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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 computationFri, 04 Dec 2009 05:09:12 -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/04/t1259928592d3w3bewkcyr06up.htm/, Retrieved Sat, 27 Apr 2024 14:25:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63358, Retrieved Sat, 27 Apr 2024 14:25:20 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact92

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] [] [2009-11-26 19:32:46] [58e1a7a2c10f1de09acf218271f55dfd]
-    D            [(Partial) Autocorrelation Function] [] [2009-12-04 12:09:12] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

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

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=63358&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=63358&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63358&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
10.2543721.97040.026708
20.0050890.03940.484342
30.1456431.12810.131874
40.0593330.45960.323736
50.281782.18270.016493
60.3092252.39520.009874
70.172751.33810.092954
8-0.016668-0.12910.448853
9-0.095778-0.74190.230522
10-0.292433-2.26520.013563
11-0.007281-0.05640.477607
120.4266823.30510.000803
13-0.055901-0.4330.33328
14-0.265259-2.05470.022136
15-0.214391-1.66070.050999
16-0.137985-1.06880.144714
170.0394360.30550.380533
180.0059570.04610.481675
190.0022350.01730.493124
20-0.15174-1.17540.122245
21-0.215518-1.66940.050124
22-0.260848-2.02050.0239
23-0.073796-0.57160.284858
240.2361331.82910.036179
25-0.057526-0.44560.328746
26-0.275762-2.1360.018383
27-0.19485-1.50930.068235
28-0.10784-0.83530.203425
29-0.02139-0.16570.434481
30-0.003039-0.02350.490648
31-0.012363-0.09580.462014
32-0.148007-1.14650.128079
33-0.160941-1.24660.108687
34-0.131768-1.02070.155754
35-0.080011-0.61980.268882
360.1854831.43670.077992

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.254372 & 1.9704 & 0.026708 \tabularnewline
2 & 0.005089 & 0.0394 & 0.484342 \tabularnewline
3 & 0.145643 & 1.1281 & 0.131874 \tabularnewline
4 & 0.059333 & 0.4596 & 0.323736 \tabularnewline
5 & 0.28178 & 2.1827 & 0.016493 \tabularnewline
6 & 0.309225 & 2.3952 & 0.009874 \tabularnewline
7 & 0.17275 & 1.3381 & 0.092954 \tabularnewline
8 & -0.016668 & -0.1291 & 0.448853 \tabularnewline
9 & -0.095778 & -0.7419 & 0.230522 \tabularnewline
10 & -0.292433 & -2.2652 & 0.013563 \tabularnewline
11 & -0.007281 & -0.0564 & 0.477607 \tabularnewline
12 & 0.426682 & 3.3051 & 0.000803 \tabularnewline
13 & -0.055901 & -0.433 & 0.33328 \tabularnewline
14 & -0.265259 & -2.0547 & 0.022136 \tabularnewline
15 & -0.214391 & -1.6607 & 0.050999 \tabularnewline
16 & -0.137985 & -1.0688 & 0.144714 \tabularnewline
17 & 0.039436 & 0.3055 & 0.380533 \tabularnewline
18 & 0.005957 & 0.0461 & 0.481675 \tabularnewline
19 & 0.002235 & 0.0173 & 0.493124 \tabularnewline
20 & -0.15174 & -1.1754 & 0.122245 \tabularnewline
21 & -0.215518 & -1.6694 & 0.050124 \tabularnewline
22 & -0.260848 & -2.0205 & 0.0239 \tabularnewline
23 & -0.073796 & -0.5716 & 0.284858 \tabularnewline
24 & 0.236133 & 1.8291 & 0.036179 \tabularnewline
25 & -0.057526 & -0.4456 & 0.328746 \tabularnewline
26 & -0.275762 & -2.136 & 0.018383 \tabularnewline
27 & -0.19485 & -1.5093 & 0.068235 \tabularnewline
28 & -0.10784 & -0.8353 & 0.203425 \tabularnewline
29 & -0.02139 & -0.1657 & 0.434481 \tabularnewline
30 & -0.003039 & -0.0235 & 0.490648 \tabularnewline
31 & -0.012363 & -0.0958 & 0.462014 \tabularnewline
32 & -0.148007 & -1.1465 & 0.128079 \tabularnewline
33 & -0.160941 & -1.2466 & 0.108687 \tabularnewline
34 & -0.131768 & -1.0207 & 0.155754 \tabularnewline
35 & -0.080011 & -0.6198 & 0.268882 \tabularnewline
36 & 0.185483 & 1.4367 & 0.077992 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63358&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]0.254372[/C][C]1.9704[/C][C]0.026708[/C][/ROW]
[ROW][C]2[/C][C]0.005089[/C][C]0.0394[/C][C]0.484342[/C][/ROW]
[ROW][C]3[/C][C]0.145643[/C][C]1.1281[/C][C]0.131874[/C][/ROW]
[ROW][C]4[/C][C]0.059333[/C][C]0.4596[/C][C]0.323736[/C][/ROW]
[ROW][C]5[/C][C]0.28178[/C][C]2.1827[/C][C]0.016493[/C][/ROW]
[ROW][C]6[/C][C]0.309225[/C][C]2.3952[/C][C]0.009874[/C][/ROW]
[ROW][C]7[/C][C]0.17275[/C][C]1.3381[/C][C]0.092954[/C][/ROW]
[ROW][C]8[/C][C]-0.016668[/C][C]-0.1291[/C][C]0.448853[/C][/ROW]
[ROW][C]9[/C][C]-0.095778[/C][C]-0.7419[/C][C]0.230522[/C][/ROW]
[ROW][C]10[/C][C]-0.292433[/C][C]-2.2652[/C][C]0.013563[/C][/ROW]
[ROW][C]11[/C][C]-0.007281[/C][C]-0.0564[/C][C]0.477607[/C][/ROW]
[ROW][C]12[/C][C]0.426682[/C][C]3.3051[/C][C]0.000803[/C][/ROW]
[ROW][C]13[/C][C]-0.055901[/C][C]-0.433[/C][C]0.33328[/C][/ROW]
[ROW][C]14[/C][C]-0.265259[/C][C]-2.0547[/C][C]0.022136[/C][/ROW]
[ROW][C]15[/C][C]-0.214391[/C][C]-1.6607[/C][C]0.050999[/C][/ROW]
[ROW][C]16[/C][C]-0.137985[/C][C]-1.0688[/C][C]0.144714[/C][/ROW]
[ROW][C]17[/C][C]0.039436[/C][C]0.3055[/C][C]0.380533[/C][/ROW]
[ROW][C]18[/C][C]0.005957[/C][C]0.0461[/C][C]0.481675[/C][/ROW]
[ROW][C]19[/C][C]0.002235[/C][C]0.0173[/C][C]0.493124[/C][/ROW]
[ROW][C]20[/C][C]-0.15174[/C][C]-1.1754[/C][C]0.122245[/C][/ROW]
[ROW][C]21[/C][C]-0.215518[/C][C]-1.6694[/C][C]0.050124[/C][/ROW]
[ROW][C]22[/C][C]-0.260848[/C][C]-2.0205[/C][C]0.0239[/C][/ROW]
[ROW][C]23[/C][C]-0.073796[/C][C]-0.5716[/C][C]0.284858[/C][/ROW]
[ROW][C]24[/C][C]0.236133[/C][C]1.8291[/C][C]0.036179[/C][/ROW]
[ROW][C]25[/C][C]-0.057526[/C][C]-0.4456[/C][C]0.328746[/C][/ROW]
[ROW][C]26[/C][C]-0.275762[/C][C]-2.136[/C][C]0.018383[/C][/ROW]
[ROW][C]27[/C][C]-0.19485[/C][C]-1.5093[/C][C]0.068235[/C][/ROW]
[ROW][C]28[/C][C]-0.10784[/C][C]-0.8353[/C][C]0.203425[/C][/ROW]
[ROW][C]29[/C][C]-0.02139[/C][C]-0.1657[/C][C]0.434481[/C][/ROW]
[ROW][C]30[/C][C]-0.003039[/C][C]-0.0235[/C][C]0.490648[/C][/ROW]
[ROW][C]31[/C][C]-0.012363[/C][C]-0.0958[/C][C]0.462014[/C][/ROW]
[ROW][C]32[/C][C]-0.148007[/C][C]-1.1465[/C][C]0.128079[/C][/ROW]
[ROW][C]33[/C][C]-0.160941[/C][C]-1.2466[/C][C]0.108687[/C][/ROW]
[ROW][C]34[/C][C]-0.131768[/C][C]-1.0207[/C][C]0.155754[/C][/ROW]
[ROW][C]35[/C][C]-0.080011[/C][C]-0.6198[/C][C]0.268882[/C][/ROW]
[ROW][C]36[/C][C]0.185483[/C][C]1.4367[/C][C]0.077992[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63358&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63358&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
10.2543721.97040.026708
20.0050890.03940.484342
30.1456431.12810.131874
40.0593330.45960.323736
50.281782.18270.016493
60.3092252.39520.009874
70.172751.33810.092954
8-0.016668-0.12910.448853
9-0.095778-0.74190.230522
10-0.292433-2.26520.013563
11-0.007281-0.05640.477607
120.4266823.30510.000803
13-0.055901-0.4330.33328
14-0.265259-2.05470.022136
15-0.214391-1.66070.050999
16-0.137985-1.06880.144714
170.0394360.30550.380533
180.0059570.04610.481675
190.0022350.01730.493124
20-0.15174-1.17540.122245
21-0.215518-1.66940.050124
22-0.260848-2.02050.0239
23-0.073796-0.57160.284858
240.2361331.82910.036179
25-0.057526-0.44560.328746
26-0.275762-2.1360.018383
27-0.19485-1.50930.068235
28-0.10784-0.83530.203425
29-0.02139-0.16570.434481
30-0.003039-0.02350.490648
31-0.012363-0.09580.462014
32-0.148007-1.14650.128079
33-0.160941-1.24660.108687
34-0.131768-1.02070.155754
35-0.080011-0.61980.268882
360.1854831.43670.077992






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.2543721.97040.026708
2-0.06374-0.49370.31165
30.1722821.33450.093543
4-0.027591-0.21370.415746
50.3182272.4650.008291
60.153231.18690.11997
70.1284360.99490.1619
8-0.156189-1.20980.115544
9-0.12208-0.94560.174065
10-0.494008-3.82660.000156
110.0157770.12220.45157
120.4115373.18780.001139
13-0.077934-0.60370.274167
14-0.175058-1.3560.090091
15-0.108977-0.84410.200974
160.1911911.4810.071925
17-0.000164-0.00130.499497
18-0.20349-1.57620.060116
19-0.03327-0.25770.398756
20-0.089193-0.69090.246151
210.0226350.17530.430705
220.0544430.42170.337369
23-0.07424-0.57510.283699
24-0.075858-0.58760.279506
25-0.025453-0.19720.422186
260.020630.15980.436789
270.0499460.38690.350106
28-0.167621-1.29840.099561
29-0.145929-1.13040.131412
30-0.001323-0.01020.495929
310.0463330.35890.360466
32-0.054639-0.42320.33682
33-0.082532-0.63930.262534
340.1045840.81010.210541
35-0.098081-0.75970.225194
36-0.012614-0.09770.461244

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.254372 & 1.9704 & 0.026708 \tabularnewline
2 & -0.06374 & -0.4937 & 0.31165 \tabularnewline
3 & 0.172282 & 1.3345 & 0.093543 \tabularnewline
4 & -0.027591 & -0.2137 & 0.415746 \tabularnewline
5 & 0.318227 & 2.465 & 0.008291 \tabularnewline
6 & 0.15323 & 1.1869 & 0.11997 \tabularnewline
7 & 0.128436 & 0.9949 & 0.1619 \tabularnewline
8 & -0.156189 & -1.2098 & 0.115544 \tabularnewline
9 & -0.12208 & -0.9456 & 0.174065 \tabularnewline
10 & -0.494008 & -3.8266 & 0.000156 \tabularnewline
11 & 0.015777 & 0.1222 & 0.45157 \tabularnewline
12 & 0.411537 & 3.1878 & 0.001139 \tabularnewline
13 & -0.077934 & -0.6037 & 0.274167 \tabularnewline
14 & -0.175058 & -1.356 & 0.090091 \tabularnewline
15 & -0.108977 & -0.8441 & 0.200974 \tabularnewline
16 & 0.191191 & 1.481 & 0.071925 \tabularnewline
17 & -0.000164 & -0.0013 & 0.499497 \tabularnewline
18 & -0.20349 & -1.5762 & 0.060116 \tabularnewline
19 & -0.03327 & -0.2577 & 0.398756 \tabularnewline
20 & -0.089193 & -0.6909 & 0.246151 \tabularnewline
21 & 0.022635 & 0.1753 & 0.430705 \tabularnewline
22 & 0.054443 & 0.4217 & 0.337369 \tabularnewline
23 & -0.07424 & -0.5751 & 0.283699 \tabularnewline
24 & -0.075858 & -0.5876 & 0.279506 \tabularnewline
25 & -0.025453 & -0.1972 & 0.422186 \tabularnewline
26 & 0.02063 & 0.1598 & 0.436789 \tabularnewline
27 & 0.049946 & 0.3869 & 0.350106 \tabularnewline
28 & -0.167621 & -1.2984 & 0.099561 \tabularnewline
29 & -0.145929 & -1.1304 & 0.131412 \tabularnewline
30 & -0.001323 & -0.0102 & 0.495929 \tabularnewline
31 & 0.046333 & 0.3589 & 0.360466 \tabularnewline
32 & -0.054639 & -0.4232 & 0.33682 \tabularnewline
33 & -0.082532 & -0.6393 & 0.262534 \tabularnewline
34 & 0.104584 & 0.8101 & 0.210541 \tabularnewline
35 & -0.098081 & -0.7597 & 0.225194 \tabularnewline
36 & -0.012614 & -0.0977 & 0.461244 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63358&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]0.254372[/C][C]1.9704[/C][C]0.026708[/C][/ROW]
[ROW][C]2[/C][C]-0.06374[/C][C]-0.4937[/C][C]0.31165[/C][/ROW]
[ROW][C]3[/C][C]0.172282[/C][C]1.3345[/C][C]0.093543[/C][/ROW]
[ROW][C]4[/C][C]-0.027591[/C][C]-0.2137[/C][C]0.415746[/C][/ROW]
[ROW][C]5[/C][C]0.318227[/C][C]2.465[/C][C]0.008291[/C][/ROW]
[ROW][C]6[/C][C]0.15323[/C][C]1.1869[/C][C]0.11997[/C][/ROW]
[ROW][C]7[/C][C]0.128436[/C][C]0.9949[/C][C]0.1619[/C][/ROW]
[ROW][C]8[/C][C]-0.156189[/C][C]-1.2098[/C][C]0.115544[/C][/ROW]
[ROW][C]9[/C][C]-0.12208[/C][C]-0.9456[/C][C]0.174065[/C][/ROW]
[ROW][C]10[/C][C]-0.494008[/C][C]-3.8266[/C][C]0.000156[/C][/ROW]
[ROW][C]11[/C][C]0.015777[/C][C]0.1222[/C][C]0.45157[/C][/ROW]
[ROW][C]12[/C][C]0.411537[/C][C]3.1878[/C][C]0.001139[/C][/ROW]
[ROW][C]13[/C][C]-0.077934[/C][C]-0.6037[/C][C]0.274167[/C][/ROW]
[ROW][C]14[/C][C]-0.175058[/C][C]-1.356[/C][C]0.090091[/C][/ROW]
[ROW][C]15[/C][C]-0.108977[/C][C]-0.8441[/C][C]0.200974[/C][/ROW]
[ROW][C]16[/C][C]0.191191[/C][C]1.481[/C][C]0.071925[/C][/ROW]
[ROW][C]17[/C][C]-0.000164[/C][C]-0.0013[/C][C]0.499497[/C][/ROW]
[ROW][C]18[/C][C]-0.20349[/C][C]-1.5762[/C][C]0.060116[/C][/ROW]
[ROW][C]19[/C][C]-0.03327[/C][C]-0.2577[/C][C]0.398756[/C][/ROW]
[ROW][C]20[/C][C]-0.089193[/C][C]-0.6909[/C][C]0.246151[/C][/ROW]
[ROW][C]21[/C][C]0.022635[/C][C]0.1753[/C][C]0.430705[/C][/ROW]
[ROW][C]22[/C][C]0.054443[/C][C]0.4217[/C][C]0.337369[/C][/ROW]
[ROW][C]23[/C][C]-0.07424[/C][C]-0.5751[/C][C]0.283699[/C][/ROW]
[ROW][C]24[/C][C]-0.075858[/C][C]-0.5876[/C][C]0.279506[/C][/ROW]
[ROW][C]25[/C][C]-0.025453[/C][C]-0.1972[/C][C]0.422186[/C][/ROW]
[ROW][C]26[/C][C]0.02063[/C][C]0.1598[/C][C]0.436789[/C][/ROW]
[ROW][C]27[/C][C]0.049946[/C][C]0.3869[/C][C]0.350106[/C][/ROW]
[ROW][C]28[/C][C]-0.167621[/C][C]-1.2984[/C][C]0.099561[/C][/ROW]
[ROW][C]29[/C][C]-0.145929[/C][C]-1.1304[/C][C]0.131412[/C][/ROW]
[ROW][C]30[/C][C]-0.001323[/C][C]-0.0102[/C][C]0.495929[/C][/ROW]
[ROW][C]31[/C][C]0.046333[/C][C]0.3589[/C][C]0.360466[/C][/ROW]
[ROW][C]32[/C][C]-0.054639[/C][C]-0.4232[/C][C]0.33682[/C][/ROW]
[ROW][C]33[/C][C]-0.082532[/C][C]-0.6393[/C][C]0.262534[/C][/ROW]
[ROW][C]34[/C][C]0.104584[/C][C]0.8101[/C][C]0.210541[/C][/ROW]
[ROW][C]35[/C][C]-0.098081[/C][C]-0.7597[/C][C]0.225194[/C][/ROW]
[ROW][C]36[/C][C]-0.012614[/C][C]-0.0977[/C][C]0.461244[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63358&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63358&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
10.2543721.97040.026708
2-0.06374-0.49370.31165
30.1722821.33450.093543
4-0.027591-0.21370.415746
50.3182272.4650.008291
60.153231.18690.11997
70.1284360.99490.1619
8-0.156189-1.20980.115544
9-0.12208-0.94560.174065
10-0.494008-3.82660.000156
110.0157770.12220.45157
120.4115373.18780.001139
13-0.077934-0.60370.274167
14-0.175058-1.3560.090091
15-0.108977-0.84410.200974
160.1911911.4810.071925
17-0.000164-0.00130.499497
18-0.20349-1.57620.060116
19-0.03327-0.25770.398756
20-0.089193-0.69090.246151
210.0226350.17530.430705
220.0544430.42170.337369
23-0.07424-0.57510.283699
24-0.075858-0.58760.279506
25-0.025453-0.19720.422186
260.020630.15980.436789
270.0499460.38690.350106
28-0.167621-1.29840.099561
29-0.145929-1.13040.131412
30-0.001323-0.01020.495929
310.0463330.35890.360466
32-0.054639-0.42320.33682
33-0.082532-0.63930.262534
340.1045840.81010.210541
35-0.098081-0.75970.225194
36-0.012614-0.09770.461244


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')