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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 computationWed, 29 Dec 2010 12:52:24 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/29/t1293627059ti7lxumvr256xsw.htm/, Retrieved Fri, 03 May 2024 10:48:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=116772, Retrieved Fri, 03 May 2024 10:48:16 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact180
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] [] [2009-11-24 09:55:25] [fef2f8976fa1eef1b54e2cee317fe737]
-    D          [(Partial) Autocorrelation Function] [] [2009-12-18 11:14:21] [fef2f8976fa1eef1b54e2cee317fe737]
- R               [(Partial) Autocorrelation Function] [Paper: ACF] [2010-12-22 20:09:28] [29e492448d11757ae0fad5ef6e7f8e86]
-    D                [(Partial) Autocorrelation Function] [] [2010-12-29 12:52:24] [e180d4cd19004beeddc12e67012247dc] [Current]
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Dataseries X:
00,521505
00,424828
00,425031
00,477194
00,828021
00,615619
00,366627
00,430888
00,281029
00,464625
00,269395
00,577905
00,566115
00,507758
00,750718
00,680840
00,766109
00,456147
00,497750
00,419327
00,609551
00,457337
00,570548
00,347900
00,387499
00,582429
00,239103
00,236745
00,262616
00,424093
00,365275
00,375076
00,409006
00,389168
00,240261
00,158950
00,439337
00,509468
00,374347
00,433983
00,413056
00,328893
00,518665
00,548650
00,546911
00,496349
00,530893
00,595776
00,557058
00,573133
00,500542
00,543127
00,559366
00,691169
00,440349
00,567666
00,596911
00,473554
00,592394
00,597556
00,633413
00,605712
00,704611
00,480526
00,702686
00,700902
00,603085
00,698092
00,597656
00,802342
00,601711
00,599313
00,602563
00,701663
00,499571
00,498092
00,497569
00,600183
00,333954
00,274437
00,320943
00,540667
00,405021
00,288596
00,327594
00,313261
00,257556
00,213839
00,186186
00,159271




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 2 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116772&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116772&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116772&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 time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.5607675.31990
20.4619694.38261.6e-05
30.3762853.56980.000288
40.3997233.79210.000135
50.3239173.07290.001402
60.2104421.99640.024455
70.2553352.42230.008713
80.1872191.77610.039547
90.2100611.99280.024655
100.0540470.51270.304695
110.0876210.83120.204016
12-0.064818-0.61490.27008
13-0.095318-0.90430.184134
14-0.152669-1.44830.075497
15-0.169849-1.61130.055305
16-0.119221-1.1310.130523
17-0.139763-1.32590.094114
18-0.18842-1.78750.038611
19-0.284417-2.69820.004162
20-0.222369-2.10960.018835
21-0.206262-1.95680.026737
22-0.202727-1.92320.028806
23-0.254073-2.41040.008986
24-0.228585-2.16850.016377
25-0.182608-1.73240.043317
26-0.198851-1.88650.031228
27-0.22658-2.14950.017138
28-0.143215-1.35870.088826
29-0.198831-1.88630.031241
30-0.241025-2.28660.012284
31-0.203283-1.92850.028472
32-0.185347-1.75840.041043
33-0.138359-1.31260.09633
34-0.234157-2.22140.014416
35-0.20783-1.97160.02586
36-0.238558-2.26320.013015

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.560767 & 5.3199 & 0 \tabularnewline
2 & 0.461969 & 4.3826 & 1.6e-05 \tabularnewline
3 & 0.376285 & 3.5698 & 0.000288 \tabularnewline
4 & 0.399723 & 3.7921 & 0.000135 \tabularnewline
5 & 0.323917 & 3.0729 & 0.001402 \tabularnewline
6 & 0.210442 & 1.9964 & 0.024455 \tabularnewline
7 & 0.255335 & 2.4223 & 0.008713 \tabularnewline
8 & 0.187219 & 1.7761 & 0.039547 \tabularnewline
9 & 0.210061 & 1.9928 & 0.024655 \tabularnewline
10 & 0.054047 & 0.5127 & 0.304695 \tabularnewline
11 & 0.087621 & 0.8312 & 0.204016 \tabularnewline
12 & -0.064818 & -0.6149 & 0.27008 \tabularnewline
13 & -0.095318 & -0.9043 & 0.184134 \tabularnewline
14 & -0.152669 & -1.4483 & 0.075497 \tabularnewline
15 & -0.169849 & -1.6113 & 0.055305 \tabularnewline
16 & -0.119221 & -1.131 & 0.130523 \tabularnewline
17 & -0.139763 & -1.3259 & 0.094114 \tabularnewline
18 & -0.18842 & -1.7875 & 0.038611 \tabularnewline
19 & -0.284417 & -2.6982 & 0.004162 \tabularnewline
20 & -0.222369 & -2.1096 & 0.018835 \tabularnewline
21 & -0.206262 & -1.9568 & 0.026737 \tabularnewline
22 & -0.202727 & -1.9232 & 0.028806 \tabularnewline
23 & -0.254073 & -2.4104 & 0.008986 \tabularnewline
24 & -0.228585 & -2.1685 & 0.016377 \tabularnewline
25 & -0.182608 & -1.7324 & 0.043317 \tabularnewline
26 & -0.198851 & -1.8865 & 0.031228 \tabularnewline
27 & -0.22658 & -2.1495 & 0.017138 \tabularnewline
28 & -0.143215 & -1.3587 & 0.088826 \tabularnewline
29 & -0.198831 & -1.8863 & 0.031241 \tabularnewline
30 & -0.241025 & -2.2866 & 0.012284 \tabularnewline
31 & -0.203283 & -1.9285 & 0.028472 \tabularnewline
32 & -0.185347 & -1.7584 & 0.041043 \tabularnewline
33 & -0.138359 & -1.3126 & 0.09633 \tabularnewline
34 & -0.234157 & -2.2214 & 0.014416 \tabularnewline
35 & -0.20783 & -1.9716 & 0.02586 \tabularnewline
36 & -0.238558 & -2.2632 & 0.013015 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116772&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]0.560767[/C][C]5.3199[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.461969[/C][C]4.3826[/C][C]1.6e-05[/C][/ROW]
[ROW][C]3[/C][C]0.376285[/C][C]3.5698[/C][C]0.000288[/C][/ROW]
[ROW][C]4[/C][C]0.399723[/C][C]3.7921[/C][C]0.000135[/C][/ROW]
[ROW][C]5[/C][C]0.323917[/C][C]3.0729[/C][C]0.001402[/C][/ROW]
[ROW][C]6[/C][C]0.210442[/C][C]1.9964[/C][C]0.024455[/C][/ROW]
[ROW][C]7[/C][C]0.255335[/C][C]2.4223[/C][C]0.008713[/C][/ROW]
[ROW][C]8[/C][C]0.187219[/C][C]1.7761[/C][C]0.039547[/C][/ROW]
[ROW][C]9[/C][C]0.210061[/C][C]1.9928[/C][C]0.024655[/C][/ROW]
[ROW][C]10[/C][C]0.054047[/C][C]0.5127[/C][C]0.304695[/C][/ROW]
[ROW][C]11[/C][C]0.087621[/C][C]0.8312[/C][C]0.204016[/C][/ROW]
[ROW][C]12[/C][C]-0.064818[/C][C]-0.6149[/C][C]0.27008[/C][/ROW]
[ROW][C]13[/C][C]-0.095318[/C][C]-0.9043[/C][C]0.184134[/C][/ROW]
[ROW][C]14[/C][C]-0.152669[/C][C]-1.4483[/C][C]0.075497[/C][/ROW]
[ROW][C]15[/C][C]-0.169849[/C][C]-1.6113[/C][C]0.055305[/C][/ROW]
[ROW][C]16[/C][C]-0.119221[/C][C]-1.131[/C][C]0.130523[/C][/ROW]
[ROW][C]17[/C][C]-0.139763[/C][C]-1.3259[/C][C]0.094114[/C][/ROW]
[ROW][C]18[/C][C]-0.18842[/C][C]-1.7875[/C][C]0.038611[/C][/ROW]
[ROW][C]19[/C][C]-0.284417[/C][C]-2.6982[/C][C]0.004162[/C][/ROW]
[ROW][C]20[/C][C]-0.222369[/C][C]-2.1096[/C][C]0.018835[/C][/ROW]
[ROW][C]21[/C][C]-0.206262[/C][C]-1.9568[/C][C]0.026737[/C][/ROW]
[ROW][C]22[/C][C]-0.202727[/C][C]-1.9232[/C][C]0.028806[/C][/ROW]
[ROW][C]23[/C][C]-0.254073[/C][C]-2.4104[/C][C]0.008986[/C][/ROW]
[ROW][C]24[/C][C]-0.228585[/C][C]-2.1685[/C][C]0.016377[/C][/ROW]
[ROW][C]25[/C][C]-0.182608[/C][C]-1.7324[/C][C]0.043317[/C][/ROW]
[ROW][C]26[/C][C]-0.198851[/C][C]-1.8865[/C][C]0.031228[/C][/ROW]
[ROW][C]27[/C][C]-0.22658[/C][C]-2.1495[/C][C]0.017138[/C][/ROW]
[ROW][C]28[/C][C]-0.143215[/C][C]-1.3587[/C][C]0.088826[/C][/ROW]
[ROW][C]29[/C][C]-0.198831[/C][C]-1.8863[/C][C]0.031241[/C][/ROW]
[ROW][C]30[/C][C]-0.241025[/C][C]-2.2866[/C][C]0.012284[/C][/ROW]
[ROW][C]31[/C][C]-0.203283[/C][C]-1.9285[/C][C]0.028472[/C][/ROW]
[ROW][C]32[/C][C]-0.185347[/C][C]-1.7584[/C][C]0.041043[/C][/ROW]
[ROW][C]33[/C][C]-0.138359[/C][C]-1.3126[/C][C]0.09633[/C][/ROW]
[ROW][C]34[/C][C]-0.234157[/C][C]-2.2214[/C][C]0.014416[/C][/ROW]
[ROW][C]35[/C][C]-0.20783[/C][C]-1.9716[/C][C]0.02586[/C][/ROW]
[ROW][C]36[/C][C]-0.238558[/C][C]-2.2632[/C][C]0.013015[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116772&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116772&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
10.5607675.31990
20.4619694.38261.6e-05
30.3762853.56980.000288
40.3997233.79210.000135
50.3239173.07290.001402
60.2104421.99640.024455
70.2553352.42230.008713
80.1872191.77610.039547
90.2100611.99280.024655
100.0540470.51270.304695
110.0876210.83120.204016
12-0.064818-0.61490.27008
13-0.095318-0.90430.184134
14-0.152669-1.44830.075497
15-0.169849-1.61130.055305
16-0.119221-1.1310.130523
17-0.139763-1.32590.094114
18-0.18842-1.78750.038611
19-0.284417-2.69820.004162
20-0.222369-2.10960.018835
21-0.206262-1.95680.026737
22-0.202727-1.92320.028806
23-0.254073-2.41040.008986
24-0.228585-2.16850.016377
25-0.182608-1.73240.043317
26-0.198851-1.88650.031228
27-0.22658-2.14950.017138
28-0.143215-1.35870.088826
29-0.198831-1.88630.031241
30-0.241025-2.28660.012284
31-0.203283-1.92850.028472
32-0.185347-1.75840.041043
33-0.138359-1.31260.09633
34-0.234157-2.22140.014416
35-0.20783-1.97160.02586
36-0.238558-2.26320.013015







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.5607675.31990
20.2151712.04130.022075
30.0800080.7590.224912
40.1733241.64430.051802
50.0065810.06240.475177
6-0.104434-0.99070.162232
70.1262391.19760.117108
8-0.052271-0.49590.310593
90.0598380.56770.285836
10-0.161995-1.53680.063922
110.0335720.31850.375425
12-0.22216-2.10760.018924
13-0.06534-0.61990.268456
14-0.080095-0.75990.224665
15-0.028048-0.26610.39539
160.0595980.56540.286604
170.0539890.51220.304887
18-0.145252-1.3780.085813
19-0.100919-0.95740.170466
200.0023440.02220.491153
210.0739790.70180.2423
22-0.013081-0.12410.450759
23-0.029928-0.28390.38856
24-0.046865-0.44460.328838
25-0.01962-0.18610.426382
26-0.053241-0.50510.307366
27-0.079411-0.75340.226599
280.1252421.18810.118951
29-0.157095-1.49030.069817
30-0.10856-1.02990.15291
31-0.002353-0.02230.491119
32-0.0821-0.77890.21905
330.0013090.01240.495059
34-0.135716-1.28750.100608
35-0.039111-0.3710.355741
36-0.113675-1.07840.141864

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.560767 & 5.3199 & 0 \tabularnewline
2 & 0.215171 & 2.0413 & 0.022075 \tabularnewline
3 & 0.080008 & 0.759 & 0.224912 \tabularnewline
4 & 0.173324 & 1.6443 & 0.051802 \tabularnewline
5 & 0.006581 & 0.0624 & 0.475177 \tabularnewline
6 & -0.104434 & -0.9907 & 0.162232 \tabularnewline
7 & 0.126239 & 1.1976 & 0.117108 \tabularnewline
8 & -0.052271 & -0.4959 & 0.310593 \tabularnewline
9 & 0.059838 & 0.5677 & 0.285836 \tabularnewline
10 & -0.161995 & -1.5368 & 0.063922 \tabularnewline
11 & 0.033572 & 0.3185 & 0.375425 \tabularnewline
12 & -0.22216 & -2.1076 & 0.018924 \tabularnewline
13 & -0.06534 & -0.6199 & 0.268456 \tabularnewline
14 & -0.080095 & -0.7599 & 0.224665 \tabularnewline
15 & -0.028048 & -0.2661 & 0.39539 \tabularnewline
16 & 0.059598 & 0.5654 & 0.286604 \tabularnewline
17 & 0.053989 & 0.5122 & 0.304887 \tabularnewline
18 & -0.145252 & -1.378 & 0.085813 \tabularnewline
19 & -0.100919 & -0.9574 & 0.170466 \tabularnewline
20 & 0.002344 & 0.0222 & 0.491153 \tabularnewline
21 & 0.073979 & 0.7018 & 0.2423 \tabularnewline
22 & -0.013081 & -0.1241 & 0.450759 \tabularnewline
23 & -0.029928 & -0.2839 & 0.38856 \tabularnewline
24 & -0.046865 & -0.4446 & 0.328838 \tabularnewline
25 & -0.01962 & -0.1861 & 0.426382 \tabularnewline
26 & -0.053241 & -0.5051 & 0.307366 \tabularnewline
27 & -0.079411 & -0.7534 & 0.226599 \tabularnewline
28 & 0.125242 & 1.1881 & 0.118951 \tabularnewline
29 & -0.157095 & -1.4903 & 0.069817 \tabularnewline
30 & -0.10856 & -1.0299 & 0.15291 \tabularnewline
31 & -0.002353 & -0.0223 & 0.491119 \tabularnewline
32 & -0.0821 & -0.7789 & 0.21905 \tabularnewline
33 & 0.001309 & 0.0124 & 0.495059 \tabularnewline
34 & -0.135716 & -1.2875 & 0.100608 \tabularnewline
35 & -0.039111 & -0.371 & 0.355741 \tabularnewline
36 & -0.113675 & -1.0784 & 0.141864 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116772&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]0.560767[/C][C]5.3199[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.215171[/C][C]2.0413[/C][C]0.022075[/C][/ROW]
[ROW][C]3[/C][C]0.080008[/C][C]0.759[/C][C]0.224912[/C][/ROW]
[ROW][C]4[/C][C]0.173324[/C][C]1.6443[/C][C]0.051802[/C][/ROW]
[ROW][C]5[/C][C]0.006581[/C][C]0.0624[/C][C]0.475177[/C][/ROW]
[ROW][C]6[/C][C]-0.104434[/C][C]-0.9907[/C][C]0.162232[/C][/ROW]
[ROW][C]7[/C][C]0.126239[/C][C]1.1976[/C][C]0.117108[/C][/ROW]
[ROW][C]8[/C][C]-0.052271[/C][C]-0.4959[/C][C]0.310593[/C][/ROW]
[ROW][C]9[/C][C]0.059838[/C][C]0.5677[/C][C]0.285836[/C][/ROW]
[ROW][C]10[/C][C]-0.161995[/C][C]-1.5368[/C][C]0.063922[/C][/ROW]
[ROW][C]11[/C][C]0.033572[/C][C]0.3185[/C][C]0.375425[/C][/ROW]
[ROW][C]12[/C][C]-0.22216[/C][C]-2.1076[/C][C]0.018924[/C][/ROW]
[ROW][C]13[/C][C]-0.06534[/C][C]-0.6199[/C][C]0.268456[/C][/ROW]
[ROW][C]14[/C][C]-0.080095[/C][C]-0.7599[/C][C]0.224665[/C][/ROW]
[ROW][C]15[/C][C]-0.028048[/C][C]-0.2661[/C][C]0.39539[/C][/ROW]
[ROW][C]16[/C][C]0.059598[/C][C]0.5654[/C][C]0.286604[/C][/ROW]
[ROW][C]17[/C][C]0.053989[/C][C]0.5122[/C][C]0.304887[/C][/ROW]
[ROW][C]18[/C][C]-0.145252[/C][C]-1.378[/C][C]0.085813[/C][/ROW]
[ROW][C]19[/C][C]-0.100919[/C][C]-0.9574[/C][C]0.170466[/C][/ROW]
[ROW][C]20[/C][C]0.002344[/C][C]0.0222[/C][C]0.491153[/C][/ROW]
[ROW][C]21[/C][C]0.073979[/C][C]0.7018[/C][C]0.2423[/C][/ROW]
[ROW][C]22[/C][C]-0.013081[/C][C]-0.1241[/C][C]0.450759[/C][/ROW]
[ROW][C]23[/C][C]-0.029928[/C][C]-0.2839[/C][C]0.38856[/C][/ROW]
[ROW][C]24[/C][C]-0.046865[/C][C]-0.4446[/C][C]0.328838[/C][/ROW]
[ROW][C]25[/C][C]-0.01962[/C][C]-0.1861[/C][C]0.426382[/C][/ROW]
[ROW][C]26[/C][C]-0.053241[/C][C]-0.5051[/C][C]0.307366[/C][/ROW]
[ROW][C]27[/C][C]-0.079411[/C][C]-0.7534[/C][C]0.226599[/C][/ROW]
[ROW][C]28[/C][C]0.125242[/C][C]1.1881[/C][C]0.118951[/C][/ROW]
[ROW][C]29[/C][C]-0.157095[/C][C]-1.4903[/C][C]0.069817[/C][/ROW]
[ROW][C]30[/C][C]-0.10856[/C][C]-1.0299[/C][C]0.15291[/C][/ROW]
[ROW][C]31[/C][C]-0.002353[/C][C]-0.0223[/C][C]0.491119[/C][/ROW]
[ROW][C]32[/C][C]-0.0821[/C][C]-0.7789[/C][C]0.21905[/C][/ROW]
[ROW][C]33[/C][C]0.001309[/C][C]0.0124[/C][C]0.495059[/C][/ROW]
[ROW][C]34[/C][C]-0.135716[/C][C]-1.2875[/C][C]0.100608[/C][/ROW]
[ROW][C]35[/C][C]-0.039111[/C][C]-0.371[/C][C]0.355741[/C][/ROW]
[ROW][C]36[/C][C]-0.113675[/C][C]-1.0784[/C][C]0.141864[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116772&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116772&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
10.5607675.31990
20.2151712.04130.022075
30.0800080.7590.224912
40.1733241.64430.051802
50.0065810.06240.475177
6-0.104434-0.99070.162232
70.1262391.19760.117108
8-0.052271-0.49590.310593
90.0598380.56770.285836
10-0.161995-1.53680.063922
110.0335720.31850.375425
12-0.22216-2.10760.018924
13-0.06534-0.61990.268456
14-0.080095-0.75990.224665
15-0.028048-0.26610.39539
160.0595980.56540.286604
170.0539890.51220.304887
18-0.145252-1.3780.085813
19-0.100919-0.95740.170466
200.0023440.02220.491153
210.0739790.70180.2423
22-0.013081-0.12410.450759
23-0.029928-0.28390.38856
24-0.046865-0.44460.328838
25-0.01962-0.18610.426382
26-0.053241-0.50510.307366
27-0.079411-0.75340.226599
280.1252421.18810.118951
29-0.157095-1.49030.069817
30-0.10856-1.02990.15291
31-0.002353-0.02230.491119
32-0.0821-0.77890.21905
330.0013090.01240.495059
34-0.135716-1.28750.100608
35-0.039111-0.3710.355741
36-0.113675-1.07840.141864



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 = ;
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 (par8 != '') par8 <- as.numeric(par8)
ox <- x
if (par8 == '') {
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
} else {
x <- log(x,base=par8)
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='picts.png')
op <- par(mfrow=c(2,1))
plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')
if (par8=='') {
mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
} else {
mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
}
plot(x,type='l', main=mytitle,xlab='time',ylab='value')
par(op)
dev.off()
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)
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')