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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 computationThu, 10 Dec 2009 14:27:59 -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/10/t1260480551cl9k7k3rzdvfli7.htm/, Retrieved Tue, 23 Apr 2024 11:46:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=65810, Retrieved Tue, 23 Apr 2024 11:46:49 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact129
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]
- R PD          [(Partial) Autocorrelation Function] [Workshop9 R2 blog 2] [2009-12-10 21:27:59] [5ed0eef5d4509bbfdac0ae6d87f3b4bf] [Current]
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Dataseries X:
106370
109375
116476
123297
114813
117925
126466
131235
120546
123791
129813
133463
122987
125418
130199
133016
121454
122044
128313
131556
120027
123001
130111
132524
123742
124931
133646
136557
127509
128945
137191
139716
129083
131604
139413
143125
133948
137116
144864
149277
138796
143258
150034
154708
144888
148762
156500
161088
152772
158011
163318
169969
162269
165765
170600
174681
166364
170240
176150
182056
172218
177856
182253
188090
176863
183273
187969
194650
183036
189516
193805
200499
188142
193732
197126
205140
191751
196700
199784
207360
196101
200824
205743
212489
200810
203683
207286
210910
194915
217920




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=65810&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=65810&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65810&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
1-0.149984-1.38280.085177
2-0.04621-0.4260.335579
3-0.007534-0.06950.472393
4-0.104641-0.96470.168705
5-0.018494-0.17050.432508
6-0.051415-0.4740.318351
70.0550960.5080.3064
8-0.018639-0.17180.431986
90.0808710.74560.228983
100.002930.0270.489258
11-0.047182-0.4350.332333
12-0.013686-0.12620.449943
13-0.039437-0.36360.358532
140.0331660.30580.380262
150.0274580.25320.400381
16-0.058068-0.53540.296898
17-0.016865-0.15550.438402
180.0030740.02830.488728
19-0.043772-0.40360.343775
20-0.007775-0.07170.47151
21-0.015051-0.13880.444983
220.0418650.3860.350239
230.0377510.3480.364334
240.0499090.46010.323297
25-0.049393-0.45540.324998
26-0.031797-0.29320.385058
27-0.08934-0.82370.206216
280.0616690.56860.285576
29-0.10832-0.99870.160397
300.0883870.81490.208708
310.039750.36650.357461
320.0326360.30090.382116
330.002710.0250.490064
34-0.10051-0.92670.178365
35-0.015218-0.14030.444376
36-0.09686-0.8930.187188

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.149984 & -1.3828 & 0.085177 \tabularnewline
2 & -0.04621 & -0.426 & 0.335579 \tabularnewline
3 & -0.007534 & -0.0695 & 0.472393 \tabularnewline
4 & -0.104641 & -0.9647 & 0.168705 \tabularnewline
5 & -0.018494 & -0.1705 & 0.432508 \tabularnewline
6 & -0.051415 & -0.474 & 0.318351 \tabularnewline
7 & 0.055096 & 0.508 & 0.3064 \tabularnewline
8 & -0.018639 & -0.1718 & 0.431986 \tabularnewline
9 & 0.080871 & 0.7456 & 0.228983 \tabularnewline
10 & 0.00293 & 0.027 & 0.489258 \tabularnewline
11 & -0.047182 & -0.435 & 0.332333 \tabularnewline
12 & -0.013686 & -0.1262 & 0.449943 \tabularnewline
13 & -0.039437 & -0.3636 & 0.358532 \tabularnewline
14 & 0.033166 & 0.3058 & 0.380262 \tabularnewline
15 & 0.027458 & 0.2532 & 0.400381 \tabularnewline
16 & -0.058068 & -0.5354 & 0.296898 \tabularnewline
17 & -0.016865 & -0.1555 & 0.438402 \tabularnewline
18 & 0.003074 & 0.0283 & 0.488728 \tabularnewline
19 & -0.043772 & -0.4036 & 0.343775 \tabularnewline
20 & -0.007775 & -0.0717 & 0.47151 \tabularnewline
21 & -0.015051 & -0.1388 & 0.444983 \tabularnewline
22 & 0.041865 & 0.386 & 0.350239 \tabularnewline
23 & 0.037751 & 0.348 & 0.364334 \tabularnewline
24 & 0.049909 & 0.4601 & 0.323297 \tabularnewline
25 & -0.049393 & -0.4554 & 0.324998 \tabularnewline
26 & -0.031797 & -0.2932 & 0.385058 \tabularnewline
27 & -0.08934 & -0.8237 & 0.206216 \tabularnewline
28 & 0.061669 & 0.5686 & 0.285576 \tabularnewline
29 & -0.10832 & -0.9987 & 0.160397 \tabularnewline
30 & 0.088387 & 0.8149 & 0.208708 \tabularnewline
31 & 0.03975 & 0.3665 & 0.357461 \tabularnewline
32 & 0.032636 & 0.3009 & 0.382116 \tabularnewline
33 & 0.00271 & 0.025 & 0.490064 \tabularnewline
34 & -0.10051 & -0.9267 & 0.178365 \tabularnewline
35 & -0.015218 & -0.1403 & 0.444376 \tabularnewline
36 & -0.09686 & -0.893 & 0.187188 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65810&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]-0.149984[/C][C]-1.3828[/C][C]0.085177[/C][/ROW]
[ROW][C]2[/C][C]-0.04621[/C][C]-0.426[/C][C]0.335579[/C][/ROW]
[ROW][C]3[/C][C]-0.007534[/C][C]-0.0695[/C][C]0.472393[/C][/ROW]
[ROW][C]4[/C][C]-0.104641[/C][C]-0.9647[/C][C]0.168705[/C][/ROW]
[ROW][C]5[/C][C]-0.018494[/C][C]-0.1705[/C][C]0.432508[/C][/ROW]
[ROW][C]6[/C][C]-0.051415[/C][C]-0.474[/C][C]0.318351[/C][/ROW]
[ROW][C]7[/C][C]0.055096[/C][C]0.508[/C][C]0.3064[/C][/ROW]
[ROW][C]8[/C][C]-0.018639[/C][C]-0.1718[/C][C]0.431986[/C][/ROW]
[ROW][C]9[/C][C]0.080871[/C][C]0.7456[/C][C]0.228983[/C][/ROW]
[ROW][C]10[/C][C]0.00293[/C][C]0.027[/C][C]0.489258[/C][/ROW]
[ROW][C]11[/C][C]-0.047182[/C][C]-0.435[/C][C]0.332333[/C][/ROW]
[ROW][C]12[/C][C]-0.013686[/C][C]-0.1262[/C][C]0.449943[/C][/ROW]
[ROW][C]13[/C][C]-0.039437[/C][C]-0.3636[/C][C]0.358532[/C][/ROW]
[ROW][C]14[/C][C]0.033166[/C][C]0.3058[/C][C]0.380262[/C][/ROW]
[ROW][C]15[/C][C]0.027458[/C][C]0.2532[/C][C]0.400381[/C][/ROW]
[ROW][C]16[/C][C]-0.058068[/C][C]-0.5354[/C][C]0.296898[/C][/ROW]
[ROW][C]17[/C][C]-0.016865[/C][C]-0.1555[/C][C]0.438402[/C][/ROW]
[ROW][C]18[/C][C]0.003074[/C][C]0.0283[/C][C]0.488728[/C][/ROW]
[ROW][C]19[/C][C]-0.043772[/C][C]-0.4036[/C][C]0.343775[/C][/ROW]
[ROW][C]20[/C][C]-0.007775[/C][C]-0.0717[/C][C]0.47151[/C][/ROW]
[ROW][C]21[/C][C]-0.015051[/C][C]-0.1388[/C][C]0.444983[/C][/ROW]
[ROW][C]22[/C][C]0.041865[/C][C]0.386[/C][C]0.350239[/C][/ROW]
[ROW][C]23[/C][C]0.037751[/C][C]0.348[/C][C]0.364334[/C][/ROW]
[ROW][C]24[/C][C]0.049909[/C][C]0.4601[/C][C]0.323297[/C][/ROW]
[ROW][C]25[/C][C]-0.049393[/C][C]-0.4554[/C][C]0.324998[/C][/ROW]
[ROW][C]26[/C][C]-0.031797[/C][C]-0.2932[/C][C]0.385058[/C][/ROW]
[ROW][C]27[/C][C]-0.08934[/C][C]-0.8237[/C][C]0.206216[/C][/ROW]
[ROW][C]28[/C][C]0.061669[/C][C]0.5686[/C][C]0.285576[/C][/ROW]
[ROW][C]29[/C][C]-0.10832[/C][C]-0.9987[/C][C]0.160397[/C][/ROW]
[ROW][C]30[/C][C]0.088387[/C][C]0.8149[/C][C]0.208708[/C][/ROW]
[ROW][C]31[/C][C]0.03975[/C][C]0.3665[/C][C]0.357461[/C][/ROW]
[ROW][C]32[/C][C]0.032636[/C][C]0.3009[/C][C]0.382116[/C][/ROW]
[ROW][C]33[/C][C]0.00271[/C][C]0.025[/C][C]0.490064[/C][/ROW]
[ROW][C]34[/C][C]-0.10051[/C][C]-0.9267[/C][C]0.178365[/C][/ROW]
[ROW][C]35[/C][C]-0.015218[/C][C]-0.1403[/C][C]0.444376[/C][/ROW]
[ROW][C]36[/C][C]-0.09686[/C][C]-0.893[/C][C]0.187188[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=65810&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65810&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
1-0.149984-1.38280.085177
2-0.04621-0.4260.335579
3-0.007534-0.06950.472393
4-0.104641-0.96470.168705
5-0.018494-0.17050.432508
6-0.051415-0.4740.318351
70.0550960.5080.3064
8-0.018639-0.17180.431986
90.0808710.74560.228983
100.002930.0270.489258
11-0.047182-0.4350.332333
12-0.013686-0.12620.449943
13-0.039437-0.36360.358532
140.0331660.30580.380262
150.0274580.25320.400381
16-0.058068-0.53540.296898
17-0.016865-0.15550.438402
180.0030740.02830.488728
19-0.043772-0.40360.343775
20-0.007775-0.07170.47151
21-0.015051-0.13880.444983
220.0418650.3860.350239
230.0377510.3480.364334
240.0499090.46010.323297
25-0.049393-0.45540.324998
26-0.031797-0.29320.385058
27-0.08934-0.82370.206216
280.0616690.56860.285576
29-0.10832-0.99870.160397
300.0883870.81490.208708
310.039750.36650.357461
320.0326360.30090.382116
330.002710.0250.490064
34-0.10051-0.92670.178365
35-0.015218-0.14030.444376
36-0.09686-0.8930.187188







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.149984-1.38280.085177
2-0.070286-0.6480.259363
3-0.02621-0.24160.404819
4-0.116499-1.07410.142916
5-0.058394-0.53840.295866
6-0.082197-0.75780.225327
70.0230440.21250.41613
8-0.030872-0.28460.388311
90.0693890.63970.262032
100.0120770.11130.455802
11-0.031245-0.28810.387001
12-0.027587-0.25430.399925
13-0.032565-0.30020.382366
140.0206260.19020.424817
150.0338720.31230.377795
16-0.063068-0.58150.281236
17-0.046343-0.42730.335135
18-0.017626-0.16250.435646
19-0.053155-0.49010.312675
20-0.029-0.26740.394919
21-0.039428-0.36350.358565
220.0196060.18080.428494
230.0307920.28390.388592
240.0536390.49450.311105
25-0.029714-0.27390.392395
26-0.021958-0.20240.420027
27-0.102451-0.94450.173783
280.0484020.44620.328277
29-0.125869-1.16050.124557
300.0531860.49030.312575
310.0100430.09260.463222
320.0454090.41870.338263
33-0.02158-0.1990.421385
34-0.071503-0.65920.255766
35-0.051109-0.47120.319352
36-0.091323-0.8420.201088

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.149984 & -1.3828 & 0.085177 \tabularnewline
2 & -0.070286 & -0.648 & 0.259363 \tabularnewline
3 & -0.02621 & -0.2416 & 0.404819 \tabularnewline
4 & -0.116499 & -1.0741 & 0.142916 \tabularnewline
5 & -0.058394 & -0.5384 & 0.295866 \tabularnewline
6 & -0.082197 & -0.7578 & 0.225327 \tabularnewline
7 & 0.023044 & 0.2125 & 0.41613 \tabularnewline
8 & -0.030872 & -0.2846 & 0.388311 \tabularnewline
9 & 0.069389 & 0.6397 & 0.262032 \tabularnewline
10 & 0.012077 & 0.1113 & 0.455802 \tabularnewline
11 & -0.031245 & -0.2881 & 0.387001 \tabularnewline
12 & -0.027587 & -0.2543 & 0.399925 \tabularnewline
13 & -0.032565 & -0.3002 & 0.382366 \tabularnewline
14 & 0.020626 & 0.1902 & 0.424817 \tabularnewline
15 & 0.033872 & 0.3123 & 0.377795 \tabularnewline
16 & -0.063068 & -0.5815 & 0.281236 \tabularnewline
17 & -0.046343 & -0.4273 & 0.335135 \tabularnewline
18 & -0.017626 & -0.1625 & 0.435646 \tabularnewline
19 & -0.053155 & -0.4901 & 0.312675 \tabularnewline
20 & -0.029 & -0.2674 & 0.394919 \tabularnewline
21 & -0.039428 & -0.3635 & 0.358565 \tabularnewline
22 & 0.019606 & 0.1808 & 0.428494 \tabularnewline
23 & 0.030792 & 0.2839 & 0.388592 \tabularnewline
24 & 0.053639 & 0.4945 & 0.311105 \tabularnewline
25 & -0.029714 & -0.2739 & 0.392395 \tabularnewline
26 & -0.021958 & -0.2024 & 0.420027 \tabularnewline
27 & -0.102451 & -0.9445 & 0.173783 \tabularnewline
28 & 0.048402 & 0.4462 & 0.328277 \tabularnewline
29 & -0.125869 & -1.1605 & 0.124557 \tabularnewline
30 & 0.053186 & 0.4903 & 0.312575 \tabularnewline
31 & 0.010043 & 0.0926 & 0.463222 \tabularnewline
32 & 0.045409 & 0.4187 & 0.338263 \tabularnewline
33 & -0.02158 & -0.199 & 0.421385 \tabularnewline
34 & -0.071503 & -0.6592 & 0.255766 \tabularnewline
35 & -0.051109 & -0.4712 & 0.319352 \tabularnewline
36 & -0.091323 & -0.842 & 0.201088 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65810&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]-0.149984[/C][C]-1.3828[/C][C]0.085177[/C][/ROW]
[ROW][C]2[/C][C]-0.070286[/C][C]-0.648[/C][C]0.259363[/C][/ROW]
[ROW][C]3[/C][C]-0.02621[/C][C]-0.2416[/C][C]0.404819[/C][/ROW]
[ROW][C]4[/C][C]-0.116499[/C][C]-1.0741[/C][C]0.142916[/C][/ROW]
[ROW][C]5[/C][C]-0.058394[/C][C]-0.5384[/C][C]0.295866[/C][/ROW]
[ROW][C]6[/C][C]-0.082197[/C][C]-0.7578[/C][C]0.225327[/C][/ROW]
[ROW][C]7[/C][C]0.023044[/C][C]0.2125[/C][C]0.41613[/C][/ROW]
[ROW][C]8[/C][C]-0.030872[/C][C]-0.2846[/C][C]0.388311[/C][/ROW]
[ROW][C]9[/C][C]0.069389[/C][C]0.6397[/C][C]0.262032[/C][/ROW]
[ROW][C]10[/C][C]0.012077[/C][C]0.1113[/C][C]0.455802[/C][/ROW]
[ROW][C]11[/C][C]-0.031245[/C][C]-0.2881[/C][C]0.387001[/C][/ROW]
[ROW][C]12[/C][C]-0.027587[/C][C]-0.2543[/C][C]0.399925[/C][/ROW]
[ROW][C]13[/C][C]-0.032565[/C][C]-0.3002[/C][C]0.382366[/C][/ROW]
[ROW][C]14[/C][C]0.020626[/C][C]0.1902[/C][C]0.424817[/C][/ROW]
[ROW][C]15[/C][C]0.033872[/C][C]0.3123[/C][C]0.377795[/C][/ROW]
[ROW][C]16[/C][C]-0.063068[/C][C]-0.5815[/C][C]0.281236[/C][/ROW]
[ROW][C]17[/C][C]-0.046343[/C][C]-0.4273[/C][C]0.335135[/C][/ROW]
[ROW][C]18[/C][C]-0.017626[/C][C]-0.1625[/C][C]0.435646[/C][/ROW]
[ROW][C]19[/C][C]-0.053155[/C][C]-0.4901[/C][C]0.312675[/C][/ROW]
[ROW][C]20[/C][C]-0.029[/C][C]-0.2674[/C][C]0.394919[/C][/ROW]
[ROW][C]21[/C][C]-0.039428[/C][C]-0.3635[/C][C]0.358565[/C][/ROW]
[ROW][C]22[/C][C]0.019606[/C][C]0.1808[/C][C]0.428494[/C][/ROW]
[ROW][C]23[/C][C]0.030792[/C][C]0.2839[/C][C]0.388592[/C][/ROW]
[ROW][C]24[/C][C]0.053639[/C][C]0.4945[/C][C]0.311105[/C][/ROW]
[ROW][C]25[/C][C]-0.029714[/C][C]-0.2739[/C][C]0.392395[/C][/ROW]
[ROW][C]26[/C][C]-0.021958[/C][C]-0.2024[/C][C]0.420027[/C][/ROW]
[ROW][C]27[/C][C]-0.102451[/C][C]-0.9445[/C][C]0.173783[/C][/ROW]
[ROW][C]28[/C][C]0.048402[/C][C]0.4462[/C][C]0.328277[/C][/ROW]
[ROW][C]29[/C][C]-0.125869[/C][C]-1.1605[/C][C]0.124557[/C][/ROW]
[ROW][C]30[/C][C]0.053186[/C][C]0.4903[/C][C]0.312575[/C][/ROW]
[ROW][C]31[/C][C]0.010043[/C][C]0.0926[/C][C]0.463222[/C][/ROW]
[ROW][C]32[/C][C]0.045409[/C][C]0.4187[/C][C]0.338263[/C][/ROW]
[ROW][C]33[/C][C]-0.02158[/C][C]-0.199[/C][C]0.421385[/C][/ROW]
[ROW][C]34[/C][C]-0.071503[/C][C]-0.6592[/C][C]0.255766[/C][/ROW]
[ROW][C]35[/C][C]-0.051109[/C][C]-0.4712[/C][C]0.319352[/C][/ROW]
[ROW][C]36[/C][C]-0.091323[/C][C]-0.842[/C][C]0.201088[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=65810&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65810&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
1-0.149984-1.38280.085177
2-0.070286-0.6480.259363
3-0.02621-0.24160.404819
4-0.116499-1.07410.142916
5-0.058394-0.53840.295866
6-0.082197-0.75780.225327
70.0230440.21250.41613
8-0.030872-0.28460.388311
90.0693890.63970.262032
100.0120770.11130.455802
11-0.031245-0.28810.387001
12-0.027587-0.25430.399925
13-0.032565-0.30020.382366
140.0206260.19020.424817
150.0338720.31230.377795
16-0.063068-0.58150.281236
17-0.046343-0.42730.335135
18-0.017626-0.16250.435646
19-0.053155-0.49010.312675
20-0.029-0.26740.394919
21-0.039428-0.36350.358565
220.0196060.18080.428494
230.0307920.28390.388592
240.0536390.49450.311105
25-0.029714-0.27390.392395
26-0.021958-0.20240.420027
27-0.102451-0.94450.173783
280.0484020.44620.328277
29-0.125869-1.16050.124557
300.0531860.49030.312575
310.0100430.09260.463222
320.0454090.41870.338263
33-0.02158-0.1990.421385
34-0.071503-0.65920.255766
35-0.051109-0.47120.319352
36-0.091323-0.8420.201088



Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 4 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 4 ; 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')