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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 12:01:29 -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/t12593485060g6s8qp1d9pblzr.htm/, Retrieved Mon, 29 Apr 2024 17:49:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=61135, Retrieved Mon, 29 Apr 2024 17:49:23 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact134

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] [] [2009-11-25 15:48:54] [80b559301b076f6db87527dfd2199d75]
-    D            [(Partial) Autocorrelation Function] [] [2009-11-27 19:01:29] [f066b5fba39549422fd1c7a1f2ce0075] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
160,90
193,70
201,40
176,60
172,00
200,10
172,00
136,10
182,60
208,70
142,30
188,80
143,90
149,70
196,90
231,50
219,20
220,70
244,20
182,50
229,80
238,10
206,50
249,30
181,80
218,00
246,40
214,30
242,30
220,70
204,50
180,70
233,00
236,50
239,40
208,70
209,00
247,20
284,30
245,80
249,10
251,40
251,20
207,20
228,30
254,30
217,90
244,40
233,20
212,60
239,50
335,50
248,80
264,60
275,40
180,70
256,10
247,40
227,80
248,10

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=61135&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=61135&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61135&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
10.4497823.4840.000464
20.3886883.01080.001904
30.5091063.94350.000106
40.2758922.1370.01834
50.3714682.87740.002773
60.4409973.4160.000573
70.2992532.3180.011938
80.1604041.24250.109446
90.224161.73630.043818
100.1552221.20230.116978
110.1512661.17170.122974
120.2985842.31280.012089
130.1515321.17380.122565
140.0817790.63350.264422
150.0301380.23340.408104
160.0126930.09830.461002
170.0781060.6050.273728
180.0718820.55680.28987
190.1109150.85910.19684
20-0.027557-0.21350.415847
21-0.026298-0.20370.419637
22-0.021245-0.16460.434921
23-0.022093-0.17110.432347
240.0615960.47710.317505
25-0.03308-0.25620.399321
26-0.138916-1.0760.143109
27-0.135936-1.0530.148292
28-0.110666-0.85720.197369
29-0.138178-1.07030.144381
30-0.072549-0.5620.288117
31-0.070441-0.54560.29367
32-0.226889-1.75750.041969
33-0.076861-0.59540.276919
34-0.186902-1.44770.076448
35-0.182838-1.41630.080936
36-0.016685-0.12920.4488

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.449782 & 3.484 & 0.000464 \tabularnewline
2 & 0.388688 & 3.0108 & 0.001904 \tabularnewline
3 & 0.509106 & 3.9435 & 0.000106 \tabularnewline
4 & 0.275892 & 2.137 & 0.01834 \tabularnewline
5 & 0.371468 & 2.8774 & 0.002773 \tabularnewline
6 & 0.440997 & 3.416 & 0.000573 \tabularnewline
7 & 0.299253 & 2.318 & 0.011938 \tabularnewline
8 & 0.160404 & 1.2425 & 0.109446 \tabularnewline
9 & 0.22416 & 1.7363 & 0.043818 \tabularnewline
10 & 0.155222 & 1.2023 & 0.116978 \tabularnewline
11 & 0.151266 & 1.1717 & 0.122974 \tabularnewline
12 & 0.298584 & 2.3128 & 0.012089 \tabularnewline
13 & 0.151532 & 1.1738 & 0.122565 \tabularnewline
14 & 0.081779 & 0.6335 & 0.264422 \tabularnewline
15 & 0.030138 & 0.2334 & 0.408104 \tabularnewline
16 & 0.012693 & 0.0983 & 0.461002 \tabularnewline
17 & 0.078106 & 0.605 & 0.273728 \tabularnewline
18 & 0.071882 & 0.5568 & 0.28987 \tabularnewline
19 & 0.110915 & 0.8591 & 0.19684 \tabularnewline
20 & -0.027557 & -0.2135 & 0.415847 \tabularnewline
21 & -0.026298 & -0.2037 & 0.419637 \tabularnewline
22 & -0.021245 & -0.1646 & 0.434921 \tabularnewline
23 & -0.022093 & -0.1711 & 0.432347 \tabularnewline
24 & 0.061596 & 0.4771 & 0.317505 \tabularnewline
25 & -0.03308 & -0.2562 & 0.399321 \tabularnewline
26 & -0.138916 & -1.076 & 0.143109 \tabularnewline
27 & -0.135936 & -1.053 & 0.148292 \tabularnewline
28 & -0.110666 & -0.8572 & 0.197369 \tabularnewline
29 & -0.138178 & -1.0703 & 0.144381 \tabularnewline
30 & -0.072549 & -0.562 & 0.288117 \tabularnewline
31 & -0.070441 & -0.5456 & 0.29367 \tabularnewline
32 & -0.226889 & -1.7575 & 0.041969 \tabularnewline
33 & -0.076861 & -0.5954 & 0.276919 \tabularnewline
34 & -0.186902 & -1.4477 & 0.076448 \tabularnewline
35 & -0.182838 & -1.4163 & 0.080936 \tabularnewline
36 & -0.016685 & -0.1292 & 0.4488 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61135&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]0.449782[/C][C]3.484[/C][C]0.000464[/C][/ROW]
[ROW][C]2[/C][C]0.388688[/C][C]3.0108[/C][C]0.001904[/C][/ROW]
[ROW][C]3[/C][C]0.509106[/C][C]3.9435[/C][C]0.000106[/C][/ROW]
[ROW][C]4[/C][C]0.275892[/C][C]2.137[/C][C]0.01834[/C][/ROW]
[ROW][C]5[/C][C]0.371468[/C][C]2.8774[/C][C]0.002773[/C][/ROW]
[ROW][C]6[/C][C]0.440997[/C][C]3.416[/C][C]0.000573[/C][/ROW]
[ROW][C]7[/C][C]0.299253[/C][C]2.318[/C][C]0.011938[/C][/ROW]
[ROW][C]8[/C][C]0.160404[/C][C]1.2425[/C][C]0.109446[/C][/ROW]
[ROW][C]9[/C][C]0.22416[/C][C]1.7363[/C][C]0.043818[/C][/ROW]
[ROW][C]10[/C][C]0.155222[/C][C]1.2023[/C][C]0.116978[/C][/ROW]
[ROW][C]11[/C][C]0.151266[/C][C]1.1717[/C][C]0.122974[/C][/ROW]
[ROW][C]12[/C][C]0.298584[/C][C]2.3128[/C][C]0.012089[/C][/ROW]
[ROW][C]13[/C][C]0.151532[/C][C]1.1738[/C][C]0.122565[/C][/ROW]
[ROW][C]14[/C][C]0.081779[/C][C]0.6335[/C][C]0.264422[/C][/ROW]
[ROW][C]15[/C][C]0.030138[/C][C]0.2334[/C][C]0.408104[/C][/ROW]
[ROW][C]16[/C][C]0.012693[/C][C]0.0983[/C][C]0.461002[/C][/ROW]
[ROW][C]17[/C][C]0.078106[/C][C]0.605[/C][C]0.273728[/C][/ROW]
[ROW][C]18[/C][C]0.071882[/C][C]0.5568[/C][C]0.28987[/C][/ROW]
[ROW][C]19[/C][C]0.110915[/C][C]0.8591[/C][C]0.19684[/C][/ROW]
[ROW][C]20[/C][C]-0.027557[/C][C]-0.2135[/C][C]0.415847[/C][/ROW]
[ROW][C]21[/C][C]-0.026298[/C][C]-0.2037[/C][C]0.419637[/C][/ROW]
[ROW][C]22[/C][C]-0.021245[/C][C]-0.1646[/C][C]0.434921[/C][/ROW]
[ROW][C]23[/C][C]-0.022093[/C][C]-0.1711[/C][C]0.432347[/C][/ROW]
[ROW][C]24[/C][C]0.061596[/C][C]0.4771[/C][C]0.317505[/C][/ROW]
[ROW][C]25[/C][C]-0.03308[/C][C]-0.2562[/C][C]0.399321[/C][/ROW]
[ROW][C]26[/C][C]-0.138916[/C][C]-1.076[/C][C]0.143109[/C][/ROW]
[ROW][C]27[/C][C]-0.135936[/C][C]-1.053[/C][C]0.148292[/C][/ROW]
[ROW][C]28[/C][C]-0.110666[/C][C]-0.8572[/C][C]0.197369[/C][/ROW]
[ROW][C]29[/C][C]-0.138178[/C][C]-1.0703[/C][C]0.144381[/C][/ROW]
[ROW][C]30[/C][C]-0.072549[/C][C]-0.562[/C][C]0.288117[/C][/ROW]
[ROW][C]31[/C][C]-0.070441[/C][C]-0.5456[/C][C]0.29367[/C][/ROW]
[ROW][C]32[/C][C]-0.226889[/C][C]-1.7575[/C][C]0.041969[/C][/ROW]
[ROW][C]33[/C][C]-0.076861[/C][C]-0.5954[/C][C]0.276919[/C][/ROW]
[ROW][C]34[/C][C]-0.186902[/C][C]-1.4477[/C][C]0.076448[/C][/ROW]
[ROW][C]35[/C][C]-0.182838[/C][C]-1.4163[/C][C]0.080936[/C][/ROW]
[ROW][C]36[/C][C]-0.016685[/C][C]-0.1292[/C][C]0.4488[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61135&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61135&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
10.4497823.4840.000464
20.3886883.01080.001904
30.5091063.94350.000106
40.2758922.1370.01834
50.3714682.87740.002773
60.4409973.4160.000573
70.2992532.3180.011938
80.1604041.24250.109446
90.224161.73630.043818
100.1552221.20230.116978
110.1512661.17170.122974
120.2985842.31280.012089
130.1515321.17380.122565
140.0817790.63350.264422
150.0301380.23340.408104
160.0126930.09830.461002
170.0781060.6050.273728
180.0718820.55680.28987
190.1109150.85910.19684
20-0.027557-0.21350.415847
21-0.026298-0.20370.419637
22-0.021245-0.16460.434921
23-0.022093-0.17110.432347
240.0615960.47710.317505
25-0.03308-0.25620.399321
26-0.138916-1.0760.143109
27-0.135936-1.0530.148292
28-0.110666-0.85720.197369
29-0.138178-1.07030.144381
30-0.072549-0.5620.288117
31-0.070441-0.54560.29367
32-0.226889-1.75750.041969
33-0.076861-0.59540.276919
34-0.186902-1.44770.076448
35-0.182838-1.41630.080936
36-0.016685-0.12920.4488






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.4497823.4840.000464
20.2336531.80990.037663
30.3580692.77360.003689
4-0.092624-0.71750.237937
50.187281.45070.07604
60.1619431.25440.10728
70.0298010.23080.409112
8-0.26561-2.05740.022001
90.0083180.06440.474421
10-0.025979-0.20120.420599
110.072430.5610.288429
120.1391161.07760.142766
13-0.022741-0.17620.430384
14-0.05892-0.45640.324878
15-0.205781-1.5940.058099
16-0.008756-0.06780.473076
170.0615110.47650.317738
180.0224310.17380.431323
190.0929570.720.237146
20-0.081513-0.63140.265089
210.0250910.19440.423277
22-0.0761-0.58950.27888
230.0102310.07930.468548
240.0067920.05260.479109
25-0.07747-0.60010.275356
26-0.181363-1.40480.082614
270.0035880.02780.488958
280.0761080.58950.278861
29-0.036071-0.27940.390449
30-0.005305-0.04110.48368
31-0.012713-0.09850.460942
32-0.069983-0.54210.294884
330.1607141.24490.109007
34-0.166323-1.28830.101288
350.0164990.12780.449367
360.0088360.06840.472829

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.449782 & 3.484 & 0.000464 \tabularnewline
2 & 0.233653 & 1.8099 & 0.037663 \tabularnewline
3 & 0.358069 & 2.7736 & 0.003689 \tabularnewline
4 & -0.092624 & -0.7175 & 0.237937 \tabularnewline
5 & 0.18728 & 1.4507 & 0.07604 \tabularnewline
6 & 0.161943 & 1.2544 & 0.10728 \tabularnewline
7 & 0.029801 & 0.2308 & 0.409112 \tabularnewline
8 & -0.26561 & -2.0574 & 0.022001 \tabularnewline
9 & 0.008318 & 0.0644 & 0.474421 \tabularnewline
10 & -0.025979 & -0.2012 & 0.420599 \tabularnewline
11 & 0.07243 & 0.561 & 0.288429 \tabularnewline
12 & 0.139116 & 1.0776 & 0.142766 \tabularnewline
13 & -0.022741 & -0.1762 & 0.430384 \tabularnewline
14 & -0.05892 & -0.4564 & 0.324878 \tabularnewline
15 & -0.205781 & -1.594 & 0.058099 \tabularnewline
16 & -0.008756 & -0.0678 & 0.473076 \tabularnewline
17 & 0.061511 & 0.4765 & 0.317738 \tabularnewline
18 & 0.022431 & 0.1738 & 0.431323 \tabularnewline
19 & 0.092957 & 0.72 & 0.237146 \tabularnewline
20 & -0.081513 & -0.6314 & 0.265089 \tabularnewline
21 & 0.025091 & 0.1944 & 0.423277 \tabularnewline
22 & -0.0761 & -0.5895 & 0.27888 \tabularnewline
23 & 0.010231 & 0.0793 & 0.468548 \tabularnewline
24 & 0.006792 & 0.0526 & 0.479109 \tabularnewline
25 & -0.07747 & -0.6001 & 0.275356 \tabularnewline
26 & -0.181363 & -1.4048 & 0.082614 \tabularnewline
27 & 0.003588 & 0.0278 & 0.488958 \tabularnewline
28 & 0.076108 & 0.5895 & 0.278861 \tabularnewline
29 & -0.036071 & -0.2794 & 0.390449 \tabularnewline
30 & -0.005305 & -0.0411 & 0.48368 \tabularnewline
31 & -0.012713 & -0.0985 & 0.460942 \tabularnewline
32 & -0.069983 & -0.5421 & 0.294884 \tabularnewline
33 & 0.160714 & 1.2449 & 0.109007 \tabularnewline
34 & -0.166323 & -1.2883 & 0.101288 \tabularnewline
35 & 0.016499 & 0.1278 & 0.449367 \tabularnewline
36 & 0.008836 & 0.0684 & 0.472829 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61135&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]0.449782[/C][C]3.484[/C][C]0.000464[/C][/ROW]
[ROW][C]2[/C][C]0.233653[/C][C]1.8099[/C][C]0.037663[/C][/ROW]
[ROW][C]3[/C][C]0.358069[/C][C]2.7736[/C][C]0.003689[/C][/ROW]
[ROW][C]4[/C][C]-0.092624[/C][C]-0.7175[/C][C]0.237937[/C][/ROW]
[ROW][C]5[/C][C]0.18728[/C][C]1.4507[/C][C]0.07604[/C][/ROW]
[ROW][C]6[/C][C]0.161943[/C][C]1.2544[/C][C]0.10728[/C][/ROW]
[ROW][C]7[/C][C]0.029801[/C][C]0.2308[/C][C]0.409112[/C][/ROW]
[ROW][C]8[/C][C]-0.26561[/C][C]-2.0574[/C][C]0.022001[/C][/ROW]
[ROW][C]9[/C][C]0.008318[/C][C]0.0644[/C][C]0.474421[/C][/ROW]
[ROW][C]10[/C][C]-0.025979[/C][C]-0.2012[/C][C]0.420599[/C][/ROW]
[ROW][C]11[/C][C]0.07243[/C][C]0.561[/C][C]0.288429[/C][/ROW]
[ROW][C]12[/C][C]0.139116[/C][C]1.0776[/C][C]0.142766[/C][/ROW]
[ROW][C]13[/C][C]-0.022741[/C][C]-0.1762[/C][C]0.430384[/C][/ROW]
[ROW][C]14[/C][C]-0.05892[/C][C]-0.4564[/C][C]0.324878[/C][/ROW]
[ROW][C]15[/C][C]-0.205781[/C][C]-1.594[/C][C]0.058099[/C][/ROW]
[ROW][C]16[/C][C]-0.008756[/C][C]-0.0678[/C][C]0.473076[/C][/ROW]
[ROW][C]17[/C][C]0.061511[/C][C]0.4765[/C][C]0.317738[/C][/ROW]
[ROW][C]18[/C][C]0.022431[/C][C]0.1738[/C][C]0.431323[/C][/ROW]
[ROW][C]19[/C][C]0.092957[/C][C]0.72[/C][C]0.237146[/C][/ROW]
[ROW][C]20[/C][C]-0.081513[/C][C]-0.6314[/C][C]0.265089[/C][/ROW]
[ROW][C]21[/C][C]0.025091[/C][C]0.1944[/C][C]0.423277[/C][/ROW]
[ROW][C]22[/C][C]-0.0761[/C][C]-0.5895[/C][C]0.27888[/C][/ROW]
[ROW][C]23[/C][C]0.010231[/C][C]0.0793[/C][C]0.468548[/C][/ROW]
[ROW][C]24[/C][C]0.006792[/C][C]0.0526[/C][C]0.479109[/C][/ROW]
[ROW][C]25[/C][C]-0.07747[/C][C]-0.6001[/C][C]0.275356[/C][/ROW]
[ROW][C]26[/C][C]-0.181363[/C][C]-1.4048[/C][C]0.082614[/C][/ROW]
[ROW][C]27[/C][C]0.003588[/C][C]0.0278[/C][C]0.488958[/C][/ROW]
[ROW][C]28[/C][C]0.076108[/C][C]0.5895[/C][C]0.278861[/C][/ROW]
[ROW][C]29[/C][C]-0.036071[/C][C]-0.2794[/C][C]0.390449[/C][/ROW]
[ROW][C]30[/C][C]-0.005305[/C][C]-0.0411[/C][C]0.48368[/C][/ROW]
[ROW][C]31[/C][C]-0.012713[/C][C]-0.0985[/C][C]0.460942[/C][/ROW]
[ROW][C]32[/C][C]-0.069983[/C][C]-0.5421[/C][C]0.294884[/C][/ROW]
[ROW][C]33[/C][C]0.160714[/C][C]1.2449[/C][C]0.109007[/C][/ROW]
[ROW][C]34[/C][C]-0.166323[/C][C]-1.2883[/C][C]0.101288[/C][/ROW]
[ROW][C]35[/C][C]0.016499[/C][C]0.1278[/C][C]0.449367[/C][/ROW]
[ROW][C]36[/C][C]0.008836[/C][C]0.0684[/C][C]0.472829[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61135&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61135&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
10.4497823.4840.000464
20.2336531.80990.037663
30.3580692.77360.003689
4-0.092624-0.71750.237937
50.187281.45070.07604
60.1619431.25440.10728
70.0298010.23080.409112
8-0.26561-2.05740.022001
90.0083180.06440.474421
10-0.025979-0.20120.420599
110.072430.5610.288429
120.1391161.07760.142766
13-0.022741-0.17620.430384
14-0.05892-0.45640.324878
15-0.205781-1.5940.058099
16-0.008756-0.06780.473076
170.0615110.47650.317738
180.0224310.17380.431323
190.0929570.720.237146
20-0.081513-0.63140.265089
210.0250910.19440.423277
22-0.0761-0.58950.27888
230.0102310.07930.468548
240.0067920.05260.479109
25-0.07747-0.60010.275356
26-0.181363-1.40480.082614
270.0035880.02780.488958
280.0761080.58950.278861
29-0.036071-0.27940.390449
30-0.005305-0.04110.48368
31-0.012713-0.09850.460942
32-0.069983-0.54210.294884
330.1607141.24490.109007
34-0.166323-1.28830.101288
350.0164990.12780.449367
360.0088360.06840.472829


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 ;
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')