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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 11:13:42 -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/t126064167938d23sya40jtqbu.htm/, Retrieved Mon, 29 Apr 2024 09:14:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=67113, Retrieved Mon, 29 Apr 2024 09:14:41 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact187

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]
-   P               [(Partial) Autocorrelation Function] [Paper PAF IGP d=0...] [2009-12-12 18:13:42] [4f297b039e1043ebee7ff7a83b1eaaaa] [Current]
Feedback Forum

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
100.01
103.84
104.48
95.43
104.80
108.64
105.65
108.42
115.35
113.64
115.24
100.33
101.29
104.48
99.26
100.11
103.52
101.18
96.39
97.56
96.39
85.10
79.77
79.13
80.84
82.75
92.55
96.60
96.92
95.32
98.52
100.22
104.91
103.10
97.13
103.42
111.72
118.11
111.62
100.22
102.03
105.76
107.68
110.77
105.44
112.26
114.07
117.90
124.72
126.42
134.73
135.79
143.36
140.37
144.74
151.98
150.92
163.38
154.43
146.66
157.95
162.10
180.42
179.57
171.58
185.43
190.64
203.00
202.36
193.41
186.17
192.24
209.60
206.41
209.82
230.37
235.80
232.07
244.64
242.19
217.48
209.39
211.73
221.00
203.11
214.71
224.19
238.04
238.36
246.24
259.87
249.97
266.48
282.98
306.31
301.73
314.62
332.62
355.51
370.32
408.13
433.58
440.51
386.29
342.84
254.97
203.42
170.09
174.03
167.85
177.01
188.19
211.20
240.91
230.26
251.25
241.66

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67113&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]2 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=67113&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67113&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.9328249.55860
20.8329468.53520
30.7291717.47180
40.6214166.36760
50.4978825.10181e-06
60.3664043.75450.000143
70.2453072.51360.006734
80.1371351.40520.081455
90.0497080.50940.305788
10-0.023412-0.23990.405437
11-0.100206-1.02680.153436
12-0.166052-1.70150.045902
13-0.176783-1.81150.036462
14-0.145934-1.49540.068908
15-0.102017-1.04540.149128
16-0.06262-0.64170.261246
17-0.017731-0.18170.428089
180.0204150.20920.417354
190.0592840.60750.272423
200.0918530.94120.174379
210.1038591.06420.14483
220.1003091.02790.153189
230.0887810.90970.182523
240.086480.88620.188779
250.0853870.8750.191797
260.057750.59180.27764
270.0207430.21260.416043
28-0.017142-0.17560.430454
29-0.053578-0.5490.292081
30-0.073916-0.75740.225249
31-0.100892-1.03380.151794
32-0.130059-1.33270.092755
33-0.15497-1.5880.05765
34-0.162053-1.66060.049893
35-0.152243-1.560.060882
36-0.151458-1.5520.061838

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.932824 & 9.5586 & 0 \tabularnewline
2 & 0.832946 & 8.5352 & 0 \tabularnewline
3 & 0.729171 & 7.4718 & 0 \tabularnewline
4 & 0.621416 & 6.3676 & 0 \tabularnewline
5 & 0.497882 & 5.1018 & 1e-06 \tabularnewline
6 & 0.366404 & 3.7545 & 0.000143 \tabularnewline
7 & 0.245307 & 2.5136 & 0.006734 \tabularnewline
8 & 0.137135 & 1.4052 & 0.081455 \tabularnewline
9 & 0.049708 & 0.5094 & 0.305788 \tabularnewline
10 & -0.023412 & -0.2399 & 0.405437 \tabularnewline
11 & -0.100206 & -1.0268 & 0.153436 \tabularnewline
12 & -0.166052 & -1.7015 & 0.045902 \tabularnewline
13 & -0.176783 & -1.8115 & 0.036462 \tabularnewline
14 & -0.145934 & -1.4954 & 0.068908 \tabularnewline
15 & -0.102017 & -1.0454 & 0.149128 \tabularnewline
16 & -0.06262 & -0.6417 & 0.261246 \tabularnewline
17 & -0.017731 & -0.1817 & 0.428089 \tabularnewline
18 & 0.020415 & 0.2092 & 0.417354 \tabularnewline
19 & 0.059284 & 0.6075 & 0.272423 \tabularnewline
20 & 0.091853 & 0.9412 & 0.174379 \tabularnewline
21 & 0.103859 & 1.0642 & 0.14483 \tabularnewline
22 & 0.100309 & 1.0279 & 0.153189 \tabularnewline
23 & 0.088781 & 0.9097 & 0.182523 \tabularnewline
24 & 0.08648 & 0.8862 & 0.188779 \tabularnewline
25 & 0.085387 & 0.875 & 0.191797 \tabularnewline
26 & 0.05775 & 0.5918 & 0.27764 \tabularnewline
27 & 0.020743 & 0.2126 & 0.416043 \tabularnewline
28 & -0.017142 & -0.1756 & 0.430454 \tabularnewline
29 & -0.053578 & -0.549 & 0.292081 \tabularnewline
30 & -0.073916 & -0.7574 & 0.225249 \tabularnewline
31 & -0.100892 & -1.0338 & 0.151794 \tabularnewline
32 & -0.130059 & -1.3327 & 0.092755 \tabularnewline
33 & -0.15497 & -1.588 & 0.05765 \tabularnewline
34 & -0.162053 & -1.6606 & 0.049893 \tabularnewline
35 & -0.152243 & -1.56 & 0.060882 \tabularnewline
36 & -0.151458 & -1.552 & 0.061838 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67113&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]0.932824[/C][C]9.5586[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.832946[/C][C]8.5352[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.729171[/C][C]7.4718[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.621416[/C][C]6.3676[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.497882[/C][C]5.1018[/C][C]1e-06[/C][/ROW]
[ROW][C]6[/C][C]0.366404[/C][C]3.7545[/C][C]0.000143[/C][/ROW]
[ROW][C]7[/C][C]0.245307[/C][C]2.5136[/C][C]0.006734[/C][/ROW]
[ROW][C]8[/C][C]0.137135[/C][C]1.4052[/C][C]0.081455[/C][/ROW]
[ROW][C]9[/C][C]0.049708[/C][C]0.5094[/C][C]0.305788[/C][/ROW]
[ROW][C]10[/C][C]-0.023412[/C][C]-0.2399[/C][C]0.405437[/C][/ROW]
[ROW][C]11[/C][C]-0.100206[/C][C]-1.0268[/C][C]0.153436[/C][/ROW]
[ROW][C]12[/C][C]-0.166052[/C][C]-1.7015[/C][C]0.045902[/C][/ROW]
[ROW][C]13[/C][C]-0.176783[/C][C]-1.8115[/C][C]0.036462[/C][/ROW]
[ROW][C]14[/C][C]-0.145934[/C][C]-1.4954[/C][C]0.068908[/C][/ROW]
[ROW][C]15[/C][C]-0.102017[/C][C]-1.0454[/C][C]0.149128[/C][/ROW]
[ROW][C]16[/C][C]-0.06262[/C][C]-0.6417[/C][C]0.261246[/C][/ROW]
[ROW][C]17[/C][C]-0.017731[/C][C]-0.1817[/C][C]0.428089[/C][/ROW]
[ROW][C]18[/C][C]0.020415[/C][C]0.2092[/C][C]0.417354[/C][/ROW]
[ROW][C]19[/C][C]0.059284[/C][C]0.6075[/C][C]0.272423[/C][/ROW]
[ROW][C]20[/C][C]0.091853[/C][C]0.9412[/C][C]0.174379[/C][/ROW]
[ROW][C]21[/C][C]0.103859[/C][C]1.0642[/C][C]0.14483[/C][/ROW]
[ROW][C]22[/C][C]0.100309[/C][C]1.0279[/C][C]0.153189[/C][/ROW]
[ROW][C]23[/C][C]0.088781[/C][C]0.9097[/C][C]0.182523[/C][/ROW]
[ROW][C]24[/C][C]0.08648[/C][C]0.8862[/C][C]0.188779[/C][/ROW]
[ROW][C]25[/C][C]0.085387[/C][C]0.875[/C][C]0.191797[/C][/ROW]
[ROW][C]26[/C][C]0.05775[/C][C]0.5918[/C][C]0.27764[/C][/ROW]
[ROW][C]27[/C][C]0.020743[/C][C]0.2126[/C][C]0.416043[/C][/ROW]
[ROW][C]28[/C][C]-0.017142[/C][C]-0.1756[/C][C]0.430454[/C][/ROW]
[ROW][C]29[/C][C]-0.053578[/C][C]-0.549[/C][C]0.292081[/C][/ROW]
[ROW][C]30[/C][C]-0.073916[/C][C]-0.7574[/C][C]0.225249[/C][/ROW]
[ROW][C]31[/C][C]-0.100892[/C][C]-1.0338[/C][C]0.151794[/C][/ROW]
[ROW][C]32[/C][C]-0.130059[/C][C]-1.3327[/C][C]0.092755[/C][/ROW]
[ROW][C]33[/C][C]-0.15497[/C][C]-1.588[/C][C]0.05765[/C][/ROW]
[ROW][C]34[/C][C]-0.162053[/C][C]-1.6606[/C][C]0.049893[/C][/ROW]
[ROW][C]35[/C][C]-0.152243[/C][C]-1.56[/C][C]0.060882[/C][/ROW]
[ROW][C]36[/C][C]-0.151458[/C][C]-1.552[/C][C]0.061838[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67113&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67113&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
10.9328249.55860
20.8329468.53520
30.7291717.47180
40.6214166.36760
50.4978825.10181e-06
60.3664043.75450.000143
70.2453072.51360.006734
80.1371351.40520.081455
90.0497080.50940.305788
10-0.023412-0.23990.405437
11-0.100206-1.02680.153436
12-0.166052-1.70150.045902
13-0.176783-1.81150.036462
14-0.145934-1.49540.068908
15-0.102017-1.04540.149128
16-0.06262-0.64170.261246
17-0.017731-0.18170.428089
180.0204150.20920.417354
190.0592840.60750.272423
200.0918530.94120.174379
210.1038591.06420.14483
220.1003091.02790.153189
230.0887810.90970.182523
240.086480.88620.188779
250.0853870.8750.191797
260.057750.59180.27764
270.0207430.21260.416043
28-0.017142-0.17560.430454
29-0.053578-0.5490.292081
30-0.073916-0.75740.225249
31-0.100892-1.03380.151794
32-0.130059-1.33270.092755
33-0.15497-1.5880.05765
34-0.162053-1.66060.049893
35-0.152243-1.560.060882
36-0.151458-1.5520.061838






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9328249.55860
2-0.286622-2.9370.002037
3-0.026486-0.27140.393306
4-0.094245-0.96570.1682
5-0.186247-1.90850.029531
6-0.098403-1.00830.157807
70.0053810.05510.478067
8-0.026894-0.27560.391707
90.0641550.65740.256182
10-0.018532-0.18990.424878
11-0.167748-1.71890.044289
120.0069210.07090.471799
130.3333873.41620.000452
140.1312341.34470.090802
150.0244320.25040.4014
16-0.077294-0.7920.215064
17-0.048189-0.49380.311241
18-0.170651-1.74860.041637
190.0698210.71550.237959
200.0235260.24110.404984
21-0.056976-0.58380.280292
22-0.009998-0.10240.459299
23-0.114248-1.17070.122186
240.0356310.36510.357882
250.1815861.86070.032792
26-0.075967-0.77840.219034
270.030190.30940.378833
28-0.057448-0.58870.278675
29-0.110358-1.13080.130352
300.0933170.95620.17058
31-0.080083-0.82060.206863
32-0.033667-0.3450.365397
33-0.017593-0.18030.428642
34-0.022966-0.23530.407204
350.0190210.19490.42292
36-0.040867-0.41880.338122

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.932824 & 9.5586 & 0 \tabularnewline
2 & -0.286622 & -2.937 & 0.002037 \tabularnewline
3 & -0.026486 & -0.2714 & 0.393306 \tabularnewline
4 & -0.094245 & -0.9657 & 0.1682 \tabularnewline
5 & -0.186247 & -1.9085 & 0.029531 \tabularnewline
6 & -0.098403 & -1.0083 & 0.157807 \tabularnewline
7 & 0.005381 & 0.0551 & 0.478067 \tabularnewline
8 & -0.026894 & -0.2756 & 0.391707 \tabularnewline
9 & 0.064155 & 0.6574 & 0.256182 \tabularnewline
10 & -0.018532 & -0.1899 & 0.424878 \tabularnewline
11 & -0.167748 & -1.7189 & 0.044289 \tabularnewline
12 & 0.006921 & 0.0709 & 0.471799 \tabularnewline
13 & 0.333387 & 3.4162 & 0.000452 \tabularnewline
14 & 0.131234 & 1.3447 & 0.090802 \tabularnewline
15 & 0.024432 & 0.2504 & 0.4014 \tabularnewline
16 & -0.077294 & -0.792 & 0.215064 \tabularnewline
17 & -0.048189 & -0.4938 & 0.311241 \tabularnewline
18 & -0.170651 & -1.7486 & 0.041637 \tabularnewline
19 & 0.069821 & 0.7155 & 0.237959 \tabularnewline
20 & 0.023526 & 0.2411 & 0.404984 \tabularnewline
21 & -0.056976 & -0.5838 & 0.280292 \tabularnewline
22 & -0.009998 & -0.1024 & 0.459299 \tabularnewline
23 & -0.114248 & -1.1707 & 0.122186 \tabularnewline
24 & 0.035631 & 0.3651 & 0.357882 \tabularnewline
25 & 0.181586 & 1.8607 & 0.032792 \tabularnewline
26 & -0.075967 & -0.7784 & 0.219034 \tabularnewline
27 & 0.03019 & 0.3094 & 0.378833 \tabularnewline
28 & -0.057448 & -0.5887 & 0.278675 \tabularnewline
29 & -0.110358 & -1.1308 & 0.130352 \tabularnewline
30 & 0.093317 & 0.9562 & 0.17058 \tabularnewline
31 & -0.080083 & -0.8206 & 0.206863 \tabularnewline
32 & -0.033667 & -0.345 & 0.365397 \tabularnewline
33 & -0.017593 & -0.1803 & 0.428642 \tabularnewline
34 & -0.022966 & -0.2353 & 0.407204 \tabularnewline
35 & 0.019021 & 0.1949 & 0.42292 \tabularnewline
36 & -0.040867 & -0.4188 & 0.338122 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67113&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]0.932824[/C][C]9.5586[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.286622[/C][C]-2.937[/C][C]0.002037[/C][/ROW]
[ROW][C]3[/C][C]-0.026486[/C][C]-0.2714[/C][C]0.393306[/C][/ROW]
[ROW][C]4[/C][C]-0.094245[/C][C]-0.9657[/C][C]0.1682[/C][/ROW]
[ROW][C]5[/C][C]-0.186247[/C][C]-1.9085[/C][C]0.029531[/C][/ROW]
[ROW][C]6[/C][C]-0.098403[/C][C]-1.0083[/C][C]0.157807[/C][/ROW]
[ROW][C]7[/C][C]0.005381[/C][C]0.0551[/C][C]0.478067[/C][/ROW]
[ROW][C]8[/C][C]-0.026894[/C][C]-0.2756[/C][C]0.391707[/C][/ROW]
[ROW][C]9[/C][C]0.064155[/C][C]0.6574[/C][C]0.256182[/C][/ROW]
[ROW][C]10[/C][C]-0.018532[/C][C]-0.1899[/C][C]0.424878[/C][/ROW]
[ROW][C]11[/C][C]-0.167748[/C][C]-1.7189[/C][C]0.044289[/C][/ROW]
[ROW][C]12[/C][C]0.006921[/C][C]0.0709[/C][C]0.471799[/C][/ROW]
[ROW][C]13[/C][C]0.333387[/C][C]3.4162[/C][C]0.000452[/C][/ROW]
[ROW][C]14[/C][C]0.131234[/C][C]1.3447[/C][C]0.090802[/C][/ROW]
[ROW][C]15[/C][C]0.024432[/C][C]0.2504[/C][C]0.4014[/C][/ROW]
[ROW][C]16[/C][C]-0.077294[/C][C]-0.792[/C][C]0.215064[/C][/ROW]
[ROW][C]17[/C][C]-0.048189[/C][C]-0.4938[/C][C]0.311241[/C][/ROW]
[ROW][C]18[/C][C]-0.170651[/C][C]-1.7486[/C][C]0.041637[/C][/ROW]
[ROW][C]19[/C][C]0.069821[/C][C]0.7155[/C][C]0.237959[/C][/ROW]
[ROW][C]20[/C][C]0.023526[/C][C]0.2411[/C][C]0.404984[/C][/ROW]
[ROW][C]21[/C][C]-0.056976[/C][C]-0.5838[/C][C]0.280292[/C][/ROW]
[ROW][C]22[/C][C]-0.009998[/C][C]-0.1024[/C][C]0.459299[/C][/ROW]
[ROW][C]23[/C][C]-0.114248[/C][C]-1.1707[/C][C]0.122186[/C][/ROW]
[ROW][C]24[/C][C]0.035631[/C][C]0.3651[/C][C]0.357882[/C][/ROW]
[ROW][C]25[/C][C]0.181586[/C][C]1.8607[/C][C]0.032792[/C][/ROW]
[ROW][C]26[/C][C]-0.075967[/C][C]-0.7784[/C][C]0.219034[/C][/ROW]
[ROW][C]27[/C][C]0.03019[/C][C]0.3094[/C][C]0.378833[/C][/ROW]
[ROW][C]28[/C][C]-0.057448[/C][C]-0.5887[/C][C]0.278675[/C][/ROW]
[ROW][C]29[/C][C]-0.110358[/C][C]-1.1308[/C][C]0.130352[/C][/ROW]
[ROW][C]30[/C][C]0.093317[/C][C]0.9562[/C][C]0.17058[/C][/ROW]
[ROW][C]31[/C][C]-0.080083[/C][C]-0.8206[/C][C]0.206863[/C][/ROW]
[ROW][C]32[/C][C]-0.033667[/C][C]-0.345[/C][C]0.365397[/C][/ROW]
[ROW][C]33[/C][C]-0.017593[/C][C]-0.1803[/C][C]0.428642[/C][/ROW]
[ROW][C]34[/C][C]-0.022966[/C][C]-0.2353[/C][C]0.407204[/C][/ROW]
[ROW][C]35[/C][C]0.019021[/C][C]0.1949[/C][C]0.42292[/C][/ROW]
[ROW][C]36[/C][C]-0.040867[/C][C]-0.4188[/C][C]0.338122[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67113&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67113&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
10.9328249.55860
2-0.286622-2.9370.002037
3-0.026486-0.27140.393306
4-0.094245-0.96570.1682
5-0.186247-1.90850.029531
6-0.098403-1.00830.157807
70.0053810.05510.478067
8-0.026894-0.27560.391707
90.0641550.65740.256182
10-0.018532-0.18990.424878
11-0.167748-1.71890.044289
120.0069210.07090.471799
130.3333873.41620.000452
140.1312341.34470.090802
150.0244320.25040.4014
16-0.077294-0.7920.215064
17-0.048189-0.49380.311241
18-0.170651-1.74860.041637
190.0698210.71550.237959
200.0235260.24110.404984
21-0.056976-0.58380.280292
22-0.009998-0.10240.459299
23-0.114248-1.17070.122186
240.0356310.36510.357882
250.1815861.86070.032792
26-0.075967-0.77840.219034
270.030190.30940.378833
28-0.057448-0.58870.278675
29-0.110358-1.13080.130352
300.0933170.95620.17058
31-0.080083-0.82060.206863
32-0.033667-0.3450.365397
33-0.017593-0.18030.428642
34-0.022966-0.23530.407204
350.0190210.19490.42292
36-0.040867-0.41880.338122


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = -0.7 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = -0.7 ; 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')