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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, 12 Dec 2009 09:53:58 -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/12/t12606368884rxvheey5bwoxuq.htm/, Retrieved Mon, 29 Apr 2024 15:25:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=67062, Retrieved Mon, 29 Apr 2024 15:25:10 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact126

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] [WS8 D=0 en d=0] [2009-11-25 16:06:53] [445b292c553470d9fed8bc2796fd3a00]
-    D          [(Partial) Autocorrelation Function] [ws 8 d=0 D=0] [2009-11-25 20:46:27] [134dc66689e3d457a82860db6471d419]
-    D              [(Partial) Autocorrelation Function] [Paper PAF ICP] [2009-12-12 16:53:58] [4f297b039e1043ebee7ff7a83b1eaaaa] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
100.00
102.04
102.51
102.71
103.00
103.39
102.32
103.88
104.65
104.46
104.65
104.36
102.71
104.55
104.76
105.72
106.20
106.50
105.14
106.50
106.69
106.50
106.50
106.39
105.43
107.18
107.37
107.46
107.66
107.37
106.30
107.85
107.95
107.85
107.66
107.76
106.69
108.92
109.22
109.02
108.62
109.02
107.76
109.60
109.80
109.41
109.60
109.60
108.15
110.18
110.27
110.87
111.25
111.15
109.99
111.83
111.73
112.31
112.12
111.73
110.27
112.71
113.38
113.57
113.77
114.15
112.99
115.03
115.03
114.84
114.75
114.84
113.32
115.92
115.84
116.49
116.90
116.99
115.74
117.73
117.17
116.83
117.08
117.23
115.25
117.98
117.97
118.56
118.42
118.51
117.25
119.08
118.85
119.41
120.43
120.87
119.31
122.24
123.14
123.39
124.46
125.33
124.17
125.48
125.35
125.15
124.31
124.14
121.81
124.62
123.93
124.29
124.16
124.02
122.00
124.58
124.06

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=67062&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=67062&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67062&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
10.96110510.39590
20.93536310.11750
30.914179.88830
40.888859.61440
50.8628329.3330
60.8471269.16310
70.8089348.750
80.7824078.4630
90.7621918.24440
100.7367627.96930
110.7109297.68990
120.6909527.47380
130.6471366.99980
140.6163476.66680
150.5875776.35560
160.5578266.03380
170.5305955.73930
180.514765.5680
190.4778895.16920
200.4545974.91721e-06
210.4369424.72623e-06
220.4154554.49388e-06
230.3936484.2582.1e-05
240.3814734.12633.5e-05
250.3500873.78680.000121
260.3299893.56940.00026
270.3128073.38350.000487
280.2932173.17160.000968
290.2738142.96170.001853
300.2609572.82270.002799
310.2302672.49070.007076
320.2109672.2820.01215
330.1965142.12560.017819
340.1775081.920.028644
350.1578331.70720.045216
360.1455681.57460.059029

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.961105 & 10.3959 & 0 \tabularnewline
2 & 0.935363 & 10.1175 & 0 \tabularnewline
3 & 0.91417 & 9.8883 & 0 \tabularnewline
4 & 0.88885 & 9.6144 & 0 \tabularnewline
5 & 0.862832 & 9.333 & 0 \tabularnewline
6 & 0.847126 & 9.1631 & 0 \tabularnewline
7 & 0.808934 & 8.75 & 0 \tabularnewline
8 & 0.782407 & 8.463 & 0 \tabularnewline
9 & 0.762191 & 8.2444 & 0 \tabularnewline
10 & 0.736762 & 7.9693 & 0 \tabularnewline
11 & 0.710929 & 7.6899 & 0 \tabularnewline
12 & 0.690952 & 7.4738 & 0 \tabularnewline
13 & 0.647136 & 6.9998 & 0 \tabularnewline
14 & 0.616347 & 6.6668 & 0 \tabularnewline
15 & 0.587577 & 6.3556 & 0 \tabularnewline
16 & 0.557826 & 6.0338 & 0 \tabularnewline
17 & 0.530595 & 5.7393 & 0 \tabularnewline
18 & 0.51476 & 5.568 & 0 \tabularnewline
19 & 0.477889 & 5.1692 & 0 \tabularnewline
20 & 0.454597 & 4.9172 & 1e-06 \tabularnewline
21 & 0.436942 & 4.7262 & 3e-06 \tabularnewline
22 & 0.415455 & 4.4938 & 8e-06 \tabularnewline
23 & 0.393648 & 4.258 & 2.1e-05 \tabularnewline
24 & 0.381473 & 4.1263 & 3.5e-05 \tabularnewline
25 & 0.350087 & 3.7868 & 0.000121 \tabularnewline
26 & 0.329989 & 3.5694 & 0.00026 \tabularnewline
27 & 0.312807 & 3.3835 & 0.000487 \tabularnewline
28 & 0.293217 & 3.1716 & 0.000968 \tabularnewline
29 & 0.273814 & 2.9617 & 0.001853 \tabularnewline
30 & 0.260957 & 2.8227 & 0.002799 \tabularnewline
31 & 0.230267 & 2.4907 & 0.007076 \tabularnewline
32 & 0.210967 & 2.282 & 0.01215 \tabularnewline
33 & 0.196514 & 2.1256 & 0.017819 \tabularnewline
34 & 0.177508 & 1.92 & 0.028644 \tabularnewline
35 & 0.157833 & 1.7072 & 0.045216 \tabularnewline
36 & 0.145568 & 1.5746 & 0.059029 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67062&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]0.961105[/C][C]10.3959[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.935363[/C][C]10.1175[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.91417[/C][C]9.8883[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.88885[/C][C]9.6144[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.862832[/C][C]9.333[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.847126[/C][C]9.1631[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.808934[/C][C]8.75[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]0.782407[/C][C]8.463[/C][C]0[/C][/ROW]
[ROW][C]9[/C][C]0.762191[/C][C]8.2444[/C][C]0[/C][/ROW]
[ROW][C]10[/C][C]0.736762[/C][C]7.9693[/C][C]0[/C][/ROW]
[ROW][C]11[/C][C]0.710929[/C][C]7.6899[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.690952[/C][C]7.4738[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.647136[/C][C]6.9998[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]0.616347[/C][C]6.6668[/C][C]0[/C][/ROW]
[ROW][C]15[/C][C]0.587577[/C][C]6.3556[/C][C]0[/C][/ROW]
[ROW][C]16[/C][C]0.557826[/C][C]6.0338[/C][C]0[/C][/ROW]
[ROW][C]17[/C][C]0.530595[/C][C]5.7393[/C][C]0[/C][/ROW]
[ROW][C]18[/C][C]0.51476[/C][C]5.568[/C][C]0[/C][/ROW]
[ROW][C]19[/C][C]0.477889[/C][C]5.1692[/C][C]0[/C][/ROW]
[ROW][C]20[/C][C]0.454597[/C][C]4.9172[/C][C]1e-06[/C][/ROW]
[ROW][C]21[/C][C]0.436942[/C][C]4.7262[/C][C]3e-06[/C][/ROW]
[ROW][C]22[/C][C]0.415455[/C][C]4.4938[/C][C]8e-06[/C][/ROW]
[ROW][C]23[/C][C]0.393648[/C][C]4.258[/C][C]2.1e-05[/C][/ROW]
[ROW][C]24[/C][C]0.381473[/C][C]4.1263[/C][C]3.5e-05[/C][/ROW]
[ROW][C]25[/C][C]0.350087[/C][C]3.7868[/C][C]0.000121[/C][/ROW]
[ROW][C]26[/C][C]0.329989[/C][C]3.5694[/C][C]0.00026[/C][/ROW]
[ROW][C]27[/C][C]0.312807[/C][C]3.3835[/C][C]0.000487[/C][/ROW]
[ROW][C]28[/C][C]0.293217[/C][C]3.1716[/C][C]0.000968[/C][/ROW]
[ROW][C]29[/C][C]0.273814[/C][C]2.9617[/C][C]0.001853[/C][/ROW]
[ROW][C]30[/C][C]0.260957[/C][C]2.8227[/C][C]0.002799[/C][/ROW]
[ROW][C]31[/C][C]0.230267[/C][C]2.4907[/C][C]0.007076[/C][/ROW]
[ROW][C]32[/C][C]0.210967[/C][C]2.282[/C][C]0.01215[/C][/ROW]
[ROW][C]33[/C][C]0.196514[/C][C]2.1256[/C][C]0.017819[/C][/ROW]
[ROW][C]34[/C][C]0.177508[/C][C]1.92[/C][C]0.028644[/C][/ROW]
[ROW][C]35[/C][C]0.157833[/C][C]1.7072[/C][C]0.045216[/C][/ROW]
[ROW][C]36[/C][C]0.145568[/C][C]1.5746[/C][C]0.059029[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67062&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67062&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
10.96110510.39590
20.93536310.11750
30.914179.88830
40.888859.61440
50.8628329.3330
60.8471269.16310
70.8089348.750
80.7824078.4630
90.7621918.24440
100.7367627.96930
110.7109297.68990
120.6909527.47380
130.6471366.99980
140.6163476.66680
150.5875776.35560
160.5578266.03380
170.5305955.73930
180.514765.5680
190.4778895.16920
200.4545974.91721e-06
210.4369424.72623e-06
220.4154554.49388e-06
230.3936484.2582.1e-05
240.3814734.12633.5e-05
250.3500873.78680.000121
260.3299893.56940.00026
270.3128073.38350.000487
280.2932173.17160.000968
290.2738142.96170.001853
300.2609572.82270.002799
310.2302672.49070.007076
320.2109672.2820.01215
330.1965142.12560.017819
340.1775081.920.028644
350.1578331.70720.045216
360.1455681.57460.059029






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.96110510.39590
20.1526051.65070.050744
30.0766240.82880.204449
4-0.040595-0.43910.330699
5-0.032345-0.34990.363534
60.1142641.2360.109476
7-0.270275-2.92350.002078
80.0735860.7960.213835
90.0647720.70060.242468
10-0.030958-0.33490.369163
11-0.006956-0.07520.470074
12-0.008028-0.08680.465473
13-0.249956-2.70370.00394
140.0525760.56870.285328
15-0.032788-0.35470.361741
160.0372980.40340.343679
170.0466170.50420.307521
180.0874320.94570.17312
19-0.139023-1.50380.067669
200.0404580.43760.331234
210.0391590.42360.336328
22-0.00117-0.01270.494964
23-0.00099-0.01070.495736
240.0459390.49690.310093
25-0.094651-1.02380.15402
260.0112620.12180.451627
27-0.021167-0.2290.40965
28-0.000945-0.01020.49593
290.0017880.01930.492303
30-0.028195-0.3050.380462
31-0.083505-0.90320.184126
32-0.002854-0.03090.487713
330.0275660.29820.383052
34-0.016768-0.18140.428192
35-0.012047-0.13030.448272
360.0010770.01170.495362

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.961105 & 10.3959 & 0 \tabularnewline
2 & 0.152605 & 1.6507 & 0.050744 \tabularnewline
3 & 0.076624 & 0.8288 & 0.204449 \tabularnewline
4 & -0.040595 & -0.4391 & 0.330699 \tabularnewline
5 & -0.032345 & -0.3499 & 0.363534 \tabularnewline
6 & 0.114264 & 1.236 & 0.109476 \tabularnewline
7 & -0.270275 & -2.9235 & 0.002078 \tabularnewline
8 & 0.073586 & 0.796 & 0.213835 \tabularnewline
9 & 0.064772 & 0.7006 & 0.242468 \tabularnewline
10 & -0.030958 & -0.3349 & 0.369163 \tabularnewline
11 & -0.006956 & -0.0752 & 0.470074 \tabularnewline
12 & -0.008028 & -0.0868 & 0.465473 \tabularnewline
13 & -0.249956 & -2.7037 & 0.00394 \tabularnewline
14 & 0.052576 & 0.5687 & 0.285328 \tabularnewline
15 & -0.032788 & -0.3547 & 0.361741 \tabularnewline
16 & 0.037298 & 0.4034 & 0.343679 \tabularnewline
17 & 0.046617 & 0.5042 & 0.307521 \tabularnewline
18 & 0.087432 & 0.9457 & 0.17312 \tabularnewline
19 & -0.139023 & -1.5038 & 0.067669 \tabularnewline
20 & 0.040458 & 0.4376 & 0.331234 \tabularnewline
21 & 0.039159 & 0.4236 & 0.336328 \tabularnewline
22 & -0.00117 & -0.0127 & 0.494964 \tabularnewline
23 & -0.00099 & -0.0107 & 0.495736 \tabularnewline
24 & 0.045939 & 0.4969 & 0.310093 \tabularnewline
25 & -0.094651 & -1.0238 & 0.15402 \tabularnewline
26 & 0.011262 & 0.1218 & 0.451627 \tabularnewline
27 & -0.021167 & -0.229 & 0.40965 \tabularnewline
28 & -0.000945 & -0.0102 & 0.49593 \tabularnewline
29 & 0.001788 & 0.0193 & 0.492303 \tabularnewline
30 & -0.028195 & -0.305 & 0.380462 \tabularnewline
31 & -0.083505 & -0.9032 & 0.184126 \tabularnewline
32 & -0.002854 & -0.0309 & 0.487713 \tabularnewline
33 & 0.027566 & 0.2982 & 0.383052 \tabularnewline
34 & -0.016768 & -0.1814 & 0.428192 \tabularnewline
35 & -0.012047 & -0.1303 & 0.448272 \tabularnewline
36 & 0.001077 & 0.0117 & 0.495362 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67062&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]0.961105[/C][C]10.3959[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.152605[/C][C]1.6507[/C][C]0.050744[/C][/ROW]
[ROW][C]3[/C][C]0.076624[/C][C]0.8288[/C][C]0.204449[/C][/ROW]
[ROW][C]4[/C][C]-0.040595[/C][C]-0.4391[/C][C]0.330699[/C][/ROW]
[ROW][C]5[/C][C]-0.032345[/C][C]-0.3499[/C][C]0.363534[/C][/ROW]
[ROW][C]6[/C][C]0.114264[/C][C]1.236[/C][C]0.109476[/C][/ROW]
[ROW][C]7[/C][C]-0.270275[/C][C]-2.9235[/C][C]0.002078[/C][/ROW]
[ROW][C]8[/C][C]0.073586[/C][C]0.796[/C][C]0.213835[/C][/ROW]
[ROW][C]9[/C][C]0.064772[/C][C]0.7006[/C][C]0.242468[/C][/ROW]
[ROW][C]10[/C][C]-0.030958[/C][C]-0.3349[/C][C]0.369163[/C][/ROW]
[ROW][C]11[/C][C]-0.006956[/C][C]-0.0752[/C][C]0.470074[/C][/ROW]
[ROW][C]12[/C][C]-0.008028[/C][C]-0.0868[/C][C]0.465473[/C][/ROW]
[ROW][C]13[/C][C]-0.249956[/C][C]-2.7037[/C][C]0.00394[/C][/ROW]
[ROW][C]14[/C][C]0.052576[/C][C]0.5687[/C][C]0.285328[/C][/ROW]
[ROW][C]15[/C][C]-0.032788[/C][C]-0.3547[/C][C]0.361741[/C][/ROW]
[ROW][C]16[/C][C]0.037298[/C][C]0.4034[/C][C]0.343679[/C][/ROW]
[ROW][C]17[/C][C]0.046617[/C][C]0.5042[/C][C]0.307521[/C][/ROW]
[ROW][C]18[/C][C]0.087432[/C][C]0.9457[/C][C]0.17312[/C][/ROW]
[ROW][C]19[/C][C]-0.139023[/C][C]-1.5038[/C][C]0.067669[/C][/ROW]
[ROW][C]20[/C][C]0.040458[/C][C]0.4376[/C][C]0.331234[/C][/ROW]
[ROW][C]21[/C][C]0.039159[/C][C]0.4236[/C][C]0.336328[/C][/ROW]
[ROW][C]22[/C][C]-0.00117[/C][C]-0.0127[/C][C]0.494964[/C][/ROW]
[ROW][C]23[/C][C]-0.00099[/C][C]-0.0107[/C][C]0.495736[/C][/ROW]
[ROW][C]24[/C][C]0.045939[/C][C]0.4969[/C][C]0.310093[/C][/ROW]
[ROW][C]25[/C][C]-0.094651[/C][C]-1.0238[/C][C]0.15402[/C][/ROW]
[ROW][C]26[/C][C]0.011262[/C][C]0.1218[/C][C]0.451627[/C][/ROW]
[ROW][C]27[/C][C]-0.021167[/C][C]-0.229[/C][C]0.40965[/C][/ROW]
[ROW][C]28[/C][C]-0.000945[/C][C]-0.0102[/C][C]0.49593[/C][/ROW]
[ROW][C]29[/C][C]0.001788[/C][C]0.0193[/C][C]0.492303[/C][/ROW]
[ROW][C]30[/C][C]-0.028195[/C][C]-0.305[/C][C]0.380462[/C][/ROW]
[ROW][C]31[/C][C]-0.083505[/C][C]-0.9032[/C][C]0.184126[/C][/ROW]
[ROW][C]32[/C][C]-0.002854[/C][C]-0.0309[/C][C]0.487713[/C][/ROW]
[ROW][C]33[/C][C]0.027566[/C][C]0.2982[/C][C]0.383052[/C][/ROW]
[ROW][C]34[/C][C]-0.016768[/C][C]-0.1814[/C][C]0.428192[/C][/ROW]
[ROW][C]35[/C][C]-0.012047[/C][C]-0.1303[/C][C]0.448272[/C][/ROW]
[ROW][C]36[/C][C]0.001077[/C][C]0.0117[/C][C]0.495362[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67062&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67062&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
10.96110510.39590
20.1526051.65070.050744
30.0766240.82880.204449
4-0.040595-0.43910.330699
5-0.032345-0.34990.363534
60.1142641.2360.109476
7-0.270275-2.92350.002078
80.0735860.7960.213835
90.0647720.70060.242468
10-0.030958-0.33490.369163
11-0.006956-0.07520.470074
12-0.008028-0.08680.465473
13-0.249956-2.70370.00394
140.0525760.56870.285328
15-0.032788-0.35470.361741
160.0372980.40340.343679
170.0466170.50420.307521
180.0874320.94570.17312
19-0.139023-1.50380.067669
200.0404580.43760.331234
210.0391590.42360.336328
22-0.00117-0.01270.494964
23-0.00099-0.01070.495736
240.0459390.49690.310093
25-0.094651-1.02380.15402
260.0112620.12180.451627
27-0.021167-0.2290.40965
28-0.000945-0.01020.49593
290.0017880.01930.492303
30-0.028195-0.3050.380462
31-0.083505-0.90320.184126
32-0.002854-0.03090.487713
330.0275660.29820.383052
34-0.016768-0.18140.428192
35-0.012047-0.13030.448272
360.0010770.01170.495362


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')