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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 computationWed, 03 Dec 2008 14:05:57 -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/2008/Dec/03/t1228338498rfg0xi14iyyyxmd.htm/, Retrieved Fri, 17 May 2024 05:03:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=28885, Retrieved Fri, 17 May 2024 05:03:46 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact214

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [Airline data] [2007-10-18 09:58:47] [42daae401fd3def69a25014f2252b4c2]
- RMPD  [(Partial) Autocorrelation Function] [blok 17 Q6 ACF] [2008-12-02 20:15:24] [6173c35e31b784a490c8cd5476f785d4]
-    D    [(Partial) Autocorrelation Function] [blok 17 Q8 acf x(t)] [2008-12-03 21:00:52] [6173c35e31b784a490c8cd5476f785d4]
-   PD        [(Partial) Autocorrelation Function] [blok 17 Q8 acf x(...] [2008-12-03 21:05:57] [1237f4df7e9be807e4c0a07b90c45721] [Current]
-   P           [(Partial) Autocorrelation Function] [blok 17 Q8 acf x(...] [2008-12-03 21:08:53] [6173c35e31b784a490c8cd5476f785d4]
-   PD            [(Partial) Autocorrelation Function] [blok 17 Q8 acf y(t)] [2008-12-03 21:21:49] [6173c35e31b784a490c8cd5476f785d4]
-   PD              [(Partial) Autocorrelation Function] [blok 17 Q8 acf y(...] [2008-12-03 21:25:22] [6173c35e31b784a490c8cd5476f785d4]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
98.6
98
106.8
96.6
100.1
107.7
91.5
97.8
107.4
117.5
105.6
97.4
99.5
98
104.3
100.6
101.1
103.9
96.9
95.5
108.4
117
103.8
100.8
110.6
104
112.6
107.3
98.9
109.8
104.9
102.2
123.9
124.9
112.7
121.9
100.6
104.3
120.4
107.5
102.9
125.6
107.5
108.8
128.4
121.1
119.5
128.7
108.7
105.5
119.8
111.3
110.6
120.1
97.5
107.7
127.3
117.2
119.8
116.2
111
112.4
130.6
109.1
118.8
123.9
101.6
112.8
128
129.6
125.8
119.5

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'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28885&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28885&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28885&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'George Udny Yule' @ 72.249.76.132






Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.467724-3.59270.000334
2-0.139294-1.06990.144503
30.2756222.11710.019239
4-0.234141-1.79850.038609
50.0005470.00420.498331
60.2576561.97910.026239
7-0.342314-2.62940.005446
80.0977720.7510.227819
90.2891082.22070.015113
10-0.32773-2.51730.00728
110.1766681.3570.089973
12-0.052783-0.40540.343311
13-0.233198-1.79120.039193
140.3366642.5860.0061
15-0.105237-0.80830.211072
16-0.232052-1.78240.039913
170.3785872.9080.00256
18-0.15505-1.1910.119219
19-0.100851-0.77470.220819
200.1409671.08280.141654
21-0.057233-0.43960.330912
22-0.128718-0.98870.163423
230.3321672.55140.00667
24-0.266682-2.04840.022488
25-0.018736-0.14390.443029
260.1207940.92780.178636
27-0.078569-0.60350.274244
280.0180010.13830.445248
290.0554840.42620.335763
30-0.100677-0.77330.221212
310.0490630.37690.353815
320.1013040.77810.219801
33-0.183264-1.40770.082237
340.090980.69880.243701
350.005650.04340.482766
36-0.068822-0.52860.299522

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.467724 & -3.5927 & 0.000334 \tabularnewline
2 & -0.139294 & -1.0699 & 0.144503 \tabularnewline
3 & 0.275622 & 2.1171 & 0.019239 \tabularnewline
4 & -0.234141 & -1.7985 & 0.038609 \tabularnewline
5 & 0.000547 & 0.0042 & 0.498331 \tabularnewline
6 & 0.257656 & 1.9791 & 0.026239 \tabularnewline
7 & -0.342314 & -2.6294 & 0.005446 \tabularnewline
8 & 0.097772 & 0.751 & 0.227819 \tabularnewline
9 & 0.289108 & 2.2207 & 0.015113 \tabularnewline
10 & -0.32773 & -2.5173 & 0.00728 \tabularnewline
11 & 0.176668 & 1.357 & 0.089973 \tabularnewline
12 & -0.052783 & -0.4054 & 0.343311 \tabularnewline
13 & -0.233198 & -1.7912 & 0.039193 \tabularnewline
14 & 0.336664 & 2.586 & 0.0061 \tabularnewline
15 & -0.105237 & -0.8083 & 0.211072 \tabularnewline
16 & -0.232052 & -1.7824 & 0.039913 \tabularnewline
17 & 0.378587 & 2.908 & 0.00256 \tabularnewline
18 & -0.15505 & -1.191 & 0.119219 \tabularnewline
19 & -0.100851 & -0.7747 & 0.220819 \tabularnewline
20 & 0.140967 & 1.0828 & 0.141654 \tabularnewline
21 & -0.057233 & -0.4396 & 0.330912 \tabularnewline
22 & -0.128718 & -0.9887 & 0.163423 \tabularnewline
23 & 0.332167 & 2.5514 & 0.00667 \tabularnewline
24 & -0.266682 & -2.0484 & 0.022488 \tabularnewline
25 & -0.018736 & -0.1439 & 0.443029 \tabularnewline
26 & 0.120794 & 0.9278 & 0.178636 \tabularnewline
27 & -0.078569 & -0.6035 & 0.274244 \tabularnewline
28 & 0.018001 & 0.1383 & 0.445248 \tabularnewline
29 & 0.055484 & 0.4262 & 0.335763 \tabularnewline
30 & -0.100677 & -0.7733 & 0.221212 \tabularnewline
31 & 0.049063 & 0.3769 & 0.353815 \tabularnewline
32 & 0.101304 & 0.7781 & 0.219801 \tabularnewline
33 & -0.183264 & -1.4077 & 0.082237 \tabularnewline
34 & 0.09098 & 0.6988 & 0.243701 \tabularnewline
35 & 0.00565 & 0.0434 & 0.482766 \tabularnewline
36 & -0.068822 & -0.5286 & 0.299522 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28885&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]-0.467724[/C][C]-3.5927[/C][C]0.000334[/C][/ROW]
[ROW][C]2[/C][C]-0.139294[/C][C]-1.0699[/C][C]0.144503[/C][/ROW]
[ROW][C]3[/C][C]0.275622[/C][C]2.1171[/C][C]0.019239[/C][/ROW]
[ROW][C]4[/C][C]-0.234141[/C][C]-1.7985[/C][C]0.038609[/C][/ROW]
[ROW][C]5[/C][C]0.000547[/C][C]0.0042[/C][C]0.498331[/C][/ROW]
[ROW][C]6[/C][C]0.257656[/C][C]1.9791[/C][C]0.026239[/C][/ROW]
[ROW][C]7[/C][C]-0.342314[/C][C]-2.6294[/C][C]0.005446[/C][/ROW]
[ROW][C]8[/C][C]0.097772[/C][C]0.751[/C][C]0.227819[/C][/ROW]
[ROW][C]9[/C][C]0.289108[/C][C]2.2207[/C][C]0.015113[/C][/ROW]
[ROW][C]10[/C][C]-0.32773[/C][C]-2.5173[/C][C]0.00728[/C][/ROW]
[ROW][C]11[/C][C]0.176668[/C][C]1.357[/C][C]0.089973[/C][/ROW]
[ROW][C]12[/C][C]-0.052783[/C][C]-0.4054[/C][C]0.343311[/C][/ROW]
[ROW][C]13[/C][C]-0.233198[/C][C]-1.7912[/C][C]0.039193[/C][/ROW]
[ROW][C]14[/C][C]0.336664[/C][C]2.586[/C][C]0.0061[/C][/ROW]
[ROW][C]15[/C][C]-0.105237[/C][C]-0.8083[/C][C]0.211072[/C][/ROW]
[ROW][C]16[/C][C]-0.232052[/C][C]-1.7824[/C][C]0.039913[/C][/ROW]
[ROW][C]17[/C][C]0.378587[/C][C]2.908[/C][C]0.00256[/C][/ROW]
[ROW][C]18[/C][C]-0.15505[/C][C]-1.191[/C][C]0.119219[/C][/ROW]
[ROW][C]19[/C][C]-0.100851[/C][C]-0.7747[/C][C]0.220819[/C][/ROW]
[ROW][C]20[/C][C]0.140967[/C][C]1.0828[/C][C]0.141654[/C][/ROW]
[ROW][C]21[/C][C]-0.057233[/C][C]-0.4396[/C][C]0.330912[/C][/ROW]
[ROW][C]22[/C][C]-0.128718[/C][C]-0.9887[/C][C]0.163423[/C][/ROW]
[ROW][C]23[/C][C]0.332167[/C][C]2.5514[/C][C]0.00667[/C][/ROW]
[ROW][C]24[/C][C]-0.266682[/C][C]-2.0484[/C][C]0.022488[/C][/ROW]
[ROW][C]25[/C][C]-0.018736[/C][C]-0.1439[/C][C]0.443029[/C][/ROW]
[ROW][C]26[/C][C]0.120794[/C][C]0.9278[/C][C]0.178636[/C][/ROW]
[ROW][C]27[/C][C]-0.078569[/C][C]-0.6035[/C][C]0.274244[/C][/ROW]
[ROW][C]28[/C][C]0.018001[/C][C]0.1383[/C][C]0.445248[/C][/ROW]
[ROW][C]29[/C][C]0.055484[/C][C]0.4262[/C][C]0.335763[/C][/ROW]
[ROW][C]30[/C][C]-0.100677[/C][C]-0.7733[/C][C]0.221212[/C][/ROW]
[ROW][C]31[/C][C]0.049063[/C][C]0.3769[/C][C]0.353815[/C][/ROW]
[ROW][C]32[/C][C]0.101304[/C][C]0.7781[/C][C]0.219801[/C][/ROW]
[ROW][C]33[/C][C]-0.183264[/C][C]-1.4077[/C][C]0.082237[/C][/ROW]
[ROW][C]34[/C][C]0.09098[/C][C]0.6988[/C][C]0.243701[/C][/ROW]
[ROW][C]35[/C][C]0.00565[/C][C]0.0434[/C][C]0.482766[/C][/ROW]
[ROW][C]36[/C][C]-0.068822[/C][C]-0.5286[/C][C]0.299522[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28885&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28885&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
1-0.467724-3.59270.000334
2-0.139294-1.06990.144503
30.2756222.11710.019239
4-0.234141-1.79850.038609
50.0005470.00420.498331
60.2576561.97910.026239
7-0.342314-2.62940.005446
80.0977720.7510.227819
90.2891082.22070.015113
10-0.32773-2.51730.00728
110.1766681.3570.089973
12-0.052783-0.40540.343311
13-0.233198-1.79120.039193
140.3366642.5860.0061
15-0.105237-0.80830.211072
16-0.232052-1.78240.039913
170.3785872.9080.00256
18-0.15505-1.1910.119219
19-0.100851-0.77470.220819
200.1409671.08280.141654
21-0.057233-0.43960.330912
22-0.128718-0.98870.163423
230.3321672.55140.00667
24-0.266682-2.04840.022488
25-0.018736-0.14390.443029
260.1207940.92780.178636
27-0.078569-0.60350.274244
280.0180010.13830.445248
290.0554840.42620.335763
30-0.100677-0.77330.221212
310.0490630.37690.353815
320.1013040.77810.219801
33-0.183264-1.40770.082237
340.090980.69880.243701
350.005650.04340.482766
36-0.068822-0.52860.299522






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.467724-3.59270.000334
2-0.458326-3.52050.000419
3-0.054705-0.42020.337935
4-0.217554-1.67110.050003
5-0.225694-1.73360.044107
60.076050.58420.280672
7-0.216472-1.66280.050833
8-0.204038-1.56720.061203
90.1498521.1510.127181
100.0211410.16240.435779
110.1566381.20320.11686
12-0.063317-0.48630.314261
13-0.239794-1.84190.035259
140.0025370.01950.492258
15-0.07553-0.58020.282009
16-0.212506-1.63230.053972
170.0373340.28680.387646
180.0184160.14150.443996
190.0171510.13170.44782
20-0.188739-1.44970.076214
210.1276650.98060.165394
22-0.028526-0.21910.41366
230.1481681.13810.129839
240.065310.50170.30889
25-0.064786-0.49760.310297
26-0.243903-1.87350.032981
27-0.105866-0.81320.209694
28-0.160488-1.23270.111282
29-0.057344-0.44050.330603
300.0174270.13390.446985
31-0.063471-0.48750.313846
32-0.070175-0.5390.295949
33-0.03475-0.26690.395231
34-0.019076-0.14650.442002
35-0.002544-0.01950.492239
360.0080510.06180.475451

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.467724 & -3.5927 & 0.000334 \tabularnewline
2 & -0.458326 & -3.5205 & 0.000419 \tabularnewline
3 & -0.054705 & -0.4202 & 0.337935 \tabularnewline
4 & -0.217554 & -1.6711 & 0.050003 \tabularnewline
5 & -0.225694 & -1.7336 & 0.044107 \tabularnewline
6 & 0.07605 & 0.5842 & 0.280672 \tabularnewline
7 & -0.216472 & -1.6628 & 0.050833 \tabularnewline
8 & -0.204038 & -1.5672 & 0.061203 \tabularnewline
9 & 0.149852 & 1.151 & 0.127181 \tabularnewline
10 & 0.021141 & 0.1624 & 0.435779 \tabularnewline
11 & 0.156638 & 1.2032 & 0.11686 \tabularnewline
12 & -0.063317 & -0.4863 & 0.314261 \tabularnewline
13 & -0.239794 & -1.8419 & 0.035259 \tabularnewline
14 & 0.002537 & 0.0195 & 0.492258 \tabularnewline
15 & -0.07553 & -0.5802 & 0.282009 \tabularnewline
16 & -0.212506 & -1.6323 & 0.053972 \tabularnewline
17 & 0.037334 & 0.2868 & 0.387646 \tabularnewline
18 & 0.018416 & 0.1415 & 0.443996 \tabularnewline
19 & 0.017151 & 0.1317 & 0.44782 \tabularnewline
20 & -0.188739 & -1.4497 & 0.076214 \tabularnewline
21 & 0.127665 & 0.9806 & 0.165394 \tabularnewline
22 & -0.028526 & -0.2191 & 0.41366 \tabularnewline
23 & 0.148168 & 1.1381 & 0.129839 \tabularnewline
24 & 0.06531 & 0.5017 & 0.30889 \tabularnewline
25 & -0.064786 & -0.4976 & 0.310297 \tabularnewline
26 & -0.243903 & -1.8735 & 0.032981 \tabularnewline
27 & -0.105866 & -0.8132 & 0.209694 \tabularnewline
28 & -0.160488 & -1.2327 & 0.111282 \tabularnewline
29 & -0.057344 & -0.4405 & 0.330603 \tabularnewline
30 & 0.017427 & 0.1339 & 0.446985 \tabularnewline
31 & -0.063471 & -0.4875 & 0.313846 \tabularnewline
32 & -0.070175 & -0.539 & 0.295949 \tabularnewline
33 & -0.03475 & -0.2669 & 0.395231 \tabularnewline
34 & -0.019076 & -0.1465 & 0.442002 \tabularnewline
35 & -0.002544 & -0.0195 & 0.492239 \tabularnewline
36 & 0.008051 & 0.0618 & 0.475451 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28885&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]-0.467724[/C][C]-3.5927[/C][C]0.000334[/C][/ROW]
[ROW][C]2[/C][C]-0.458326[/C][C]-3.5205[/C][C]0.000419[/C][/ROW]
[ROW][C]3[/C][C]-0.054705[/C][C]-0.4202[/C][C]0.337935[/C][/ROW]
[ROW][C]4[/C][C]-0.217554[/C][C]-1.6711[/C][C]0.050003[/C][/ROW]
[ROW][C]5[/C][C]-0.225694[/C][C]-1.7336[/C][C]0.044107[/C][/ROW]
[ROW][C]6[/C][C]0.07605[/C][C]0.5842[/C][C]0.280672[/C][/ROW]
[ROW][C]7[/C][C]-0.216472[/C][C]-1.6628[/C][C]0.050833[/C][/ROW]
[ROW][C]8[/C][C]-0.204038[/C][C]-1.5672[/C][C]0.061203[/C][/ROW]
[ROW][C]9[/C][C]0.149852[/C][C]1.151[/C][C]0.127181[/C][/ROW]
[ROW][C]10[/C][C]0.021141[/C][C]0.1624[/C][C]0.435779[/C][/ROW]
[ROW][C]11[/C][C]0.156638[/C][C]1.2032[/C][C]0.11686[/C][/ROW]
[ROW][C]12[/C][C]-0.063317[/C][C]-0.4863[/C][C]0.314261[/C][/ROW]
[ROW][C]13[/C][C]-0.239794[/C][C]-1.8419[/C][C]0.035259[/C][/ROW]
[ROW][C]14[/C][C]0.002537[/C][C]0.0195[/C][C]0.492258[/C][/ROW]
[ROW][C]15[/C][C]-0.07553[/C][C]-0.5802[/C][C]0.282009[/C][/ROW]
[ROW][C]16[/C][C]-0.212506[/C][C]-1.6323[/C][C]0.053972[/C][/ROW]
[ROW][C]17[/C][C]0.037334[/C][C]0.2868[/C][C]0.387646[/C][/ROW]
[ROW][C]18[/C][C]0.018416[/C][C]0.1415[/C][C]0.443996[/C][/ROW]
[ROW][C]19[/C][C]0.017151[/C][C]0.1317[/C][C]0.44782[/C][/ROW]
[ROW][C]20[/C][C]-0.188739[/C][C]-1.4497[/C][C]0.076214[/C][/ROW]
[ROW][C]21[/C][C]0.127665[/C][C]0.9806[/C][C]0.165394[/C][/ROW]
[ROW][C]22[/C][C]-0.028526[/C][C]-0.2191[/C][C]0.41366[/C][/ROW]
[ROW][C]23[/C][C]0.148168[/C][C]1.1381[/C][C]0.129839[/C][/ROW]
[ROW][C]24[/C][C]0.06531[/C][C]0.5017[/C][C]0.30889[/C][/ROW]
[ROW][C]25[/C][C]-0.064786[/C][C]-0.4976[/C][C]0.310297[/C][/ROW]
[ROW][C]26[/C][C]-0.243903[/C][C]-1.8735[/C][C]0.032981[/C][/ROW]
[ROW][C]27[/C][C]-0.105866[/C][C]-0.8132[/C][C]0.209694[/C][/ROW]
[ROW][C]28[/C][C]-0.160488[/C][C]-1.2327[/C][C]0.111282[/C][/ROW]
[ROW][C]29[/C][C]-0.057344[/C][C]-0.4405[/C][C]0.330603[/C][/ROW]
[ROW][C]30[/C][C]0.017427[/C][C]0.1339[/C][C]0.446985[/C][/ROW]
[ROW][C]31[/C][C]-0.063471[/C][C]-0.4875[/C][C]0.313846[/C][/ROW]
[ROW][C]32[/C][C]-0.070175[/C][C]-0.539[/C][C]0.295949[/C][/ROW]
[ROW][C]33[/C][C]-0.03475[/C][C]-0.2669[/C][C]0.395231[/C][/ROW]
[ROW][C]34[/C][C]-0.019076[/C][C]-0.1465[/C][C]0.442002[/C][/ROW]
[ROW][C]35[/C][C]-0.002544[/C][C]-0.0195[/C][C]0.492239[/C][/ROW]
[ROW][C]36[/C][C]0.008051[/C][C]0.0618[/C][C]0.475451[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28885&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28885&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
1-0.467724-3.59270.000334
2-0.458326-3.52050.000419
3-0.054705-0.42020.337935
4-0.217554-1.67110.050003
5-0.225694-1.73360.044107
60.076050.58420.280672
7-0.216472-1.66280.050833
8-0.204038-1.56720.061203
90.1498521.1510.127181
100.0211410.16240.435779
110.1566381.20320.11686
12-0.063317-0.48630.314261
13-0.239794-1.84190.035259
140.0025370.01950.492258
15-0.07553-0.58020.282009
16-0.212506-1.63230.053972
170.0373340.28680.387646
180.0184160.14150.443996
190.0171510.13170.44782
20-0.188739-1.44970.076214
210.1276650.98060.165394
22-0.028526-0.21910.41366
230.1481681.13810.129839
240.065310.50170.30889
25-0.064786-0.49760.310297
26-0.243903-1.87350.032981
27-0.105866-0.81320.209694
28-0.160488-1.23270.111282
29-0.057344-0.44050.330603
300.0174270.13390.446985
31-0.063471-0.48750.313846
32-0.070175-0.5390.295949
33-0.03475-0.26690.395231
34-0.019076-0.14650.442002
35-0.002544-0.01950.492239
360.0080510.06180.475451


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ;
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 (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='lags',ylab='ACF')
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')