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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 04:25:31 -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/t1259407785m2q364t4vgdxvqh.htm/, Retrieved Fri, 03 May 2024 11:42:13 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=61435, Retrieved Fri, 03 May 2024 11:42:13 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact141

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]
- R  D        [(Partial) Autocorrelation Function] [Model 1 (autocorr...] [2009-11-25 16:46:20] [c0117c881d5fcd069841276db0c34efe]
-   PD          [(Partial) Autocorrelation Function] [Model 1: D=1] [2009-11-25 16:54:24] [c0117c881d5fcd069841276db0c34efe]
-   P             [(Partial) Autocorrelation Function] [Model 1: D=1, d=1] [2009-11-25 17:09:22] [c0117c881d5fcd069841276db0c34efe]
-   PD                [(Partial) Autocorrelation Function] [] [2009-11-28 11:25:31] [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=61435&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=61435&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61435&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
10.8322935.76630
20.6962294.82367e-06
30.6079874.21235.5e-05
40.5532993.83340.000184
50.5305173.67550.000299
60.4513663.12720.001498
70.3449912.39020.010407
80.3200442.21730.015685
90.3049292.11260.019931
100.2544921.76320.042118
110.2092151.44950.076852
120.0966120.66930.253241
130.1039250.720.237504
140.075120.52040.302572
15-0.014023-0.09720.461504
16-0.061204-0.4240.336717
17-0.126549-0.87680.192493
18-0.170508-1.18130.121649
19-0.154035-1.06720.145613
20-0.188747-1.30770.098606
21-0.250445-1.73510.044567
22-0.285357-1.9770.0269
23-0.336799-2.33340.011931
24-0.343075-2.37690.010747
25-0.351814-2.43740.009273
26-0.352886-2.44490.009106
27-0.307909-2.13330.019022
28-0.310058-2.14810.018389
29-0.314369-2.1780.017175
30-0.304205-2.10760.020157
31-0.304862-2.11210.019952
32-0.296201-2.05210.022816
33-0.279295-1.9350.029446
34-0.29125-2.01780.024609
35-0.272862-1.89040.032372
36-0.227345-1.57510.060902

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.832293 & 5.7663 & 0 \tabularnewline
2 & 0.696229 & 4.8236 & 7e-06 \tabularnewline
3 & 0.607987 & 4.2123 & 5.5e-05 \tabularnewline
4 & 0.553299 & 3.8334 & 0.000184 \tabularnewline
5 & 0.530517 & 3.6755 & 0.000299 \tabularnewline
6 & 0.451366 & 3.1272 & 0.001498 \tabularnewline
7 & 0.344991 & 2.3902 & 0.010407 \tabularnewline
8 & 0.320044 & 2.2173 & 0.015685 \tabularnewline
9 & 0.304929 & 2.1126 & 0.019931 \tabularnewline
10 & 0.254492 & 1.7632 & 0.042118 \tabularnewline
11 & 0.209215 & 1.4495 & 0.076852 \tabularnewline
12 & 0.096612 & 0.6693 & 0.253241 \tabularnewline
13 & 0.103925 & 0.72 & 0.237504 \tabularnewline
14 & 0.07512 & 0.5204 & 0.302572 \tabularnewline
15 & -0.014023 & -0.0972 & 0.461504 \tabularnewline
16 & -0.061204 & -0.424 & 0.336717 \tabularnewline
17 & -0.126549 & -0.8768 & 0.192493 \tabularnewline
18 & -0.170508 & -1.1813 & 0.121649 \tabularnewline
19 & -0.154035 & -1.0672 & 0.145613 \tabularnewline
20 & -0.188747 & -1.3077 & 0.098606 \tabularnewline
21 & -0.250445 & -1.7351 & 0.044567 \tabularnewline
22 & -0.285357 & -1.977 & 0.0269 \tabularnewline
23 & -0.336799 & -2.3334 & 0.011931 \tabularnewline
24 & -0.343075 & -2.3769 & 0.010747 \tabularnewline
25 & -0.351814 & -2.4374 & 0.009273 \tabularnewline
26 & -0.352886 & -2.4449 & 0.009106 \tabularnewline
27 & -0.307909 & -2.1333 & 0.019022 \tabularnewline
28 & -0.310058 & -2.1481 & 0.018389 \tabularnewline
29 & -0.314369 & -2.178 & 0.017175 \tabularnewline
30 & -0.304205 & -2.1076 & 0.020157 \tabularnewline
31 & -0.304862 & -2.1121 & 0.019952 \tabularnewline
32 & -0.296201 & -2.0521 & 0.022816 \tabularnewline
33 & -0.279295 & -1.935 & 0.029446 \tabularnewline
34 & -0.29125 & -2.0178 & 0.024609 \tabularnewline
35 & -0.272862 & -1.8904 & 0.032372 \tabularnewline
36 & -0.227345 & -1.5751 & 0.060902 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61435&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]0.832293[/C][C]5.7663[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.696229[/C][C]4.8236[/C][C]7e-06[/C][/ROW]
[ROW][C]3[/C][C]0.607987[/C][C]4.2123[/C][C]5.5e-05[/C][/ROW]
[ROW][C]4[/C][C]0.553299[/C][C]3.8334[/C][C]0.000184[/C][/ROW]
[ROW][C]5[/C][C]0.530517[/C][C]3.6755[/C][C]0.000299[/C][/ROW]
[ROW][C]6[/C][C]0.451366[/C][C]3.1272[/C][C]0.001498[/C][/ROW]
[ROW][C]7[/C][C]0.344991[/C][C]2.3902[/C][C]0.010407[/C][/ROW]
[ROW][C]8[/C][C]0.320044[/C][C]2.2173[/C][C]0.015685[/C][/ROW]
[ROW][C]9[/C][C]0.304929[/C][C]2.1126[/C][C]0.019931[/C][/ROW]
[ROW][C]10[/C][C]0.254492[/C][C]1.7632[/C][C]0.042118[/C][/ROW]
[ROW][C]11[/C][C]0.209215[/C][C]1.4495[/C][C]0.076852[/C][/ROW]
[ROW][C]12[/C][C]0.096612[/C][C]0.6693[/C][C]0.253241[/C][/ROW]
[ROW][C]13[/C][C]0.103925[/C][C]0.72[/C][C]0.237504[/C][/ROW]
[ROW][C]14[/C][C]0.07512[/C][C]0.5204[/C][C]0.302572[/C][/ROW]
[ROW][C]15[/C][C]-0.014023[/C][C]-0.0972[/C][C]0.461504[/C][/ROW]
[ROW][C]16[/C][C]-0.061204[/C][C]-0.424[/C][C]0.336717[/C][/ROW]
[ROW][C]17[/C][C]-0.126549[/C][C]-0.8768[/C][C]0.192493[/C][/ROW]
[ROW][C]18[/C][C]-0.170508[/C][C]-1.1813[/C][C]0.121649[/C][/ROW]
[ROW][C]19[/C][C]-0.154035[/C][C]-1.0672[/C][C]0.145613[/C][/ROW]
[ROW][C]20[/C][C]-0.188747[/C][C]-1.3077[/C][C]0.098606[/C][/ROW]
[ROW][C]21[/C][C]-0.250445[/C][C]-1.7351[/C][C]0.044567[/C][/ROW]
[ROW][C]22[/C][C]-0.285357[/C][C]-1.977[/C][C]0.0269[/C][/ROW]
[ROW][C]23[/C][C]-0.336799[/C][C]-2.3334[/C][C]0.011931[/C][/ROW]
[ROW][C]24[/C][C]-0.343075[/C][C]-2.3769[/C][C]0.010747[/C][/ROW]
[ROW][C]25[/C][C]-0.351814[/C][C]-2.4374[/C][C]0.009273[/C][/ROW]
[ROW][C]26[/C][C]-0.352886[/C][C]-2.4449[/C][C]0.009106[/C][/ROW]
[ROW][C]27[/C][C]-0.307909[/C][C]-2.1333[/C][C]0.019022[/C][/ROW]
[ROW][C]28[/C][C]-0.310058[/C][C]-2.1481[/C][C]0.018389[/C][/ROW]
[ROW][C]29[/C][C]-0.314369[/C][C]-2.178[/C][C]0.017175[/C][/ROW]
[ROW][C]30[/C][C]-0.304205[/C][C]-2.1076[/C][C]0.020157[/C][/ROW]
[ROW][C]31[/C][C]-0.304862[/C][C]-2.1121[/C][C]0.019952[/C][/ROW]
[ROW][C]32[/C][C]-0.296201[/C][C]-2.0521[/C][C]0.022816[/C][/ROW]
[ROW][C]33[/C][C]-0.279295[/C][C]-1.935[/C][C]0.029446[/C][/ROW]
[ROW][C]34[/C][C]-0.29125[/C][C]-2.0178[/C][C]0.024609[/C][/ROW]
[ROW][C]35[/C][C]-0.272862[/C][C]-1.8904[/C][C]0.032372[/C][/ROW]
[ROW][C]36[/C][C]-0.227345[/C][C]-1.5751[/C][C]0.060902[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61435&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61435&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
10.8322935.76630
20.6962294.82367e-06
30.6079874.21235.5e-05
40.5532993.83340.000184
50.5305173.67550.000299
60.4513663.12720.001498
70.3449912.39020.010407
80.3200442.21730.015685
90.3049292.11260.019931
100.2544921.76320.042118
110.2092151.44950.076852
120.0966120.66930.253241
130.1039250.720.237504
140.075120.52040.302572
15-0.014023-0.09720.461504
16-0.061204-0.4240.336717
17-0.126549-0.87680.192493
18-0.170508-1.18130.121649
19-0.154035-1.06720.145613
20-0.188747-1.30770.098606
21-0.250445-1.73510.044567
22-0.285357-1.9770.0269
23-0.336799-2.33340.011931
24-0.343075-2.37690.010747
25-0.351814-2.43740.009273
26-0.352886-2.44490.009106
27-0.307909-2.13330.019022
28-0.310058-2.14810.018389
29-0.314369-2.1780.017175
30-0.304205-2.10760.020157
31-0.304862-2.11210.019952
32-0.296201-2.05210.022816
33-0.279295-1.9350.029446
34-0.29125-2.01780.024609
35-0.272862-1.89040.032372
36-0.227345-1.57510.060902






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8322935.76630
20.0114480.07930.468557
30.0834070.57790.283031
40.0787850.54580.293853
50.1085230.75190.2279
6-0.149283-1.03430.153098
7-0.124411-0.86190.196502
80.1753081.21460.115236
90.0128270.08890.464779
10-0.132549-0.91830.18152
110.0209320.1450.442651
12-0.207215-1.43560.078797
130.2600391.80160.038945
14-0.228817-1.58530.059734
15-0.157838-1.09350.139809
160.1122010.77740.220383
17-0.130117-0.90150.185918
18-0.059185-0.410.341799
190.0845970.58610.280276
20-0.034964-0.24220.404815
21-0.119788-0.82990.205348
22-0.126449-0.87610.19268
230.0257120.17810.429682
24-0.083472-0.57830.282878
250.0524160.36310.359045
260.0802370.55590.290432
270.0348350.24130.405157
28-0.059949-0.41530.339872
29-0.072655-0.50340.308503
30-0.028095-0.19460.423245
310.0895270.62030.26901
32-0.140518-0.97350.167584
33-0.037186-0.25760.398895
340.0488940.33870.36814
35-0.003321-0.0230.49087
360.0342010.2370.406851

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.832293 & 5.7663 & 0 \tabularnewline
2 & 0.011448 & 0.0793 & 0.468557 \tabularnewline
3 & 0.083407 & 0.5779 & 0.283031 \tabularnewline
4 & 0.078785 & 0.5458 & 0.293853 \tabularnewline
5 & 0.108523 & 0.7519 & 0.2279 \tabularnewline
6 & -0.149283 & -1.0343 & 0.153098 \tabularnewline
7 & -0.124411 & -0.8619 & 0.196502 \tabularnewline
8 & 0.175308 & 1.2146 & 0.115236 \tabularnewline
9 & 0.012827 & 0.0889 & 0.464779 \tabularnewline
10 & -0.132549 & -0.9183 & 0.18152 \tabularnewline
11 & 0.020932 & 0.145 & 0.442651 \tabularnewline
12 & -0.207215 & -1.4356 & 0.078797 \tabularnewline
13 & 0.260039 & 1.8016 & 0.038945 \tabularnewline
14 & -0.228817 & -1.5853 & 0.059734 \tabularnewline
15 & -0.157838 & -1.0935 & 0.139809 \tabularnewline
16 & 0.112201 & 0.7774 & 0.220383 \tabularnewline
17 & -0.130117 & -0.9015 & 0.185918 \tabularnewline
18 & -0.059185 & -0.41 & 0.341799 \tabularnewline
19 & 0.084597 & 0.5861 & 0.280276 \tabularnewline
20 & -0.034964 & -0.2422 & 0.404815 \tabularnewline
21 & -0.119788 & -0.8299 & 0.205348 \tabularnewline
22 & -0.126449 & -0.8761 & 0.19268 \tabularnewline
23 & 0.025712 & 0.1781 & 0.429682 \tabularnewline
24 & -0.083472 & -0.5783 & 0.282878 \tabularnewline
25 & 0.052416 & 0.3631 & 0.359045 \tabularnewline
26 & 0.080237 & 0.5559 & 0.290432 \tabularnewline
27 & 0.034835 & 0.2413 & 0.405157 \tabularnewline
28 & -0.059949 & -0.4153 & 0.339872 \tabularnewline
29 & -0.072655 & -0.5034 & 0.308503 \tabularnewline
30 & -0.028095 & -0.1946 & 0.423245 \tabularnewline
31 & 0.089527 & 0.6203 & 0.26901 \tabularnewline
32 & -0.140518 & -0.9735 & 0.167584 \tabularnewline
33 & -0.037186 & -0.2576 & 0.398895 \tabularnewline
34 & 0.048894 & 0.3387 & 0.36814 \tabularnewline
35 & -0.003321 & -0.023 & 0.49087 \tabularnewline
36 & 0.034201 & 0.237 & 0.406851 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61435&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]0.832293[/C][C]5.7663[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.011448[/C][C]0.0793[/C][C]0.468557[/C][/ROW]
[ROW][C]3[/C][C]0.083407[/C][C]0.5779[/C][C]0.283031[/C][/ROW]
[ROW][C]4[/C][C]0.078785[/C][C]0.5458[/C][C]0.293853[/C][/ROW]
[ROW][C]5[/C][C]0.108523[/C][C]0.7519[/C][C]0.2279[/C][/ROW]
[ROW][C]6[/C][C]-0.149283[/C][C]-1.0343[/C][C]0.153098[/C][/ROW]
[ROW][C]7[/C][C]-0.124411[/C][C]-0.8619[/C][C]0.196502[/C][/ROW]
[ROW][C]8[/C][C]0.175308[/C][C]1.2146[/C][C]0.115236[/C][/ROW]
[ROW][C]9[/C][C]0.012827[/C][C]0.0889[/C][C]0.464779[/C][/ROW]
[ROW][C]10[/C][C]-0.132549[/C][C]-0.9183[/C][C]0.18152[/C][/ROW]
[ROW][C]11[/C][C]0.020932[/C][C]0.145[/C][C]0.442651[/C][/ROW]
[ROW][C]12[/C][C]-0.207215[/C][C]-1.4356[/C][C]0.078797[/C][/ROW]
[ROW][C]13[/C][C]0.260039[/C][C]1.8016[/C][C]0.038945[/C][/ROW]
[ROW][C]14[/C][C]-0.228817[/C][C]-1.5853[/C][C]0.059734[/C][/ROW]
[ROW][C]15[/C][C]-0.157838[/C][C]-1.0935[/C][C]0.139809[/C][/ROW]
[ROW][C]16[/C][C]0.112201[/C][C]0.7774[/C][C]0.220383[/C][/ROW]
[ROW][C]17[/C][C]-0.130117[/C][C]-0.9015[/C][C]0.185918[/C][/ROW]
[ROW][C]18[/C][C]-0.059185[/C][C]-0.41[/C][C]0.341799[/C][/ROW]
[ROW][C]19[/C][C]0.084597[/C][C]0.5861[/C][C]0.280276[/C][/ROW]
[ROW][C]20[/C][C]-0.034964[/C][C]-0.2422[/C][C]0.404815[/C][/ROW]
[ROW][C]21[/C][C]-0.119788[/C][C]-0.8299[/C][C]0.205348[/C][/ROW]
[ROW][C]22[/C][C]-0.126449[/C][C]-0.8761[/C][C]0.19268[/C][/ROW]
[ROW][C]23[/C][C]0.025712[/C][C]0.1781[/C][C]0.429682[/C][/ROW]
[ROW][C]24[/C][C]-0.083472[/C][C]-0.5783[/C][C]0.282878[/C][/ROW]
[ROW][C]25[/C][C]0.052416[/C][C]0.3631[/C][C]0.359045[/C][/ROW]
[ROW][C]26[/C][C]0.080237[/C][C]0.5559[/C][C]0.290432[/C][/ROW]
[ROW][C]27[/C][C]0.034835[/C][C]0.2413[/C][C]0.405157[/C][/ROW]
[ROW][C]28[/C][C]-0.059949[/C][C]-0.4153[/C][C]0.339872[/C][/ROW]
[ROW][C]29[/C][C]-0.072655[/C][C]-0.5034[/C][C]0.308503[/C][/ROW]
[ROW][C]30[/C][C]-0.028095[/C][C]-0.1946[/C][C]0.423245[/C][/ROW]
[ROW][C]31[/C][C]0.089527[/C][C]0.6203[/C][C]0.26901[/C][/ROW]
[ROW][C]32[/C][C]-0.140518[/C][C]-0.9735[/C][C]0.167584[/C][/ROW]
[ROW][C]33[/C][C]-0.037186[/C][C]-0.2576[/C][C]0.398895[/C][/ROW]
[ROW][C]34[/C][C]0.048894[/C][C]0.3387[/C][C]0.36814[/C][/ROW]
[ROW][C]35[/C][C]-0.003321[/C][C]-0.023[/C][C]0.49087[/C][/ROW]
[ROW][C]36[/C][C]0.034201[/C][C]0.237[/C][C]0.406851[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61435&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61435&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
10.8322935.76630
20.0114480.07930.468557
30.0834070.57790.283031
40.0787850.54580.293853
50.1085230.75190.2279
6-0.149283-1.03430.153098
7-0.124411-0.86190.196502
80.1753081.21460.115236
90.0128270.08890.464779
10-0.132549-0.91830.18152
110.0209320.1450.442651
12-0.207215-1.43560.078797
130.2600391.80160.038945
14-0.228817-1.58530.059734
15-0.157838-1.09350.139809
160.1122010.77740.220383
17-0.130117-0.90150.185918
18-0.059185-0.410.341799
190.0845970.58610.280276
20-0.034964-0.24220.404815
21-0.119788-0.82990.205348
22-0.126449-0.87610.19268
230.0257120.17810.429682
24-0.083472-0.57830.282878
250.0524160.36310.359045
260.0802370.55590.290432
270.0348350.24130.405157
28-0.059949-0.41530.339872
29-0.072655-0.50340.308503
30-0.028095-0.19460.423245
310.0895270.62030.26901
32-0.140518-0.97350.167584
33-0.037186-0.25760.398895
340.0488940.33870.36814
35-0.003321-0.0230.49087
360.0342010.2370.406851


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')