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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 computationThu, 03 Dec 2009 10:25:00 -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/03/t1259861171vu3d703kqq62ls0.htm/, Retrieved Thu, 18 Apr 2024 08:15:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62945, Retrieved Thu, 18 Apr 2024 08:15:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact160

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] [Workshop 8 - Meth...] [2009-11-24 15:58:42] [1646a2766cb8c4a6f9d3b2fffef409b3]
-               [(Partial) Autocorrelation Function] [] [2009-11-30 16:42:34] [74be16979710d4c4e7c6647856088456]
-                   [(Partial) Autocorrelation Function] [] [2009-12-03 17:25:00] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
269645
267037
258113
262813
267413
267366
264777
258863
254844
254868
277267
285351
286602
283042
276687
277915
277128
277103
275037
270150
267140
264993
287259
291186
292300
288186
281477
282656
280190
280408
276836
275216
274352
271311
289802
290726
292300
278506
269826
265861
269034
264176
255198
253353
246057
235372
258556
260993
254663
250643
243422
247105
248541
245039
237080
237085
225554
226839
247934
248333
246969
245098
246263
255765
264319
268347
273046
273963
267430
271993
292710
295881

Tables (Output of Computation)





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=62945&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=62945&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62945&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.8673417.35960
20.7046925.97950
30.6091265.16861e-06
40.561244.76235e-06
50.5407574.58859e-06
60.4948024.19853.8e-05
70.4020553.41160.000531
80.2831512.40260.009429
90.2213341.87810.03221
100.2217841.88190.031946
110.2661072.2580.013489
120.2739642.32470.011457
130.128081.08680.140376
14-0.020408-0.17320.431503
15-0.101877-0.86450.195104
16-0.13508-1.14620.127755
17-0.141203-1.19810.117394
18-0.163269-1.38540.085106
19-0.226888-1.92520.029077
20-0.310471-2.63440.005156
21-0.336733-2.85730.002791
22-0.308304-2.6160.005416
23-0.254729-2.16140.016993
24-0.229649-1.94860.027618
25-0.320105-2.71620.004132
26-0.396017-3.36030.000624
27-0.402539-3.41570.000525
28-0.375808-3.18880.001058
29-0.328187-2.78480.00342
30-0.293699-2.49210.007501
31-0.299151-2.53840.00665
32-0.320168-2.71670.004126
33-0.286814-2.43370.008714
34-0.219001-1.85830.033608
35-0.13666-1.15960.125022
36-0.095312-0.80880.210661

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.867341 & 7.3596 & 0 \tabularnewline
2 & 0.704692 & 5.9795 & 0 \tabularnewline
3 & 0.609126 & 5.1686 & 1e-06 \tabularnewline
4 & 0.56124 & 4.7623 & 5e-06 \tabularnewline
5 & 0.540757 & 4.5885 & 9e-06 \tabularnewline
6 & 0.494802 & 4.1985 & 3.8e-05 \tabularnewline
7 & 0.402055 & 3.4116 & 0.000531 \tabularnewline
8 & 0.283151 & 2.4026 & 0.009429 \tabularnewline
9 & 0.221334 & 1.8781 & 0.03221 \tabularnewline
10 & 0.221784 & 1.8819 & 0.031946 \tabularnewline
11 & 0.266107 & 2.258 & 0.013489 \tabularnewline
12 & 0.273964 & 2.3247 & 0.011457 \tabularnewline
13 & 0.12808 & 1.0868 & 0.140376 \tabularnewline
14 & -0.020408 & -0.1732 & 0.431503 \tabularnewline
15 & -0.101877 & -0.8645 & 0.195104 \tabularnewline
16 & -0.13508 & -1.1462 & 0.127755 \tabularnewline
17 & -0.141203 & -1.1981 & 0.117394 \tabularnewline
18 & -0.163269 & -1.3854 & 0.085106 \tabularnewline
19 & -0.226888 & -1.9252 & 0.029077 \tabularnewline
20 & -0.310471 & -2.6344 & 0.005156 \tabularnewline
21 & -0.336733 & -2.8573 & 0.002791 \tabularnewline
22 & -0.308304 & -2.616 & 0.005416 \tabularnewline
23 & -0.254729 & -2.1614 & 0.016993 \tabularnewline
24 & -0.229649 & -1.9486 & 0.027618 \tabularnewline
25 & -0.320105 & -2.7162 & 0.004132 \tabularnewline
26 & -0.396017 & -3.3603 & 0.000624 \tabularnewline
27 & -0.402539 & -3.4157 & 0.000525 \tabularnewline
28 & -0.375808 & -3.1888 & 0.001058 \tabularnewline
29 & -0.328187 & -2.7848 & 0.00342 \tabularnewline
30 & -0.293699 & -2.4921 & 0.007501 \tabularnewline
31 & -0.299151 & -2.5384 & 0.00665 \tabularnewline
32 & -0.320168 & -2.7167 & 0.004126 \tabularnewline
33 & -0.286814 & -2.4337 & 0.008714 \tabularnewline
34 & -0.219001 & -1.8583 & 0.033608 \tabularnewline
35 & -0.13666 & -1.1596 & 0.125022 \tabularnewline
36 & -0.095312 & -0.8088 & 0.210661 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62945&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]0.867341[/C][C]7.3596[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.704692[/C][C]5.9795[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.609126[/C][C]5.1686[/C][C]1e-06[/C][/ROW]
[ROW][C]4[/C][C]0.56124[/C][C]4.7623[/C][C]5e-06[/C][/ROW]
[ROW][C]5[/C][C]0.540757[/C][C]4.5885[/C][C]9e-06[/C][/ROW]
[ROW][C]6[/C][C]0.494802[/C][C]4.1985[/C][C]3.8e-05[/C][/ROW]
[ROW][C]7[/C][C]0.402055[/C][C]3.4116[/C][C]0.000531[/C][/ROW]
[ROW][C]8[/C][C]0.283151[/C][C]2.4026[/C][C]0.009429[/C][/ROW]
[ROW][C]9[/C][C]0.221334[/C][C]1.8781[/C][C]0.03221[/C][/ROW]
[ROW][C]10[/C][C]0.221784[/C][C]1.8819[/C][C]0.031946[/C][/ROW]
[ROW][C]11[/C][C]0.266107[/C][C]2.258[/C][C]0.013489[/C][/ROW]
[ROW][C]12[/C][C]0.273964[/C][C]2.3247[/C][C]0.011457[/C][/ROW]
[ROW][C]13[/C][C]0.12808[/C][C]1.0868[/C][C]0.140376[/C][/ROW]
[ROW][C]14[/C][C]-0.020408[/C][C]-0.1732[/C][C]0.431503[/C][/ROW]
[ROW][C]15[/C][C]-0.101877[/C][C]-0.8645[/C][C]0.195104[/C][/ROW]
[ROW][C]16[/C][C]-0.13508[/C][C]-1.1462[/C][C]0.127755[/C][/ROW]
[ROW][C]17[/C][C]-0.141203[/C][C]-1.1981[/C][C]0.117394[/C][/ROW]
[ROW][C]18[/C][C]-0.163269[/C][C]-1.3854[/C][C]0.085106[/C][/ROW]
[ROW][C]19[/C][C]-0.226888[/C][C]-1.9252[/C][C]0.029077[/C][/ROW]
[ROW][C]20[/C][C]-0.310471[/C][C]-2.6344[/C][C]0.005156[/C][/ROW]
[ROW][C]21[/C][C]-0.336733[/C][C]-2.8573[/C][C]0.002791[/C][/ROW]
[ROW][C]22[/C][C]-0.308304[/C][C]-2.616[/C][C]0.005416[/C][/ROW]
[ROW][C]23[/C][C]-0.254729[/C][C]-2.1614[/C][C]0.016993[/C][/ROW]
[ROW][C]24[/C][C]-0.229649[/C][C]-1.9486[/C][C]0.027618[/C][/ROW]
[ROW][C]25[/C][C]-0.320105[/C][C]-2.7162[/C][C]0.004132[/C][/ROW]
[ROW][C]26[/C][C]-0.396017[/C][C]-3.3603[/C][C]0.000624[/C][/ROW]
[ROW][C]27[/C][C]-0.402539[/C][C]-3.4157[/C][C]0.000525[/C][/ROW]
[ROW][C]28[/C][C]-0.375808[/C][C]-3.1888[/C][C]0.001058[/C][/ROW]
[ROW][C]29[/C][C]-0.328187[/C][C]-2.7848[/C][C]0.00342[/C][/ROW]
[ROW][C]30[/C][C]-0.293699[/C][C]-2.4921[/C][C]0.007501[/C][/ROW]
[ROW][C]31[/C][C]-0.299151[/C][C]-2.5384[/C][C]0.00665[/C][/ROW]
[ROW][C]32[/C][C]-0.320168[/C][C]-2.7167[/C][C]0.004126[/C][/ROW]
[ROW][C]33[/C][C]-0.286814[/C][C]-2.4337[/C][C]0.008714[/C][/ROW]
[ROW][C]34[/C][C]-0.219001[/C][C]-1.8583[/C][C]0.033608[/C][/ROW]
[ROW][C]35[/C][C]-0.13666[/C][C]-1.1596[/C][C]0.125022[/C][/ROW]
[ROW][C]36[/C][C]-0.095312[/C][C]-0.8088[/C][C]0.210661[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62945&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62945&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
10.8673417.35960
20.7046925.97950
30.6091265.16861e-06
40.561244.76235e-06
50.5407574.58859e-06
60.4948024.19853.8e-05
70.4020553.41160.000531
80.2831512.40260.009429
90.2213341.87810.03221
100.2217841.88190.031946
110.2661072.2580.013489
120.2739642.32470.011457
130.128081.08680.140376
14-0.020408-0.17320.431503
15-0.101877-0.86450.195104
16-0.13508-1.14620.127755
17-0.141203-1.19810.117394
18-0.163269-1.38540.085106
19-0.226888-1.92520.029077
20-0.310471-2.63440.005156
21-0.336733-2.85730.002791
22-0.308304-2.6160.005416
23-0.254729-2.16140.016993
24-0.229649-1.94860.027618
25-0.320105-2.71620.004132
26-0.396017-3.36030.000624
27-0.402539-3.41570.000525
28-0.375808-3.18880.001058
29-0.328187-2.78480.00342
30-0.293699-2.49210.007501
31-0.299151-2.53840.00665
32-0.320168-2.71670.004126
33-0.286814-2.43370.008714
34-0.219001-1.85830.033608
35-0.13666-1.15960.125022
36-0.095312-0.80880.210661






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8673417.35960
2-0.192106-1.63010.053727
30.197511.67590.049045
40.0710610.6030.274211
50.1058840.89850.185968
6-0.08858-0.75160.227362
7-0.134514-1.14140.128745
8-0.146787-1.24550.108488
90.1270741.07830.14226
100.0814080.69080.245965
110.1953461.65760.050878
12-0.079754-0.67670.25037
13-0.527881-4.47921.4e-05
140.0104890.0890.464664
15-0.068907-0.58470.280291
16-0.005081-0.04310.482865
170.0521670.44260.329674
180.0299850.25440.399943
19-0.007695-0.06530.47406
20-0.040538-0.3440.365933
21-0.061301-0.52020.302276
22-0.052447-0.4450.328819
23-0.017157-0.14560.442329
240.0319690.27130.393483
25-0.161621-1.37140.087254
260.0855230.72570.235191
270.0177690.15080.440287
28-0.050485-0.42840.334828
290.0395060.33520.369216
30-0.00068-0.00580.497705
31-0.012524-0.10630.457832
320.0249810.2120.416365
33-0.00834-0.07080.471889
34-0.048245-0.40940.34174
350.0748930.63550.263562
36-0.09786-0.83040.204538

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.867341 & 7.3596 & 0 \tabularnewline
2 & -0.192106 & -1.6301 & 0.053727 \tabularnewline
3 & 0.19751 & 1.6759 & 0.049045 \tabularnewline
4 & 0.071061 & 0.603 & 0.274211 \tabularnewline
5 & 0.105884 & 0.8985 & 0.185968 \tabularnewline
6 & -0.08858 & -0.7516 & 0.227362 \tabularnewline
7 & -0.134514 & -1.1414 & 0.128745 \tabularnewline
8 & -0.146787 & -1.2455 & 0.108488 \tabularnewline
9 & 0.127074 & 1.0783 & 0.14226 \tabularnewline
10 & 0.081408 & 0.6908 & 0.245965 \tabularnewline
11 & 0.195346 & 1.6576 & 0.050878 \tabularnewline
12 & -0.079754 & -0.6767 & 0.25037 \tabularnewline
13 & -0.527881 & -4.4792 & 1.4e-05 \tabularnewline
14 & 0.010489 & 0.089 & 0.464664 \tabularnewline
15 & -0.068907 & -0.5847 & 0.280291 \tabularnewline
16 & -0.005081 & -0.0431 & 0.482865 \tabularnewline
17 & 0.052167 & 0.4426 & 0.329674 \tabularnewline
18 & 0.029985 & 0.2544 & 0.399943 \tabularnewline
19 & -0.007695 & -0.0653 & 0.47406 \tabularnewline
20 & -0.040538 & -0.344 & 0.365933 \tabularnewline
21 & -0.061301 & -0.5202 & 0.302276 \tabularnewline
22 & -0.052447 & -0.445 & 0.328819 \tabularnewline
23 & -0.017157 & -0.1456 & 0.442329 \tabularnewline
24 & 0.031969 & 0.2713 & 0.393483 \tabularnewline
25 & -0.161621 & -1.3714 & 0.087254 \tabularnewline
26 & 0.085523 & 0.7257 & 0.235191 \tabularnewline
27 & 0.017769 & 0.1508 & 0.440287 \tabularnewline
28 & -0.050485 & -0.4284 & 0.334828 \tabularnewline
29 & 0.039506 & 0.3352 & 0.369216 \tabularnewline
30 & -0.00068 & -0.0058 & 0.497705 \tabularnewline
31 & -0.012524 & -0.1063 & 0.457832 \tabularnewline
32 & 0.024981 & 0.212 & 0.416365 \tabularnewline
33 & -0.00834 & -0.0708 & 0.471889 \tabularnewline
34 & -0.048245 & -0.4094 & 0.34174 \tabularnewline
35 & 0.074893 & 0.6355 & 0.263562 \tabularnewline
36 & -0.09786 & -0.8304 & 0.204538 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62945&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]0.867341[/C][C]7.3596[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.192106[/C][C]-1.6301[/C][C]0.053727[/C][/ROW]
[ROW][C]3[/C][C]0.19751[/C][C]1.6759[/C][C]0.049045[/C][/ROW]
[ROW][C]4[/C][C]0.071061[/C][C]0.603[/C][C]0.274211[/C][/ROW]
[ROW][C]5[/C][C]0.105884[/C][C]0.8985[/C][C]0.185968[/C][/ROW]
[ROW][C]6[/C][C]-0.08858[/C][C]-0.7516[/C][C]0.227362[/C][/ROW]
[ROW][C]7[/C][C]-0.134514[/C][C]-1.1414[/C][C]0.128745[/C][/ROW]
[ROW][C]8[/C][C]-0.146787[/C][C]-1.2455[/C][C]0.108488[/C][/ROW]
[ROW][C]9[/C][C]0.127074[/C][C]1.0783[/C][C]0.14226[/C][/ROW]
[ROW][C]10[/C][C]0.081408[/C][C]0.6908[/C][C]0.245965[/C][/ROW]
[ROW][C]11[/C][C]0.195346[/C][C]1.6576[/C][C]0.050878[/C][/ROW]
[ROW][C]12[/C][C]-0.079754[/C][C]-0.6767[/C][C]0.25037[/C][/ROW]
[ROW][C]13[/C][C]-0.527881[/C][C]-4.4792[/C][C]1.4e-05[/C][/ROW]
[ROW][C]14[/C][C]0.010489[/C][C]0.089[/C][C]0.464664[/C][/ROW]
[ROW][C]15[/C][C]-0.068907[/C][C]-0.5847[/C][C]0.280291[/C][/ROW]
[ROW][C]16[/C][C]-0.005081[/C][C]-0.0431[/C][C]0.482865[/C][/ROW]
[ROW][C]17[/C][C]0.052167[/C][C]0.4426[/C][C]0.329674[/C][/ROW]
[ROW][C]18[/C][C]0.029985[/C][C]0.2544[/C][C]0.399943[/C][/ROW]
[ROW][C]19[/C][C]-0.007695[/C][C]-0.0653[/C][C]0.47406[/C][/ROW]
[ROW][C]20[/C][C]-0.040538[/C][C]-0.344[/C][C]0.365933[/C][/ROW]
[ROW][C]21[/C][C]-0.061301[/C][C]-0.5202[/C][C]0.302276[/C][/ROW]
[ROW][C]22[/C][C]-0.052447[/C][C]-0.445[/C][C]0.328819[/C][/ROW]
[ROW][C]23[/C][C]-0.017157[/C][C]-0.1456[/C][C]0.442329[/C][/ROW]
[ROW][C]24[/C][C]0.031969[/C][C]0.2713[/C][C]0.393483[/C][/ROW]
[ROW][C]25[/C][C]-0.161621[/C][C]-1.3714[/C][C]0.087254[/C][/ROW]
[ROW][C]26[/C][C]0.085523[/C][C]0.7257[/C][C]0.235191[/C][/ROW]
[ROW][C]27[/C][C]0.017769[/C][C]0.1508[/C][C]0.440287[/C][/ROW]
[ROW][C]28[/C][C]-0.050485[/C][C]-0.4284[/C][C]0.334828[/C][/ROW]
[ROW][C]29[/C][C]0.039506[/C][C]0.3352[/C][C]0.369216[/C][/ROW]
[ROW][C]30[/C][C]-0.00068[/C][C]-0.0058[/C][C]0.497705[/C][/ROW]
[ROW][C]31[/C][C]-0.012524[/C][C]-0.1063[/C][C]0.457832[/C][/ROW]
[ROW][C]32[/C][C]0.024981[/C][C]0.212[/C][C]0.416365[/C][/ROW]
[ROW][C]33[/C][C]-0.00834[/C][C]-0.0708[/C][C]0.471889[/C][/ROW]
[ROW][C]34[/C][C]-0.048245[/C][C]-0.4094[/C][C]0.34174[/C][/ROW]
[ROW][C]35[/C][C]0.074893[/C][C]0.6355[/C][C]0.263562[/C][/ROW]
[ROW][C]36[/C][C]-0.09786[/C][C]-0.8304[/C][C]0.204538[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62945&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62945&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
10.8673417.35960
2-0.192106-1.63010.053727
30.197511.67590.049045
40.0710610.6030.274211
50.1058840.89850.185968
6-0.08858-0.75160.227362
7-0.134514-1.14140.128745
8-0.146787-1.24550.108488
90.1270741.07830.14226
100.0814080.69080.245965
110.1953461.65760.050878
12-0.079754-0.67670.25037
13-0.527881-4.47921.4e-05
140.0104890.0890.464664
15-0.068907-0.58470.280291
16-0.005081-0.04310.482865
170.0521670.44260.329674
180.0299850.25440.399943
19-0.007695-0.06530.47406
20-0.040538-0.3440.365933
21-0.061301-0.52020.302276
22-0.052447-0.4450.328819
23-0.017157-0.14560.442329
240.0319690.27130.393483
25-0.161621-1.37140.087254
260.0855230.72570.235191
270.0177690.15080.440287
28-0.050485-0.42840.334828
290.0395060.33520.369216
30-0.00068-0.00580.497705
31-0.012524-0.10630.457832
320.0249810.2120.416365
33-0.00834-0.07080.471889
34-0.048245-0.40940.34174
350.0748930.63550.263562
36-0.09786-0.83040.204538


Figures (Output of Computation)

Input Parameters & R Code

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 = 0 ; par4 = 0 ; par5 = 12 ; par6 = MA ; 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 (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')