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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 08:53:36 -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/t1259337488xaygdk9bubbbngp.htm/, Retrieved Mon, 29 Apr 2024 03:55:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60923, Retrieved Mon, 29 Apr 2024 03:55:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsWS8ACFMLDG
Estimated Impact143

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: autoc...] [2009-11-27 15:53:36] [3d2053c5f7c50d3c075d87ce0bd87294] [Current]
-   P             [(Partial) Autocorrelation Function] [Workshop 8: autoc...] [2009-11-27 16:03:39] [7c2a5b25a196bd646844b8f5223c9b3e]
-   P               [(Partial) Autocorrelation Function] [Workshop 8: autoc...] [2009-11-27 16:14:31] [7c2a5b25a196bd646844b8f5223c9b3e]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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
293299

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=60923&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=60923&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60923&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
10.878837.30010
20.7207865.98730
30.6000844.98472e-06
40.5448384.52581.2e-05
50.5304084.40591.9e-05
60.4836164.01727.4e-05
70.3928013.26280.000858
80.2835652.35550.010674
90.2153461.78880.039018
100.1993221.65570.051163
110.2366781.9660.026662
120.2441392.0280.023213
130.1054490.87590.192054
14-0.03855-0.32020.374884
15-0.146037-1.21310.114619
16-0.182291-1.51420.067269
17-0.176396-1.46530.073696
18-0.199563-1.65770.05096
19-0.247217-2.05350.021906
20-0.313558-2.60460.005628
21-0.339491-2.820.003132
22-0.320788-2.66470.004794
23-0.262978-2.18450.016165
24-0.235846-1.95910.027073
25-0.314198-2.60990.005549
26-0.390678-3.24520.000906
27-0.428018-3.55540.000343
28-0.38988-3.23860.000924
29-0.335102-2.78360.003466
30-0.299632-2.48890.007615
31-0.290649-2.41430.009211
32-0.2964-2.46210.008158
33-0.267127-2.21890.014892
34-0.200655-1.66680.050047
35-0.116347-0.96650.168596
36-0.061665-0.51220.305065

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.87883 & 7.3001 & 0 \tabularnewline
2 & 0.720786 & 5.9873 & 0 \tabularnewline
3 & 0.600084 & 4.9847 & 2e-06 \tabularnewline
4 & 0.544838 & 4.5258 & 1.2e-05 \tabularnewline
5 & 0.530408 & 4.4059 & 1.9e-05 \tabularnewline
6 & 0.483616 & 4.0172 & 7.4e-05 \tabularnewline
7 & 0.392801 & 3.2628 & 0.000858 \tabularnewline
8 & 0.283565 & 2.3555 & 0.010674 \tabularnewline
9 & 0.215346 & 1.7888 & 0.039018 \tabularnewline
10 & 0.199322 & 1.6557 & 0.051163 \tabularnewline
11 & 0.236678 & 1.966 & 0.026662 \tabularnewline
12 & 0.244139 & 2.028 & 0.023213 \tabularnewline
13 & 0.105449 & 0.8759 & 0.192054 \tabularnewline
14 & -0.03855 & -0.3202 & 0.374884 \tabularnewline
15 & -0.146037 & -1.2131 & 0.114619 \tabularnewline
16 & -0.182291 & -1.5142 & 0.067269 \tabularnewline
17 & -0.176396 & -1.4653 & 0.073696 \tabularnewline
18 & -0.199563 & -1.6577 & 0.05096 \tabularnewline
19 & -0.247217 & -2.0535 & 0.021906 \tabularnewline
20 & -0.313558 & -2.6046 & 0.005628 \tabularnewline
21 & -0.339491 & -2.82 & 0.003132 \tabularnewline
22 & -0.320788 & -2.6647 & 0.004794 \tabularnewline
23 & -0.262978 & -2.1845 & 0.016165 \tabularnewline
24 & -0.235846 & -1.9591 & 0.027073 \tabularnewline
25 & -0.314198 & -2.6099 & 0.005549 \tabularnewline
26 & -0.390678 & -3.2452 & 0.000906 \tabularnewline
27 & -0.428018 & -3.5554 & 0.000343 \tabularnewline
28 & -0.38988 & -3.2386 & 0.000924 \tabularnewline
29 & -0.335102 & -2.7836 & 0.003466 \tabularnewline
30 & -0.299632 & -2.4889 & 0.007615 \tabularnewline
31 & -0.290649 & -2.4143 & 0.009211 \tabularnewline
32 & -0.2964 & -2.4621 & 0.008158 \tabularnewline
33 & -0.267127 & -2.2189 & 0.014892 \tabularnewline
34 & -0.200655 & -1.6668 & 0.050047 \tabularnewline
35 & -0.116347 & -0.9665 & 0.168596 \tabularnewline
36 & -0.061665 & -0.5122 & 0.305065 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60923&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]0.87883[/C][C]7.3001[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.720786[/C][C]5.9873[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.600084[/C][C]4.9847[/C][C]2e-06[/C][/ROW]
[ROW][C]4[/C][C]0.544838[/C][C]4.5258[/C][C]1.2e-05[/C][/ROW]
[ROW][C]5[/C][C]0.530408[/C][C]4.4059[/C][C]1.9e-05[/C][/ROW]
[ROW][C]6[/C][C]0.483616[/C][C]4.0172[/C][C]7.4e-05[/C][/ROW]
[ROW][C]7[/C][C]0.392801[/C][C]3.2628[/C][C]0.000858[/C][/ROW]
[ROW][C]8[/C][C]0.283565[/C][C]2.3555[/C][C]0.010674[/C][/ROW]
[ROW][C]9[/C][C]0.215346[/C][C]1.7888[/C][C]0.039018[/C][/ROW]
[ROW][C]10[/C][C]0.199322[/C][C]1.6557[/C][C]0.051163[/C][/ROW]
[ROW][C]11[/C][C]0.236678[/C][C]1.966[/C][C]0.026662[/C][/ROW]
[ROW][C]12[/C][C]0.244139[/C][C]2.028[/C][C]0.023213[/C][/ROW]
[ROW][C]13[/C][C]0.105449[/C][C]0.8759[/C][C]0.192054[/C][/ROW]
[ROW][C]14[/C][C]-0.03855[/C][C]-0.3202[/C][C]0.374884[/C][/ROW]
[ROW][C]15[/C][C]-0.146037[/C][C]-1.2131[/C][C]0.114619[/C][/ROW]
[ROW][C]16[/C][C]-0.182291[/C][C]-1.5142[/C][C]0.067269[/C][/ROW]
[ROW][C]17[/C][C]-0.176396[/C][C]-1.4653[/C][C]0.073696[/C][/ROW]
[ROW][C]18[/C][C]-0.199563[/C][C]-1.6577[/C][C]0.05096[/C][/ROW]
[ROW][C]19[/C][C]-0.247217[/C][C]-2.0535[/C][C]0.021906[/C][/ROW]
[ROW][C]20[/C][C]-0.313558[/C][C]-2.6046[/C][C]0.005628[/C][/ROW]
[ROW][C]21[/C][C]-0.339491[/C][C]-2.82[/C][C]0.003132[/C][/ROW]
[ROW][C]22[/C][C]-0.320788[/C][C]-2.6647[/C][C]0.004794[/C][/ROW]
[ROW][C]23[/C][C]-0.262978[/C][C]-2.1845[/C][C]0.016165[/C][/ROW]
[ROW][C]24[/C][C]-0.235846[/C][C]-1.9591[/C][C]0.027073[/C][/ROW]
[ROW][C]25[/C][C]-0.314198[/C][C]-2.6099[/C][C]0.005549[/C][/ROW]
[ROW][C]26[/C][C]-0.390678[/C][C]-3.2452[/C][C]0.000906[/C][/ROW]
[ROW][C]27[/C][C]-0.428018[/C][C]-3.5554[/C][C]0.000343[/C][/ROW]
[ROW][C]28[/C][C]-0.38988[/C][C]-3.2386[/C][C]0.000924[/C][/ROW]
[ROW][C]29[/C][C]-0.335102[/C][C]-2.7836[/C][C]0.003466[/C][/ROW]
[ROW][C]30[/C][C]-0.299632[/C][C]-2.4889[/C][C]0.007615[/C][/ROW]
[ROW][C]31[/C][C]-0.290649[/C][C]-2.4143[/C][C]0.009211[/C][/ROW]
[ROW][C]32[/C][C]-0.2964[/C][C]-2.4621[/C][C]0.008158[/C][/ROW]
[ROW][C]33[/C][C]-0.267127[/C][C]-2.2189[/C][C]0.014892[/C][/ROW]
[ROW][C]34[/C][C]-0.200655[/C][C]-1.6668[/C][C]0.050047[/C][/ROW]
[ROW][C]35[/C][C]-0.116347[/C][C]-0.9665[/C][C]0.168596[/C][/ROW]
[ROW][C]36[/C][C]-0.061665[/C][C]-0.5122[/C][C]0.305065[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60923&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60923&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
10.878837.30010
20.7207865.98730
30.6000844.98472e-06
40.5448384.52581.2e-05
50.5304084.40591.9e-05
60.4836164.01727.4e-05
70.3928013.26280.000858
80.2835652.35550.010674
90.2153461.78880.039018
100.1993221.65570.051163
110.2366781.9660.026662
120.2441392.0280.023213
130.1054490.87590.192054
14-0.03855-0.32020.374884
15-0.146037-1.21310.114619
16-0.182291-1.51420.067269
17-0.176396-1.46530.073696
18-0.199563-1.65770.05096
19-0.247217-2.05350.021906
20-0.313558-2.60460.005628
21-0.339491-2.820.003132
22-0.320788-2.66470.004794
23-0.262978-2.18450.016165
24-0.235846-1.95910.027073
25-0.314198-2.60990.005549
26-0.390678-3.24520.000906
27-0.428018-3.55540.000343
28-0.38988-3.23860.000924
29-0.335102-2.78360.003466
30-0.299632-2.48890.007615
31-0.290649-2.41430.009211
32-0.2964-2.46210.008158
33-0.267127-2.21890.014892
34-0.200655-1.66680.050047
35-0.116347-0.96650.168596
36-0.061665-0.51220.305065






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.878837.30010
2-0.226464-1.88120.032085
30.1028130.8540.198021
40.1722811.43110.078462
50.0910020.75590.226135
6-0.15133-1.2570.106488
7-0.11124-0.9240.179346
8-0.072517-0.60240.274451
90.0814160.67630.250558
100.0562120.46690.32101
110.184251.53050.065233
12-0.103184-0.85710.197176
13-0.573578-4.76455e-06
140.1337511.1110.135208
15-0.03834-0.31850.375544
16-0.033832-0.2810.389763
170.018850.15660.438017
18-0.013352-0.11090.456004
190.0680290.56510.286921
20-0.117838-0.97880.165541
210.0549210.45620.324836
22-0.006554-0.05440.478372
23-0.112915-0.93790.175773
24-0.001025-0.00850.496615
25-0.126261-1.04880.148964
260.0014540.01210.495198
270.0512280.42550.335887
280.0397210.32990.371219
29-0.104119-0.86490.195052
300.1007420.83680.202789
31-0.031046-0.25790.398629
320.0161530.13420.446827
33-0.02404-0.19970.421156
340.0683450.56770.286034
35-0.081027-0.67310.251579
360.024390.20260.420024

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.87883 & 7.3001 & 0 \tabularnewline
2 & -0.226464 & -1.8812 & 0.032085 \tabularnewline
3 & 0.102813 & 0.854 & 0.198021 \tabularnewline
4 & 0.172281 & 1.4311 & 0.078462 \tabularnewline
5 & 0.091002 & 0.7559 & 0.226135 \tabularnewline
6 & -0.15133 & -1.257 & 0.106488 \tabularnewline
7 & -0.11124 & -0.924 & 0.179346 \tabularnewline
8 & -0.072517 & -0.6024 & 0.274451 \tabularnewline
9 & 0.081416 & 0.6763 & 0.250558 \tabularnewline
10 & 0.056212 & 0.4669 & 0.32101 \tabularnewline
11 & 0.18425 & 1.5305 & 0.065233 \tabularnewline
12 & -0.103184 & -0.8571 & 0.197176 \tabularnewline
13 & -0.573578 & -4.7645 & 5e-06 \tabularnewline
14 & 0.133751 & 1.111 & 0.135208 \tabularnewline
15 & -0.03834 & -0.3185 & 0.375544 \tabularnewline
16 & -0.033832 & -0.281 & 0.389763 \tabularnewline
17 & 0.01885 & 0.1566 & 0.438017 \tabularnewline
18 & -0.013352 & -0.1109 & 0.456004 \tabularnewline
19 & 0.068029 & 0.5651 & 0.286921 \tabularnewline
20 & -0.117838 & -0.9788 & 0.165541 \tabularnewline
21 & 0.054921 & 0.4562 & 0.324836 \tabularnewline
22 & -0.006554 & -0.0544 & 0.478372 \tabularnewline
23 & -0.112915 & -0.9379 & 0.175773 \tabularnewline
24 & -0.001025 & -0.0085 & 0.496615 \tabularnewline
25 & -0.126261 & -1.0488 & 0.148964 \tabularnewline
26 & 0.001454 & 0.0121 & 0.495198 \tabularnewline
27 & 0.051228 & 0.4255 & 0.335887 \tabularnewline
28 & 0.039721 & 0.3299 & 0.371219 \tabularnewline
29 & -0.104119 & -0.8649 & 0.195052 \tabularnewline
30 & 0.100742 & 0.8368 & 0.202789 \tabularnewline
31 & -0.031046 & -0.2579 & 0.398629 \tabularnewline
32 & 0.016153 & 0.1342 & 0.446827 \tabularnewline
33 & -0.02404 & -0.1997 & 0.421156 \tabularnewline
34 & 0.068345 & 0.5677 & 0.286034 \tabularnewline
35 & -0.081027 & -0.6731 & 0.251579 \tabularnewline
36 & 0.02439 & 0.2026 & 0.420024 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60923&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]0.87883[/C][C]7.3001[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.226464[/C][C]-1.8812[/C][C]0.032085[/C][/ROW]
[ROW][C]3[/C][C]0.102813[/C][C]0.854[/C][C]0.198021[/C][/ROW]
[ROW][C]4[/C][C]0.172281[/C][C]1.4311[/C][C]0.078462[/C][/ROW]
[ROW][C]5[/C][C]0.091002[/C][C]0.7559[/C][C]0.226135[/C][/ROW]
[ROW][C]6[/C][C]-0.15133[/C][C]-1.257[/C][C]0.106488[/C][/ROW]
[ROW][C]7[/C][C]-0.11124[/C][C]-0.924[/C][C]0.179346[/C][/ROW]
[ROW][C]8[/C][C]-0.072517[/C][C]-0.6024[/C][C]0.274451[/C][/ROW]
[ROW][C]9[/C][C]0.081416[/C][C]0.6763[/C][C]0.250558[/C][/ROW]
[ROW][C]10[/C][C]0.056212[/C][C]0.4669[/C][C]0.32101[/C][/ROW]
[ROW][C]11[/C][C]0.18425[/C][C]1.5305[/C][C]0.065233[/C][/ROW]
[ROW][C]12[/C][C]-0.103184[/C][C]-0.8571[/C][C]0.197176[/C][/ROW]
[ROW][C]13[/C][C]-0.573578[/C][C]-4.7645[/C][C]5e-06[/C][/ROW]
[ROW][C]14[/C][C]0.133751[/C][C]1.111[/C][C]0.135208[/C][/ROW]
[ROW][C]15[/C][C]-0.03834[/C][C]-0.3185[/C][C]0.375544[/C][/ROW]
[ROW][C]16[/C][C]-0.033832[/C][C]-0.281[/C][C]0.389763[/C][/ROW]
[ROW][C]17[/C][C]0.01885[/C][C]0.1566[/C][C]0.438017[/C][/ROW]
[ROW][C]18[/C][C]-0.013352[/C][C]-0.1109[/C][C]0.456004[/C][/ROW]
[ROW][C]19[/C][C]0.068029[/C][C]0.5651[/C][C]0.286921[/C][/ROW]
[ROW][C]20[/C][C]-0.117838[/C][C]-0.9788[/C][C]0.165541[/C][/ROW]
[ROW][C]21[/C][C]0.054921[/C][C]0.4562[/C][C]0.324836[/C][/ROW]
[ROW][C]22[/C][C]-0.006554[/C][C]-0.0544[/C][C]0.478372[/C][/ROW]
[ROW][C]23[/C][C]-0.112915[/C][C]-0.9379[/C][C]0.175773[/C][/ROW]
[ROW][C]24[/C][C]-0.001025[/C][C]-0.0085[/C][C]0.496615[/C][/ROW]
[ROW][C]25[/C][C]-0.126261[/C][C]-1.0488[/C][C]0.148964[/C][/ROW]
[ROW][C]26[/C][C]0.001454[/C][C]0.0121[/C][C]0.495198[/C][/ROW]
[ROW][C]27[/C][C]0.051228[/C][C]0.4255[/C][C]0.335887[/C][/ROW]
[ROW][C]28[/C][C]0.039721[/C][C]0.3299[/C][C]0.371219[/C][/ROW]
[ROW][C]29[/C][C]-0.104119[/C][C]-0.8649[/C][C]0.195052[/C][/ROW]
[ROW][C]30[/C][C]0.100742[/C][C]0.8368[/C][C]0.202789[/C][/ROW]
[ROW][C]31[/C][C]-0.031046[/C][C]-0.2579[/C][C]0.398629[/C][/ROW]
[ROW][C]32[/C][C]0.016153[/C][C]0.1342[/C][C]0.446827[/C][/ROW]
[ROW][C]33[/C][C]-0.02404[/C][C]-0.1997[/C][C]0.421156[/C][/ROW]
[ROW][C]34[/C][C]0.068345[/C][C]0.5677[/C][C]0.286034[/C][/ROW]
[ROW][C]35[/C][C]-0.081027[/C][C]-0.6731[/C][C]0.251579[/C][/ROW]
[ROW][C]36[/C][C]0.02439[/C][C]0.2026[/C][C]0.420024[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60923&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60923&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
10.878837.30010
2-0.226464-1.88120.032085
30.1028130.8540.198021
40.1722811.43110.078462
50.0910020.75590.226135
6-0.15133-1.2570.106488
7-0.11124-0.9240.179346
8-0.072517-0.60240.274451
90.0814160.67630.250558
100.0562120.46690.32101
110.184251.53050.065233
12-0.103184-0.85710.197176
13-0.573578-4.76455e-06
140.1337511.1110.135208
15-0.03834-0.31850.375544
16-0.033832-0.2810.389763
170.018850.15660.438017
18-0.013352-0.11090.456004
190.0680290.56510.286921
20-0.117838-0.97880.165541
210.0549210.45620.324836
22-0.006554-0.05440.478372
23-0.112915-0.93790.175773
24-0.001025-0.00850.496615
25-0.126261-1.04880.148964
260.0014540.01210.495198
270.0512280.42550.335887
280.0397210.32990.371219
29-0.104119-0.86490.195052
300.1007420.83680.202789
31-0.031046-0.25790.398629
320.0161530.13420.446827
33-0.02404-0.19970.421156
340.0683450.56770.286034
35-0.081027-0.67310.251579
360.024390.20260.420024


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')