Free Statistics

of Irreproducible Research!

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, 30 Nov 2009 12:37:11 -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/30/t1259609875sbbyq2qjl5fxx2e.htm/, Retrieved Wed, 01 May 2024 16:34:30 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=61869, Retrieved Wed, 01 May 2024 16:34:30 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact145
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] [ACF D=d=o, lambda=1] [2009-11-30 11:39:52] [005293453b571dbccb80b45226e44173]
-   P           [(Partial) Autocorrelation Function] [ACF d=D=lambda=1] [2009-11-30 11:44:53] [005293453b571dbccb80b45226e44173]
-   P             [(Partial) Autocorrelation Function] [d=2 en D=1] [2009-11-30 19:33:11] [cd6314e7e707a6546bd4604c9d1f2b69]
-   P                 [(Partial) Autocorrelation Function] [d=1 en D=2] [2009-11-30 19:37:11] [ea241b681aafed79da4b5b99fad98471] [Current]
-   P                   [(Partial) Autocorrelation Function] [d=D=2] [2009-11-30 19:39:04] [cd6314e7e707a6546bd4604c9d1f2b69]
Feedback Forum

Post a new message
Dataseries X:
244.576
241.572
240.541
236.089
236.997
264.579
270.349
269.645
267.037
258.113
262.813
267.413
267.366
264.777
258.863
254.844
254.868
277.267
285.351
286.602
283.042
276.687
277.915
277.128
277.103
275.037
270.150
267.140
264.993
287.259
291.186
292.300
288.186
281.477
282.656
280.190
280.408
276.836
275.216
274.352
271.311
289.802
290.726
292.300
278.506
269.826
265.861
269.034
264.176
255.198
253.353
246.057
235.372
258.556
260.993
254.663
250.643
243.422
247.105
248.541
245.039
237.080
237.085
225.554
226.839
247.934
248.333
246.969
245.098
246.263
255.765
264.319
268.347
273.046
273.963
267.430
271.993
292.710
295.881




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=61869&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=61869&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61869&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
1-0.215415-1.5830.059634
20.1624751.19390.11886
30.1230430.90420.184959
40.0810740.59580.27691
5-0.092781-0.68180.249139
60.1282590.94250.175066
70.0225580.16580.434479
80.1118430.82190.20738
90.0014680.01080.495717
10-0.13587-0.99840.161261
110.3949012.90190.002679
12-0.447989-3.2920.000879
130.0754520.55450.290778
140.0227470.16720.433936
150.0551070.40490.343558
16-0.086666-0.63690.263452
170.127520.93710.176445
18-0.062647-0.46040.323552
190.0288890.21230.416339
20-0.134743-0.99020.163257
21-0.00814-0.05980.476261
220.0604510.44420.329328
23-0.257922-1.89530.031703
240.0489530.35970.360226
25-0.043998-0.32330.373851
26-0.077-0.56580.286926
27-0.064424-0.47340.318913
28-0.046338-0.34050.367396
29-0.05014-0.36850.356987
30-0.02325-0.17090.432489
31-0.068345-0.50220.308773
320.040690.2990.383039
33-0.038701-0.28440.388597
34-0.093379-0.68620.247764
350.0925980.68050.249562
36-0.0548-0.40270.34438

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.215415 & -1.583 & 0.059634 \tabularnewline
2 & 0.162475 & 1.1939 & 0.11886 \tabularnewline
3 & 0.123043 & 0.9042 & 0.184959 \tabularnewline
4 & 0.081074 & 0.5958 & 0.27691 \tabularnewline
5 & -0.092781 & -0.6818 & 0.249139 \tabularnewline
6 & 0.128259 & 0.9425 & 0.175066 \tabularnewline
7 & 0.022558 & 0.1658 & 0.434479 \tabularnewline
8 & 0.111843 & 0.8219 & 0.20738 \tabularnewline
9 & 0.001468 & 0.0108 & 0.495717 \tabularnewline
10 & -0.13587 & -0.9984 & 0.161261 \tabularnewline
11 & 0.394901 & 2.9019 & 0.002679 \tabularnewline
12 & -0.447989 & -3.292 & 0.000879 \tabularnewline
13 & 0.075452 & 0.5545 & 0.290778 \tabularnewline
14 & 0.022747 & 0.1672 & 0.433936 \tabularnewline
15 & 0.055107 & 0.4049 & 0.343558 \tabularnewline
16 & -0.086666 & -0.6369 & 0.263452 \tabularnewline
17 & 0.12752 & 0.9371 & 0.176445 \tabularnewline
18 & -0.062647 & -0.4604 & 0.323552 \tabularnewline
19 & 0.028889 & 0.2123 & 0.416339 \tabularnewline
20 & -0.134743 & -0.9902 & 0.163257 \tabularnewline
21 & -0.00814 & -0.0598 & 0.476261 \tabularnewline
22 & 0.060451 & 0.4442 & 0.329328 \tabularnewline
23 & -0.257922 & -1.8953 & 0.031703 \tabularnewline
24 & 0.048953 & 0.3597 & 0.360226 \tabularnewline
25 & -0.043998 & -0.3233 & 0.373851 \tabularnewline
26 & -0.077 & -0.5658 & 0.286926 \tabularnewline
27 & -0.064424 & -0.4734 & 0.318913 \tabularnewline
28 & -0.046338 & -0.3405 & 0.367396 \tabularnewline
29 & -0.05014 & -0.3685 & 0.356987 \tabularnewline
30 & -0.02325 & -0.1709 & 0.432489 \tabularnewline
31 & -0.068345 & -0.5022 & 0.308773 \tabularnewline
32 & 0.04069 & 0.299 & 0.383039 \tabularnewline
33 & -0.038701 & -0.2844 & 0.388597 \tabularnewline
34 & -0.093379 & -0.6862 & 0.247764 \tabularnewline
35 & 0.092598 & 0.6805 & 0.249562 \tabularnewline
36 & -0.0548 & -0.4027 & 0.34438 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61869&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]-0.215415[/C][C]-1.583[/C][C]0.059634[/C][/ROW]
[ROW][C]2[/C][C]0.162475[/C][C]1.1939[/C][C]0.11886[/C][/ROW]
[ROW][C]3[/C][C]0.123043[/C][C]0.9042[/C][C]0.184959[/C][/ROW]
[ROW][C]4[/C][C]0.081074[/C][C]0.5958[/C][C]0.27691[/C][/ROW]
[ROW][C]5[/C][C]-0.092781[/C][C]-0.6818[/C][C]0.249139[/C][/ROW]
[ROW][C]6[/C][C]0.128259[/C][C]0.9425[/C][C]0.175066[/C][/ROW]
[ROW][C]7[/C][C]0.022558[/C][C]0.1658[/C][C]0.434479[/C][/ROW]
[ROW][C]8[/C][C]0.111843[/C][C]0.8219[/C][C]0.20738[/C][/ROW]
[ROW][C]9[/C][C]0.001468[/C][C]0.0108[/C][C]0.495717[/C][/ROW]
[ROW][C]10[/C][C]-0.13587[/C][C]-0.9984[/C][C]0.161261[/C][/ROW]
[ROW][C]11[/C][C]0.394901[/C][C]2.9019[/C][C]0.002679[/C][/ROW]
[ROW][C]12[/C][C]-0.447989[/C][C]-3.292[/C][C]0.000879[/C][/ROW]
[ROW][C]13[/C][C]0.075452[/C][C]0.5545[/C][C]0.290778[/C][/ROW]
[ROW][C]14[/C][C]0.022747[/C][C]0.1672[/C][C]0.433936[/C][/ROW]
[ROW][C]15[/C][C]0.055107[/C][C]0.4049[/C][C]0.343558[/C][/ROW]
[ROW][C]16[/C][C]-0.086666[/C][C]-0.6369[/C][C]0.263452[/C][/ROW]
[ROW][C]17[/C][C]0.12752[/C][C]0.9371[/C][C]0.176445[/C][/ROW]
[ROW][C]18[/C][C]-0.062647[/C][C]-0.4604[/C][C]0.323552[/C][/ROW]
[ROW][C]19[/C][C]0.028889[/C][C]0.2123[/C][C]0.416339[/C][/ROW]
[ROW][C]20[/C][C]-0.134743[/C][C]-0.9902[/C][C]0.163257[/C][/ROW]
[ROW][C]21[/C][C]-0.00814[/C][C]-0.0598[/C][C]0.476261[/C][/ROW]
[ROW][C]22[/C][C]0.060451[/C][C]0.4442[/C][C]0.329328[/C][/ROW]
[ROW][C]23[/C][C]-0.257922[/C][C]-1.8953[/C][C]0.031703[/C][/ROW]
[ROW][C]24[/C][C]0.048953[/C][C]0.3597[/C][C]0.360226[/C][/ROW]
[ROW][C]25[/C][C]-0.043998[/C][C]-0.3233[/C][C]0.373851[/C][/ROW]
[ROW][C]26[/C][C]-0.077[/C][C]-0.5658[/C][C]0.286926[/C][/ROW]
[ROW][C]27[/C][C]-0.064424[/C][C]-0.4734[/C][C]0.318913[/C][/ROW]
[ROW][C]28[/C][C]-0.046338[/C][C]-0.3405[/C][C]0.367396[/C][/ROW]
[ROW][C]29[/C][C]-0.05014[/C][C]-0.3685[/C][C]0.356987[/C][/ROW]
[ROW][C]30[/C][C]-0.02325[/C][C]-0.1709[/C][C]0.432489[/C][/ROW]
[ROW][C]31[/C][C]-0.068345[/C][C]-0.5022[/C][C]0.308773[/C][/ROW]
[ROW][C]32[/C][C]0.04069[/C][C]0.299[/C][C]0.383039[/C][/ROW]
[ROW][C]33[/C][C]-0.038701[/C][C]-0.2844[/C][C]0.388597[/C][/ROW]
[ROW][C]34[/C][C]-0.093379[/C][C]-0.6862[/C][C]0.247764[/C][/ROW]
[ROW][C]35[/C][C]0.092598[/C][C]0.6805[/C][C]0.249562[/C][/ROW]
[ROW][C]36[/C][C]-0.0548[/C][C]-0.4027[/C][C]0.34438[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61869&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61869&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
1-0.215415-1.5830.059634
20.1624751.19390.11886
30.1230430.90420.184959
40.0810740.59580.27691
5-0.092781-0.68180.249139
60.1282590.94250.175066
70.0225580.16580.434479
80.1118430.82190.20738
90.0014680.01080.495717
10-0.13587-0.99840.161261
110.3949012.90190.002679
12-0.447989-3.2920.000879
130.0754520.55450.290778
140.0227470.16720.433936
150.0551070.40490.343558
16-0.086666-0.63690.263452
170.127520.93710.176445
18-0.062647-0.46040.323552
190.0288890.21230.416339
20-0.134743-0.99020.163257
21-0.00814-0.05980.476261
220.0604510.44420.329328
23-0.257922-1.89530.031703
240.0489530.35970.360226
25-0.043998-0.32330.373851
26-0.077-0.56580.286926
27-0.064424-0.47340.318913
28-0.046338-0.34050.367396
29-0.05014-0.36850.356987
30-0.02325-0.17090.432489
31-0.068345-0.50220.308773
320.040690.2990.383039
33-0.038701-0.28440.388597
34-0.093379-0.68620.247764
350.0925980.68050.249562
36-0.0548-0.40270.34438







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.215415-1.5830.059634
20.1217190.89450.187525
30.19161.4080.082436
40.1357270.99740.161514
5-0.108995-0.80090.213336
60.0275950.20280.420034
70.0645610.47440.318556
80.148931.09440.139318
90.0307790.22620.410958
10-0.250127-1.83810.035779
110.3417852.51160.007521
12-0.36661-2.6940.004694
13-0.099007-0.72750.235017
140.0487960.35860.360655
150.1462021.07440.14372
160.1237660.90950.183567
17-0.137853-1.0130.157787
180.0148860.10940.456649
19-0.031633-0.23250.408533
20-0.072593-0.53340.297957
210.041860.30760.379784
22-0.20172-1.48230.072032
230.0549470.40380.343985
24-0.167574-1.23140.111752
25-0.088298-0.64890.259592
26-0.018188-0.13370.447086
270.0572230.42050.337893
28-0.003148-0.02310.490816
29-0.028082-0.20640.418643
30-0.002933-0.02150.491443
310.0626090.46010.323654
32-0.032706-0.24030.40549
33-0.059431-0.43670.332026
34-0.02951-0.21690.414569
350.0802380.58960.278949
36-0.060471-0.44440.329275

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.215415 & -1.583 & 0.059634 \tabularnewline
2 & 0.121719 & 0.8945 & 0.187525 \tabularnewline
3 & 0.1916 & 1.408 & 0.082436 \tabularnewline
4 & 0.135727 & 0.9974 & 0.161514 \tabularnewline
5 & -0.108995 & -0.8009 & 0.213336 \tabularnewline
6 & 0.027595 & 0.2028 & 0.420034 \tabularnewline
7 & 0.064561 & 0.4744 & 0.318556 \tabularnewline
8 & 0.14893 & 1.0944 & 0.139318 \tabularnewline
9 & 0.030779 & 0.2262 & 0.410958 \tabularnewline
10 & -0.250127 & -1.8381 & 0.035779 \tabularnewline
11 & 0.341785 & 2.5116 & 0.007521 \tabularnewline
12 & -0.36661 & -2.694 & 0.004694 \tabularnewline
13 & -0.099007 & -0.7275 & 0.235017 \tabularnewline
14 & 0.048796 & 0.3586 & 0.360655 \tabularnewline
15 & 0.146202 & 1.0744 & 0.14372 \tabularnewline
16 & 0.123766 & 0.9095 & 0.183567 \tabularnewline
17 & -0.137853 & -1.013 & 0.157787 \tabularnewline
18 & 0.014886 & 0.1094 & 0.456649 \tabularnewline
19 & -0.031633 & -0.2325 & 0.408533 \tabularnewline
20 & -0.072593 & -0.5334 & 0.297957 \tabularnewline
21 & 0.04186 & 0.3076 & 0.379784 \tabularnewline
22 & -0.20172 & -1.4823 & 0.072032 \tabularnewline
23 & 0.054947 & 0.4038 & 0.343985 \tabularnewline
24 & -0.167574 & -1.2314 & 0.111752 \tabularnewline
25 & -0.088298 & -0.6489 & 0.259592 \tabularnewline
26 & -0.018188 & -0.1337 & 0.447086 \tabularnewline
27 & 0.057223 & 0.4205 & 0.337893 \tabularnewline
28 & -0.003148 & -0.0231 & 0.490816 \tabularnewline
29 & -0.028082 & -0.2064 & 0.418643 \tabularnewline
30 & -0.002933 & -0.0215 & 0.491443 \tabularnewline
31 & 0.062609 & 0.4601 & 0.323654 \tabularnewline
32 & -0.032706 & -0.2403 & 0.40549 \tabularnewline
33 & -0.059431 & -0.4367 & 0.332026 \tabularnewline
34 & -0.02951 & -0.2169 & 0.414569 \tabularnewline
35 & 0.080238 & 0.5896 & 0.278949 \tabularnewline
36 & -0.060471 & -0.4444 & 0.329275 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61869&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]-0.215415[/C][C]-1.583[/C][C]0.059634[/C][/ROW]
[ROW][C]2[/C][C]0.121719[/C][C]0.8945[/C][C]0.187525[/C][/ROW]
[ROW][C]3[/C][C]0.1916[/C][C]1.408[/C][C]0.082436[/C][/ROW]
[ROW][C]4[/C][C]0.135727[/C][C]0.9974[/C][C]0.161514[/C][/ROW]
[ROW][C]5[/C][C]-0.108995[/C][C]-0.8009[/C][C]0.213336[/C][/ROW]
[ROW][C]6[/C][C]0.027595[/C][C]0.2028[/C][C]0.420034[/C][/ROW]
[ROW][C]7[/C][C]0.064561[/C][C]0.4744[/C][C]0.318556[/C][/ROW]
[ROW][C]8[/C][C]0.14893[/C][C]1.0944[/C][C]0.139318[/C][/ROW]
[ROW][C]9[/C][C]0.030779[/C][C]0.2262[/C][C]0.410958[/C][/ROW]
[ROW][C]10[/C][C]-0.250127[/C][C]-1.8381[/C][C]0.035779[/C][/ROW]
[ROW][C]11[/C][C]0.341785[/C][C]2.5116[/C][C]0.007521[/C][/ROW]
[ROW][C]12[/C][C]-0.36661[/C][C]-2.694[/C][C]0.004694[/C][/ROW]
[ROW][C]13[/C][C]-0.099007[/C][C]-0.7275[/C][C]0.235017[/C][/ROW]
[ROW][C]14[/C][C]0.048796[/C][C]0.3586[/C][C]0.360655[/C][/ROW]
[ROW][C]15[/C][C]0.146202[/C][C]1.0744[/C][C]0.14372[/C][/ROW]
[ROW][C]16[/C][C]0.123766[/C][C]0.9095[/C][C]0.183567[/C][/ROW]
[ROW][C]17[/C][C]-0.137853[/C][C]-1.013[/C][C]0.157787[/C][/ROW]
[ROW][C]18[/C][C]0.014886[/C][C]0.1094[/C][C]0.456649[/C][/ROW]
[ROW][C]19[/C][C]-0.031633[/C][C]-0.2325[/C][C]0.408533[/C][/ROW]
[ROW][C]20[/C][C]-0.072593[/C][C]-0.5334[/C][C]0.297957[/C][/ROW]
[ROW][C]21[/C][C]0.04186[/C][C]0.3076[/C][C]0.379784[/C][/ROW]
[ROW][C]22[/C][C]-0.20172[/C][C]-1.4823[/C][C]0.072032[/C][/ROW]
[ROW][C]23[/C][C]0.054947[/C][C]0.4038[/C][C]0.343985[/C][/ROW]
[ROW][C]24[/C][C]-0.167574[/C][C]-1.2314[/C][C]0.111752[/C][/ROW]
[ROW][C]25[/C][C]-0.088298[/C][C]-0.6489[/C][C]0.259592[/C][/ROW]
[ROW][C]26[/C][C]-0.018188[/C][C]-0.1337[/C][C]0.447086[/C][/ROW]
[ROW][C]27[/C][C]0.057223[/C][C]0.4205[/C][C]0.337893[/C][/ROW]
[ROW][C]28[/C][C]-0.003148[/C][C]-0.0231[/C][C]0.490816[/C][/ROW]
[ROW][C]29[/C][C]-0.028082[/C][C]-0.2064[/C][C]0.418643[/C][/ROW]
[ROW][C]30[/C][C]-0.002933[/C][C]-0.0215[/C][C]0.491443[/C][/ROW]
[ROW][C]31[/C][C]0.062609[/C][C]0.4601[/C][C]0.323654[/C][/ROW]
[ROW][C]32[/C][C]-0.032706[/C][C]-0.2403[/C][C]0.40549[/C][/ROW]
[ROW][C]33[/C][C]-0.059431[/C][C]-0.4367[/C][C]0.332026[/C][/ROW]
[ROW][C]34[/C][C]-0.02951[/C][C]-0.2169[/C][C]0.414569[/C][/ROW]
[ROW][C]35[/C][C]0.080238[/C][C]0.5896[/C][C]0.278949[/C][/ROW]
[ROW][C]36[/C][C]-0.060471[/C][C]-0.4444[/C][C]0.329275[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61869&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61869&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
1-0.215415-1.5830.059634
20.1217190.89450.187525
30.19161.4080.082436
40.1357270.99740.161514
5-0.108995-0.80090.213336
60.0275950.20280.420034
70.0645610.47440.318556
80.148931.09440.139318
90.0307790.22620.410958
10-0.250127-1.83810.035779
110.3417852.51160.007521
12-0.36661-2.6940.004694
13-0.099007-0.72750.235017
140.0487960.35860.360655
150.1462021.07440.14372
160.1237660.90950.183567
17-0.137853-1.0130.157787
180.0148860.10940.456649
19-0.031633-0.23250.408533
20-0.072593-0.53340.297957
210.041860.30760.379784
22-0.20172-1.48230.072032
230.0549470.40380.343985
24-0.167574-1.23140.111752
25-0.088298-0.64890.259592
26-0.018188-0.13370.447086
270.0572230.42050.337893
28-0.003148-0.02310.490816
29-0.028082-0.20640.418643
30-0.002933-0.02150.491443
310.0626090.46010.323654
32-0.032706-0.24030.40549
33-0.059431-0.43670.332026
34-0.02951-0.21690.414569
350.0802380.58960.278949
36-0.060471-0.44440.329275



Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 2 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 2 ; 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')