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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 14:08:53 -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/t12283386056nezxgsgwry2jjt.htm/, Retrieved Sat, 18 May 2024 05:30:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=28886, Retrieved Sat, 18 May 2024 05:30:10 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact199

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] [6173c35e31b784a490c8cd5476f785d4]
-   P           [(Partial) Autocorrelation Function] [blok 17 Q8 acf x(...] [2008-12-03 21:08:53] [1237f4df7e9be807e4c0a07b90c45721] [Current]
-   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 time0 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 & 0 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28886&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]0 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=28886&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28886&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 time0 seconds
R Server'George Udny Yule' @ 72.249.76.132






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.1431891.10910.135898
20.0855760.66290.254975
30.2633372.03980.02289
4-0.023449-0.18160.42824
50.0870770.67450.251293
60.1913571.48220.071754
7-0.135291-1.0480.149429
80.1152820.8930.18772
90.2021631.56590.06131
10-0.207435-1.60680.056676
11-0.057854-0.44810.327834
12-0.204951-1.58750.058823
13-0.253044-1.96010.027318
140.0924820.71640.238274
15-0.135341-1.04830.149343
16-0.184691-1.43060.078864
170.1533941.18820.119722
18-0.1473-1.1410.129206
19-0.180209-1.39590.083945
20-0.041983-0.32520.373081
21-0.135291-1.0480.149431
22-0.138711-1.07450.143461
230.0793040.61430.270673
24-0.257669-1.99590.025245
25-0.172125-1.33330.093741
26-0.043582-0.33760.368428
27-0.113466-0.87890.19148
28-0.057185-0.4430.329696
29-0.027684-0.21440.415465
30-0.080209-0.62130.268378
310.0250730.19420.423331
320.0507280.39290.34788
33-0.099155-0.76810.222734
340.0553680.42890.334773
350.0657130.5090.306305
360.0666640.51640.303744

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.143189 & 1.1091 & 0.135898 \tabularnewline
2 & 0.085576 & 0.6629 & 0.254975 \tabularnewline
3 & 0.263337 & 2.0398 & 0.02289 \tabularnewline
4 & -0.023449 & -0.1816 & 0.42824 \tabularnewline
5 & 0.087077 & 0.6745 & 0.251293 \tabularnewline
6 & 0.191357 & 1.4822 & 0.071754 \tabularnewline
7 & -0.135291 & -1.048 & 0.149429 \tabularnewline
8 & 0.115282 & 0.893 & 0.18772 \tabularnewline
9 & 0.202163 & 1.5659 & 0.06131 \tabularnewline
10 & -0.207435 & -1.6068 & 0.056676 \tabularnewline
11 & -0.057854 & -0.4481 & 0.327834 \tabularnewline
12 & -0.204951 & -1.5875 & 0.058823 \tabularnewline
13 & -0.253044 & -1.9601 & 0.027318 \tabularnewline
14 & 0.092482 & 0.7164 & 0.238274 \tabularnewline
15 & -0.135341 & -1.0483 & 0.149343 \tabularnewline
16 & -0.184691 & -1.4306 & 0.078864 \tabularnewline
17 & 0.153394 & 1.1882 & 0.119722 \tabularnewline
18 & -0.1473 & -1.141 & 0.129206 \tabularnewline
19 & -0.180209 & -1.3959 & 0.083945 \tabularnewline
20 & -0.041983 & -0.3252 & 0.373081 \tabularnewline
21 & -0.135291 & -1.048 & 0.149431 \tabularnewline
22 & -0.138711 & -1.0745 & 0.143461 \tabularnewline
23 & 0.079304 & 0.6143 & 0.270673 \tabularnewline
24 & -0.257669 & -1.9959 & 0.025245 \tabularnewline
25 & -0.172125 & -1.3333 & 0.093741 \tabularnewline
26 & -0.043582 & -0.3376 & 0.368428 \tabularnewline
27 & -0.113466 & -0.8789 & 0.19148 \tabularnewline
28 & -0.057185 & -0.443 & 0.329696 \tabularnewline
29 & -0.027684 & -0.2144 & 0.415465 \tabularnewline
30 & -0.080209 & -0.6213 & 0.268378 \tabularnewline
31 & 0.025073 & 0.1942 & 0.423331 \tabularnewline
32 & 0.050728 & 0.3929 & 0.34788 \tabularnewline
33 & -0.099155 & -0.7681 & 0.222734 \tabularnewline
34 & 0.055368 & 0.4289 & 0.334773 \tabularnewline
35 & 0.065713 & 0.509 & 0.306305 \tabularnewline
36 & 0.066664 & 0.5164 & 0.303744 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28886&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]0.143189[/C][C]1.1091[/C][C]0.135898[/C][/ROW]
[ROW][C]2[/C][C]0.085576[/C][C]0.6629[/C][C]0.254975[/C][/ROW]
[ROW][C]3[/C][C]0.263337[/C][C]2.0398[/C][C]0.02289[/C][/ROW]
[ROW][C]4[/C][C]-0.023449[/C][C]-0.1816[/C][C]0.42824[/C][/ROW]
[ROW][C]5[/C][C]0.087077[/C][C]0.6745[/C][C]0.251293[/C][/ROW]
[ROW][C]6[/C][C]0.191357[/C][C]1.4822[/C][C]0.071754[/C][/ROW]
[ROW][C]7[/C][C]-0.135291[/C][C]-1.048[/C][C]0.149429[/C][/ROW]
[ROW][C]8[/C][C]0.115282[/C][C]0.893[/C][C]0.18772[/C][/ROW]
[ROW][C]9[/C][C]0.202163[/C][C]1.5659[/C][C]0.06131[/C][/ROW]
[ROW][C]10[/C][C]-0.207435[/C][C]-1.6068[/C][C]0.056676[/C][/ROW]
[ROW][C]11[/C][C]-0.057854[/C][C]-0.4481[/C][C]0.327834[/C][/ROW]
[ROW][C]12[/C][C]-0.204951[/C][C]-1.5875[/C][C]0.058823[/C][/ROW]
[ROW][C]13[/C][C]-0.253044[/C][C]-1.9601[/C][C]0.027318[/C][/ROW]
[ROW][C]14[/C][C]0.092482[/C][C]0.7164[/C][C]0.238274[/C][/ROW]
[ROW][C]15[/C][C]-0.135341[/C][C]-1.0483[/C][C]0.149343[/C][/ROW]
[ROW][C]16[/C][C]-0.184691[/C][C]-1.4306[/C][C]0.078864[/C][/ROW]
[ROW][C]17[/C][C]0.153394[/C][C]1.1882[/C][C]0.119722[/C][/ROW]
[ROW][C]18[/C][C]-0.1473[/C][C]-1.141[/C][C]0.129206[/C][/ROW]
[ROW][C]19[/C][C]-0.180209[/C][C]-1.3959[/C][C]0.083945[/C][/ROW]
[ROW][C]20[/C][C]-0.041983[/C][C]-0.3252[/C][C]0.373081[/C][/ROW]
[ROW][C]21[/C][C]-0.135291[/C][C]-1.048[/C][C]0.149431[/C][/ROW]
[ROW][C]22[/C][C]-0.138711[/C][C]-1.0745[/C][C]0.143461[/C][/ROW]
[ROW][C]23[/C][C]0.079304[/C][C]0.6143[/C][C]0.270673[/C][/ROW]
[ROW][C]24[/C][C]-0.257669[/C][C]-1.9959[/C][C]0.025245[/C][/ROW]
[ROW][C]25[/C][C]-0.172125[/C][C]-1.3333[/C][C]0.093741[/C][/ROW]
[ROW][C]26[/C][C]-0.043582[/C][C]-0.3376[/C][C]0.368428[/C][/ROW]
[ROW][C]27[/C][C]-0.113466[/C][C]-0.8789[/C][C]0.19148[/C][/ROW]
[ROW][C]28[/C][C]-0.057185[/C][C]-0.443[/C][C]0.329696[/C][/ROW]
[ROW][C]29[/C][C]-0.027684[/C][C]-0.2144[/C][C]0.415465[/C][/ROW]
[ROW][C]30[/C][C]-0.080209[/C][C]-0.6213[/C][C]0.268378[/C][/ROW]
[ROW][C]31[/C][C]0.025073[/C][C]0.1942[/C][C]0.423331[/C][/ROW]
[ROW][C]32[/C][C]0.050728[/C][C]0.3929[/C][C]0.34788[/C][/ROW]
[ROW][C]33[/C][C]-0.099155[/C][C]-0.7681[/C][C]0.222734[/C][/ROW]
[ROW][C]34[/C][C]0.055368[/C][C]0.4289[/C][C]0.334773[/C][/ROW]
[ROW][C]35[/C][C]0.065713[/C][C]0.509[/C][C]0.306305[/C][/ROW]
[ROW][C]36[/C][C]0.066664[/C][C]0.5164[/C][C]0.303744[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28886&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28886&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
10.1431891.10910.135898
20.0855760.66290.254975
30.2633372.03980.02289
4-0.023449-0.18160.42824
50.0870770.67450.251293
60.1913571.48220.071754
7-0.135291-1.0480.149429
80.1152820.8930.18772
90.2021631.56590.06131
10-0.207435-1.60680.056676
11-0.057854-0.44810.327834
12-0.204951-1.58750.058823
13-0.253044-1.96010.027318
140.0924820.71640.238274
15-0.135341-1.04830.149343
16-0.184691-1.43060.078864
170.1533941.18820.119722
18-0.1473-1.1410.129206
19-0.180209-1.39590.083945
20-0.041983-0.32520.373081
21-0.135291-1.0480.149431
22-0.138711-1.07450.143461
230.0793040.61430.270673
24-0.257669-1.99590.025245
25-0.172125-1.33330.093741
26-0.043582-0.33760.368428
27-0.113466-0.87890.19148
28-0.057185-0.4430.329696
29-0.027684-0.21440.415465
30-0.080209-0.62130.268378
310.0250730.19420.423331
320.0507280.39290.34788
33-0.099155-0.76810.222734
340.0553680.42890.334773
350.0657130.5090.306305
360.0666640.51640.303744






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1431891.10910.135898
20.0664350.51460.304359
30.2485561.92530.029467
4-0.101358-0.78510.217737
50.0806270.62450.267321
60.1210720.93780.176049
7-0.171394-1.32760.094667
80.1209670.9370.176256
90.1357091.05120.148691
10-0.224446-1.73860.043622
11-0.111703-0.86520.195175
12-0.264648-2.050.022373
13-0.065311-0.50590.307392
140.1416951.09760.13839
15-0.083251-0.64490.260738
16-0.010799-0.08360.466808
170.138271.0710.144221
18-0.105701-0.81880.208083
19-0.090348-0.69980.243368
20-0.090579-0.70160.242814
210.1301131.00790.158787
22-0.190988-1.47940.072134
23-0.044852-0.34740.364744
24-0.222295-1.72190.045121
25-0.205028-1.58810.058756
26-0.096324-0.74610.229254
270.1121320.86860.194272
28-0.001264-0.00980.49611
290.0596670.46220.322812
30-0.02665-0.20640.418576
31-0.086981-0.67380.251529
32-0.010783-0.08350.466855
330.0055510.0430.482924
34-0.013722-0.10630.457855
35-0.02502-0.19380.423493
36-0.037177-0.2880.387181

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.143189 & 1.1091 & 0.135898 \tabularnewline
2 & 0.066435 & 0.5146 & 0.304359 \tabularnewline
3 & 0.248556 & 1.9253 & 0.029467 \tabularnewline
4 & -0.101358 & -0.7851 & 0.217737 \tabularnewline
5 & 0.080627 & 0.6245 & 0.267321 \tabularnewline
6 & 0.121072 & 0.9378 & 0.176049 \tabularnewline
7 & -0.171394 & -1.3276 & 0.094667 \tabularnewline
8 & 0.120967 & 0.937 & 0.176256 \tabularnewline
9 & 0.135709 & 1.0512 & 0.148691 \tabularnewline
10 & -0.224446 & -1.7386 & 0.043622 \tabularnewline
11 & -0.111703 & -0.8652 & 0.195175 \tabularnewline
12 & -0.264648 & -2.05 & 0.022373 \tabularnewline
13 & -0.065311 & -0.5059 & 0.307392 \tabularnewline
14 & 0.141695 & 1.0976 & 0.13839 \tabularnewline
15 & -0.083251 & -0.6449 & 0.260738 \tabularnewline
16 & -0.010799 & -0.0836 & 0.466808 \tabularnewline
17 & 0.13827 & 1.071 & 0.144221 \tabularnewline
18 & -0.105701 & -0.8188 & 0.208083 \tabularnewline
19 & -0.090348 & -0.6998 & 0.243368 \tabularnewline
20 & -0.090579 & -0.7016 & 0.242814 \tabularnewline
21 & 0.130113 & 1.0079 & 0.158787 \tabularnewline
22 & -0.190988 & -1.4794 & 0.072134 \tabularnewline
23 & -0.044852 & -0.3474 & 0.364744 \tabularnewline
24 & -0.222295 & -1.7219 & 0.045121 \tabularnewline
25 & -0.205028 & -1.5881 & 0.058756 \tabularnewline
26 & -0.096324 & -0.7461 & 0.229254 \tabularnewline
27 & 0.112132 & 0.8686 & 0.194272 \tabularnewline
28 & -0.001264 & -0.0098 & 0.49611 \tabularnewline
29 & 0.059667 & 0.4622 & 0.322812 \tabularnewline
30 & -0.02665 & -0.2064 & 0.418576 \tabularnewline
31 & -0.086981 & -0.6738 & 0.251529 \tabularnewline
32 & -0.010783 & -0.0835 & 0.466855 \tabularnewline
33 & 0.005551 & 0.043 & 0.482924 \tabularnewline
34 & -0.013722 & -0.1063 & 0.457855 \tabularnewline
35 & -0.02502 & -0.1938 & 0.423493 \tabularnewline
36 & -0.037177 & -0.288 & 0.387181 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28886&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]0.143189[/C][C]1.1091[/C][C]0.135898[/C][/ROW]
[ROW][C]2[/C][C]0.066435[/C][C]0.5146[/C][C]0.304359[/C][/ROW]
[ROW][C]3[/C][C]0.248556[/C][C]1.9253[/C][C]0.029467[/C][/ROW]
[ROW][C]4[/C][C]-0.101358[/C][C]-0.7851[/C][C]0.217737[/C][/ROW]
[ROW][C]5[/C][C]0.080627[/C][C]0.6245[/C][C]0.267321[/C][/ROW]
[ROW][C]6[/C][C]0.121072[/C][C]0.9378[/C][C]0.176049[/C][/ROW]
[ROW][C]7[/C][C]-0.171394[/C][C]-1.3276[/C][C]0.094667[/C][/ROW]
[ROW][C]8[/C][C]0.120967[/C][C]0.937[/C][C]0.176256[/C][/ROW]
[ROW][C]9[/C][C]0.135709[/C][C]1.0512[/C][C]0.148691[/C][/ROW]
[ROW][C]10[/C][C]-0.224446[/C][C]-1.7386[/C][C]0.043622[/C][/ROW]
[ROW][C]11[/C][C]-0.111703[/C][C]-0.8652[/C][C]0.195175[/C][/ROW]
[ROW][C]12[/C][C]-0.264648[/C][C]-2.05[/C][C]0.022373[/C][/ROW]
[ROW][C]13[/C][C]-0.065311[/C][C]-0.5059[/C][C]0.307392[/C][/ROW]
[ROW][C]14[/C][C]0.141695[/C][C]1.0976[/C][C]0.13839[/C][/ROW]
[ROW][C]15[/C][C]-0.083251[/C][C]-0.6449[/C][C]0.260738[/C][/ROW]
[ROW][C]16[/C][C]-0.010799[/C][C]-0.0836[/C][C]0.466808[/C][/ROW]
[ROW][C]17[/C][C]0.13827[/C][C]1.071[/C][C]0.144221[/C][/ROW]
[ROW][C]18[/C][C]-0.105701[/C][C]-0.8188[/C][C]0.208083[/C][/ROW]
[ROW][C]19[/C][C]-0.090348[/C][C]-0.6998[/C][C]0.243368[/C][/ROW]
[ROW][C]20[/C][C]-0.090579[/C][C]-0.7016[/C][C]0.242814[/C][/ROW]
[ROW][C]21[/C][C]0.130113[/C][C]1.0079[/C][C]0.158787[/C][/ROW]
[ROW][C]22[/C][C]-0.190988[/C][C]-1.4794[/C][C]0.072134[/C][/ROW]
[ROW][C]23[/C][C]-0.044852[/C][C]-0.3474[/C][C]0.364744[/C][/ROW]
[ROW][C]24[/C][C]-0.222295[/C][C]-1.7219[/C][C]0.045121[/C][/ROW]
[ROW][C]25[/C][C]-0.205028[/C][C]-1.5881[/C][C]0.058756[/C][/ROW]
[ROW][C]26[/C][C]-0.096324[/C][C]-0.7461[/C][C]0.229254[/C][/ROW]
[ROW][C]27[/C][C]0.112132[/C][C]0.8686[/C][C]0.194272[/C][/ROW]
[ROW][C]28[/C][C]-0.001264[/C][C]-0.0098[/C][C]0.49611[/C][/ROW]
[ROW][C]29[/C][C]0.059667[/C][C]0.4622[/C][C]0.322812[/C][/ROW]
[ROW][C]30[/C][C]-0.02665[/C][C]-0.2064[/C][C]0.418576[/C][/ROW]
[ROW][C]31[/C][C]-0.086981[/C][C]-0.6738[/C][C]0.251529[/C][/ROW]
[ROW][C]32[/C][C]-0.010783[/C][C]-0.0835[/C][C]0.466855[/C][/ROW]
[ROW][C]33[/C][C]0.005551[/C][C]0.043[/C][C]0.482924[/C][/ROW]
[ROW][C]34[/C][C]-0.013722[/C][C]-0.1063[/C][C]0.457855[/C][/ROW]
[ROW][C]35[/C][C]-0.02502[/C][C]-0.1938[/C][C]0.423493[/C][/ROW]
[ROW][C]36[/C][C]-0.037177[/C][C]-0.288[/C][C]0.387181[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28886&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28886&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
10.1431891.10910.135898
20.0664350.51460.304359
30.2485561.92530.029467
4-0.101358-0.78510.217737
50.0806270.62450.267321
60.1210720.93780.176049
7-0.171394-1.32760.094667
80.1209670.9370.176256
90.1357091.05120.148691
10-0.224446-1.73860.043622
11-0.111703-0.86520.195175
12-0.264648-2.050.022373
13-0.065311-0.50590.307392
140.1416951.09760.13839
15-0.083251-0.64490.260738
16-0.010799-0.08360.466808
170.138271.0710.144221
18-0.105701-0.81880.208083
19-0.090348-0.69980.243368
20-0.090579-0.70160.242814
210.1301131.00790.158787
22-0.190988-1.47940.072134
23-0.044852-0.34740.364744
24-0.222295-1.72190.045121
25-0.205028-1.58810.058756
26-0.096324-0.74610.229254
270.1121320.86860.194272
28-0.001264-0.00980.49611
290.0596670.46220.322812
30-0.02665-0.20640.418576
31-0.086981-0.67380.251529
32-0.010783-0.08350.466855
330.0055510.0430.482924
34-0.013722-0.10630.457855
35-0.02502-0.19380.423493
36-0.037177-0.2880.387181


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 0 ; 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')