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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 computationSat, 28 Nov 2009 04:08:30 -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/28/t1259406589xwtqzp44jie0te6.htm/, Retrieved Fri, 03 May 2024 09:06:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=61423, Retrieved Fri, 03 May 2024 09:06:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact152

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] [] [2009-11-25 11:59:25] [d811f621c525a990f9b60f1ae1e2e8fd]
- R  D            [(Partial) Autocorrelation Function] [ACF] [2009-11-28 11:08:30] [d1818fb1d9a1b0f34f8553ada228d3d5] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
107.11
107.57
107.81
108.75
109.43
109.62
109.54
109.53
109.84
109.67
109.79
109.56
110.22
110.40
110.69
110.72
110.89
110.58
110.94
110.91
111.22
111.09
111.00
111.06
111.55
112.32
112.64
112.36
112.04
112.37
112.59
112.89
113.22
112.85
113.06
112.99
113.32
113.74
113.91
114.52
114.96
114.91
115.30
115.44
115.52
116.08
115.94
115.56
115.88
116.66
117.41
117.68
117.85
118.21
118.92
119.03
119.17
118.95
118.92
118.90

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=61423&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=61423&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61423&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
10.9398777.28030
20.8786926.80630
30.816296.3230
40.7596175.8840
50.7078245.48280
60.6549485.07322e-06
70.6039924.67858e-06
80.5551514.30023.2e-05
90.5089463.94230.000107
100.4614933.57470.00035
110.4188923.24470.000962
120.3767822.91850.002472
130.3405432.63780.005306
140.2993132.31850.011924
150.2565791.98750.025721
160.217661.6860.048496
170.1792441.38840.085072
180.1371091.0620.146236
190.1003350.77720.220049
200.0605770.46920.320305
210.0253860.19660.422388
22-0.006834-0.05290.478978
23-0.040371-0.31270.377791
24-0.070692-0.54760.293007
25-0.09664-0.74860.228521
26-0.1185-0.91790.181175
27-0.137077-1.06180.146292
28-0.163118-1.26350.105647
29-0.190875-1.47850.072251
30-0.214926-1.66480.050582
31-0.236872-1.83480.035747
32-0.254301-1.96980.026741
33-0.27198-2.10680.019665
34-0.296677-2.2980.01253
35-0.31781-2.46170.008359
36-0.334557-2.59150.005992

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.939877 & 7.2803 & 0 \tabularnewline
2 & 0.878692 & 6.8063 & 0 \tabularnewline
3 & 0.81629 & 6.323 & 0 \tabularnewline
4 & 0.759617 & 5.884 & 0 \tabularnewline
5 & 0.707824 & 5.4828 & 0 \tabularnewline
6 & 0.654948 & 5.0732 & 2e-06 \tabularnewline
7 & 0.603992 & 4.6785 & 8e-06 \tabularnewline
8 & 0.555151 & 4.3002 & 3.2e-05 \tabularnewline
9 & 0.508946 & 3.9423 & 0.000107 \tabularnewline
10 & 0.461493 & 3.5747 & 0.00035 \tabularnewline
11 & 0.418892 & 3.2447 & 0.000962 \tabularnewline
12 & 0.376782 & 2.9185 & 0.002472 \tabularnewline
13 & 0.340543 & 2.6378 & 0.005306 \tabularnewline
14 & 0.299313 & 2.3185 & 0.011924 \tabularnewline
15 & 0.256579 & 1.9875 & 0.025721 \tabularnewline
16 & 0.21766 & 1.686 & 0.048496 \tabularnewline
17 & 0.179244 & 1.3884 & 0.085072 \tabularnewline
18 & 0.137109 & 1.062 & 0.146236 \tabularnewline
19 & 0.100335 & 0.7772 & 0.220049 \tabularnewline
20 & 0.060577 & 0.4692 & 0.320305 \tabularnewline
21 & 0.025386 & 0.1966 & 0.422388 \tabularnewline
22 & -0.006834 & -0.0529 & 0.478978 \tabularnewline
23 & -0.040371 & -0.3127 & 0.377791 \tabularnewline
24 & -0.070692 & -0.5476 & 0.293007 \tabularnewline
25 & -0.09664 & -0.7486 & 0.228521 \tabularnewline
26 & -0.1185 & -0.9179 & 0.181175 \tabularnewline
27 & -0.137077 & -1.0618 & 0.146292 \tabularnewline
28 & -0.163118 & -1.2635 & 0.105647 \tabularnewline
29 & -0.190875 & -1.4785 & 0.072251 \tabularnewline
30 & -0.214926 & -1.6648 & 0.050582 \tabularnewline
31 & -0.236872 & -1.8348 & 0.035747 \tabularnewline
32 & -0.254301 & -1.9698 & 0.026741 \tabularnewline
33 & -0.27198 & -2.1068 & 0.019665 \tabularnewline
34 & -0.296677 & -2.298 & 0.01253 \tabularnewline
35 & -0.31781 & -2.4617 & 0.008359 \tabularnewline
36 & -0.334557 & -2.5915 & 0.005992 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61423&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]0.939877[/C][C]7.2803[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.878692[/C][C]6.8063[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.81629[/C][C]6.323[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.759617[/C][C]5.884[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.707824[/C][C]5.4828[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.654948[/C][C]5.0732[/C][C]2e-06[/C][/ROW]
[ROW][C]7[/C][C]0.603992[/C][C]4.6785[/C][C]8e-06[/C][/ROW]
[ROW][C]8[/C][C]0.555151[/C][C]4.3002[/C][C]3.2e-05[/C][/ROW]
[ROW][C]9[/C][C]0.508946[/C][C]3.9423[/C][C]0.000107[/C][/ROW]
[ROW][C]10[/C][C]0.461493[/C][C]3.5747[/C][C]0.00035[/C][/ROW]
[ROW][C]11[/C][C]0.418892[/C][C]3.2447[/C][C]0.000962[/C][/ROW]
[ROW][C]12[/C][C]0.376782[/C][C]2.9185[/C][C]0.002472[/C][/ROW]
[ROW][C]13[/C][C]0.340543[/C][C]2.6378[/C][C]0.005306[/C][/ROW]
[ROW][C]14[/C][C]0.299313[/C][C]2.3185[/C][C]0.011924[/C][/ROW]
[ROW][C]15[/C][C]0.256579[/C][C]1.9875[/C][C]0.025721[/C][/ROW]
[ROW][C]16[/C][C]0.21766[/C][C]1.686[/C][C]0.048496[/C][/ROW]
[ROW][C]17[/C][C]0.179244[/C][C]1.3884[/C][C]0.085072[/C][/ROW]
[ROW][C]18[/C][C]0.137109[/C][C]1.062[/C][C]0.146236[/C][/ROW]
[ROW][C]19[/C][C]0.100335[/C][C]0.7772[/C][C]0.220049[/C][/ROW]
[ROW][C]20[/C][C]0.060577[/C][C]0.4692[/C][C]0.320305[/C][/ROW]
[ROW][C]21[/C][C]0.025386[/C][C]0.1966[/C][C]0.422388[/C][/ROW]
[ROW][C]22[/C][C]-0.006834[/C][C]-0.0529[/C][C]0.478978[/C][/ROW]
[ROW][C]23[/C][C]-0.040371[/C][C]-0.3127[/C][C]0.377791[/C][/ROW]
[ROW][C]24[/C][C]-0.070692[/C][C]-0.5476[/C][C]0.293007[/C][/ROW]
[ROW][C]25[/C][C]-0.09664[/C][C]-0.7486[/C][C]0.228521[/C][/ROW]
[ROW][C]26[/C][C]-0.1185[/C][C]-0.9179[/C][C]0.181175[/C][/ROW]
[ROW][C]27[/C][C]-0.137077[/C][C]-1.0618[/C][C]0.146292[/C][/ROW]
[ROW][C]28[/C][C]-0.163118[/C][C]-1.2635[/C][C]0.105647[/C][/ROW]
[ROW][C]29[/C][C]-0.190875[/C][C]-1.4785[/C][C]0.072251[/C][/ROW]
[ROW][C]30[/C][C]-0.214926[/C][C]-1.6648[/C][C]0.050582[/C][/ROW]
[ROW][C]31[/C][C]-0.236872[/C][C]-1.8348[/C][C]0.035747[/C][/ROW]
[ROW][C]32[/C][C]-0.254301[/C][C]-1.9698[/C][C]0.026741[/C][/ROW]
[ROW][C]33[/C][C]-0.27198[/C][C]-2.1068[/C][C]0.019665[/C][/ROW]
[ROW][C]34[/C][C]-0.296677[/C][C]-2.298[/C][C]0.01253[/C][/ROW]
[ROW][C]35[/C][C]-0.31781[/C][C]-2.4617[/C][C]0.008359[/C][/ROW]
[ROW][C]36[/C][C]-0.334557[/C][C]-2.5915[/C][C]0.005992[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61423&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61423&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
10.9398777.28030
20.8786926.80630
30.816296.3230
40.7596175.8840
50.7078245.48280
60.6549485.07322e-06
70.6039924.67858e-06
80.5551514.30023.2e-05
90.5089463.94230.000107
100.4614933.57470.00035
110.4188923.24470.000962
120.3767822.91850.002472
130.3405432.63780.005306
140.2993132.31850.011924
150.2565791.98750.025721
160.217661.6860.048496
170.1792441.38840.085072
180.1371091.0620.146236
190.1003350.77720.220049
200.0605770.46920.320305
210.0253860.19660.422388
22-0.006834-0.05290.478978
23-0.040371-0.31270.377791
24-0.070692-0.54760.293007
25-0.09664-0.74860.228521
26-0.1185-0.91790.181175
27-0.137077-1.06180.146292
28-0.163118-1.26350.105647
29-0.190875-1.47850.072251
30-0.214926-1.66480.050582
31-0.236872-1.83480.035747
32-0.254301-1.96980.026741
33-0.27198-2.10680.019665
34-0.296677-2.2980.01253
35-0.31781-2.46170.008359
36-0.334557-2.59150.005992






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9398777.28030
2-0.040111-0.31070.378553
3-0.042936-0.33260.370306
40.0151030.1170.453631
50.0089630.06940.47244
6-0.041713-0.32310.37387
7-0.014185-0.10990.456437
8-0.010087-0.07810.468991
9-0.009128-0.07070.471934
10-0.042149-0.32650.372596
110.011870.09190.463525
12-0.024003-0.18590.426564
130.0185940.1440.44298
14-0.070188-0.54370.294339
15-0.040929-0.3170.376159
160.0043290.03350.48668
17-0.027787-0.21520.415158
18-0.0716-0.55460.290612
190.0167770.130.44852
20-0.058086-0.44990.327192
21-0.000812-0.00630.497501
22-0.011442-0.08860.464835
23-0.040565-0.31420.377223
24-0.011643-0.09020.464219
250.0080540.06240.475232
26-0.002993-0.02320.490789
27-0.000197-0.00150.499394
28-0.091544-0.70910.240506
29-0.042161-0.32660.372563
30-0.005778-0.04480.482227
31-0.011821-0.09160.463674
32-0.005675-0.0440.482541
33-0.030949-0.23970.405679
34-0.091722-0.71050.240081
35-0.00797-0.06170.475488
360.0018060.0140.494442

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.939877 & 7.2803 & 0 \tabularnewline
2 & -0.040111 & -0.3107 & 0.378553 \tabularnewline
3 & -0.042936 & -0.3326 & 0.370306 \tabularnewline
4 & 0.015103 & 0.117 & 0.453631 \tabularnewline
5 & 0.008963 & 0.0694 & 0.47244 \tabularnewline
6 & -0.041713 & -0.3231 & 0.37387 \tabularnewline
7 & -0.014185 & -0.1099 & 0.456437 \tabularnewline
8 & -0.010087 & -0.0781 & 0.468991 \tabularnewline
9 & -0.009128 & -0.0707 & 0.471934 \tabularnewline
10 & -0.042149 & -0.3265 & 0.372596 \tabularnewline
11 & 0.01187 & 0.0919 & 0.463525 \tabularnewline
12 & -0.024003 & -0.1859 & 0.426564 \tabularnewline
13 & 0.018594 & 0.144 & 0.44298 \tabularnewline
14 & -0.070188 & -0.5437 & 0.294339 \tabularnewline
15 & -0.040929 & -0.317 & 0.376159 \tabularnewline
16 & 0.004329 & 0.0335 & 0.48668 \tabularnewline
17 & -0.027787 & -0.2152 & 0.415158 \tabularnewline
18 & -0.0716 & -0.5546 & 0.290612 \tabularnewline
19 & 0.016777 & 0.13 & 0.44852 \tabularnewline
20 & -0.058086 & -0.4499 & 0.327192 \tabularnewline
21 & -0.000812 & -0.0063 & 0.497501 \tabularnewline
22 & -0.011442 & -0.0886 & 0.464835 \tabularnewline
23 & -0.040565 & -0.3142 & 0.377223 \tabularnewline
24 & -0.011643 & -0.0902 & 0.464219 \tabularnewline
25 & 0.008054 & 0.0624 & 0.475232 \tabularnewline
26 & -0.002993 & -0.0232 & 0.490789 \tabularnewline
27 & -0.000197 & -0.0015 & 0.499394 \tabularnewline
28 & -0.091544 & -0.7091 & 0.240506 \tabularnewline
29 & -0.042161 & -0.3266 & 0.372563 \tabularnewline
30 & -0.005778 & -0.0448 & 0.482227 \tabularnewline
31 & -0.011821 & -0.0916 & 0.463674 \tabularnewline
32 & -0.005675 & -0.044 & 0.482541 \tabularnewline
33 & -0.030949 & -0.2397 & 0.405679 \tabularnewline
34 & -0.091722 & -0.7105 & 0.240081 \tabularnewline
35 & -0.00797 & -0.0617 & 0.475488 \tabularnewline
36 & 0.001806 & 0.014 & 0.494442 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61423&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]0.939877[/C][C]7.2803[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.040111[/C][C]-0.3107[/C][C]0.378553[/C][/ROW]
[ROW][C]3[/C][C]-0.042936[/C][C]-0.3326[/C][C]0.370306[/C][/ROW]
[ROW][C]4[/C][C]0.015103[/C][C]0.117[/C][C]0.453631[/C][/ROW]
[ROW][C]5[/C][C]0.008963[/C][C]0.0694[/C][C]0.47244[/C][/ROW]
[ROW][C]6[/C][C]-0.041713[/C][C]-0.3231[/C][C]0.37387[/C][/ROW]
[ROW][C]7[/C][C]-0.014185[/C][C]-0.1099[/C][C]0.456437[/C][/ROW]
[ROW][C]8[/C][C]-0.010087[/C][C]-0.0781[/C][C]0.468991[/C][/ROW]
[ROW][C]9[/C][C]-0.009128[/C][C]-0.0707[/C][C]0.471934[/C][/ROW]
[ROW][C]10[/C][C]-0.042149[/C][C]-0.3265[/C][C]0.372596[/C][/ROW]
[ROW][C]11[/C][C]0.01187[/C][C]0.0919[/C][C]0.463525[/C][/ROW]
[ROW][C]12[/C][C]-0.024003[/C][C]-0.1859[/C][C]0.426564[/C][/ROW]
[ROW][C]13[/C][C]0.018594[/C][C]0.144[/C][C]0.44298[/C][/ROW]
[ROW][C]14[/C][C]-0.070188[/C][C]-0.5437[/C][C]0.294339[/C][/ROW]
[ROW][C]15[/C][C]-0.040929[/C][C]-0.317[/C][C]0.376159[/C][/ROW]
[ROW][C]16[/C][C]0.004329[/C][C]0.0335[/C][C]0.48668[/C][/ROW]
[ROW][C]17[/C][C]-0.027787[/C][C]-0.2152[/C][C]0.415158[/C][/ROW]
[ROW][C]18[/C][C]-0.0716[/C][C]-0.5546[/C][C]0.290612[/C][/ROW]
[ROW][C]19[/C][C]0.016777[/C][C]0.13[/C][C]0.44852[/C][/ROW]
[ROW][C]20[/C][C]-0.058086[/C][C]-0.4499[/C][C]0.327192[/C][/ROW]
[ROW][C]21[/C][C]-0.000812[/C][C]-0.0063[/C][C]0.497501[/C][/ROW]
[ROW][C]22[/C][C]-0.011442[/C][C]-0.0886[/C][C]0.464835[/C][/ROW]
[ROW][C]23[/C][C]-0.040565[/C][C]-0.3142[/C][C]0.377223[/C][/ROW]
[ROW][C]24[/C][C]-0.011643[/C][C]-0.0902[/C][C]0.464219[/C][/ROW]
[ROW][C]25[/C][C]0.008054[/C][C]0.0624[/C][C]0.475232[/C][/ROW]
[ROW][C]26[/C][C]-0.002993[/C][C]-0.0232[/C][C]0.490789[/C][/ROW]
[ROW][C]27[/C][C]-0.000197[/C][C]-0.0015[/C][C]0.499394[/C][/ROW]
[ROW][C]28[/C][C]-0.091544[/C][C]-0.7091[/C][C]0.240506[/C][/ROW]
[ROW][C]29[/C][C]-0.042161[/C][C]-0.3266[/C][C]0.372563[/C][/ROW]
[ROW][C]30[/C][C]-0.005778[/C][C]-0.0448[/C][C]0.482227[/C][/ROW]
[ROW][C]31[/C][C]-0.011821[/C][C]-0.0916[/C][C]0.463674[/C][/ROW]
[ROW][C]32[/C][C]-0.005675[/C][C]-0.044[/C][C]0.482541[/C][/ROW]
[ROW][C]33[/C][C]-0.030949[/C][C]-0.2397[/C][C]0.405679[/C][/ROW]
[ROW][C]34[/C][C]-0.091722[/C][C]-0.7105[/C][C]0.240081[/C][/ROW]
[ROW][C]35[/C][C]-0.00797[/C][C]-0.0617[/C][C]0.475488[/C][/ROW]
[ROW][C]36[/C][C]0.001806[/C][C]0.014[/C][C]0.494442[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61423&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61423&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
10.9398777.28030
2-0.040111-0.31070.378553
3-0.042936-0.33260.370306
40.0151030.1170.453631
50.0089630.06940.47244
6-0.041713-0.32310.37387
7-0.014185-0.10990.456437
8-0.010087-0.07810.468991
9-0.009128-0.07070.471934
10-0.042149-0.32650.372596
110.011870.09190.463525
12-0.024003-0.18590.426564
130.0185940.1440.44298
14-0.070188-0.54370.294339
15-0.040929-0.3170.376159
160.0043290.03350.48668
17-0.027787-0.21520.415158
18-0.0716-0.55460.290612
190.0167770.130.44852
20-0.058086-0.44990.327192
21-0.000812-0.00630.497501
22-0.011442-0.08860.464835
23-0.040565-0.31420.377223
24-0.011643-0.09020.464219
250.0080540.06240.475232
26-0.002993-0.02320.490789
27-0.000197-0.00150.499394
28-0.091544-0.70910.240506
29-0.042161-0.32660.372563
30-0.005778-0.04480.482227
31-0.011821-0.09160.463674
32-0.005675-0.0440.482541
33-0.030949-0.23970.405679
34-0.091722-0.71050.240081
35-0.00797-0.06170.475488
360.0018060.0140.494442


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')