43987[/C][/ROW]
[ROW][C]11[/C][C]-0.411002[/C][C]-3.157[/C][C]0.001256[/C][/ROW]
[ROW][C]12[/C][C]0.119981[/C][C]0.9216[/C][C]0.180247[/C][/ROW]
[ROW][C]13[/C][C]0.125588[/C][C]0.9647[/C][C]0.169326[/C][/ROW]
[ROW][C]14[/C][C]0.052923[/C][C]0.4065[/C][C]0.34292[/C][/ROW]
[ROW][C]15[/C][C]-0.224485[/C][C]-1.7243[/C][C]0.044945[/C][/ROW]
[ROW][C]16[/C][C]0.012325[/C][C]0.0947[/C][C]0.462448[/C][/ROW]
[ROW][C]17[/C][C]0.076352[/C][C]0.5865[/C][C]0.279899[/C][/ROW]
[ROW][C]18[/C][C]-0.087552[/C][C]-0.6725[/C][C]0.251946[/C][/ROW]
[ROW][C]19[/C][C]0.065038[/C][C]0.4996[/C][C]0.309618[/C][/ROW]
[ROW][C]20[/C][C]-0.007289[/C][C]-0.056[/C][C]0.47777[/C][/ROW]
[ROW][C]21[/C][C]-0.050963[/C][C]-0.3915[/C][C]0.348437[/C][/ROW]
[ROW][C]22[/C][C]0.034096[/C][C]0.2619[/C][C]0.397158[/C][/ROW]
[ROW][C]23[/C][C]-0.003329[/C][C]-0.0256[/C][C]0.489844[/C][/ROW]
[ROW][C]24[/C][C]-0.040904[/C][C]-0.3142[/C][C]0.377243[/C][/ROW]
[ROW][C]25[/C][C]-0.12515[/C][C]-0.9613[/C][C]0.170163[/C][/ROW]
[ROW][C]26[/C][C]-0.098412[/C][C]-0.7559[/C][C]0.226354[/C][/ROW]
[ROW][C]27[/C][C]0.00473[/C][C]0.0363[/C][C]0.485569[/C][/ROW]
[ROW][C]28[/C][C]-0.039155[/C][C]-0.3008[/C][C]0.38233[/C][/ROW]
[ROW][C]29[/C][C]-0.014277[/C][C]-0.1097[/C][C]0.456523[/C][/ROW]
[ROW][C]30[/C][C]-0.017925[/C][C]-0.1377[/C][C]0.445479[/C][/ROW]
[ROW][C]31[/C][C]0.048044[/C][C]0.369[/C][C]0.356712[/C][/ROW]
[ROW][C]32[/C][C]0.020734[/C][C]0.1593[/C][C]0.437004[/C][/ROW]
[ROW][C]33[/C][C]-0.082723[/C][C]-0.6354[/C][C]0.263809[/C][/ROW]
[ROW][C]34[/C][C]0.10945[/C][C]0.8407[/C][C]0.201955[/C][/ROW]
[ROW][C]35[/C][C]-0.054506[/C][C]-0.4187[/C][C]0.338489[/C][/ROW]
[ROW][C]36[/C][C]-0.107033[/C][C]-0.8221[/C][C]0.207154[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62311&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62311&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
1-0.357051-2.74260.00403
2-0.404406-3.10630.001456
3-0.161632-1.24150.109663
4-0.409633-3.14640.001295
5-0.194783-1.49620.069971
6-0.137201-1.05390.148121
70.1358371.04340.150513
80.1031790.79250.215614
90.4073833.12920.001362
10-0.019783-0.1520.43987
11-0.411002-3.1570.001256
120.1199810.92160.180247
130.1255880.96470.169326
140.0529230.40650.34292
15-0.224485-1.72430.044945
160.0123250.09470.462448
170.0763520.58650.279899
18-0.087552-0.67250.251946
190.0650380.49960.309618
20-0.007289-0.0560.47777
21-0.050963-0.39150.348437
220.0340960.26190.397158
23-0.003329-0.02560.489844
24-0.040904-0.31420.377243
25-0.12515-0.96130.170163
26-0.098412-0.75590.226354
270.004730.03630.485569
28-0.039155-0.30080.38233
29-0.014277-0.10970.456523
30-0.017925-0.13770.445479
310.0480440.3690.356712
320.0207340.15930.437004
33-0.082723-0.63540.263809
340.109450.84070.201955
35-0.054506-0.41870.338489
36-0.107033-0.82210.207154


Figures (Output of Computation)

Input Parameters & R Code

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