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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 computationFri, 27 Nov 2009 06:58:46 -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/27/t1259330399eobxn9k33uvfnye.htm/, Retrieved Mon, 29 Apr 2024 00:44:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60784, Retrieved Mon, 29 Apr 2024 00:44:37 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact132

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 12:19:56] [b98453cac15ba1066b407e146608df68]
-    D          [(Partial) Autocorrelation Function] [] [2009-11-27 13:58:46] [3e9f70e60513fc8919624add68d96eca] [Current]
-                 [(Partial) Autocorrelation Function] [] [2009-11-27 18:34:42] [4d62210f0915d3a20cbf115865da7cd4]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
5560
3922
3759
4138
4634
3996
4308
4143
4429
5219
4929
5755
5592
4163
4962
5208
4755
4491
5732
5731
5040
6102
4904
5369
5578
4619
4731
5011
5299
4146
4625
4736
4219
5116
4205
4121
5103
4300
4578
3809
5526
4247
3830
4394
4826
4409
4569
4106
4794
3914
3793
4405
4022
4100
4788
3163
3585
3903
4178
3863
4187

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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 & 0 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60784&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]0 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=60784&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60784&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 time0 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.3882582.71780.00453
20.2604451.82310.037195
30.4674583.27220.00098
40.3357152.350.011423
50.1910251.33720.09367
60.1709691.19680.118575
70.2149391.50460.069426
80.0607640.42530.336222
9-0.058451-0.40920.342104
100.0720470.50430.308146
11-0.136121-0.95280.172672
12-0.225324-1.57730.060584
13-0.039691-0.27780.391153
14-0.188667-1.32070.096374
15-0.222335-1.55630.063031
16-0.184829-1.29380.1009
17-0.140906-0.98630.164405
18-0.143165-1.00220.160597
19-0.067753-0.47430.318708
20-0.097055-0.67940.250046
21-0.068969-0.48280.315701
220.03260.22820.410221
230.0436430.30550.380639
24-0.086824-0.60780.273074
250.081580.57110.285284
260.1583051.10810.136606
27-0.012234-0.08560.46605
28-0.038134-0.26690.395319
290.0453390.31740.376153
30-0.012312-0.08620.465837
31-0.125539-0.87880.191906
32-0.018103-0.12670.449841
33-0.019541-0.13680.44588
34-0.099164-0.69410.245433
35-0.081835-0.57280.284685
36-0.071669-0.50170.309068

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.388258 & 2.7178 & 0.00453 \tabularnewline
2 & 0.260445 & 1.8231 & 0.037195 \tabularnewline
3 & 0.467458 & 3.2722 & 0.00098 \tabularnewline
4 & 0.335715 & 2.35 & 0.011423 \tabularnewline
5 & 0.191025 & 1.3372 & 0.09367 \tabularnewline
6 & 0.170969 & 1.1968 & 0.118575 \tabularnewline
7 & 0.214939 & 1.5046 & 0.069426 \tabularnewline
8 & 0.060764 & 0.4253 & 0.336222 \tabularnewline
9 & -0.058451 & -0.4092 & 0.342104 \tabularnewline
10 & 0.072047 & 0.5043 & 0.308146 \tabularnewline
11 & -0.136121 & -0.9528 & 0.172672 \tabularnewline
12 & -0.225324 & -1.5773 & 0.060584 \tabularnewline
13 & -0.039691 & -0.2778 & 0.391153 \tabularnewline
14 & -0.188667 & -1.3207 & 0.096374 \tabularnewline
15 & -0.222335 & -1.5563 & 0.063031 \tabularnewline
16 & -0.184829 & -1.2938 & 0.1009 \tabularnewline
17 & -0.140906 & -0.9863 & 0.164405 \tabularnewline
18 & -0.143165 & -1.0022 & 0.160597 \tabularnewline
19 & -0.067753 & -0.4743 & 0.318708 \tabularnewline
20 & -0.097055 & -0.6794 & 0.250046 \tabularnewline
21 & -0.068969 & -0.4828 & 0.315701 \tabularnewline
22 & 0.0326 & 0.2282 & 0.410221 \tabularnewline
23 & 0.043643 & 0.3055 & 0.380639 \tabularnewline
24 & -0.086824 & -0.6078 & 0.273074 \tabularnewline
25 & 0.08158 & 0.5711 & 0.285284 \tabularnewline
26 & 0.158305 & 1.1081 & 0.136606 \tabularnewline
27 & -0.012234 & -0.0856 & 0.46605 \tabularnewline
28 & -0.038134 & -0.2669 & 0.395319 \tabularnewline
29 & 0.045339 & 0.3174 & 0.376153 \tabularnewline
30 & -0.012312 & -0.0862 & 0.465837 \tabularnewline
31 & -0.125539 & -0.8788 & 0.191906 \tabularnewline
32 & -0.018103 & -0.1267 & 0.449841 \tabularnewline
33 & -0.019541 & -0.1368 & 0.44588 \tabularnewline
34 & -0.099164 & -0.6941 & 0.245433 \tabularnewline
35 & -0.081835 & -0.5728 & 0.284685 \tabularnewline
36 & -0.071669 & -0.5017 & 0.309068 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60784&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]0.388258[/C][C]2.7178[/C][C]0.00453[/C][/ROW]
[ROW][C]2[/C][C]0.260445[/C][C]1.8231[/C][C]0.037195[/C][/ROW]
[ROW][C]3[/C][C]0.467458[/C][C]3.2722[/C][C]0.00098[/C][/ROW]
[ROW][C]4[/C][C]0.335715[/C][C]2.35[/C][C]0.011423[/C][/ROW]
[ROW][C]5[/C][C]0.191025[/C][C]1.3372[/C][C]0.09367[/C][/ROW]
[ROW][C]6[/C][C]0.170969[/C][C]1.1968[/C][C]0.118575[/C][/ROW]
[ROW][C]7[/C][C]0.214939[/C][C]1.5046[/C][C]0.069426[/C][/ROW]
[ROW][C]8[/C][C]0.060764[/C][C]0.4253[/C][C]0.336222[/C][/ROW]
[ROW][C]9[/C][C]-0.058451[/C][C]-0.4092[/C][C]0.342104[/C][/ROW]
[ROW][C]10[/C][C]0.072047[/C][C]0.5043[/C][C]0.308146[/C][/ROW]
[ROW][C]11[/C][C]-0.136121[/C][C]-0.9528[/C][C]0.172672[/C][/ROW]
[ROW][C]12[/C][C]-0.225324[/C][C]-1.5773[/C][C]0.060584[/C][/ROW]
[ROW][C]13[/C][C]-0.039691[/C][C]-0.2778[/C][C]0.391153[/C][/ROW]
[ROW][C]14[/C][C]-0.188667[/C][C]-1.3207[/C][C]0.096374[/C][/ROW]
[ROW][C]15[/C][C]-0.222335[/C][C]-1.5563[/C][C]0.063031[/C][/ROW]
[ROW][C]16[/C][C]-0.184829[/C][C]-1.2938[/C][C]0.1009[/C][/ROW]
[ROW][C]17[/C][C]-0.140906[/C][C]-0.9863[/C][C]0.164405[/C][/ROW]
[ROW][C]18[/C][C]-0.143165[/C][C]-1.0022[/C][C]0.160597[/C][/ROW]
[ROW][C]19[/C][C]-0.067753[/C][C]-0.4743[/C][C]0.318708[/C][/ROW]
[ROW][C]20[/C][C]-0.097055[/C][C]-0.6794[/C][C]0.250046[/C][/ROW]
[ROW][C]21[/C][C]-0.068969[/C][C]-0.4828[/C][C]0.315701[/C][/ROW]
[ROW][C]22[/C][C]0.0326[/C][C]0.2282[/C][C]0.410221[/C][/ROW]
[ROW][C]23[/C][C]0.043643[/C][C]0.3055[/C][C]0.380639[/C][/ROW]
[ROW][C]24[/C][C]-0.086824[/C][C]-0.6078[/C][C]0.273074[/C][/ROW]
[ROW][C]25[/C][C]0.08158[/C][C]0.5711[/C][C]0.285284[/C][/ROW]
[ROW][C]26[/C][C]0.158305[/C][C]1.1081[/C][C]0.136606[/C][/ROW]
[ROW][C]27[/C][C]-0.012234[/C][C]-0.0856[/C][C]0.46605[/C][/ROW]
[ROW][C]28[/C][C]-0.038134[/C][C]-0.2669[/C][C]0.395319[/C][/ROW]
[ROW][C]29[/C][C]0.045339[/C][C]0.3174[/C][C]0.376153[/C][/ROW]
[ROW][C]30[/C][C]-0.012312[/C][C]-0.0862[/C][C]0.465837[/C][/ROW]
[ROW][C]31[/C][C]-0.125539[/C][C]-0.8788[/C][C]0.191906[/C][/ROW]
[ROW][C]32[/C][C]-0.018103[/C][C]-0.1267[/C][C]0.449841[/C][/ROW]
[ROW][C]33[/C][C]-0.019541[/C][C]-0.1368[/C][C]0.44588[/C][/ROW]
[ROW][C]34[/C][C]-0.099164[/C][C]-0.6941[/C][C]0.245433[/C][/ROW]
[ROW][C]35[/C][C]-0.081835[/C][C]-0.5728[/C][C]0.284685[/C][/ROW]
[ROW][C]36[/C][C]-0.071669[/C][C]-0.5017[/C][C]0.309068[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60784&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60784&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
10.3882582.71780.00453
20.2604451.82310.037195
30.4674583.27220.00098
40.3357152.350.011423
50.1910251.33720.09367
60.1709691.19680.118575
70.2149391.50460.069426
80.0607640.42530.336222
9-0.058451-0.40920.342104
100.0720470.50430.308146
11-0.136121-0.95280.172672
12-0.225324-1.57730.060584
13-0.039691-0.27780.391153
14-0.188667-1.32070.096374
15-0.222335-1.55630.063031
16-0.184829-1.29380.1009
17-0.140906-0.98630.164405
18-0.143165-1.00220.160597
19-0.067753-0.47430.318708
20-0.097055-0.67940.250046
21-0.068969-0.48280.315701
220.03260.22820.410221
230.0436430.30550.380639
24-0.086824-0.60780.273074
250.081580.57110.285284
260.1583051.10810.136606
27-0.012234-0.08560.46605
28-0.038134-0.26690.395319
290.0453390.31740.376153
30-0.012312-0.08620.465837
31-0.125539-0.87880.191906
32-0.018103-0.12670.449841
33-0.019541-0.13680.44588
34-0.099164-0.69410.245433
35-0.081835-0.57280.284685
36-0.071669-0.50170.309068






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3882582.71780.00453
20.1291720.90420.185156
30.3942682.75990.004055
40.0701430.4910.312809
5-0.02704-0.18930.425328
6-0.093416-0.65390.258114
70.0451910.31630.376545
8-0.121255-0.84880.200063
9-0.141842-0.99290.16282
100.0524750.36730.357479
11-0.228803-1.60160.057834
12-0.092452-0.64720.260273
130.0993080.69520.245122
14-0.102956-0.72070.237261
150.0428810.30020.382661
16-0.051543-0.36080.359901
170.0343890.24070.405387
180.0490780.34350.366328
190.1964491.37510.087671
20-0.14053-0.98370.165045
210.0649530.45470.325676
220.0915520.64090.262299
23-0.048618-0.34030.367533
24-0.145236-1.01670.157156
250.1260570.88240.190935
26-0.015442-0.10810.45718
27-0.09762-0.68330.248806
28-0.12051-0.84360.201504
29-0.105249-0.73670.232396
30-0.047581-0.33310.370251
31-0.038669-0.27070.393885
32-0.015251-0.10680.45771
330.0526130.36830.357121
340.1283270.89830.186712
35-0.025584-0.17910.429302
36-0.069393-0.48580.314654

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.388258 & 2.7178 & 0.00453 \tabularnewline
2 & 0.129172 & 0.9042 & 0.185156 \tabularnewline
3 & 0.394268 & 2.7599 & 0.004055 \tabularnewline
4 & 0.070143 & 0.491 & 0.312809 \tabularnewline
5 & -0.02704 & -0.1893 & 0.425328 \tabularnewline
6 & -0.093416 & -0.6539 & 0.258114 \tabularnewline
7 & 0.045191 & 0.3163 & 0.376545 \tabularnewline
8 & -0.121255 & -0.8488 & 0.200063 \tabularnewline
9 & -0.141842 & -0.9929 & 0.16282 \tabularnewline
10 & 0.052475 & 0.3673 & 0.357479 \tabularnewline
11 & -0.228803 & -1.6016 & 0.057834 \tabularnewline
12 & -0.092452 & -0.6472 & 0.260273 \tabularnewline
13 & 0.099308 & 0.6952 & 0.245122 \tabularnewline
14 & -0.102956 & -0.7207 & 0.237261 \tabularnewline
15 & 0.042881 & 0.3002 & 0.382661 \tabularnewline
16 & -0.051543 & -0.3608 & 0.359901 \tabularnewline
17 & 0.034389 & 0.2407 & 0.405387 \tabularnewline
18 & 0.049078 & 0.3435 & 0.366328 \tabularnewline
19 & 0.196449 & 1.3751 & 0.087671 \tabularnewline
20 & -0.14053 & -0.9837 & 0.165045 \tabularnewline
21 & 0.064953 & 0.4547 & 0.325676 \tabularnewline
22 & 0.091552 & 0.6409 & 0.262299 \tabularnewline
23 & -0.048618 & -0.3403 & 0.367533 \tabularnewline
24 & -0.145236 & -1.0167 & 0.157156 \tabularnewline
25 & 0.126057 & 0.8824 & 0.190935 \tabularnewline
26 & -0.015442 & -0.1081 & 0.45718 \tabularnewline
27 & -0.09762 & -0.6833 & 0.248806 \tabularnewline
28 & -0.12051 & -0.8436 & 0.201504 \tabularnewline
29 & -0.105249 & -0.7367 & 0.232396 \tabularnewline
30 & -0.047581 & -0.3331 & 0.370251 \tabularnewline
31 & -0.038669 & -0.2707 & 0.393885 \tabularnewline
32 & -0.015251 & -0.1068 & 0.45771 \tabularnewline
33 & 0.052613 & 0.3683 & 0.357121 \tabularnewline
34 & 0.128327 & 0.8983 & 0.186712 \tabularnewline
35 & -0.025584 & -0.1791 & 0.429302 \tabularnewline
36 & -0.069393 & -0.4858 & 0.314654 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60784&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]0.388258[/C][C]2.7178[/C][C]0.00453[/C][/ROW]
[ROW][C]2[/C][C]0.129172[/C][C]0.9042[/C][C]0.185156[/C][/ROW]
[ROW][C]3[/C][C]0.394268[/C][C]2.7599[/C][C]0.004055[/C][/ROW]
[ROW][C]4[/C][C]0.070143[/C][C]0.491[/C][C]0.312809[/C][/ROW]
[ROW][C]5[/C][C]-0.02704[/C][C]-0.1893[/C][C]0.425328[/C][/ROW]
[ROW][C]6[/C][C]-0.093416[/C][C]-0.6539[/C][C]0.258114[/C][/ROW]
[ROW][C]7[/C][C]0.045191[/C][C]0.3163[/C][C]0.376545[/C][/ROW]
[ROW][C]8[/C][C]-0.121255[/C][C]-0.8488[/C][C]0.200063[/C][/ROW]
[ROW][C]9[/C][C]-0.141842[/C][C]-0.9929[/C][C]0.16282[/C][/ROW]
[ROW][C]10[/C][C]0.052475[/C][C]0.3673[/C][C]0.357479[/C][/ROW]
[ROW][C]11[/C][C]-0.228803[/C][C]-1.6016[/C][C]0.057834[/C][/ROW]
[ROW][C]12[/C][C]-0.092452[/C][C]-0.6472[/C][C]0.260273[/C][/ROW]
[ROW][C]13[/C][C]0.099308[/C][C]0.6952[/C][C]0.245122[/C][/ROW]
[ROW][C]14[/C][C]-0.102956[/C][C]-0.7207[/C][C]0.237261[/C][/ROW]
[ROW][C]15[/C][C]0.042881[/C][C]0.3002[/C][C]0.382661[/C][/ROW]
[ROW][C]16[/C][C]-0.051543[/C][C]-0.3608[/C][C]0.359901[/C][/ROW]
[ROW][C]17[/C][C]0.034389[/C][C]0.2407[/C][C]0.405387[/C][/ROW]
[ROW][C]18[/C][C]0.049078[/C][C]0.3435[/C][C]0.366328[/C][/ROW]
[ROW][C]19[/C][C]0.196449[/C][C]1.3751[/C][C]0.087671[/C][/ROW]
[ROW][C]20[/C][C]-0.14053[/C][C]-0.9837[/C][C]0.165045[/C][/ROW]
[ROW][C]21[/C][C]0.064953[/C][C]0.4547[/C][C]0.325676[/C][/ROW]
[ROW][C]22[/C][C]0.091552[/C][C]0.6409[/C][C]0.262299[/C][/ROW]
[ROW][C]23[/C][C]-0.048618[/C][C]-0.3403[/C][C]0.367533[/C][/ROW]
[ROW][C]24[/C][C]-0.145236[/C][C]-1.0167[/C][C]0.157156[/C][/ROW]
[ROW][C]25[/C][C]0.126057[/C][C]0.8824[/C][C]0.190935[/C][/ROW]
[ROW][C]26[/C][C]-0.015442[/C][C]-0.1081[/C][C]0.45718[/C][/ROW]
[ROW][C]27[/C][C]-0.09762[/C][C]-0.6833[/C][C]0.248806[/C][/ROW]
[ROW][C]28[/C][C]-0.12051[/C][C]-0.8436[/C][C]0.201504[/C][/ROW]
[ROW][C]29[/C][C]-0.105249[/C][C]-0.7367[/C][C]0.232396[/C][/ROW]
[ROW][C]30[/C][C]-0.047581[/C][C]-0.3331[/C][C]0.370251[/C][/ROW]
[ROW][C]31[/C][C]-0.038669[/C][C]-0.2707[/C][C]0.393885[/C][/ROW]
[ROW][C]32[/C][C]-0.015251[/C][C]-0.1068[/C][C]0.45771[/C][/ROW]
[ROW][C]33[/C][C]0.052613[/C][C]0.3683[/C][C]0.357121[/C][/ROW]
[ROW][C]34[/C][C]0.128327[/C][C]0.8983[/C][C]0.186712[/C][/ROW]
[ROW][C]35[/C][C]-0.025584[/C][C]-0.1791[/C][C]0.429302[/C][/ROW]
[ROW][C]36[/C][C]-0.069393[/C][C]-0.4858[/C][C]0.314654[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60784&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60784&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
10.3882582.71780.00453
20.1291720.90420.185156
30.3942682.75990.004055
40.0701430.4910.312809
5-0.02704-0.18930.425328
6-0.093416-0.65390.258114
70.0451910.31630.376545
8-0.121255-0.84880.200063
9-0.141842-0.99290.16282
100.0524750.36730.357479
11-0.228803-1.60160.057834
12-0.092452-0.64720.260273
130.0993080.69520.245122
14-0.102956-0.72070.237261
150.0428810.30020.382661
16-0.051543-0.36080.359901
170.0343890.24070.405387
180.0490780.34350.366328
190.1964491.37510.087671
20-0.14053-0.98370.165045
210.0649530.45470.325676
220.0915520.64090.262299
23-0.048618-0.34030.367533
24-0.145236-1.01670.157156
250.1260570.88240.190935
26-0.015442-0.10810.45718
27-0.09762-0.68330.248806
28-0.12051-0.84360.201504
29-0.105249-0.73670.232396
30-0.047581-0.33310.370251
31-0.038669-0.27070.393885
32-0.015251-0.10680.45771
330.0526130.36830.357121
340.1283270.89830.186712
35-0.025584-0.17910.429302
36-0.069393-0.48580.314654


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')