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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 computationMon, 28 Dec 2009 12:06:40 -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/28/t12620272599n3ekjwkj8t6a29.htm/, Retrieved Sun, 05 May 2024 16:36:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=71036, Retrieved Sun, 05 May 2024 16:36:49 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact97
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] [tijdreeks d] [2009-12-28 19:06:40] [f47dffd5f5a8c03c3681db4cc9472742] [Current]
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Dataseries X:
286.445
288.576
293.299
295.881
292.710
271.993
267.430
273.963
273.046
268.347
264.319
255.765
246.263
245.098
246.969
248.333
247.934
226.839
225.554
237.085
237.080
245.039
248.541
247.105
243.422
250.643
254.663
260.993
258.556
235.372
246.057
253.353
255.198
264.176
269.034
265.861
269.826
278.506
292.300
290.726
289.802
271.311
274.352
275.216
276.836
280.408
280.190
282.656
281.477
288.186
292.300
291.186
287.259
264.993
267.140
270.150
275.037
277.103
277.128




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=71036&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=71036&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71036&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.1153690.78250.218974
20.305872.07450.021827
30.3192562.16530.017793
40.2251881.52730.066767
50.0593260.40240.344637
60.1498571.01640.157383
70.0148140.10050.460201
80.0792870.53770.296671
90.0242210.16430.435117
10-0.149944-1.0170.157244
110.2746561.86280.034441
12-0.213181-1.44590.077498
13-0.023015-0.15610.43832
140.0367230.24910.402208
150.0666760.45220.326619
16-0.132333-0.89750.187057
170.0525980.35670.36146
18-0.146528-0.99380.162759
19-0.046108-0.31270.377953
20-0.152994-1.03770.152427
21-0.212196-1.43920.078435
22-0.084154-0.57080.28547
23-0.232102-1.57420.061148
24-0.182847-1.24010.110608
25-0.147122-0.99780.161792
26-0.043028-0.29180.385864
27-0.235962-1.60040.058181
28-0.101351-0.68740.247643
29-0.100413-0.6810.249632
30-0.049904-0.33850.368275
31-0.051391-0.34860.364508
32-0.051366-0.34840.36457
33-0.002749-0.01860.492602
34-0.021837-0.14810.441453
350.0424470.28790.387361
360.0155960.10580.45811

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.115369 & 0.7825 & 0.218974 \tabularnewline
2 & 0.30587 & 2.0745 & 0.021827 \tabularnewline
3 & 0.319256 & 2.1653 & 0.017793 \tabularnewline
4 & 0.225188 & 1.5273 & 0.066767 \tabularnewline
5 & 0.059326 & 0.4024 & 0.344637 \tabularnewline
6 & 0.149857 & 1.0164 & 0.157383 \tabularnewline
7 & 0.014814 & 0.1005 & 0.460201 \tabularnewline
8 & 0.079287 & 0.5377 & 0.296671 \tabularnewline
9 & 0.024221 & 0.1643 & 0.435117 \tabularnewline
10 & -0.149944 & -1.017 & 0.157244 \tabularnewline
11 & 0.274656 & 1.8628 & 0.034441 \tabularnewline
12 & -0.213181 & -1.4459 & 0.077498 \tabularnewline
13 & -0.023015 & -0.1561 & 0.43832 \tabularnewline
14 & 0.036723 & 0.2491 & 0.402208 \tabularnewline
15 & 0.066676 & 0.4522 & 0.326619 \tabularnewline
16 & -0.132333 & -0.8975 & 0.187057 \tabularnewline
17 & 0.052598 & 0.3567 & 0.36146 \tabularnewline
18 & -0.146528 & -0.9938 & 0.162759 \tabularnewline
19 & -0.046108 & -0.3127 & 0.377953 \tabularnewline
20 & -0.152994 & -1.0377 & 0.152427 \tabularnewline
21 & -0.212196 & -1.4392 & 0.078435 \tabularnewline
22 & -0.084154 & -0.5708 & 0.28547 \tabularnewline
23 & -0.232102 & -1.5742 & 0.061148 \tabularnewline
24 & -0.182847 & -1.2401 & 0.110608 \tabularnewline
25 & -0.147122 & -0.9978 & 0.161792 \tabularnewline
26 & -0.043028 & -0.2918 & 0.385864 \tabularnewline
27 & -0.235962 & -1.6004 & 0.058181 \tabularnewline
28 & -0.101351 & -0.6874 & 0.247643 \tabularnewline
29 & -0.100413 & -0.681 & 0.249632 \tabularnewline
30 & -0.049904 & -0.3385 & 0.368275 \tabularnewline
31 & -0.051391 & -0.3486 & 0.364508 \tabularnewline
32 & -0.051366 & -0.3484 & 0.36457 \tabularnewline
33 & -0.002749 & -0.0186 & 0.492602 \tabularnewline
34 & -0.021837 & -0.1481 & 0.441453 \tabularnewline
35 & 0.042447 & 0.2879 & 0.387361 \tabularnewline
36 & 0.015596 & 0.1058 & 0.45811 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71036&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]0.115369[/C][C]0.7825[/C][C]0.218974[/C][/ROW]
[ROW][C]2[/C][C]0.30587[/C][C]2.0745[/C][C]0.021827[/C][/ROW]
[ROW][C]3[/C][C]0.319256[/C][C]2.1653[/C][C]0.017793[/C][/ROW]
[ROW][C]4[/C][C]0.225188[/C][C]1.5273[/C][C]0.066767[/C][/ROW]
[ROW][C]5[/C][C]0.059326[/C][C]0.4024[/C][C]0.344637[/C][/ROW]
[ROW][C]6[/C][C]0.149857[/C][C]1.0164[/C][C]0.157383[/C][/ROW]
[ROW][C]7[/C][C]0.014814[/C][C]0.1005[/C][C]0.460201[/C][/ROW]
[ROW][C]8[/C][C]0.079287[/C][C]0.5377[/C][C]0.296671[/C][/ROW]
[ROW][C]9[/C][C]0.024221[/C][C]0.1643[/C][C]0.435117[/C][/ROW]
[ROW][C]10[/C][C]-0.149944[/C][C]-1.017[/C][C]0.157244[/C][/ROW]
[ROW][C]11[/C][C]0.274656[/C][C]1.8628[/C][C]0.034441[/C][/ROW]
[ROW][C]12[/C][C]-0.213181[/C][C]-1.4459[/C][C]0.077498[/C][/ROW]
[ROW][C]13[/C][C]-0.023015[/C][C]-0.1561[/C][C]0.43832[/C][/ROW]
[ROW][C]14[/C][C]0.036723[/C][C]0.2491[/C][C]0.402208[/C][/ROW]
[ROW][C]15[/C][C]0.066676[/C][C]0.4522[/C][C]0.326619[/C][/ROW]
[ROW][C]16[/C][C]-0.132333[/C][C]-0.8975[/C][C]0.187057[/C][/ROW]
[ROW][C]17[/C][C]0.052598[/C][C]0.3567[/C][C]0.36146[/C][/ROW]
[ROW][C]18[/C][C]-0.146528[/C][C]-0.9938[/C][C]0.162759[/C][/ROW]
[ROW][C]19[/C][C]-0.046108[/C][C]-0.3127[/C][C]0.377953[/C][/ROW]
[ROW][C]20[/C][C]-0.152994[/C][C]-1.0377[/C][C]0.152427[/C][/ROW]
[ROW][C]21[/C][C]-0.212196[/C][C]-1.4392[/C][C]0.078435[/C][/ROW]
[ROW][C]22[/C][C]-0.084154[/C][C]-0.5708[/C][C]0.28547[/C][/ROW]
[ROW][C]23[/C][C]-0.232102[/C][C]-1.5742[/C][C]0.061148[/C][/ROW]
[ROW][C]24[/C][C]-0.182847[/C][C]-1.2401[/C][C]0.110608[/C][/ROW]
[ROW][C]25[/C][C]-0.147122[/C][C]-0.9978[/C][C]0.161792[/C][/ROW]
[ROW][C]26[/C][C]-0.043028[/C][C]-0.2918[/C][C]0.385864[/C][/ROW]
[ROW][C]27[/C][C]-0.235962[/C][C]-1.6004[/C][C]0.058181[/C][/ROW]
[ROW][C]28[/C][C]-0.101351[/C][C]-0.6874[/C][C]0.247643[/C][/ROW]
[ROW][C]29[/C][C]-0.100413[/C][C]-0.681[/C][C]0.249632[/C][/ROW]
[ROW][C]30[/C][C]-0.049904[/C][C]-0.3385[/C][C]0.368275[/C][/ROW]
[ROW][C]31[/C][C]-0.051391[/C][C]-0.3486[/C][C]0.364508[/C][/ROW]
[ROW][C]32[/C][C]-0.051366[/C][C]-0.3484[/C][C]0.36457[/C][/ROW]
[ROW][C]33[/C][C]-0.002749[/C][C]-0.0186[/C][C]0.492602[/C][/ROW]
[ROW][C]34[/C][C]-0.021837[/C][C]-0.1481[/C][C]0.441453[/C][/ROW]
[ROW][C]35[/C][C]0.042447[/C][C]0.2879[/C][C]0.387361[/C][/ROW]
[ROW][C]36[/C][C]0.015596[/C][C]0.1058[/C][C]0.45811[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71036&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71036&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
10.1153690.78250.218974
20.305872.07450.021827
30.3192562.16530.017793
40.2251881.52730.066767
50.0593260.40240.344637
60.1498571.01640.157383
70.0148140.10050.460201
80.0792870.53770.296671
90.0242210.16430.435117
10-0.149944-1.0170.157244
110.2746561.86280.034441
12-0.213181-1.44590.077498
13-0.023015-0.15610.43832
140.0367230.24910.402208
150.0666760.45220.326619
16-0.132333-0.89750.187057
170.0525980.35670.36146
18-0.146528-0.99380.162759
19-0.046108-0.31270.377953
20-0.152994-1.03770.152427
21-0.212196-1.43920.078435
22-0.084154-0.57080.28547
23-0.232102-1.57420.061148
24-0.182847-1.24010.110608
25-0.147122-0.99780.161792
26-0.043028-0.29180.385864
27-0.235962-1.60040.058181
28-0.101351-0.68740.247643
29-0.100413-0.6810.249632
30-0.049904-0.33850.368275
31-0.051391-0.34860.364508
32-0.051366-0.34840.36457
33-0.002749-0.01860.492602
34-0.021837-0.14810.441453
350.0424470.28790.387361
360.0155960.10580.45811







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1153690.78250.218974
20.2965072.0110.025103
30.2891551.96110.027966
40.1331080.90280.185672
5-0.136441-0.92540.179797
6-0.04637-0.31450.377283
7-0.088747-0.60190.275094
80.0528120.35820.360922
90.0382670.25950.398189
10-0.211281-1.4330.079313
110.3289252.23090.015303
12-0.232267-1.57530.061019
13-0.045179-0.30640.380333
140.0461730.31320.377787
150.1220120.82750.206106
16-0.022268-0.1510.440308
17-0.110798-0.75150.228098
18-0.154298-1.04650.150399
19-0.06864-0.46550.32187
20-0.090079-0.61090.272121
21-0.030843-0.20920.417614
22-0.116085-0.78730.217565
230.0252080.1710.432499
24-0.025073-0.17010.432857
25-0.05278-0.3580.361001
260.0812140.55080.292211
27-0.038648-0.26210.397199
28-0.145148-0.98440.165024
290.0408110.27680.391589
30-0.035809-0.24290.404593
310.137510.93260.177938
32-0.046439-0.3150.377106
33-0.013095-0.08880.464807
34-0.033693-0.22850.410129
350.1056970.71690.238538
360.086810.58880.279446

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.115369 & 0.7825 & 0.218974 \tabularnewline
2 & 0.296507 & 2.011 & 0.025103 \tabularnewline
3 & 0.289155 & 1.9611 & 0.027966 \tabularnewline
4 & 0.133108 & 0.9028 & 0.185672 \tabularnewline
5 & -0.136441 & -0.9254 & 0.179797 \tabularnewline
6 & -0.04637 & -0.3145 & 0.377283 \tabularnewline
7 & -0.088747 & -0.6019 & 0.275094 \tabularnewline
8 & 0.052812 & 0.3582 & 0.360922 \tabularnewline
9 & 0.038267 & 0.2595 & 0.398189 \tabularnewline
10 & -0.211281 & -1.433 & 0.079313 \tabularnewline
11 & 0.328925 & 2.2309 & 0.015303 \tabularnewline
12 & -0.232267 & -1.5753 & 0.061019 \tabularnewline
13 & -0.045179 & -0.3064 & 0.380333 \tabularnewline
14 & 0.046173 & 0.3132 & 0.377787 \tabularnewline
15 & 0.122012 & 0.8275 & 0.206106 \tabularnewline
16 & -0.022268 & -0.151 & 0.440308 \tabularnewline
17 & -0.110798 & -0.7515 & 0.228098 \tabularnewline
18 & -0.154298 & -1.0465 & 0.150399 \tabularnewline
19 & -0.06864 & -0.4655 & 0.32187 \tabularnewline
20 & -0.090079 & -0.6109 & 0.272121 \tabularnewline
21 & -0.030843 & -0.2092 & 0.417614 \tabularnewline
22 & -0.116085 & -0.7873 & 0.217565 \tabularnewline
23 & 0.025208 & 0.171 & 0.432499 \tabularnewline
24 & -0.025073 & -0.1701 & 0.432857 \tabularnewline
25 & -0.05278 & -0.358 & 0.361001 \tabularnewline
26 & 0.081214 & 0.5508 & 0.292211 \tabularnewline
27 & -0.038648 & -0.2621 & 0.397199 \tabularnewline
28 & -0.145148 & -0.9844 & 0.165024 \tabularnewline
29 & 0.040811 & 0.2768 & 0.391589 \tabularnewline
30 & -0.035809 & -0.2429 & 0.404593 \tabularnewline
31 & 0.13751 & 0.9326 & 0.177938 \tabularnewline
32 & -0.046439 & -0.315 & 0.377106 \tabularnewline
33 & -0.013095 & -0.0888 & 0.464807 \tabularnewline
34 & -0.033693 & -0.2285 & 0.410129 \tabularnewline
35 & 0.105697 & 0.7169 & 0.238538 \tabularnewline
36 & 0.08681 & 0.5888 & 0.279446 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71036&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]0.115369[/C][C]0.7825[/C][C]0.218974[/C][/ROW]
[ROW][C]2[/C][C]0.296507[/C][C]2.011[/C][C]0.025103[/C][/ROW]
[ROW][C]3[/C][C]0.289155[/C][C]1.9611[/C][C]0.027966[/C][/ROW]
[ROW][C]4[/C][C]0.133108[/C][C]0.9028[/C][C]0.185672[/C][/ROW]
[ROW][C]5[/C][C]-0.136441[/C][C]-0.9254[/C][C]0.179797[/C][/ROW]
[ROW][C]6[/C][C]-0.04637[/C][C]-0.3145[/C][C]0.377283[/C][/ROW]
[ROW][C]7[/C][C]-0.088747[/C][C]-0.6019[/C][C]0.275094[/C][/ROW]
[ROW][C]8[/C][C]0.052812[/C][C]0.3582[/C][C]0.360922[/C][/ROW]
[ROW][C]9[/C][C]0.038267[/C][C]0.2595[/C][C]0.398189[/C][/ROW]
[ROW][C]10[/C][C]-0.211281[/C][C]-1.433[/C][C]0.079313[/C][/ROW]
[ROW][C]11[/C][C]0.328925[/C][C]2.2309[/C][C]0.015303[/C][/ROW]
[ROW][C]12[/C][C]-0.232267[/C][C]-1.5753[/C][C]0.061019[/C][/ROW]
[ROW][C]13[/C][C]-0.045179[/C][C]-0.3064[/C][C]0.380333[/C][/ROW]
[ROW][C]14[/C][C]0.046173[/C][C]0.3132[/C][C]0.377787[/C][/ROW]
[ROW][C]15[/C][C]0.122012[/C][C]0.8275[/C][C]0.206106[/C][/ROW]
[ROW][C]16[/C][C]-0.022268[/C][C]-0.151[/C][C]0.440308[/C][/ROW]
[ROW][C]17[/C][C]-0.110798[/C][C]-0.7515[/C][C]0.228098[/C][/ROW]
[ROW][C]18[/C][C]-0.154298[/C][C]-1.0465[/C][C]0.150399[/C][/ROW]
[ROW][C]19[/C][C]-0.06864[/C][C]-0.4655[/C][C]0.32187[/C][/ROW]
[ROW][C]20[/C][C]-0.090079[/C][C]-0.6109[/C][C]0.272121[/C][/ROW]
[ROW][C]21[/C][C]-0.030843[/C][C]-0.2092[/C][C]0.417614[/C][/ROW]
[ROW][C]22[/C][C]-0.116085[/C][C]-0.7873[/C][C]0.217565[/C][/ROW]
[ROW][C]23[/C][C]0.025208[/C][C]0.171[/C][C]0.432499[/C][/ROW]
[ROW][C]24[/C][C]-0.025073[/C][C]-0.1701[/C][C]0.432857[/C][/ROW]
[ROW][C]25[/C][C]-0.05278[/C][C]-0.358[/C][C]0.361001[/C][/ROW]
[ROW][C]26[/C][C]0.081214[/C][C]0.5508[/C][C]0.292211[/C][/ROW]
[ROW][C]27[/C][C]-0.038648[/C][C]-0.2621[/C][C]0.397199[/C][/ROW]
[ROW][C]28[/C][C]-0.145148[/C][C]-0.9844[/C][C]0.165024[/C][/ROW]
[ROW][C]29[/C][C]0.040811[/C][C]0.2768[/C][C]0.391589[/C][/ROW]
[ROW][C]30[/C][C]-0.035809[/C][C]-0.2429[/C][C]0.404593[/C][/ROW]
[ROW][C]31[/C][C]0.13751[/C][C]0.9326[/C][C]0.177938[/C][/ROW]
[ROW][C]32[/C][C]-0.046439[/C][C]-0.315[/C][C]0.377106[/C][/ROW]
[ROW][C]33[/C][C]-0.013095[/C][C]-0.0888[/C][C]0.464807[/C][/ROW]
[ROW][C]34[/C][C]-0.033693[/C][C]-0.2285[/C][C]0.410129[/C][/ROW]
[ROW][C]35[/C][C]0.105697[/C][C]0.7169[/C][C]0.238538[/C][/ROW]
[ROW][C]36[/C][C]0.08681[/C][C]0.5888[/C][C]0.279446[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71036&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71036&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
10.1153690.78250.218974
20.2965072.0110.025103
30.2891551.96110.027966
40.1331080.90280.185672
5-0.136441-0.92540.179797
6-0.04637-0.31450.377283
7-0.088747-0.60190.275094
80.0528120.35820.360922
90.0382670.25950.398189
10-0.211281-1.4330.079313
110.3289252.23090.015303
12-0.232267-1.57530.061019
13-0.045179-0.30640.380333
140.0461730.31320.377787
150.1220120.82750.206106
16-0.022268-0.1510.440308
17-0.110798-0.75150.228098
18-0.154298-1.04650.150399
19-0.06864-0.46550.32187
20-0.090079-0.61090.272121
21-0.030843-0.20920.417614
22-0.116085-0.78730.217565
230.0252080.1710.432499
24-0.025073-0.17010.432857
25-0.05278-0.3580.361001
260.0812140.55080.292211
27-0.038648-0.26210.397199
28-0.145148-0.98440.165024
290.0408110.27680.391589
30-0.035809-0.24290.404593
310.137510.93260.177938
32-0.046439-0.3150.377106
33-0.013095-0.08880.464807
34-0.033693-0.22850.410129
350.1056970.71690.238538
360.086810.58880.279446



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 = 1 ; 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')