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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, 25 Nov 2009 12:28:04 -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/25/t1259177346le3qsa8zqg5pkcc.htm/, Retrieved Tue, 07 May 2024 18:14:30 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59582, Retrieved Tue, 07 May 2024 18:14:30 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact149

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] [Methode 1 d,D=0 l...] [2009-11-25 19:21:34] [36becc366f59efff5c3495030cea7527]
-   P             [(Partial) Autocorrelation Function] [Methode 1 d=0, D=...] [2009-11-25 19:28:04] [e1f26cfd746b288ac2a466939c6f316e] [Current]
- R P               [(Partial) Autocorrelation Function] [Methode 1 d=1, D=...] [2009-12-04 11:47:06] [74be16979710d4c4e7c6647856088456]
- R PD              [(Partial) Autocorrelation Function] [Methode 1 d=1, D=...] [2009-12-04 11:49:54] [4f1a20f787b3465111b61213cdeef1a9]
-   P                 [(Partial) Autocorrelation Function] [D=0, d=1 en λ=1] [2009-12-04 11:55:41] [4f1a20f787b3465111b61213cdeef1a9]
-   P               [(Partial) Autocorrelation Function] [Parameter d=1 en D=1] [2009-12-15 20:24:56] [36becc366f59efff5c3495030cea7527]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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

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=59582&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=59582&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59582&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
1-0.019201-0.1330.447364
20.1128350.78170.219102
30.1232490.85390.198702
40.0731750.5070.307247
50.185561.28560.102376
60.1796261.24450.109681
7-0.183671-1.27250.104661
80.0470610.3260.372902
9-0.114542-0.79360.215675
100.0170130.11790.45333
110.030610.21210.416474
12-0.344577-2.38730.01048
13-0.01816-0.12580.450201
14-0.006557-0.04540.481977
15-0.071045-0.49220.312405
16-0.043658-0.30250.3818
17-0.019262-0.13340.447198
18-0.175089-1.21310.115523
190.1246670.86370.196019
200.0534540.37030.35638
210.1496911.03710.152445
22-0.146045-1.01180.158347
230.1660371.15030.127852
240.0530190.36730.357494
250.1074140.74420.230195
260.0090320.06260.475183
270.0338450.23450.407804
28-0.023206-0.16080.436474
290.0582690.40370.344113
30-0.089744-0.62180.26852
31-0.071737-0.4970.310726
32-0.112392-0.77870.219996
33-0.050812-0.3520.363176
340.0450830.31230.378065
35-0.104855-0.72650.235543
36-0.081959-0.56780.286399

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.019201 & -0.133 & 0.447364 \tabularnewline
2 & 0.112835 & 0.7817 & 0.219102 \tabularnewline
3 & 0.123249 & 0.8539 & 0.198702 \tabularnewline
4 & 0.073175 & 0.507 & 0.307247 \tabularnewline
5 & 0.18556 & 1.2856 & 0.102376 \tabularnewline
6 & 0.179626 & 1.2445 & 0.109681 \tabularnewline
7 & -0.183671 & -1.2725 & 0.104661 \tabularnewline
8 & 0.047061 & 0.326 & 0.372902 \tabularnewline
9 & -0.114542 & -0.7936 & 0.215675 \tabularnewline
10 & 0.017013 & 0.1179 & 0.45333 \tabularnewline
11 & 0.03061 & 0.2121 & 0.416474 \tabularnewline
12 & -0.344577 & -2.3873 & 0.01048 \tabularnewline
13 & -0.01816 & -0.1258 & 0.450201 \tabularnewline
14 & -0.006557 & -0.0454 & 0.481977 \tabularnewline
15 & -0.071045 & -0.4922 & 0.312405 \tabularnewline
16 & -0.043658 & -0.3025 & 0.3818 \tabularnewline
17 & -0.019262 & -0.1334 & 0.447198 \tabularnewline
18 & -0.175089 & -1.2131 & 0.115523 \tabularnewline
19 & 0.124667 & 0.8637 & 0.196019 \tabularnewline
20 & 0.053454 & 0.3703 & 0.35638 \tabularnewline
21 & 0.149691 & 1.0371 & 0.152445 \tabularnewline
22 & -0.146045 & -1.0118 & 0.158347 \tabularnewline
23 & 0.166037 & 1.1503 & 0.127852 \tabularnewline
24 & 0.053019 & 0.3673 & 0.357494 \tabularnewline
25 & 0.107414 & 0.7442 & 0.230195 \tabularnewline
26 & 0.009032 & 0.0626 & 0.475183 \tabularnewline
27 & 0.033845 & 0.2345 & 0.407804 \tabularnewline
28 & -0.023206 & -0.1608 & 0.436474 \tabularnewline
29 & 0.058269 & 0.4037 & 0.344113 \tabularnewline
30 & -0.089744 & -0.6218 & 0.26852 \tabularnewline
31 & -0.071737 & -0.497 & 0.310726 \tabularnewline
32 & -0.112392 & -0.7787 & 0.219996 \tabularnewline
33 & -0.050812 & -0.352 & 0.363176 \tabularnewline
34 & 0.045083 & 0.3123 & 0.378065 \tabularnewline
35 & -0.104855 & -0.7265 & 0.235543 \tabularnewline
36 & -0.081959 & -0.5678 & 0.286399 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59582&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]-0.019201[/C][C]-0.133[/C][C]0.447364[/C][/ROW]
[ROW][C]2[/C][C]0.112835[/C][C]0.7817[/C][C]0.219102[/C][/ROW]
[ROW][C]3[/C][C]0.123249[/C][C]0.8539[/C][C]0.198702[/C][/ROW]
[ROW][C]4[/C][C]0.073175[/C][C]0.507[/C][C]0.307247[/C][/ROW]
[ROW][C]5[/C][C]0.18556[/C][C]1.2856[/C][C]0.102376[/C][/ROW]
[ROW][C]6[/C][C]0.179626[/C][C]1.2445[/C][C]0.109681[/C][/ROW]
[ROW][C]7[/C][C]-0.183671[/C][C]-1.2725[/C][C]0.104661[/C][/ROW]
[ROW][C]8[/C][C]0.047061[/C][C]0.326[/C][C]0.372902[/C][/ROW]
[ROW][C]9[/C][C]-0.114542[/C][C]-0.7936[/C][C]0.215675[/C][/ROW]
[ROW][C]10[/C][C]0.017013[/C][C]0.1179[/C][C]0.45333[/C][/ROW]
[ROW][C]11[/C][C]0.03061[/C][C]0.2121[/C][C]0.416474[/C][/ROW]
[ROW][C]12[/C][C]-0.344577[/C][C]-2.3873[/C][C]0.01048[/C][/ROW]
[ROW][C]13[/C][C]-0.01816[/C][C]-0.1258[/C][C]0.450201[/C][/ROW]
[ROW][C]14[/C][C]-0.006557[/C][C]-0.0454[/C][C]0.481977[/C][/ROW]
[ROW][C]15[/C][C]-0.071045[/C][C]-0.4922[/C][C]0.312405[/C][/ROW]
[ROW][C]16[/C][C]-0.043658[/C][C]-0.3025[/C][C]0.3818[/C][/ROW]
[ROW][C]17[/C][C]-0.019262[/C][C]-0.1334[/C][C]0.447198[/C][/ROW]
[ROW][C]18[/C][C]-0.175089[/C][C]-1.2131[/C][C]0.115523[/C][/ROW]
[ROW][C]19[/C][C]0.124667[/C][C]0.8637[/C][C]0.196019[/C][/ROW]
[ROW][C]20[/C][C]0.053454[/C][C]0.3703[/C][C]0.35638[/C][/ROW]
[ROW][C]21[/C][C]0.149691[/C][C]1.0371[/C][C]0.152445[/C][/ROW]
[ROW][C]22[/C][C]-0.146045[/C][C]-1.0118[/C][C]0.158347[/C][/ROW]
[ROW][C]23[/C][C]0.166037[/C][C]1.1503[/C][C]0.127852[/C][/ROW]
[ROW][C]24[/C][C]0.053019[/C][C]0.3673[/C][C]0.357494[/C][/ROW]
[ROW][C]25[/C][C]0.107414[/C][C]0.7442[/C][C]0.230195[/C][/ROW]
[ROW][C]26[/C][C]0.009032[/C][C]0.0626[/C][C]0.475183[/C][/ROW]
[ROW][C]27[/C][C]0.033845[/C][C]0.2345[/C][C]0.407804[/C][/ROW]
[ROW][C]28[/C][C]-0.023206[/C][C]-0.1608[/C][C]0.436474[/C][/ROW]
[ROW][C]29[/C][C]0.058269[/C][C]0.4037[/C][C]0.344113[/C][/ROW]
[ROW][C]30[/C][C]-0.089744[/C][C]-0.6218[/C][C]0.26852[/C][/ROW]
[ROW][C]31[/C][C]-0.071737[/C][C]-0.497[/C][C]0.310726[/C][/ROW]
[ROW][C]32[/C][C]-0.112392[/C][C]-0.7787[/C][C]0.219996[/C][/ROW]
[ROW][C]33[/C][C]-0.050812[/C][C]-0.352[/C][C]0.363176[/C][/ROW]
[ROW][C]34[/C][C]0.045083[/C][C]0.3123[/C][C]0.378065[/C][/ROW]
[ROW][C]35[/C][C]-0.104855[/C][C]-0.7265[/C][C]0.235543[/C][/ROW]
[ROW][C]36[/C][C]-0.081959[/C][C]-0.5678[/C][C]0.286399[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59582&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59582&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
1-0.019201-0.1330.447364
20.1128350.78170.219102
30.1232490.85390.198702
40.0731750.5070.307247
50.185561.28560.102376
60.1796261.24450.109681
7-0.183671-1.27250.104661
80.0470610.3260.372902
9-0.114542-0.79360.215675
100.0170130.11790.45333
110.030610.21210.416474
12-0.344577-2.38730.01048
13-0.01816-0.12580.450201
14-0.006557-0.04540.481977
15-0.071045-0.49220.312405
16-0.043658-0.30250.3818
17-0.019262-0.13340.447198
18-0.175089-1.21310.115523
190.1246670.86370.196019
200.0534540.37030.35638
210.1496911.03710.152445
22-0.146045-1.01180.158347
230.1660371.15030.127852
240.0530190.36730.357494
250.1074140.74420.230195
260.0090320.06260.475183
270.0338450.23450.407804
28-0.023206-0.16080.436474
290.0582690.40370.344113
30-0.089744-0.62180.26852
31-0.071737-0.4970.310726
32-0.112392-0.77870.219996
33-0.050812-0.3520.363176
340.0450830.31230.378065
35-0.104855-0.72650.235543
36-0.081959-0.56780.286399






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.019201-0.1330.447364
20.1125080.77950.219762
30.1290120.89380.187938
40.068620.47540.318326
50.1675661.16090.125705
60.1744661.20870.116343
7-0.234313-1.62340.055531
8-0.061082-0.42320.337024
9-0.158997-1.10160.138073
10-0.012517-0.08670.465628
110.0313380.21710.41452
12-0.309882-2.14690.01844
130.0518880.35950.360402
140.0748390.51850.303245
150.0508570.35230.363059
16-0.060943-0.42220.337372
170.1027120.71160.240075
18-0.058299-0.40390.344038
19-0.002231-0.01550.493865
200.1129610.78260.218848
210.1475571.02230.155881
22-0.181264-1.25580.107628
230.1748621.21150.115821
24-0.034839-0.24140.405149
25-0.026944-0.18670.426351
26-0.04005-0.27750.391304
27-0.027527-0.19070.424777
28-0.010445-0.07240.471305
29-0.026722-0.18510.426951
30-0.144428-1.00060.161012
31-0.130676-0.90540.184901
320.0300750.20840.417913
330.0895570.62050.268942
34-0.038679-0.2680.394932
350.1133180.78510.21813
360.0210560.14590.442313

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.019201 & -0.133 & 0.447364 \tabularnewline
2 & 0.112508 & 0.7795 & 0.219762 \tabularnewline
3 & 0.129012 & 0.8938 & 0.187938 \tabularnewline
4 & 0.06862 & 0.4754 & 0.318326 \tabularnewline
5 & 0.167566 & 1.1609 & 0.125705 \tabularnewline
6 & 0.174466 & 1.2087 & 0.116343 \tabularnewline
7 & -0.234313 & -1.6234 & 0.055531 \tabularnewline
8 & -0.061082 & -0.4232 & 0.337024 \tabularnewline
9 & -0.158997 & -1.1016 & 0.138073 \tabularnewline
10 & -0.012517 & -0.0867 & 0.465628 \tabularnewline
11 & 0.031338 & 0.2171 & 0.41452 \tabularnewline
12 & -0.309882 & -2.1469 & 0.01844 \tabularnewline
13 & 0.051888 & 0.3595 & 0.360402 \tabularnewline
14 & 0.074839 & 0.5185 & 0.303245 \tabularnewline
15 & 0.050857 & 0.3523 & 0.363059 \tabularnewline
16 & -0.060943 & -0.4222 & 0.337372 \tabularnewline
17 & 0.102712 & 0.7116 & 0.240075 \tabularnewline
18 & -0.058299 & -0.4039 & 0.344038 \tabularnewline
19 & -0.002231 & -0.0155 & 0.493865 \tabularnewline
20 & 0.112961 & 0.7826 & 0.218848 \tabularnewline
21 & 0.147557 & 1.0223 & 0.155881 \tabularnewline
22 & -0.181264 & -1.2558 & 0.107628 \tabularnewline
23 & 0.174862 & 1.2115 & 0.115821 \tabularnewline
24 & -0.034839 & -0.2414 & 0.405149 \tabularnewline
25 & -0.026944 & -0.1867 & 0.426351 \tabularnewline
26 & -0.04005 & -0.2775 & 0.391304 \tabularnewline
27 & -0.027527 & -0.1907 & 0.424777 \tabularnewline
28 & -0.010445 & -0.0724 & 0.471305 \tabularnewline
29 & -0.026722 & -0.1851 & 0.426951 \tabularnewline
30 & -0.144428 & -1.0006 & 0.161012 \tabularnewline
31 & -0.130676 & -0.9054 & 0.184901 \tabularnewline
32 & 0.030075 & 0.2084 & 0.417913 \tabularnewline
33 & 0.089557 & 0.6205 & 0.268942 \tabularnewline
34 & -0.038679 & -0.268 & 0.394932 \tabularnewline
35 & 0.113318 & 0.7851 & 0.21813 \tabularnewline
36 & 0.021056 & 0.1459 & 0.442313 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59582&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]-0.019201[/C][C]-0.133[/C][C]0.447364[/C][/ROW]
[ROW][C]2[/C][C]0.112508[/C][C]0.7795[/C][C]0.219762[/C][/ROW]
[ROW][C]3[/C][C]0.129012[/C][C]0.8938[/C][C]0.187938[/C][/ROW]
[ROW][C]4[/C][C]0.06862[/C][C]0.4754[/C][C]0.318326[/C][/ROW]
[ROW][C]5[/C][C]0.167566[/C][C]1.1609[/C][C]0.125705[/C][/ROW]
[ROW][C]6[/C][C]0.174466[/C][C]1.2087[/C][C]0.116343[/C][/ROW]
[ROW][C]7[/C][C]-0.234313[/C][C]-1.6234[/C][C]0.055531[/C][/ROW]
[ROW][C]8[/C][C]-0.061082[/C][C]-0.4232[/C][C]0.337024[/C][/ROW]
[ROW][C]9[/C][C]-0.158997[/C][C]-1.1016[/C][C]0.138073[/C][/ROW]
[ROW][C]10[/C][C]-0.012517[/C][C]-0.0867[/C][C]0.465628[/C][/ROW]
[ROW][C]11[/C][C]0.031338[/C][C]0.2171[/C][C]0.41452[/C][/ROW]
[ROW][C]12[/C][C]-0.309882[/C][C]-2.1469[/C][C]0.01844[/C][/ROW]
[ROW][C]13[/C][C]0.051888[/C][C]0.3595[/C][C]0.360402[/C][/ROW]
[ROW][C]14[/C][C]0.074839[/C][C]0.5185[/C][C]0.303245[/C][/ROW]
[ROW][C]15[/C][C]0.050857[/C][C]0.3523[/C][C]0.363059[/C][/ROW]
[ROW][C]16[/C][C]-0.060943[/C][C]-0.4222[/C][C]0.337372[/C][/ROW]
[ROW][C]17[/C][C]0.102712[/C][C]0.7116[/C][C]0.240075[/C][/ROW]
[ROW][C]18[/C][C]-0.058299[/C][C]-0.4039[/C][C]0.344038[/C][/ROW]
[ROW][C]19[/C][C]-0.002231[/C][C]-0.0155[/C][C]0.493865[/C][/ROW]
[ROW][C]20[/C][C]0.112961[/C][C]0.7826[/C][C]0.218848[/C][/ROW]
[ROW][C]21[/C][C]0.147557[/C][C]1.0223[/C][C]0.155881[/C][/ROW]
[ROW][C]22[/C][C]-0.181264[/C][C]-1.2558[/C][C]0.107628[/C][/ROW]
[ROW][C]23[/C][C]0.174862[/C][C]1.2115[/C][C]0.115821[/C][/ROW]
[ROW][C]24[/C][C]-0.034839[/C][C]-0.2414[/C][C]0.405149[/C][/ROW]
[ROW][C]25[/C][C]-0.026944[/C][C]-0.1867[/C][C]0.426351[/C][/ROW]
[ROW][C]26[/C][C]-0.04005[/C][C]-0.2775[/C][C]0.391304[/C][/ROW]
[ROW][C]27[/C][C]-0.027527[/C][C]-0.1907[/C][C]0.424777[/C][/ROW]
[ROW][C]28[/C][C]-0.010445[/C][C]-0.0724[/C][C]0.471305[/C][/ROW]
[ROW][C]29[/C][C]-0.026722[/C][C]-0.1851[/C][C]0.426951[/C][/ROW]
[ROW][C]30[/C][C]-0.144428[/C][C]-1.0006[/C][C]0.161012[/C][/ROW]
[ROW][C]31[/C][C]-0.130676[/C][C]-0.9054[/C][C]0.184901[/C][/ROW]
[ROW][C]32[/C][C]0.030075[/C][C]0.2084[/C][C]0.417913[/C][/ROW]
[ROW][C]33[/C][C]0.089557[/C][C]0.6205[/C][C]0.268942[/C][/ROW]
[ROW][C]34[/C][C]-0.038679[/C][C]-0.268[/C][C]0.394932[/C][/ROW]
[ROW][C]35[/C][C]0.113318[/C][C]0.7851[/C][C]0.21813[/C][/ROW]
[ROW][C]36[/C][C]0.021056[/C][C]0.1459[/C][C]0.442313[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59582&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59582&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
1-0.019201-0.1330.447364
20.1125080.77950.219762
30.1290120.89380.187938
40.068620.47540.318326
50.1675661.16090.125705
60.1744661.20870.116343
7-0.234313-1.62340.055531
8-0.061082-0.42320.337024
9-0.158997-1.10160.138073
10-0.012517-0.08670.465628
110.0313380.21710.41452
12-0.309882-2.14690.01844
130.0518880.35950.360402
140.0748390.51850.303245
150.0508570.35230.363059
16-0.060943-0.42220.337372
170.1027120.71160.240075
18-0.058299-0.40390.344038
19-0.002231-0.01550.493865
200.1129610.78260.218848
210.1475571.02230.155881
22-0.181264-1.25580.107628
230.1748621.21150.115821
24-0.034839-0.24140.405149
25-0.026944-0.18670.426351
26-0.04005-0.27750.391304
27-0.027527-0.19070.424777
28-0.010445-0.07240.471305
29-0.026722-0.18510.426951
30-0.144428-1.00060.161012
31-0.130676-0.90540.184901
320.0300750.20840.417913
330.0895570.62050.268942
34-0.038679-0.2680.394932
350.1133180.78510.21813
360.0210560.14590.442313


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')