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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 07:06:24 -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/t1259935688txby6zol143b8ex.htm/, Retrieved Sun, 28 Apr 2024 01:19:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63556, Retrieved Sun, 28 Apr 2024 01:19:49 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact113

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] [ACF D=d=o, lambda=1] [2009-11-30 11:39:52] [005293453b571dbccb80b45226e44173]
-   P             [(Partial) Autocorrelation Function] [verbetering works...] [2009-12-04 14:06:24] [3d2053c5f7c50d3c075d87ce0bd87294] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
244.576
241.572
240.541
236.089
236.997
264.579
270.349
269.645
267.037
258.113
262.813
267.413
267.366
264.777
258.863
254.844
254.868
277.267
285.351
286.602
283.042
276.687
277.915
277.128
277.103
275.037
270.150
267.140
264.993
287.259
291.186
292.300
288.186
281.477
282.656
280.190
280.408
276.836
275.216
274.352
271.311
289.802
290.726
292.300
278.506
269.826
265.861
269.034
264.176
255.198
253.353
246.057
235.372
258.556
260.993
254.663
250.643
243.422
247.105
248.541
245.039
237.080
237.085
225.554
226.839
247.934
248.333
246.969
245.098
246.263
255.765
264.319
268.347
273.046
273.963
267.430
271.993
292.710
295.881

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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 & 0 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63556&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]0 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=63556&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63556&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 time0 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.1641171.44940.075611
2-0.163454-1.44360.07643
3-0.199835-1.76490.040748
4-0.210208-1.85650.033579
50.1291331.14050.12879
60.2420372.13760.01784
70.1251221.10510.136267
8-0.186559-1.64760.051724
9-0.224112-1.97930.025655
10-0.200909-1.77440.039951
110.154561.3650.088083
120.7170216.33260
130.0685270.60520.273395
14-0.141971-1.25390.10682
15-0.213657-1.8870.031443
16-0.216803-1.91480.029595
170.067610.59710.276081
180.1208781.06760.144504
190.0635030.56080.288255
20-0.218982-1.9340.02837
21-0.215047-1.89920.030615
22-0.170706-1.50760.067844
230.1017480.89860.185812
240.5336564.71315e-06
25-0.007488-0.06610.473722
26-0.141641-1.25090.107348
27-0.224764-1.98510.025327
28-0.170343-1.50440.068255
290.0447710.39540.34681
300.0992240.87630.191774
310.0331860.29310.385116
32-0.204838-1.80910.037146
33-0.164371-1.45170.0753
34-0.126013-1.11290.134581
350.0798250.7050.241457
360.4119363.63810.000246

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.164117 & 1.4494 & 0.075611 \tabularnewline
2 & -0.163454 & -1.4436 & 0.07643 \tabularnewline
3 & -0.199835 & -1.7649 & 0.040748 \tabularnewline
4 & -0.210208 & -1.8565 & 0.033579 \tabularnewline
5 & 0.129133 & 1.1405 & 0.12879 \tabularnewline
6 & 0.242037 & 2.1376 & 0.01784 \tabularnewline
7 & 0.125122 & 1.1051 & 0.136267 \tabularnewline
8 & -0.186559 & -1.6476 & 0.051724 \tabularnewline
9 & -0.224112 & -1.9793 & 0.025655 \tabularnewline
10 & -0.200909 & -1.7744 & 0.039951 \tabularnewline
11 & 0.15456 & 1.365 & 0.088083 \tabularnewline
12 & 0.717021 & 6.3326 & 0 \tabularnewline
13 & 0.068527 & 0.6052 & 0.273395 \tabularnewline
14 & -0.141971 & -1.2539 & 0.10682 \tabularnewline
15 & -0.213657 & -1.887 & 0.031443 \tabularnewline
16 & -0.216803 & -1.9148 & 0.029595 \tabularnewline
17 & 0.06761 & 0.5971 & 0.276081 \tabularnewline
18 & 0.120878 & 1.0676 & 0.144504 \tabularnewline
19 & 0.063503 & 0.5608 & 0.288255 \tabularnewline
20 & -0.218982 & -1.934 & 0.02837 \tabularnewline
21 & -0.215047 & -1.8992 & 0.030615 \tabularnewline
22 & -0.170706 & -1.5076 & 0.067844 \tabularnewline
23 & 0.101748 & 0.8986 & 0.185812 \tabularnewline
24 & 0.533656 & 4.7131 & 5e-06 \tabularnewline
25 & -0.007488 & -0.0661 & 0.473722 \tabularnewline
26 & -0.141641 & -1.2509 & 0.107348 \tabularnewline
27 & -0.224764 & -1.9851 & 0.025327 \tabularnewline
28 & -0.170343 & -1.5044 & 0.068255 \tabularnewline
29 & 0.044771 & 0.3954 & 0.34681 \tabularnewline
30 & 0.099224 & 0.8763 & 0.191774 \tabularnewline
31 & 0.033186 & 0.2931 & 0.385116 \tabularnewline
32 & -0.204838 & -1.8091 & 0.037146 \tabularnewline
33 & -0.164371 & -1.4517 & 0.0753 \tabularnewline
34 & -0.126013 & -1.1129 & 0.134581 \tabularnewline
35 & 0.079825 & 0.705 & 0.241457 \tabularnewline
36 & 0.411936 & 3.6381 & 0.000246 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63556&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]0.164117[/C][C]1.4494[/C][C]0.075611[/C][/ROW]
[ROW][C]2[/C][C]-0.163454[/C][C]-1.4436[/C][C]0.07643[/C][/ROW]
[ROW][C]3[/C][C]-0.199835[/C][C]-1.7649[/C][C]0.040748[/C][/ROW]
[ROW][C]4[/C][C]-0.210208[/C][C]-1.8565[/C][C]0.033579[/C][/ROW]
[ROW][C]5[/C][C]0.129133[/C][C]1.1405[/C][C]0.12879[/C][/ROW]
[ROW][C]6[/C][C]0.242037[/C][C]2.1376[/C][C]0.01784[/C][/ROW]
[ROW][C]7[/C][C]0.125122[/C][C]1.1051[/C][C]0.136267[/C][/ROW]
[ROW][C]8[/C][C]-0.186559[/C][C]-1.6476[/C][C]0.051724[/C][/ROW]
[ROW][C]9[/C][C]-0.224112[/C][C]-1.9793[/C][C]0.025655[/C][/ROW]
[ROW][C]10[/C][C]-0.200909[/C][C]-1.7744[/C][C]0.039951[/C][/ROW]
[ROW][C]11[/C][C]0.15456[/C][C]1.365[/C][C]0.088083[/C][/ROW]
[ROW][C]12[/C][C]0.717021[/C][C]6.3326[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.068527[/C][C]0.6052[/C][C]0.273395[/C][/ROW]
[ROW][C]14[/C][C]-0.141971[/C][C]-1.2539[/C][C]0.10682[/C][/ROW]
[ROW][C]15[/C][C]-0.213657[/C][C]-1.887[/C][C]0.031443[/C][/ROW]
[ROW][C]16[/C][C]-0.216803[/C][C]-1.9148[/C][C]0.029595[/C][/ROW]
[ROW][C]17[/C][C]0.06761[/C][C]0.5971[/C][C]0.276081[/C][/ROW]
[ROW][C]18[/C][C]0.120878[/C][C]1.0676[/C][C]0.144504[/C][/ROW]
[ROW][C]19[/C][C]0.063503[/C][C]0.5608[/C][C]0.288255[/C][/ROW]
[ROW][C]20[/C][C]-0.218982[/C][C]-1.934[/C][C]0.02837[/C][/ROW]
[ROW][C]21[/C][C]-0.215047[/C][C]-1.8992[/C][C]0.030615[/C][/ROW]
[ROW][C]22[/C][C]-0.170706[/C][C]-1.5076[/C][C]0.067844[/C][/ROW]
[ROW][C]23[/C][C]0.101748[/C][C]0.8986[/C][C]0.185812[/C][/ROW]
[ROW][C]24[/C][C]0.533656[/C][C]4.7131[/C][C]5e-06[/C][/ROW]
[ROW][C]25[/C][C]-0.007488[/C][C]-0.0661[/C][C]0.473722[/C][/ROW]
[ROW][C]26[/C][C]-0.141641[/C][C]-1.2509[/C][C]0.107348[/C][/ROW]
[ROW][C]27[/C][C]-0.224764[/C][C]-1.9851[/C][C]0.025327[/C][/ROW]
[ROW][C]28[/C][C]-0.170343[/C][C]-1.5044[/C][C]0.068255[/C][/ROW]
[ROW][C]29[/C][C]0.044771[/C][C]0.3954[/C][C]0.34681[/C][/ROW]
[ROW][C]30[/C][C]0.099224[/C][C]0.8763[/C][C]0.191774[/C][/ROW]
[ROW][C]31[/C][C]0.033186[/C][C]0.2931[/C][C]0.385116[/C][/ROW]
[ROW][C]32[/C][C]-0.204838[/C][C]-1.8091[/C][C]0.037146[/C][/ROW]
[ROW][C]33[/C][C]-0.164371[/C][C]-1.4517[/C][C]0.0753[/C][/ROW]
[ROW][C]34[/C][C]-0.126013[/C][C]-1.1129[/C][C]0.134581[/C][/ROW]
[ROW][C]35[/C][C]0.079825[/C][C]0.705[/C][C]0.241457[/C][/ROW]
[ROW][C]36[/C][C]0.411936[/C][C]3.6381[/C][C]0.000246[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63556&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63556&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
10.1641171.44940.075611
2-0.163454-1.44360.07643
3-0.199835-1.76490.040748
4-0.210208-1.85650.033579
50.1291331.14050.12879
60.2420372.13760.01784
70.1251221.10510.136267
8-0.186559-1.64760.051724
9-0.224112-1.97930.025655
10-0.200909-1.77440.039951
110.154561.3650.088083
120.7170216.33260
130.0685270.60520.273395
14-0.141971-1.25390.10682
15-0.213657-1.8870.031443
16-0.216803-1.91480.029595
170.067610.59710.276081
180.1208781.06760.144504
190.0635030.56080.288255
20-0.218982-1.9340.02837
21-0.215047-1.89920.030615
22-0.170706-1.50760.067844
230.1017480.89860.185812
240.5336564.71315e-06
25-0.007488-0.06610.473722
26-0.141641-1.25090.107348
27-0.224764-1.98510.025327
28-0.170343-1.50440.068255
290.0447710.39540.34681
300.0992240.87630.191774
310.0331860.29310.385116
32-0.204838-1.80910.037146
33-0.164371-1.45170.0753
34-0.126013-1.11290.134581
350.0798250.7050.241457
360.4119363.63810.000246






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1641171.44940.075611
2-0.195659-1.7280.043972
3-0.144953-1.28020.102136
4-0.196697-1.73720.043151
50.1503611.32790.094034
60.1220831.07820.142132
70.0659890.58280.280855
8-0.191093-1.68770.047733
9-0.061834-0.54610.293275
10-0.171675-1.51620.066756
110.1609941.42190.079527
120.6335645.59550
13-0.192652-1.70150.04642
140.0055290.04880.48059
15-0.056899-0.50250.308359
16-0.004613-0.04070.483804
17-0.145326-1.28350.101562
18-0.202422-1.78770.038851
19-0.06418-0.56680.28623
20-0.126685-1.11890.133319
210.0397110.35070.363374
220.0122690.10840.456996
23-0.08946-0.79010.215936
240.0881720.77870.219252
25-0.075108-0.66330.254535
26-0.026591-0.23480.40747
27-0.119509-1.05550.147233
280.0375850.33190.370411
29-0.055941-0.49410.311327
300.0449210.39670.346324
31-0.05204-0.45960.32354
320.0244210.21570.4149
330.0002990.00260.498951
34-0.001287-0.01140.49548
35-0.098016-0.86570.194667
36-0.050921-0.44970.327078

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.164117 & 1.4494 & 0.075611 \tabularnewline
2 & -0.195659 & -1.728 & 0.043972 \tabularnewline
3 & -0.144953 & -1.2802 & 0.102136 \tabularnewline
4 & -0.196697 & -1.7372 & 0.043151 \tabularnewline
5 & 0.150361 & 1.3279 & 0.094034 \tabularnewline
6 & 0.122083 & 1.0782 & 0.142132 \tabularnewline
7 & 0.065989 & 0.5828 & 0.280855 \tabularnewline
8 & -0.191093 & -1.6877 & 0.047733 \tabularnewline
9 & -0.061834 & -0.5461 & 0.293275 \tabularnewline
10 & -0.171675 & -1.5162 & 0.066756 \tabularnewline
11 & 0.160994 & 1.4219 & 0.079527 \tabularnewline
12 & 0.633564 & 5.5955 & 0 \tabularnewline
13 & -0.192652 & -1.7015 & 0.04642 \tabularnewline
14 & 0.005529 & 0.0488 & 0.48059 \tabularnewline
15 & -0.056899 & -0.5025 & 0.308359 \tabularnewline
16 & -0.004613 & -0.0407 & 0.483804 \tabularnewline
17 & -0.145326 & -1.2835 & 0.101562 \tabularnewline
18 & -0.202422 & -1.7877 & 0.038851 \tabularnewline
19 & -0.06418 & -0.5668 & 0.28623 \tabularnewline
20 & -0.126685 & -1.1189 & 0.133319 \tabularnewline
21 & 0.039711 & 0.3507 & 0.363374 \tabularnewline
22 & 0.012269 & 0.1084 & 0.456996 \tabularnewline
23 & -0.08946 & -0.7901 & 0.215936 \tabularnewline
24 & 0.088172 & 0.7787 & 0.219252 \tabularnewline
25 & -0.075108 & -0.6633 & 0.254535 \tabularnewline
26 & -0.026591 & -0.2348 & 0.40747 \tabularnewline
27 & -0.119509 & -1.0555 & 0.147233 \tabularnewline
28 & 0.037585 & 0.3319 & 0.370411 \tabularnewline
29 & -0.055941 & -0.4941 & 0.311327 \tabularnewline
30 & 0.044921 & 0.3967 & 0.346324 \tabularnewline
31 & -0.05204 & -0.4596 & 0.32354 \tabularnewline
32 & 0.024421 & 0.2157 & 0.4149 \tabularnewline
33 & 0.000299 & 0.0026 & 0.498951 \tabularnewline
34 & -0.001287 & -0.0114 & 0.49548 \tabularnewline
35 & -0.098016 & -0.8657 & 0.194667 \tabularnewline
36 & -0.050921 & -0.4497 & 0.327078 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63556&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]0.164117[/C][C]1.4494[/C][C]0.075611[/C][/ROW]
[ROW][C]2[/C][C]-0.195659[/C][C]-1.728[/C][C]0.043972[/C][/ROW]
[ROW][C]3[/C][C]-0.144953[/C][C]-1.2802[/C][C]0.102136[/C][/ROW]
[ROW][C]4[/C][C]-0.196697[/C][C]-1.7372[/C][C]0.043151[/C][/ROW]
[ROW][C]5[/C][C]0.150361[/C][C]1.3279[/C][C]0.094034[/C][/ROW]
[ROW][C]6[/C][C]0.122083[/C][C]1.0782[/C][C]0.142132[/C][/ROW]
[ROW][C]7[/C][C]0.065989[/C][C]0.5828[/C][C]0.280855[/C][/ROW]
[ROW][C]8[/C][C]-0.191093[/C][C]-1.6877[/C][C]0.047733[/C][/ROW]
[ROW][C]9[/C][C]-0.061834[/C][C]-0.5461[/C][C]0.293275[/C][/ROW]
[ROW][C]10[/C][C]-0.171675[/C][C]-1.5162[/C][C]0.066756[/C][/ROW]
[ROW][C]11[/C][C]0.160994[/C][C]1.4219[/C][C]0.079527[/C][/ROW]
[ROW][C]12[/C][C]0.633564[/C][C]5.5955[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.192652[/C][C]-1.7015[/C][C]0.04642[/C][/ROW]
[ROW][C]14[/C][C]0.005529[/C][C]0.0488[/C][C]0.48059[/C][/ROW]
[ROW][C]15[/C][C]-0.056899[/C][C]-0.5025[/C][C]0.308359[/C][/ROW]
[ROW][C]16[/C][C]-0.004613[/C][C]-0.0407[/C][C]0.483804[/C][/ROW]
[ROW][C]17[/C][C]-0.145326[/C][C]-1.2835[/C][C]0.101562[/C][/ROW]
[ROW][C]18[/C][C]-0.202422[/C][C]-1.7877[/C][C]0.038851[/C][/ROW]
[ROW][C]19[/C][C]-0.06418[/C][C]-0.5668[/C][C]0.28623[/C][/ROW]
[ROW][C]20[/C][C]-0.126685[/C][C]-1.1189[/C][C]0.133319[/C][/ROW]
[ROW][C]21[/C][C]0.039711[/C][C]0.3507[/C][C]0.363374[/C][/ROW]
[ROW][C]22[/C][C]0.012269[/C][C]0.1084[/C][C]0.456996[/C][/ROW]
[ROW][C]23[/C][C]-0.08946[/C][C]-0.7901[/C][C]0.215936[/C][/ROW]
[ROW][C]24[/C][C]0.088172[/C][C]0.7787[/C][C]0.219252[/C][/ROW]
[ROW][C]25[/C][C]-0.075108[/C][C]-0.6633[/C][C]0.254535[/C][/ROW]
[ROW][C]26[/C][C]-0.026591[/C][C]-0.2348[/C][C]0.40747[/C][/ROW]
[ROW][C]27[/C][C]-0.119509[/C][C]-1.0555[/C][C]0.147233[/C][/ROW]
[ROW][C]28[/C][C]0.037585[/C][C]0.3319[/C][C]0.370411[/C][/ROW]
[ROW][C]29[/C][C]-0.055941[/C][C]-0.4941[/C][C]0.311327[/C][/ROW]
[ROW][C]30[/C][C]0.044921[/C][C]0.3967[/C][C]0.346324[/C][/ROW]
[ROW][C]31[/C][C]-0.05204[/C][C]-0.4596[/C][C]0.32354[/C][/ROW]
[ROW][C]32[/C][C]0.024421[/C][C]0.2157[/C][C]0.4149[/C][/ROW]
[ROW][C]33[/C][C]0.000299[/C][C]0.0026[/C][C]0.498951[/C][/ROW]
[ROW][C]34[/C][C]-0.001287[/C][C]-0.0114[/C][C]0.49548[/C][/ROW]
[ROW][C]35[/C][C]-0.098016[/C][C]-0.8657[/C][C]0.194667[/C][/ROW]
[ROW][C]36[/C][C]-0.050921[/C][C]-0.4497[/C][C]0.327078[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63556&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63556&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
10.1641171.44940.075611
2-0.195659-1.7280.043972
3-0.144953-1.28020.102136
4-0.196697-1.73720.043151
50.1503611.32790.094034
60.1220831.07820.142132
70.0659890.58280.280855
8-0.191093-1.68770.047733
9-0.061834-0.54610.293275
10-0.171675-1.51620.066756
110.1609941.42190.079527
120.6335645.59550
13-0.192652-1.70150.04642
140.0055290.04880.48059
15-0.056899-0.50250.308359
16-0.004613-0.04070.483804
17-0.145326-1.28350.101562
18-0.202422-1.78770.038851
19-0.06418-0.56680.28623
20-0.126685-1.11890.133319
210.0397110.35070.363374
220.0122690.10840.456996
23-0.08946-0.79010.215936
240.0881720.77870.219252
25-0.075108-0.66330.254535
26-0.026591-0.23480.40747
27-0.119509-1.05550.147233
280.0375850.33190.370411
29-0.055941-0.49410.311327
300.0449210.39670.346324
31-0.05204-0.45960.32354
320.0244210.21570.4149
330.0002990.00260.498951
34-0.001287-0.01140.49548
35-0.098016-0.86570.194667
36-0.050921-0.44970.327078


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')