Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Module--
Title produced by software(Partial) Autocorrelation Function
Date of computationTue, 18 Dec 2012 06:13:12 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/18/t1355829200legjdeahkm0543k.htm/, Retrieved Thu, 28 Mar 2024 22:32:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=201356, Retrieved Thu, 28 Mar 2024 22:32:36 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact104
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       [Univariate Data Series] [Identifying Integ...] [2009-11-22 12:08:06] [b98453cac15ba1066b407e146608df68]
- RMP         [(Partial) Autocorrelation Function] [Partial Autocorre...] [2011-12-07 13:38:09] [8e7c659e1b71a02d35eacc5210237549]
- R P           [(Partial) Autocorrelation Function] [Partial autocorre...] [2011-12-22 14:17:06] [74be16979710d4c4e7c6647856088456]
-  M                [(Partial) Autocorrelation Function] [] [2012-12-18 11:13:12] [68acb5451e1b1259a9abdc7e099f7f6d] [Current]
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Dataseries X:
9700
9081
9084
9743
8587
9731
9563
9998
9437
10038
9918
9252
9737
9035
9133
9487
8700
9627
8947
9283
8829
9947
9628
9318
9605
8640
9214
9567
8547
9185
9470
9123
9278
10170
9434
9655
9429
8739
9552
9687
9019
9672
9206
9069
9788
10312
10105
9863
9656
9295
9946
9701
9049
10190
9706
9765
9893
9994
10433
10073
10112
9266
9820
10097
9115
10411
9678
10408
10153
10368
10581
10597
10680
9738
9556




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'George Udny Yule' @ yule.wessa.net

\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 & 3 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=201356&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=201356&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=201356&T=0

As an alternative you can also use a 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 time3 seconds
R Server'George Udny Yule' @ yule.wessa.net







Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.439783-3.46290.000487
2-0.025308-0.19930.42135
3-0.006337-0.04990.480181
4-0.131059-1.0320.15305
50.2166091.70560.046546
6-0.001855-0.01460.494196
7-0.125075-0.98480.164265
8-0.089179-0.70220.242593
90.292592.30390.012298
10-0.175512-1.3820.085968
110.0388710.30610.380287
12-0.064769-0.510.305933
13-0.159611-1.25680.106775
140.3920863.08730.00151
15-0.229945-1.81060.037525
16-0.024-0.1890.425365
170.0294010.23150.408842
180.0726290.57190.284736
190.0063090.04970.480271
20-0.018563-0.14620.442133
21-0.080554-0.63430.264114
22-0.111977-0.88170.19067
230.3262372.56880.006313
24-0.162349-1.27830.102947
250.0227140.17880.42932
26-0.066244-0.52160.301903
270.0050090.03940.484334
280.1248480.98310.164701
29-0.108467-0.85410.198178
300.0190530.150.440618
31-0.143309-1.12840.131746
320.1735171.36630.088394
330.0378190.29780.383432
34-0.068515-0.53950.295742
350.0022370.01760.493001
36-0.137991-1.08650.140723

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.439783 & -3.4629 & 0.000487 \tabularnewline
2 & -0.025308 & -0.1993 & 0.42135 \tabularnewline
3 & -0.006337 & -0.0499 & 0.480181 \tabularnewline
4 & -0.131059 & -1.032 & 0.15305 \tabularnewline
5 & 0.216609 & 1.7056 & 0.046546 \tabularnewline
6 & -0.001855 & -0.0146 & 0.494196 \tabularnewline
7 & -0.125075 & -0.9848 & 0.164265 \tabularnewline
8 & -0.089179 & -0.7022 & 0.242593 \tabularnewline
9 & 0.29259 & 2.3039 & 0.012298 \tabularnewline
10 & -0.175512 & -1.382 & 0.085968 \tabularnewline
11 & 0.038871 & 0.3061 & 0.380287 \tabularnewline
12 & -0.064769 & -0.51 & 0.305933 \tabularnewline
13 & -0.159611 & -1.2568 & 0.106775 \tabularnewline
14 & 0.392086 & 3.0873 & 0.00151 \tabularnewline
15 & -0.229945 & -1.8106 & 0.037525 \tabularnewline
16 & -0.024 & -0.189 & 0.425365 \tabularnewline
17 & 0.029401 & 0.2315 & 0.408842 \tabularnewline
18 & 0.072629 & 0.5719 & 0.284736 \tabularnewline
19 & 0.006309 & 0.0497 & 0.480271 \tabularnewline
20 & -0.018563 & -0.1462 & 0.442133 \tabularnewline
21 & -0.080554 & -0.6343 & 0.264114 \tabularnewline
22 & -0.111977 & -0.8817 & 0.19067 \tabularnewline
23 & 0.326237 & 2.5688 & 0.006313 \tabularnewline
24 & -0.162349 & -1.2783 & 0.102947 \tabularnewline
25 & 0.022714 & 0.1788 & 0.42932 \tabularnewline
26 & -0.066244 & -0.5216 & 0.301903 \tabularnewline
27 & 0.005009 & 0.0394 & 0.484334 \tabularnewline
28 & 0.124848 & 0.9831 & 0.164701 \tabularnewline
29 & -0.108467 & -0.8541 & 0.198178 \tabularnewline
30 & 0.019053 & 0.15 & 0.440618 \tabularnewline
31 & -0.143309 & -1.1284 & 0.131746 \tabularnewline
32 & 0.173517 & 1.3663 & 0.088394 \tabularnewline
33 & 0.037819 & 0.2978 & 0.383432 \tabularnewline
34 & -0.068515 & -0.5395 & 0.295742 \tabularnewline
35 & 0.002237 & 0.0176 & 0.493001 \tabularnewline
36 & -0.137991 & -1.0865 & 0.140723 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=201356&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]-0.439783[/C][C]-3.4629[/C][C]0.000487[/C][/ROW]
[ROW][C]2[/C][C]-0.025308[/C][C]-0.1993[/C][C]0.42135[/C][/ROW]
[ROW][C]3[/C][C]-0.006337[/C][C]-0.0499[/C][C]0.480181[/C][/ROW]
[ROW][C]4[/C][C]-0.131059[/C][C]-1.032[/C][C]0.15305[/C][/ROW]
[ROW][C]5[/C][C]0.216609[/C][C]1.7056[/C][C]0.046546[/C][/ROW]
[ROW][C]6[/C][C]-0.001855[/C][C]-0.0146[/C][C]0.494196[/C][/ROW]
[ROW][C]7[/C][C]-0.125075[/C][C]-0.9848[/C][C]0.164265[/C][/ROW]
[ROW][C]8[/C][C]-0.089179[/C][C]-0.7022[/C][C]0.242593[/C][/ROW]
[ROW][C]9[/C][C]0.29259[/C][C]2.3039[/C][C]0.012298[/C][/ROW]
[ROW][C]10[/C][C]-0.175512[/C][C]-1.382[/C][C]0.085968[/C][/ROW]
[ROW][C]11[/C][C]0.038871[/C][C]0.3061[/C][C]0.380287[/C][/ROW]
[ROW][C]12[/C][C]-0.064769[/C][C]-0.51[/C][C]0.305933[/C][/ROW]
[ROW][C]13[/C][C]-0.159611[/C][C]-1.2568[/C][C]0.106775[/C][/ROW]
[ROW][C]14[/C][C]0.392086[/C][C]3.0873[/C][C]0.00151[/C][/ROW]
[ROW][C]15[/C][C]-0.229945[/C][C]-1.8106[/C][C]0.037525[/C][/ROW]
[ROW][C]16[/C][C]-0.024[/C][C]-0.189[/C][C]0.425365[/C][/ROW]
[ROW][C]17[/C][C]0.029401[/C][C]0.2315[/C][C]0.408842[/C][/ROW]
[ROW][C]18[/C][C]0.072629[/C][C]0.5719[/C][C]0.284736[/C][/ROW]
[ROW][C]19[/C][C]0.006309[/C][C]0.0497[/C][C]0.480271[/C][/ROW]
[ROW][C]20[/C][C]-0.018563[/C][C]-0.1462[/C][C]0.442133[/C][/ROW]
[ROW][C]21[/C][C]-0.080554[/C][C]-0.6343[/C][C]0.264114[/C][/ROW]
[ROW][C]22[/C][C]-0.111977[/C][C]-0.8817[/C][C]0.19067[/C][/ROW]
[ROW][C]23[/C][C]0.326237[/C][C]2.5688[/C][C]0.006313[/C][/ROW]
[ROW][C]24[/C][C]-0.162349[/C][C]-1.2783[/C][C]0.102947[/C][/ROW]
[ROW][C]25[/C][C]0.022714[/C][C]0.1788[/C][C]0.42932[/C][/ROW]
[ROW][C]26[/C][C]-0.066244[/C][C]-0.5216[/C][C]0.301903[/C][/ROW]
[ROW][C]27[/C][C]0.005009[/C][C]0.0394[/C][C]0.484334[/C][/ROW]
[ROW][C]28[/C][C]0.124848[/C][C]0.9831[/C][C]0.164701[/C][/ROW]
[ROW][C]29[/C][C]-0.108467[/C][C]-0.8541[/C][C]0.198178[/C][/ROW]
[ROW][C]30[/C][C]0.019053[/C][C]0.15[/C][C]0.440618[/C][/ROW]
[ROW][C]31[/C][C]-0.143309[/C][C]-1.1284[/C][C]0.131746[/C][/ROW]
[ROW][C]32[/C][C]0.173517[/C][C]1.3663[/C][C]0.088394[/C][/ROW]
[ROW][C]33[/C][C]0.037819[/C][C]0.2978[/C][C]0.383432[/C][/ROW]
[ROW][C]34[/C][C]-0.068515[/C][C]-0.5395[/C][C]0.295742[/C][/ROW]
[ROW][C]35[/C][C]0.002237[/C][C]0.0176[/C][C]0.493001[/C][/ROW]
[ROW][C]36[/C][C]-0.137991[/C][C]-1.0865[/C][C]0.140723[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=201356&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=201356&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.439783-3.46290.000487
2-0.025308-0.19930.42135
3-0.006337-0.04990.480181
4-0.131059-1.0320.15305
50.2166091.70560.046546
6-0.001855-0.01460.494196
7-0.125075-0.98480.164265
8-0.089179-0.70220.242593
90.292592.30390.012298
10-0.175512-1.3820.085968
110.0388710.30610.380287
12-0.064769-0.510.305933
13-0.159611-1.25680.106775
140.3920863.08730.00151
15-0.229945-1.81060.037525
16-0.024-0.1890.425365
170.0294010.23150.408842
180.0726290.57190.284736
190.0063090.04970.480271
20-0.018563-0.14620.442133
21-0.080554-0.63430.264114
22-0.111977-0.88170.19067
230.3262372.56880.006313
24-0.162349-1.27830.102947
250.0227140.17880.42932
26-0.066244-0.52160.301903
270.0050090.03940.484334
280.1248480.98310.164701
29-0.108467-0.85410.198178
300.0190530.150.440618
31-0.143309-1.12840.131746
320.1735171.36630.088394
330.0378190.29780.383432
34-0.068515-0.53950.295742
350.0022370.01760.493001
36-0.137991-1.08650.140723







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.439783-3.46290.000487
2-0.271162-2.13510.018355
3-0.186994-1.47240.072986
4-0.314314-2.47490.008038
5-0.033771-0.26590.395595
60.0816070.64260.261436
7-0.055168-0.43440.332755
8-0.243368-1.91630.029971
90.217581.71320.045834
100.0386770.30450.380866
11-0.046663-0.36740.357276
12-0.077526-0.61040.271902
13-0.205119-1.61510.055682
140.1416731.11550.134464
15-0.082508-0.64970.259153
16-0.122284-0.96290.169678
17-0.006352-0.050.480134
180.1698271.33720.093018
190.0478730.3770.353747
20-0.026734-0.21050.416981
210.0412520.32480.373205
22-0.103439-0.81450.209244
230.0081580.06420.474494
240.025060.19730.42211
250.0519310.40890.342009
26-0.042613-0.33550.369178
270.050610.39850.345814
280.023060.18160.428253
29-0.039935-0.31440.377119
300.0518990.40870.342102
31-0.137677-1.08410.141266
32-0.14053-1.10650.136385
330.0968580.76270.22428
340.0149780.11790.453249
350.0051460.04050.483905
36-0.079302-0.62440.267321

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.439783 & -3.4629 & 0.000487 \tabularnewline
2 & -0.271162 & -2.1351 & 0.018355 \tabularnewline
3 & -0.186994 & -1.4724 & 0.072986 \tabularnewline
4 & -0.314314 & -2.4749 & 0.008038 \tabularnewline
5 & -0.033771 & -0.2659 & 0.395595 \tabularnewline
6 & 0.081607 & 0.6426 & 0.261436 \tabularnewline
7 & -0.055168 & -0.4344 & 0.332755 \tabularnewline
8 & -0.243368 & -1.9163 & 0.029971 \tabularnewline
9 & 0.21758 & 1.7132 & 0.045834 \tabularnewline
10 & 0.038677 & 0.3045 & 0.380866 \tabularnewline
11 & -0.046663 & -0.3674 & 0.357276 \tabularnewline
12 & -0.077526 & -0.6104 & 0.271902 \tabularnewline
13 & -0.205119 & -1.6151 & 0.055682 \tabularnewline
14 & 0.141673 & 1.1155 & 0.134464 \tabularnewline
15 & -0.082508 & -0.6497 & 0.259153 \tabularnewline
16 & -0.122284 & -0.9629 & 0.169678 \tabularnewline
17 & -0.006352 & -0.05 & 0.480134 \tabularnewline
18 & 0.169827 & 1.3372 & 0.093018 \tabularnewline
19 & 0.047873 & 0.377 & 0.353747 \tabularnewline
20 & -0.026734 & -0.2105 & 0.416981 \tabularnewline
21 & 0.041252 & 0.3248 & 0.373205 \tabularnewline
22 & -0.103439 & -0.8145 & 0.209244 \tabularnewline
23 & 0.008158 & 0.0642 & 0.474494 \tabularnewline
24 & 0.02506 & 0.1973 & 0.42211 \tabularnewline
25 & 0.051931 & 0.4089 & 0.342009 \tabularnewline
26 & -0.042613 & -0.3355 & 0.369178 \tabularnewline
27 & 0.05061 & 0.3985 & 0.345814 \tabularnewline
28 & 0.02306 & 0.1816 & 0.428253 \tabularnewline
29 & -0.039935 & -0.3144 & 0.377119 \tabularnewline
30 & 0.051899 & 0.4087 & 0.342102 \tabularnewline
31 & -0.137677 & -1.0841 & 0.141266 \tabularnewline
32 & -0.14053 & -1.1065 & 0.136385 \tabularnewline
33 & 0.096858 & 0.7627 & 0.22428 \tabularnewline
34 & 0.014978 & 0.1179 & 0.453249 \tabularnewline
35 & 0.005146 & 0.0405 & 0.483905 \tabularnewline
36 & -0.079302 & -0.6244 & 0.267321 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=201356&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]-0.439783[/C][C]-3.4629[/C][C]0.000487[/C][/ROW]
[ROW][C]2[/C][C]-0.271162[/C][C]-2.1351[/C][C]0.018355[/C][/ROW]
[ROW][C]3[/C][C]-0.186994[/C][C]-1.4724[/C][C]0.072986[/C][/ROW]
[ROW][C]4[/C][C]-0.314314[/C][C]-2.4749[/C][C]0.008038[/C][/ROW]
[ROW][C]5[/C][C]-0.033771[/C][C]-0.2659[/C][C]0.395595[/C][/ROW]
[ROW][C]6[/C][C]0.081607[/C][C]0.6426[/C][C]0.261436[/C][/ROW]
[ROW][C]7[/C][C]-0.055168[/C][C]-0.4344[/C][C]0.332755[/C][/ROW]
[ROW][C]8[/C][C]-0.243368[/C][C]-1.9163[/C][C]0.029971[/C][/ROW]
[ROW][C]9[/C][C]0.21758[/C][C]1.7132[/C][C]0.045834[/C][/ROW]
[ROW][C]10[/C][C]0.038677[/C][C]0.3045[/C][C]0.380866[/C][/ROW]
[ROW][C]11[/C][C]-0.046663[/C][C]-0.3674[/C][C]0.357276[/C][/ROW]
[ROW][C]12[/C][C]-0.077526[/C][C]-0.6104[/C][C]0.271902[/C][/ROW]
[ROW][C]13[/C][C]-0.205119[/C][C]-1.6151[/C][C]0.055682[/C][/ROW]
[ROW][C]14[/C][C]0.141673[/C][C]1.1155[/C][C]0.134464[/C][/ROW]
[ROW][C]15[/C][C]-0.082508[/C][C]-0.6497[/C][C]0.259153[/C][/ROW]
[ROW][C]16[/C][C]-0.122284[/C][C]-0.9629[/C][C]0.169678[/C][/ROW]
[ROW][C]17[/C][C]-0.006352[/C][C]-0.05[/C][C]0.480134[/C][/ROW]
[ROW][C]18[/C][C]0.169827[/C][C]1.3372[/C][C]0.093018[/C][/ROW]
[ROW][C]19[/C][C]0.047873[/C][C]0.377[/C][C]0.353747[/C][/ROW]
[ROW][C]20[/C][C]-0.026734[/C][C]-0.2105[/C][C]0.416981[/C][/ROW]
[ROW][C]21[/C][C]0.041252[/C][C]0.3248[/C][C]0.373205[/C][/ROW]
[ROW][C]22[/C][C]-0.103439[/C][C]-0.8145[/C][C]0.209244[/C][/ROW]
[ROW][C]23[/C][C]0.008158[/C][C]0.0642[/C][C]0.474494[/C][/ROW]
[ROW][C]24[/C][C]0.02506[/C][C]0.1973[/C][C]0.42211[/C][/ROW]
[ROW][C]25[/C][C]0.051931[/C][C]0.4089[/C][C]0.342009[/C][/ROW]
[ROW][C]26[/C][C]-0.042613[/C][C]-0.3355[/C][C]0.369178[/C][/ROW]
[ROW][C]27[/C][C]0.05061[/C][C]0.3985[/C][C]0.345814[/C][/ROW]
[ROW][C]28[/C][C]0.02306[/C][C]0.1816[/C][C]0.428253[/C][/ROW]
[ROW][C]29[/C][C]-0.039935[/C][C]-0.3144[/C][C]0.377119[/C][/ROW]
[ROW][C]30[/C][C]0.051899[/C][C]0.4087[/C][C]0.342102[/C][/ROW]
[ROW][C]31[/C][C]-0.137677[/C][C]-1.0841[/C][C]0.141266[/C][/ROW]
[ROW][C]32[/C][C]-0.14053[/C][C]-1.1065[/C][C]0.136385[/C][/ROW]
[ROW][C]33[/C][C]0.096858[/C][C]0.7627[/C][C]0.22428[/C][/ROW]
[ROW][C]34[/C][C]0.014978[/C][C]0.1179[/C][C]0.453249[/C][/ROW]
[ROW][C]35[/C][C]0.005146[/C][C]0.0405[/C][C]0.483905[/C][/ROW]
[ROW][C]36[/C][C]-0.079302[/C][C]-0.6244[/C][C]0.267321[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=201356&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=201356&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.439783-3.46290.000487
2-0.271162-2.13510.018355
3-0.186994-1.47240.072986
4-0.314314-2.47490.008038
5-0.033771-0.26590.395595
60.0816070.64260.261436
7-0.055168-0.43440.332755
8-0.243368-1.91630.029971
90.217581.71320.045834
100.0386770.30450.380866
11-0.046663-0.36740.357276
12-0.077526-0.61040.271902
13-0.205119-1.61510.055682
140.1416731.11550.134464
15-0.082508-0.64970.259153
16-0.122284-0.96290.169678
17-0.006352-0.050.480134
180.1698271.33720.093018
190.0478730.3770.353747
20-0.026734-0.21050.416981
210.0412520.32480.373205
22-0.103439-0.81450.209244
230.0081580.06420.474494
240.025060.19730.42211
250.0519310.40890.342009
26-0.042613-0.33550.369178
270.050610.39850.345814
280.023060.18160.428253
29-0.039935-0.31440.377119
300.0518990.40870.342102
31-0.137677-1.08410.141266
32-0.14053-1.10650.136385
330.0968580.76270.22428
340.0149780.11790.453249
350.0051460.04050.483905
36-0.079302-0.62440.267321



Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
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 (par8 != '') par8 <- as.numeric(par8)
ox <- x
if (par8 == '') {
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
} else {
x <- log(x,base=par8)
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='picts.png')
op <- par(mfrow=c(2,1))
plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')
if (par8=='') {
mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
} else {
mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
}
plot(x,type='l', main=mytitle,xlab='time',ylab='value')
par(op)
dev.off()
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)
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')