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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 computationSun, 20 Dec 2009 10:15:06 -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/20/t1261329351ncue6bhyhqtu0q9.htm/, Retrieved Sat, 27 Apr 2024 12:42:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=69956, Retrieved Sat, 27 Apr 2024 12:42:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact143
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] [Autocorrelatie fu...] [2009-11-23 18:29:14] [d46757a0a8c9b00540ab7e7e0c34bfc4]
-   PD            [(Partial) Autocorrelation Function] [Partial autocorre...] [2009-12-20 17:15:06] [8cd69d0f4298074aa572ca2f9b39b6ae] [Current]
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Dataseries X:
-1,2
-2,4
0,8
-0,1
-1,5
-4,4
-4,2
3,5
10
8,6
9,5
9,9
10,4
16
12,7
10,2
8,9
12,6
13,6
14,8
9,5
13,7
17
14,7
17,4
9
9,1
12,2
15,9
12,9
10,9
10,6
13,2
9,6
6,4
5,8
-1
-0,2
2,7
3,6
-0,9
0,3
-1,1
-2,5
-3,4
-3,5
-3,9
-4,6
-0,1
4,3
10,2
8,7
13,3
15
20,7
20,7
26,4
31,2
31,4
26,6
26,6
19,2
6,5
3,1
-0,2
-4
-12,6
-13
-17,6
-21,7
-23,2
-16,8
-19,8




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69956&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69956&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69956&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'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.9072357.75140
20.7953536.79550
30.6536415.58470
40.5010774.28122.8e-05
50.3284872.80660.003208
60.1563581.33590.092863
7-0.025804-0.22050.413062
8-0.176792-1.51050.067614
9-0.296885-2.53660.006666
10-0.394533-3.37096e-04
11-0.475864-4.06586e-05
12-0.536922-4.58759e-06
13-0.52829-4.51371.2e-05
14-0.490402-4.193.9e-05
15-0.426637-3.64520.000249
16-0.367689-3.14150.001214
17-0.303996-2.59730.005678
18-0.243781-2.08290.020384
19-0.163421-1.39630.083432
20-0.099807-0.85270.198294
21-0.044682-0.38180.351873
220.0010510.0090.49643
230.0446730.38170.351901
240.0881970.75360.226769
250.125831.07510.142938
260.1403371.1990.117195
270.1397911.19440.118099
280.1499921.28150.102031
290.1562641.33510.092993
300.1610791.37630.086474
310.1566261.33820.09249
320.1539741.31560.096221
330.1420241.21350.114434
340.1311181.12030.133135
350.1252021.06970.144133
360.1110890.94910.172838

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.907235 & 7.7514 & 0 \tabularnewline
2 & 0.795353 & 6.7955 & 0 \tabularnewline
3 & 0.653641 & 5.5847 & 0 \tabularnewline
4 & 0.501077 & 4.2812 & 2.8e-05 \tabularnewline
5 & 0.328487 & 2.8066 & 0.003208 \tabularnewline
6 & 0.156358 & 1.3359 & 0.092863 \tabularnewline
7 & -0.025804 & -0.2205 & 0.413062 \tabularnewline
8 & -0.176792 & -1.5105 & 0.067614 \tabularnewline
9 & -0.296885 & -2.5366 & 0.006666 \tabularnewline
10 & -0.394533 & -3.3709 & 6e-04 \tabularnewline
11 & -0.475864 & -4.0658 & 6e-05 \tabularnewline
12 & -0.536922 & -4.5875 & 9e-06 \tabularnewline
13 & -0.52829 & -4.5137 & 1.2e-05 \tabularnewline
14 & -0.490402 & -4.19 & 3.9e-05 \tabularnewline
15 & -0.426637 & -3.6452 & 0.000249 \tabularnewline
16 & -0.367689 & -3.1415 & 0.001214 \tabularnewline
17 & -0.303996 & -2.5973 & 0.005678 \tabularnewline
18 & -0.243781 & -2.0829 & 0.020384 \tabularnewline
19 & -0.163421 & -1.3963 & 0.083432 \tabularnewline
20 & -0.099807 & -0.8527 & 0.198294 \tabularnewline
21 & -0.044682 & -0.3818 & 0.351873 \tabularnewline
22 & 0.001051 & 0.009 & 0.49643 \tabularnewline
23 & 0.044673 & 0.3817 & 0.351901 \tabularnewline
24 & 0.088197 & 0.7536 & 0.226769 \tabularnewline
25 & 0.12583 & 1.0751 & 0.142938 \tabularnewline
26 & 0.140337 & 1.199 & 0.117195 \tabularnewline
27 & 0.139791 & 1.1944 & 0.118099 \tabularnewline
28 & 0.149992 & 1.2815 & 0.102031 \tabularnewline
29 & 0.156264 & 1.3351 & 0.092993 \tabularnewline
30 & 0.161079 & 1.3763 & 0.086474 \tabularnewline
31 & 0.156626 & 1.3382 & 0.09249 \tabularnewline
32 & 0.153974 & 1.3156 & 0.096221 \tabularnewline
33 & 0.142024 & 1.2135 & 0.114434 \tabularnewline
34 & 0.131118 & 1.1203 & 0.133135 \tabularnewline
35 & 0.125202 & 1.0697 & 0.144133 \tabularnewline
36 & 0.111089 & 0.9491 & 0.172838 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69956&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]0.907235[/C][C]7.7514[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.795353[/C][C]6.7955[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.653641[/C][C]5.5847[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.501077[/C][C]4.2812[/C][C]2.8e-05[/C][/ROW]
[ROW][C]5[/C][C]0.328487[/C][C]2.8066[/C][C]0.003208[/C][/ROW]
[ROW][C]6[/C][C]0.156358[/C][C]1.3359[/C][C]0.092863[/C][/ROW]
[ROW][C]7[/C][C]-0.025804[/C][C]-0.2205[/C][C]0.413062[/C][/ROW]
[ROW][C]8[/C][C]-0.176792[/C][C]-1.5105[/C][C]0.067614[/C][/ROW]
[ROW][C]9[/C][C]-0.296885[/C][C]-2.5366[/C][C]0.006666[/C][/ROW]
[ROW][C]10[/C][C]-0.394533[/C][C]-3.3709[/C][C]6e-04[/C][/ROW]
[ROW][C]11[/C][C]-0.475864[/C][C]-4.0658[/C][C]6e-05[/C][/ROW]
[ROW][C]12[/C][C]-0.536922[/C][C]-4.5875[/C][C]9e-06[/C][/ROW]
[ROW][C]13[/C][C]-0.52829[/C][C]-4.5137[/C][C]1.2e-05[/C][/ROW]
[ROW][C]14[/C][C]-0.490402[/C][C]-4.19[/C][C]3.9e-05[/C][/ROW]
[ROW][C]15[/C][C]-0.426637[/C][C]-3.6452[/C][C]0.000249[/C][/ROW]
[ROW][C]16[/C][C]-0.367689[/C][C]-3.1415[/C][C]0.001214[/C][/ROW]
[ROW][C]17[/C][C]-0.303996[/C][C]-2.5973[/C][C]0.005678[/C][/ROW]
[ROW][C]18[/C][C]-0.243781[/C][C]-2.0829[/C][C]0.020384[/C][/ROW]
[ROW][C]19[/C][C]-0.163421[/C][C]-1.3963[/C][C]0.083432[/C][/ROW]
[ROW][C]20[/C][C]-0.099807[/C][C]-0.8527[/C][C]0.198294[/C][/ROW]
[ROW][C]21[/C][C]-0.044682[/C][C]-0.3818[/C][C]0.351873[/C][/ROW]
[ROW][C]22[/C][C]0.001051[/C][C]0.009[/C][C]0.49643[/C][/ROW]
[ROW][C]23[/C][C]0.044673[/C][C]0.3817[/C][C]0.351901[/C][/ROW]
[ROW][C]24[/C][C]0.088197[/C][C]0.7536[/C][C]0.226769[/C][/ROW]
[ROW][C]25[/C][C]0.12583[/C][C]1.0751[/C][C]0.142938[/C][/ROW]
[ROW][C]26[/C][C]0.140337[/C][C]1.199[/C][C]0.117195[/C][/ROW]
[ROW][C]27[/C][C]0.139791[/C][C]1.1944[/C][C]0.118099[/C][/ROW]
[ROW][C]28[/C][C]0.149992[/C][C]1.2815[/C][C]0.102031[/C][/ROW]
[ROW][C]29[/C][C]0.156264[/C][C]1.3351[/C][C]0.092993[/C][/ROW]
[ROW][C]30[/C][C]0.161079[/C][C]1.3763[/C][C]0.086474[/C][/ROW]
[ROW][C]31[/C][C]0.156626[/C][C]1.3382[/C][C]0.09249[/C][/ROW]
[ROW][C]32[/C][C]0.153974[/C][C]1.3156[/C][C]0.096221[/C][/ROW]
[ROW][C]33[/C][C]0.142024[/C][C]1.2135[/C][C]0.114434[/C][/ROW]
[ROW][C]34[/C][C]0.131118[/C][C]1.1203[/C][C]0.133135[/C][/ROW]
[ROW][C]35[/C][C]0.125202[/C][C]1.0697[/C][C]0.144133[/C][/ROW]
[ROW][C]36[/C][C]0.111089[/C][C]0.9491[/C][C]0.172838[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69956&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69956&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
10.9072357.75140
20.7953536.79550
30.6536415.58470
40.5010774.28122.8e-05
50.3284872.80660.003208
60.1563581.33590.092863
7-0.025804-0.22050.413062
8-0.176792-1.51050.067614
9-0.296885-2.53660.006666
10-0.394533-3.37096e-04
11-0.475864-4.06586e-05
12-0.536922-4.58759e-06
13-0.52829-4.51371.2e-05
14-0.490402-4.193.9e-05
15-0.426637-3.64520.000249
16-0.367689-3.14150.001214
17-0.303996-2.59730.005678
18-0.243781-2.08290.020384
19-0.163421-1.39630.083432
20-0.099807-0.85270.198294
21-0.044682-0.38180.351873
220.0010510.0090.49643
230.0446730.38170.351901
240.0881970.75360.226769
250.125831.07510.142938
260.1403371.1990.117195
270.1397911.19440.118099
280.1499921.28150.102031
290.1562641.33510.092993
300.1610791.37630.086474
310.1566261.33820.09249
320.1539741.31560.096221
330.1420241.21350.114434
340.1311181.12030.133135
350.1252021.06970.144133
360.1110890.94910.172838







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9072357.75140
2-0.156694-1.33880.092395
3-0.22505-1.92280.029202
4-0.127162-1.08650.140422
5-0.199079-1.70090.046606
6-0.113022-0.96570.168702
7-0.197902-1.69090.047563
80.0133950.11440.454599
90.0265180.22660.410697
10-0.075058-0.64130.261669
11-0.109057-0.93180.17726
12-0.115713-0.98860.16305
130.2449672.0930.019912
140.0079660.06810.472962
15-0.02301-0.19660.422346
16-0.144902-1.2380.109833
17-0.103055-0.88050.19074
18-0.083158-0.71050.239829
190.0189580.1620.435886
20-0.045691-0.39040.348695
21-0.008022-0.06850.472772
220.014480.12370.45094
23-0.033629-0.28730.387337
240.0089240.07620.469715
250.0563290.48130.31588
26-0.048523-0.41460.339832
27-0.039779-0.33990.367465
280.0511610.43710.331659
29-0.027545-0.23530.4073
30-0.026936-0.23010.409314
310.0250150.21370.415677
320.0429360.36680.357399
33-0.025481-0.21770.414132
34-0.035694-0.3050.380628
350.0845330.72220.236225
360.0130930.11190.455618

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.907235 & 7.7514 & 0 \tabularnewline
2 & -0.156694 & -1.3388 & 0.092395 \tabularnewline
3 & -0.22505 & -1.9228 & 0.029202 \tabularnewline
4 & -0.127162 & -1.0865 & 0.140422 \tabularnewline
5 & -0.199079 & -1.7009 & 0.046606 \tabularnewline
6 & -0.113022 & -0.9657 & 0.168702 \tabularnewline
7 & -0.197902 & -1.6909 & 0.047563 \tabularnewline
8 & 0.013395 & 0.1144 & 0.454599 \tabularnewline
9 & 0.026518 & 0.2266 & 0.410697 \tabularnewline
10 & -0.075058 & -0.6413 & 0.261669 \tabularnewline
11 & -0.109057 & -0.9318 & 0.17726 \tabularnewline
12 & -0.115713 & -0.9886 & 0.16305 \tabularnewline
13 & 0.244967 & 2.093 & 0.019912 \tabularnewline
14 & 0.007966 & 0.0681 & 0.472962 \tabularnewline
15 & -0.02301 & -0.1966 & 0.422346 \tabularnewline
16 & -0.144902 & -1.238 & 0.109833 \tabularnewline
17 & -0.103055 & -0.8805 & 0.19074 \tabularnewline
18 & -0.083158 & -0.7105 & 0.239829 \tabularnewline
19 & 0.018958 & 0.162 & 0.435886 \tabularnewline
20 & -0.045691 & -0.3904 & 0.348695 \tabularnewline
21 & -0.008022 & -0.0685 & 0.472772 \tabularnewline
22 & 0.01448 & 0.1237 & 0.45094 \tabularnewline
23 & -0.033629 & -0.2873 & 0.387337 \tabularnewline
24 & 0.008924 & 0.0762 & 0.469715 \tabularnewline
25 & 0.056329 & 0.4813 & 0.31588 \tabularnewline
26 & -0.048523 & -0.4146 & 0.339832 \tabularnewline
27 & -0.039779 & -0.3399 & 0.367465 \tabularnewline
28 & 0.051161 & 0.4371 & 0.331659 \tabularnewline
29 & -0.027545 & -0.2353 & 0.4073 \tabularnewline
30 & -0.026936 & -0.2301 & 0.409314 \tabularnewline
31 & 0.025015 & 0.2137 & 0.415677 \tabularnewline
32 & 0.042936 & 0.3668 & 0.357399 \tabularnewline
33 & -0.025481 & -0.2177 & 0.414132 \tabularnewline
34 & -0.035694 & -0.305 & 0.380628 \tabularnewline
35 & 0.084533 & 0.7222 & 0.236225 \tabularnewline
36 & 0.013093 & 0.1119 & 0.455618 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69956&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]0.907235[/C][C]7.7514[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.156694[/C][C]-1.3388[/C][C]0.092395[/C][/ROW]
[ROW][C]3[/C][C]-0.22505[/C][C]-1.9228[/C][C]0.029202[/C][/ROW]
[ROW][C]4[/C][C]-0.127162[/C][C]-1.0865[/C][C]0.140422[/C][/ROW]
[ROW][C]5[/C][C]-0.199079[/C][C]-1.7009[/C][C]0.046606[/C][/ROW]
[ROW][C]6[/C][C]-0.113022[/C][C]-0.9657[/C][C]0.168702[/C][/ROW]
[ROW][C]7[/C][C]-0.197902[/C][C]-1.6909[/C][C]0.047563[/C][/ROW]
[ROW][C]8[/C][C]0.013395[/C][C]0.1144[/C][C]0.454599[/C][/ROW]
[ROW][C]9[/C][C]0.026518[/C][C]0.2266[/C][C]0.410697[/C][/ROW]
[ROW][C]10[/C][C]-0.075058[/C][C]-0.6413[/C][C]0.261669[/C][/ROW]
[ROW][C]11[/C][C]-0.109057[/C][C]-0.9318[/C][C]0.17726[/C][/ROW]
[ROW][C]12[/C][C]-0.115713[/C][C]-0.9886[/C][C]0.16305[/C][/ROW]
[ROW][C]13[/C][C]0.244967[/C][C]2.093[/C][C]0.019912[/C][/ROW]
[ROW][C]14[/C][C]0.007966[/C][C]0.0681[/C][C]0.472962[/C][/ROW]
[ROW][C]15[/C][C]-0.02301[/C][C]-0.1966[/C][C]0.422346[/C][/ROW]
[ROW][C]16[/C][C]-0.144902[/C][C]-1.238[/C][C]0.109833[/C][/ROW]
[ROW][C]17[/C][C]-0.103055[/C][C]-0.8805[/C][C]0.19074[/C][/ROW]
[ROW][C]18[/C][C]-0.083158[/C][C]-0.7105[/C][C]0.239829[/C][/ROW]
[ROW][C]19[/C][C]0.018958[/C][C]0.162[/C][C]0.435886[/C][/ROW]
[ROW][C]20[/C][C]-0.045691[/C][C]-0.3904[/C][C]0.348695[/C][/ROW]
[ROW][C]21[/C][C]-0.008022[/C][C]-0.0685[/C][C]0.472772[/C][/ROW]
[ROW][C]22[/C][C]0.01448[/C][C]0.1237[/C][C]0.45094[/C][/ROW]
[ROW][C]23[/C][C]-0.033629[/C][C]-0.2873[/C][C]0.387337[/C][/ROW]
[ROW][C]24[/C][C]0.008924[/C][C]0.0762[/C][C]0.469715[/C][/ROW]
[ROW][C]25[/C][C]0.056329[/C][C]0.4813[/C][C]0.31588[/C][/ROW]
[ROW][C]26[/C][C]-0.048523[/C][C]-0.4146[/C][C]0.339832[/C][/ROW]
[ROW][C]27[/C][C]-0.039779[/C][C]-0.3399[/C][C]0.367465[/C][/ROW]
[ROW][C]28[/C][C]0.051161[/C][C]0.4371[/C][C]0.331659[/C][/ROW]
[ROW][C]29[/C][C]-0.027545[/C][C]-0.2353[/C][C]0.4073[/C][/ROW]
[ROW][C]30[/C][C]-0.026936[/C][C]-0.2301[/C][C]0.409314[/C][/ROW]
[ROW][C]31[/C][C]0.025015[/C][C]0.2137[/C][C]0.415677[/C][/ROW]
[ROW][C]32[/C][C]0.042936[/C][C]0.3668[/C][C]0.357399[/C][/ROW]
[ROW][C]33[/C][C]-0.025481[/C][C]-0.2177[/C][C]0.414132[/C][/ROW]
[ROW][C]34[/C][C]-0.035694[/C][C]-0.305[/C][C]0.380628[/C][/ROW]
[ROW][C]35[/C][C]0.084533[/C][C]0.7222[/C][C]0.236225[/C][/ROW]
[ROW][C]36[/C][C]0.013093[/C][C]0.1119[/C][C]0.455618[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69956&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69956&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
10.9072357.75140
2-0.156694-1.33880.092395
3-0.22505-1.92280.029202
4-0.127162-1.08650.140422
5-0.199079-1.70090.046606
6-0.113022-0.96570.168702
7-0.197902-1.69090.047563
80.0133950.11440.454599
90.0265180.22660.410697
10-0.075058-0.64130.261669
11-0.109057-0.93180.17726
12-0.115713-0.98860.16305
130.2449672.0930.019912
140.0079660.06810.472962
15-0.02301-0.19660.422346
16-0.144902-1.2380.109833
17-0.103055-0.88050.19074
18-0.083158-0.71050.239829
190.0189580.1620.435886
20-0.045691-0.39040.348695
21-0.008022-0.06850.472772
220.014480.12370.45094
23-0.033629-0.28730.387337
240.0089240.07620.469715
250.0563290.48130.31588
26-0.048523-0.41460.339832
27-0.039779-0.33990.367465
280.0511610.43710.331659
29-0.027545-0.23530.4073
30-0.026936-0.23010.409314
310.0250150.21370.415677
320.0429360.36680.357399
33-0.025481-0.21770.414132
34-0.035694-0.3050.380628
350.0845330.72220.236225
360.0130930.11190.455618



Parameters (Session):
par1 = 1 ; par2 = Include Monthly Dummies ; par3 = Linear Trend ;
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')