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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationWed, 24 Dec 2008 07:50:15 -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/24/t1230130279xds78vojwmfqquf.htm/, Retrieved Sun, 19 May 2024 10:20:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=36599, Retrieved Sun, 19 May 2024 10:20:22 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact134

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
F RMPD  [Variance Reduction Matrix] [Identification an...] [2008-12-09 21:59:36] [1a689e9ccc515e1757f0522229a687e9]
-    D    [Variance Reduction Matrix] [Paper Variance Re...] [2008-12-24 14:39:33] [1a689e9ccc515e1757f0522229a687e9]
- RMPD      [(Partial) Autocorrelation Function] [Paper Autocorrela...] [2008-12-24 14:44:07] [1a689e9ccc515e1757f0522229a687e9]
-   P         [(Partial) Autocorrelation Function] [Paper Variance Re...] [2008-12-24 14:47:06] [1a689e9ccc515e1757f0522229a687e9]
-   P             [(Partial) Autocorrelation Function] [Paper Autocorrela...] [2008-12-24 14:50:15] [74a138e5b32af267311b5ad4cd13bf7e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
105.7
109.5
105.3
102.8
100.6
97.6
110.3
107.2
107.2
108.1
97.1
92.2
112.2
111.6
115.7
111.3
104.2
103.2
112.7
106.4
102.6
110.6
95.2
89
112.5
116.8
107.2
113.6
101.8
102.6
122.7
110.3
110.5
121.6
100.3
100.7
123.4
127.1
124.1
131.2
111.6
114.2
130.1
125.9
119
133.8
107.5
113.5
134.4
126.8
135.6
139.9
129.8
131
153.1
134.1
144.1
155.9
123.3
128.1
144.3
153
149.9
150.9
141
138.9
157.4
142.9
151.7
161
138.5
135.9
151.5
164
159.1
157
142.1
144.8
152.1
154.6
148.7
157.7
146.4
136.5

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36599&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]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36599&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36599&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 time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.587588-4.95112e-06
20.1068750.90050.185438
30.0903390.76120.224527
4-0.095532-0.8050.211764
50.0662690.55840.289167
6-0.021553-0.18160.428204
70.0198930.16760.433679
8-0.156882-1.32190.095221
90.2957422.4920.00752
10-0.249621-2.10330.01949
110.1326531.11780.133721
12-0.145923-1.22960.111459
130.0458840.38660.350094
140.0574950.48450.314774
15-0.061342-0.51690.303423
160.075780.63850.262592
17-0.186221-1.56910.060533
180.336242.83320.002997
19-0.27502-2.31740.011686
200.0741410.62470.267077
210.0509310.42920.334555
22-0.117591-0.99080.162564
230.2368791.9960.024886
24-0.212739-1.79260.038651
250.0533280.44940.327273
260.0287480.24220.404649
270.0382510.32230.374082
28-0.195902-1.65070.051608
290.2769982.3340.011215
30-0.242967-2.04730.022166
310.0837860.7060.24125
320.104990.88470.189662
33-0.168522-1.420.079993
340.0841970.70950.240183
35-0.092608-0.78030.218897
360.0811470.68380.248176

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.587588 & -4.9511 & 2e-06 \tabularnewline
2 & 0.106875 & 0.9005 & 0.185438 \tabularnewline
3 & 0.090339 & 0.7612 & 0.224527 \tabularnewline
4 & -0.095532 & -0.805 & 0.211764 \tabularnewline
5 & 0.066269 & 0.5584 & 0.289167 \tabularnewline
6 & -0.021553 & -0.1816 & 0.428204 \tabularnewline
7 & 0.019893 & 0.1676 & 0.433679 \tabularnewline
8 & -0.156882 & -1.3219 & 0.095221 \tabularnewline
9 & 0.295742 & 2.492 & 0.00752 \tabularnewline
10 & -0.249621 & -2.1033 & 0.01949 \tabularnewline
11 & 0.132653 & 1.1178 & 0.133721 \tabularnewline
12 & -0.145923 & -1.2296 & 0.111459 \tabularnewline
13 & 0.045884 & 0.3866 & 0.350094 \tabularnewline
14 & 0.057495 & 0.4845 & 0.314774 \tabularnewline
15 & -0.061342 & -0.5169 & 0.303423 \tabularnewline
16 & 0.07578 & 0.6385 & 0.262592 \tabularnewline
17 & -0.186221 & -1.5691 & 0.060533 \tabularnewline
18 & 0.33624 & 2.8332 & 0.002997 \tabularnewline
19 & -0.27502 & -2.3174 & 0.011686 \tabularnewline
20 & 0.074141 & 0.6247 & 0.267077 \tabularnewline
21 & 0.050931 & 0.4292 & 0.334555 \tabularnewline
22 & -0.117591 & -0.9908 & 0.162564 \tabularnewline
23 & 0.236879 & 1.996 & 0.024886 \tabularnewline
24 & -0.212739 & -1.7926 & 0.038651 \tabularnewline
25 & 0.053328 & 0.4494 & 0.327273 \tabularnewline
26 & 0.028748 & 0.2422 & 0.404649 \tabularnewline
27 & 0.038251 & 0.3223 & 0.374082 \tabularnewline
28 & -0.195902 & -1.6507 & 0.051608 \tabularnewline
29 & 0.276998 & 2.334 & 0.011215 \tabularnewline
30 & -0.242967 & -2.0473 & 0.022166 \tabularnewline
31 & 0.083786 & 0.706 & 0.24125 \tabularnewline
32 & 0.10499 & 0.8847 & 0.189662 \tabularnewline
33 & -0.168522 & -1.42 & 0.079993 \tabularnewline
34 & 0.084197 & 0.7095 & 0.240183 \tabularnewline
35 & -0.092608 & -0.7803 & 0.218897 \tabularnewline
36 & 0.081147 & 0.6838 & 0.248176 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36599&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]-0.587588[/C][C]-4.9511[/C][C]2e-06[/C][/ROW]
[ROW][C]2[/C][C]0.106875[/C][C]0.9005[/C][C]0.185438[/C][/ROW]
[ROW][C]3[/C][C]0.090339[/C][C]0.7612[/C][C]0.224527[/C][/ROW]
[ROW][C]4[/C][C]-0.095532[/C][C]-0.805[/C][C]0.211764[/C][/ROW]
[ROW][C]5[/C][C]0.066269[/C][C]0.5584[/C][C]0.289167[/C][/ROW]
[ROW][C]6[/C][C]-0.021553[/C][C]-0.1816[/C][C]0.428204[/C][/ROW]
[ROW][C]7[/C][C]0.019893[/C][C]0.1676[/C][C]0.433679[/C][/ROW]
[ROW][C]8[/C][C]-0.156882[/C][C]-1.3219[/C][C]0.095221[/C][/ROW]
[ROW][C]9[/C][C]0.295742[/C][C]2.492[/C][C]0.00752[/C][/ROW]
[ROW][C]10[/C][C]-0.249621[/C][C]-2.1033[/C][C]0.01949[/C][/ROW]
[ROW][C]11[/C][C]0.132653[/C][C]1.1178[/C][C]0.133721[/C][/ROW]
[ROW][C]12[/C][C]-0.145923[/C][C]-1.2296[/C][C]0.111459[/C][/ROW]
[ROW][C]13[/C][C]0.045884[/C][C]0.3866[/C][C]0.350094[/C][/ROW]
[ROW][C]14[/C][C]0.057495[/C][C]0.4845[/C][C]0.314774[/C][/ROW]
[ROW][C]15[/C][C]-0.061342[/C][C]-0.5169[/C][C]0.303423[/C][/ROW]
[ROW][C]16[/C][C]0.07578[/C][C]0.6385[/C][C]0.262592[/C][/ROW]
[ROW][C]17[/C][C]-0.186221[/C][C]-1.5691[/C][C]0.060533[/C][/ROW]
[ROW][C]18[/C][C]0.33624[/C][C]2.8332[/C][C]0.002997[/C][/ROW]
[ROW][C]19[/C][C]-0.27502[/C][C]-2.3174[/C][C]0.011686[/C][/ROW]
[ROW][C]20[/C][C]0.074141[/C][C]0.6247[/C][C]0.267077[/C][/ROW]
[ROW][C]21[/C][C]0.050931[/C][C]0.4292[/C][C]0.334555[/C][/ROW]
[ROW][C]22[/C][C]-0.117591[/C][C]-0.9908[/C][C]0.162564[/C][/ROW]
[ROW][C]23[/C][C]0.236879[/C][C]1.996[/C][C]0.024886[/C][/ROW]
[ROW][C]24[/C][C]-0.212739[/C][C]-1.7926[/C][C]0.038651[/C][/ROW]
[ROW][C]25[/C][C]0.053328[/C][C]0.4494[/C][C]0.327273[/C][/ROW]
[ROW][C]26[/C][C]0.028748[/C][C]0.2422[/C][C]0.404649[/C][/ROW]
[ROW][C]27[/C][C]0.038251[/C][C]0.3223[/C][C]0.374082[/C][/ROW]
[ROW][C]28[/C][C]-0.195902[/C][C]-1.6507[/C][C]0.051608[/C][/ROW]
[ROW][C]29[/C][C]0.276998[/C][C]2.334[/C][C]0.011215[/C][/ROW]
[ROW][C]30[/C][C]-0.242967[/C][C]-2.0473[/C][C]0.022166[/C][/ROW]
[ROW][C]31[/C][C]0.083786[/C][C]0.706[/C][C]0.24125[/C][/ROW]
[ROW][C]32[/C][C]0.10499[/C][C]0.8847[/C][C]0.189662[/C][/ROW]
[ROW][C]33[/C][C]-0.168522[/C][C]-1.42[/C][C]0.079993[/C][/ROW]
[ROW][C]34[/C][C]0.084197[/C][C]0.7095[/C][C]0.240183[/C][/ROW]
[ROW][C]35[/C][C]-0.092608[/C][C]-0.7803[/C][C]0.218897[/C][/ROW]
[ROW][C]36[/C][C]0.081147[/C][C]0.6838[/C][C]0.248176[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36599&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36599&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
1-0.587588-4.95112e-06
20.1068750.90050.185438
30.0903390.76120.224527
4-0.095532-0.8050.211764
50.0662690.55840.289167
6-0.021553-0.18160.428204
70.0198930.16760.433679
8-0.156882-1.32190.095221
90.2957422.4920.00752
10-0.249621-2.10330.01949
110.1326531.11780.133721
12-0.145923-1.22960.111459
130.0458840.38660.350094
140.0574950.48450.314774
15-0.061342-0.51690.303423
160.075780.63850.262592
17-0.186221-1.56910.060533
180.336242.83320.002997
19-0.27502-2.31740.011686
200.0741410.62470.267077
210.0509310.42920.334555
22-0.117591-0.99080.162564
230.2368791.9960.024886
24-0.212739-1.79260.038651
250.0533280.44940.327273
260.0287480.24220.404649
270.0382510.32230.374082
28-0.195902-1.65070.051608
290.2769982.3340.011215
30-0.242967-2.04730.022166
310.0837860.7060.24125
320.104990.88470.189662
33-0.168522-1.420.079993
340.0841970.70950.240183
35-0.092608-0.78030.218897
360.0811470.68380.248176






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.587588-4.95112e-06
2-0.364091-3.06790.001525
3-0.066792-0.56280.287673
4-0.027482-0.23160.408771
50.0343020.2890.386698
60.0342840.28890.386757
70.0628640.52970.298985
8-0.219509-1.84960.034265
90.1208831.01860.155931
100.0161670.13620.446015
110.0835150.70370.241957
12-0.207518-1.74860.042343
13-0.20098-1.69350.047373
14-0.094197-0.79370.215003
150.023740.20.421013
160.1229971.03640.151769
17-0.106424-0.89670.186444
180.1853081.56140.061434
190.0656290.5530.290999
20-0.080838-0.68120.248996
210.0154950.13060.448245
22-0.076716-0.64640.260046
230.2293071.93220.028664
24-0.008733-0.07360.470774
25-0.150704-1.26990.104141
260.0129990.10950.456546
270.0276570.2330.408198
28-0.168619-1.42080.079875
290.1120650.94430.174115
300.0312710.26350.396465
310.0466310.39290.347779
32-0.105359-0.88780.188831
33-0.002192-0.01850.492658
34-0.016389-0.13810.445276
35-0.079383-0.66890.252868
36-0.218089-1.83770.035149

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.587588 & -4.9511 & 2e-06 \tabularnewline
2 & -0.364091 & -3.0679 & 0.001525 \tabularnewline
3 & -0.066792 & -0.5628 & 0.287673 \tabularnewline
4 & -0.027482 & -0.2316 & 0.408771 \tabularnewline
5 & 0.034302 & 0.289 & 0.386698 \tabularnewline
6 & 0.034284 & 0.2889 & 0.386757 \tabularnewline
7 & 0.062864 & 0.5297 & 0.298985 \tabularnewline
8 & -0.219509 & -1.8496 & 0.034265 \tabularnewline
9 & 0.120883 & 1.0186 & 0.155931 \tabularnewline
10 & 0.016167 & 0.1362 & 0.446015 \tabularnewline
11 & 0.083515 & 0.7037 & 0.241957 \tabularnewline
12 & -0.207518 & -1.7486 & 0.042343 \tabularnewline
13 & -0.20098 & -1.6935 & 0.047373 \tabularnewline
14 & -0.094197 & -0.7937 & 0.215003 \tabularnewline
15 & 0.02374 & 0.2 & 0.421013 \tabularnewline
16 & 0.122997 & 1.0364 & 0.151769 \tabularnewline
17 & -0.106424 & -0.8967 & 0.186444 \tabularnewline
18 & 0.185308 & 1.5614 & 0.061434 \tabularnewline
19 & 0.065629 & 0.553 & 0.290999 \tabularnewline
20 & -0.080838 & -0.6812 & 0.248996 \tabularnewline
21 & 0.015495 & 0.1306 & 0.448245 \tabularnewline
22 & -0.076716 & -0.6464 & 0.260046 \tabularnewline
23 & 0.229307 & 1.9322 & 0.028664 \tabularnewline
24 & -0.008733 & -0.0736 & 0.470774 \tabularnewline
25 & -0.150704 & -1.2699 & 0.104141 \tabularnewline
26 & 0.012999 & 0.1095 & 0.456546 \tabularnewline
27 & 0.027657 & 0.233 & 0.408198 \tabularnewline
28 & -0.168619 & -1.4208 & 0.079875 \tabularnewline
29 & 0.112065 & 0.9443 & 0.174115 \tabularnewline
30 & 0.031271 & 0.2635 & 0.396465 \tabularnewline
31 & 0.046631 & 0.3929 & 0.347779 \tabularnewline
32 & -0.105359 & -0.8878 & 0.188831 \tabularnewline
33 & -0.002192 & -0.0185 & 0.492658 \tabularnewline
34 & -0.016389 & -0.1381 & 0.445276 \tabularnewline
35 & -0.079383 & -0.6689 & 0.252868 \tabularnewline
36 & -0.218089 & -1.8377 & 0.035149 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36599&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]-0.587588[/C][C]-4.9511[/C][C]2e-06[/C][/ROW]
[ROW][C]2[/C][C]-0.364091[/C][C]-3.0679[/C][C]0.001525[/C][/ROW]
[ROW][C]3[/C][C]-0.066792[/C][C]-0.5628[/C][C]0.287673[/C][/ROW]
[ROW][C]4[/C][C]-0.027482[/C][C]-0.2316[/C][C]0.408771[/C][/ROW]
[ROW][C]5[/C][C]0.034302[/C][C]0.289[/C][C]0.386698[/C][/ROW]
[ROW][C]6[/C][C]0.034284[/C][C]0.2889[/C][C]0.386757[/C][/ROW]
[ROW][C]7[/C][C]0.062864[/C][C]0.5297[/C][C]0.298985[/C][/ROW]
[ROW][C]8[/C][C]-0.219509[/C][C]-1.8496[/C][C]0.034265[/C][/ROW]
[ROW][C]9[/C][C]0.120883[/C][C]1.0186[/C][C]0.155931[/C][/ROW]
[ROW][C]10[/C][C]0.016167[/C][C]0.1362[/C][C]0.446015[/C][/ROW]
[ROW][C]11[/C][C]0.083515[/C][C]0.7037[/C][C]0.241957[/C][/ROW]
[ROW][C]12[/C][C]-0.207518[/C][C]-1.7486[/C][C]0.042343[/C][/ROW]
[ROW][C]13[/C][C]-0.20098[/C][C]-1.6935[/C][C]0.047373[/C][/ROW]
[ROW][C]14[/C][C]-0.094197[/C][C]-0.7937[/C][C]0.215003[/C][/ROW]
[ROW][C]15[/C][C]0.02374[/C][C]0.2[/C][C]0.421013[/C][/ROW]
[ROW][C]16[/C][C]0.122997[/C][C]1.0364[/C][C]0.151769[/C][/ROW]
[ROW][C]17[/C][C]-0.106424[/C][C]-0.8967[/C][C]0.186444[/C][/ROW]
[ROW][C]18[/C][C]0.185308[/C][C]1.5614[/C][C]0.061434[/C][/ROW]
[ROW][C]19[/C][C]0.065629[/C][C]0.553[/C][C]0.290999[/C][/ROW]
[ROW][C]20[/C][C]-0.080838[/C][C]-0.6812[/C][C]0.248996[/C][/ROW]
[ROW][C]21[/C][C]0.015495[/C][C]0.1306[/C][C]0.448245[/C][/ROW]
[ROW][C]22[/C][C]-0.076716[/C][C]-0.6464[/C][C]0.260046[/C][/ROW]
[ROW][C]23[/C][C]0.229307[/C][C]1.9322[/C][C]0.028664[/C][/ROW]
[ROW][C]24[/C][C]-0.008733[/C][C]-0.0736[/C][C]0.470774[/C][/ROW]
[ROW][C]25[/C][C]-0.150704[/C][C]-1.2699[/C][C]0.104141[/C][/ROW]
[ROW][C]26[/C][C]0.012999[/C][C]0.1095[/C][C]0.456546[/C][/ROW]
[ROW][C]27[/C][C]0.027657[/C][C]0.233[/C][C]0.408198[/C][/ROW]
[ROW][C]28[/C][C]-0.168619[/C][C]-1.4208[/C][C]0.079875[/C][/ROW]
[ROW][C]29[/C][C]0.112065[/C][C]0.9443[/C][C]0.174115[/C][/ROW]
[ROW][C]30[/C][C]0.031271[/C][C]0.2635[/C][C]0.396465[/C][/ROW]
[ROW][C]31[/C][C]0.046631[/C][C]0.3929[/C][C]0.347779[/C][/ROW]
[ROW][C]32[/C][C]-0.105359[/C][C]-0.8878[/C][C]0.188831[/C][/ROW]
[ROW][C]33[/C][C]-0.002192[/C][C]-0.0185[/C][C]0.492658[/C][/ROW]
[ROW][C]34[/C][C]-0.016389[/C][C]-0.1381[/C][C]0.445276[/C][/ROW]
[ROW][C]35[/C][C]-0.079383[/C][C]-0.6689[/C][C]0.252868[/C][/ROW]
[ROW][C]36[/C][C]-0.218089[/C][C]-1.8377[/C][C]0.035149[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36599&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36599&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
1-0.587588-4.95112e-06
2-0.364091-3.06790.001525
3-0.066792-0.56280.287673
4-0.027482-0.23160.408771
50.0343020.2890.386698
60.0342840.28890.386757
70.0628640.52970.298985
8-0.219509-1.84960.034265
90.1208831.01860.155931
100.0161670.13620.446015
110.0835150.70370.241957
12-0.207518-1.74860.042343
13-0.20098-1.69350.047373
14-0.094197-0.79370.215003
150.023740.20.421013
160.1229971.03640.151769
17-0.106424-0.89670.186444
180.1853081.56140.061434
190.0656290.5530.290999
20-0.080838-0.68120.248996
210.0154950.13060.448245
22-0.076716-0.64640.260046
230.2293071.93220.028664
24-0.008733-0.07360.470774
25-0.150704-1.26990.104141
260.0129990.10950.456546
270.0276570.2330.408198
28-0.168619-1.42080.079875
290.1120650.94430.174115
300.0312710.26350.396465
310.0466310.39290.347779
32-0.105359-0.88780.188831
33-0.002192-0.01850.492658
34-0.016389-0.13810.445276
35-0.079383-0.66890.252868
36-0.218089-1.83770.035149


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')