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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 computationMon, 08 Dec 2008 13:06:09 -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/08/t12287668236o6gl06il3exwpp.htm/, Retrieved Thu, 16 May 2024 10:00:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=30902, Retrieved Thu, 16 May 2024 10:00:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact168

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Spectral Analysis] [Aanvulling Q8] [2008-12-08 18:54:28] [b1bd16d1f47bfe13feacf1c27a0abba5]
-    D  [Spectral Analysis] [Aanvulling Q8(2)] [2008-12-08 19:19:21] [b1bd16d1f47bfe13feacf1c27a0abba5]
-   PD    [Spectral Analysis] [Aanvulling Q8 (3)] [2008-12-08 19:22:47] [b1bd16d1f47bfe13feacf1c27a0abba5]
F RMPD        [(Partial) Autocorrelation Function] [eigen reeks stap ...] [2008-12-08 20:06:09] [e7b1048c2c3a353441b9143db4404b91] [Current]
F   PD          [(Partial) Autocorrelation Function] [step 3 ACF] [2008-12-08 20:25:32] [b1bd16d1f47bfe13feacf1c27a0abba5]
Feedback Forum
2008-12-14 16:05:37 [Sofie Mertens] [reply] 
De bevindingen van de studente zijn correct.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
97,8
107,4
117,5
105,6
97,4
99,5
98,0
104,3
100,6
101,1
103,9
96,9
95,5
108,4
117,0
103,8
100,8
110,6
104,0
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
111,0
112,4
130,6
109,1
118,8
123,9
101,6
112,8
128,0
129,6
125,8
119,5
115,7
113,6
129,7
112,0
116,8
127,0
112,1
114,2
121,1
131,6
125,0
120,4
117,7
117,5
120,6
127,5
112,3
124,5
115,2
105,4

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'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30902&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30902&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30902&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.3595383.31480.000675
20.1982611.82790.035538
30.4864074.48451.1e-05
40.1745281.60910.055655
50.2691032.4810.007536
60.5339424.92272e-06
70.1650691.52190.065878
80.1618081.49180.069728
90.36483.36330.000578
100.026420.24360.404071
110.2234182.05980.021238
120.6042345.57080
130.1513931.39580.083209
140.0626690.57780.282469
150.2374152.18890.015675
16-0.043026-0.39670.346298
170.1134381.04580.149299
180.2831852.61080.005337
19-0.039348-0.36280.358839
200.0100170.09240.463317
210.1194731.10150.136897
22-0.150362-1.38630.084646
230.0827310.76270.223865
240.2781792.56470.006042
250.0056860.05240.479157
26-0.017912-0.16510.434613
270.0538530.49650.310413
28-0.158961-1.46550.073231
290.0125910.11610.45393
300.0829780.7650.223191
31-0.099444-0.91680.180913
32-0.052247-0.48170.315631
33-0.066604-0.61410.270408
34-0.188083-1.7340.043268
350.007820.07210.471347
360.14751.35990.088732

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.359538 & 3.3148 & 0.000675 \tabularnewline
2 & 0.198261 & 1.8279 & 0.035538 \tabularnewline
3 & 0.486407 & 4.4845 & 1.1e-05 \tabularnewline
4 & 0.174528 & 1.6091 & 0.055655 \tabularnewline
5 & 0.269103 & 2.481 & 0.007536 \tabularnewline
6 & 0.533942 & 4.9227 & 2e-06 \tabularnewline
7 & 0.165069 & 1.5219 & 0.065878 \tabularnewline
8 & 0.161808 & 1.4918 & 0.069728 \tabularnewline
9 & 0.3648 & 3.3633 & 0.000578 \tabularnewline
10 & 0.02642 & 0.2436 & 0.404071 \tabularnewline
11 & 0.223418 & 2.0598 & 0.021238 \tabularnewline
12 & 0.604234 & 5.5708 & 0 \tabularnewline
13 & 0.151393 & 1.3958 & 0.083209 \tabularnewline
14 & 0.062669 & 0.5778 & 0.282469 \tabularnewline
15 & 0.237415 & 2.1889 & 0.015675 \tabularnewline
16 & -0.043026 & -0.3967 & 0.346298 \tabularnewline
17 & 0.113438 & 1.0458 & 0.149299 \tabularnewline
18 & 0.283185 & 2.6108 & 0.005337 \tabularnewline
19 & -0.039348 & -0.3628 & 0.358839 \tabularnewline
20 & 0.010017 & 0.0924 & 0.463317 \tabularnewline
21 & 0.119473 & 1.1015 & 0.136897 \tabularnewline
22 & -0.150362 & -1.3863 & 0.084646 \tabularnewline
23 & 0.082731 & 0.7627 & 0.223865 \tabularnewline
24 & 0.278179 & 2.5647 & 0.006042 \tabularnewline
25 & 0.005686 & 0.0524 & 0.479157 \tabularnewline
26 & -0.017912 & -0.1651 & 0.434613 \tabularnewline
27 & 0.053853 & 0.4965 & 0.310413 \tabularnewline
28 & -0.158961 & -1.4655 & 0.073231 \tabularnewline
29 & 0.012591 & 0.1161 & 0.45393 \tabularnewline
30 & 0.082978 & 0.765 & 0.223191 \tabularnewline
31 & -0.099444 & -0.9168 & 0.180913 \tabularnewline
32 & -0.052247 & -0.4817 & 0.315631 \tabularnewline
33 & -0.066604 & -0.6141 & 0.270408 \tabularnewline
34 & -0.188083 & -1.734 & 0.043268 \tabularnewline
35 & 0.00782 & 0.0721 & 0.471347 \tabularnewline
36 & 0.1475 & 1.3599 & 0.088732 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30902&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]0.359538[/C][C]3.3148[/C][C]0.000675[/C][/ROW]
[ROW][C]2[/C][C]0.198261[/C][C]1.8279[/C][C]0.035538[/C][/ROW]
[ROW][C]3[/C][C]0.486407[/C][C]4.4845[/C][C]1.1e-05[/C][/ROW]
[ROW][C]4[/C][C]0.174528[/C][C]1.6091[/C][C]0.055655[/C][/ROW]
[ROW][C]5[/C][C]0.269103[/C][C]2.481[/C][C]0.007536[/C][/ROW]
[ROW][C]6[/C][C]0.533942[/C][C]4.9227[/C][C]2e-06[/C][/ROW]
[ROW][C]7[/C][C]0.165069[/C][C]1.5219[/C][C]0.065878[/C][/ROW]
[ROW][C]8[/C][C]0.161808[/C][C]1.4918[/C][C]0.069728[/C][/ROW]
[ROW][C]9[/C][C]0.3648[/C][C]3.3633[/C][C]0.000578[/C][/ROW]
[ROW][C]10[/C][C]0.02642[/C][C]0.2436[/C][C]0.404071[/C][/ROW]
[ROW][C]11[/C][C]0.223418[/C][C]2.0598[/C][C]0.021238[/C][/ROW]
[ROW][C]12[/C][C]0.604234[/C][C]5.5708[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.151393[/C][C]1.3958[/C][C]0.083209[/C][/ROW]
[ROW][C]14[/C][C]0.062669[/C][C]0.5778[/C][C]0.282469[/C][/ROW]
[ROW][C]15[/C][C]0.237415[/C][C]2.1889[/C][C]0.015675[/C][/ROW]
[ROW][C]16[/C][C]-0.043026[/C][C]-0.3967[/C][C]0.346298[/C][/ROW]
[ROW][C]17[/C][C]0.113438[/C][C]1.0458[/C][C]0.149299[/C][/ROW]
[ROW][C]18[/C][C]0.283185[/C][C]2.6108[/C][C]0.005337[/C][/ROW]
[ROW][C]19[/C][C]-0.039348[/C][C]-0.3628[/C][C]0.358839[/C][/ROW]
[ROW][C]20[/C][C]0.010017[/C][C]0.0924[/C][C]0.463317[/C][/ROW]
[ROW][C]21[/C][C]0.119473[/C][C]1.1015[/C][C]0.136897[/C][/ROW]
[ROW][C]22[/C][C]-0.150362[/C][C]-1.3863[/C][C]0.084646[/C][/ROW]
[ROW][C]23[/C][C]0.082731[/C][C]0.7627[/C][C]0.223865[/C][/ROW]
[ROW][C]24[/C][C]0.278179[/C][C]2.5647[/C][C]0.006042[/C][/ROW]
[ROW][C]25[/C][C]0.005686[/C][C]0.0524[/C][C]0.479157[/C][/ROW]
[ROW][C]26[/C][C]-0.017912[/C][C]-0.1651[/C][C]0.434613[/C][/ROW]
[ROW][C]27[/C][C]0.053853[/C][C]0.4965[/C][C]0.310413[/C][/ROW]
[ROW][C]28[/C][C]-0.158961[/C][C]-1.4655[/C][C]0.073231[/C][/ROW]
[ROW][C]29[/C][C]0.012591[/C][C]0.1161[/C][C]0.45393[/C][/ROW]
[ROW][C]30[/C][C]0.082978[/C][C]0.765[/C][C]0.223191[/C][/ROW]
[ROW][C]31[/C][C]-0.099444[/C][C]-0.9168[/C][C]0.180913[/C][/ROW]
[ROW][C]32[/C][C]-0.052247[/C][C]-0.4817[/C][C]0.315631[/C][/ROW]
[ROW][C]33[/C][C]-0.066604[/C][C]-0.6141[/C][C]0.270408[/C][/ROW]
[ROW][C]34[/C][C]-0.188083[/C][C]-1.734[/C][C]0.043268[/C][/ROW]
[ROW][C]35[/C][C]0.00782[/C][C]0.0721[/C][C]0.471347[/C][/ROW]
[ROW][C]36[/C][C]0.1475[/C][C]1.3599[/C][C]0.088732[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30902&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30902&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
10.3595383.31480.000675
20.1982611.82790.035538
30.4864074.48451.1e-05
40.1745281.60910.055655
50.2691032.4810.007536
60.5339424.92272e-06
70.1650691.52190.065878
80.1618081.49180.069728
90.36483.36330.000578
100.026420.24360.404071
110.2234182.05980.021238
120.6042345.57080
130.1513931.39580.083209
140.0626690.57780.282469
150.2374152.18890.015675
16-0.043026-0.39670.346298
170.1134381.04580.149299
180.2831852.61080.005337
19-0.039348-0.36280.358839
200.0100170.09240.463317
210.1194731.10150.136897
22-0.150362-1.38630.084646
230.0827310.76270.223865
240.2781792.56470.006042
250.0056860.05240.479157
26-0.017912-0.16510.434613
270.0538530.49650.310413
28-0.158961-1.46550.073231
290.0125910.11610.45393
300.0829780.7650.223191
31-0.099444-0.91680.180913
32-0.052247-0.48170.315631
33-0.066604-0.61410.270408
34-0.188083-1.7340.043268
350.007820.07210.471347
360.14751.35990.088732






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3595383.31480.000675
20.0792360.73050.233541
30.4533694.17993.5e-05
4-0.171629-1.58230.058643
50.3090262.84910.002749
60.2471022.27820.012613
7-0.113711-1.04840.148721
80.0043310.03990.484121
90.0491010.45270.325962
10-0.191573-1.76620.040475
110.2245672.07040.020724
120.3991733.68020.000204
13-0.140109-1.29170.099975
14-0.234495-2.16190.016717
15-0.14282-1.31670.095734
16-0.078857-0.7270.234604
17-0.014838-0.13680.445758
18-0.069026-0.63640.263118
190.0391880.36130.359387
20-0.031494-0.29040.386125
21-0.024223-0.22330.411908
220.0073630.06790.473018
230.099570.9180.180612
24-0.071321-0.65750.256303
250.1230641.13460.129868
26-0.062041-0.5720.284418
270.0459010.42320.336615
28-0.114518-1.05580.147024
290.0155880.14370.443033
30-0.136172-1.25540.106379
310.1501661.38450.08492
32-0.100638-0.92780.178061
33-0.014401-0.13280.447345
34-0.005736-0.05290.478974
350.0736770.67930.249406
360.1041620.96030.169807

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.359538 & 3.3148 & 0.000675 \tabularnewline
2 & 0.079236 & 0.7305 & 0.233541 \tabularnewline
3 & 0.453369 & 4.1799 & 3.5e-05 \tabularnewline
4 & -0.171629 & -1.5823 & 0.058643 \tabularnewline
5 & 0.309026 & 2.8491 & 0.002749 \tabularnewline
6 & 0.247102 & 2.2782 & 0.012613 \tabularnewline
7 & -0.113711 & -1.0484 & 0.148721 \tabularnewline
8 & 0.004331 & 0.0399 & 0.484121 \tabularnewline
9 & 0.049101 & 0.4527 & 0.325962 \tabularnewline
10 & -0.191573 & -1.7662 & 0.040475 \tabularnewline
11 & 0.224567 & 2.0704 & 0.020724 \tabularnewline
12 & 0.399173 & 3.6802 & 0.000204 \tabularnewline
13 & -0.140109 & -1.2917 & 0.099975 \tabularnewline
14 & -0.234495 & -2.1619 & 0.016717 \tabularnewline
15 & -0.14282 & -1.3167 & 0.095734 \tabularnewline
16 & -0.078857 & -0.727 & 0.234604 \tabularnewline
17 & -0.014838 & -0.1368 & 0.445758 \tabularnewline
18 & -0.069026 & -0.6364 & 0.263118 \tabularnewline
19 & 0.039188 & 0.3613 & 0.359387 \tabularnewline
20 & -0.031494 & -0.2904 & 0.386125 \tabularnewline
21 & -0.024223 & -0.2233 & 0.411908 \tabularnewline
22 & 0.007363 & 0.0679 & 0.473018 \tabularnewline
23 & 0.09957 & 0.918 & 0.180612 \tabularnewline
24 & -0.071321 & -0.6575 & 0.256303 \tabularnewline
25 & 0.123064 & 1.1346 & 0.129868 \tabularnewline
26 & -0.062041 & -0.572 & 0.284418 \tabularnewline
27 & 0.045901 & 0.4232 & 0.336615 \tabularnewline
28 & -0.114518 & -1.0558 & 0.147024 \tabularnewline
29 & 0.015588 & 0.1437 & 0.443033 \tabularnewline
30 & -0.136172 & -1.2554 & 0.106379 \tabularnewline
31 & 0.150166 & 1.3845 & 0.08492 \tabularnewline
32 & -0.100638 & -0.9278 & 0.178061 \tabularnewline
33 & -0.014401 & -0.1328 & 0.447345 \tabularnewline
34 & -0.005736 & -0.0529 & 0.478974 \tabularnewline
35 & 0.073677 & 0.6793 & 0.249406 \tabularnewline
36 & 0.104162 & 0.9603 & 0.169807 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30902&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]0.359538[/C][C]3.3148[/C][C]0.000675[/C][/ROW]
[ROW][C]2[/C][C]0.079236[/C][C]0.7305[/C][C]0.233541[/C][/ROW]
[ROW][C]3[/C][C]0.453369[/C][C]4.1799[/C][C]3.5e-05[/C][/ROW]
[ROW][C]4[/C][C]-0.171629[/C][C]-1.5823[/C][C]0.058643[/C][/ROW]
[ROW][C]5[/C][C]0.309026[/C][C]2.8491[/C][C]0.002749[/C][/ROW]
[ROW][C]6[/C][C]0.247102[/C][C]2.2782[/C][C]0.012613[/C][/ROW]
[ROW][C]7[/C][C]-0.113711[/C][C]-1.0484[/C][C]0.148721[/C][/ROW]
[ROW][C]8[/C][C]0.004331[/C][C]0.0399[/C][C]0.484121[/C][/ROW]
[ROW][C]9[/C][C]0.049101[/C][C]0.4527[/C][C]0.325962[/C][/ROW]
[ROW][C]10[/C][C]-0.191573[/C][C]-1.7662[/C][C]0.040475[/C][/ROW]
[ROW][C]11[/C][C]0.224567[/C][C]2.0704[/C][C]0.020724[/C][/ROW]
[ROW][C]12[/C][C]0.399173[/C][C]3.6802[/C][C]0.000204[/C][/ROW]
[ROW][C]13[/C][C]-0.140109[/C][C]-1.2917[/C][C]0.099975[/C][/ROW]
[ROW][C]14[/C][C]-0.234495[/C][C]-2.1619[/C][C]0.016717[/C][/ROW]
[ROW][C]15[/C][C]-0.14282[/C][C]-1.3167[/C][C]0.095734[/C][/ROW]
[ROW][C]16[/C][C]-0.078857[/C][C]-0.727[/C][C]0.234604[/C][/ROW]
[ROW][C]17[/C][C]-0.014838[/C][C]-0.1368[/C][C]0.445758[/C][/ROW]
[ROW][C]18[/C][C]-0.069026[/C][C]-0.6364[/C][C]0.263118[/C][/ROW]
[ROW][C]19[/C][C]0.039188[/C][C]0.3613[/C][C]0.359387[/C][/ROW]
[ROW][C]20[/C][C]-0.031494[/C][C]-0.2904[/C][C]0.386125[/C][/ROW]
[ROW][C]21[/C][C]-0.024223[/C][C]-0.2233[/C][C]0.411908[/C][/ROW]
[ROW][C]22[/C][C]0.007363[/C][C]0.0679[/C][C]0.473018[/C][/ROW]
[ROW][C]23[/C][C]0.09957[/C][C]0.918[/C][C]0.180612[/C][/ROW]
[ROW][C]24[/C][C]-0.071321[/C][C]-0.6575[/C][C]0.256303[/C][/ROW]
[ROW][C]25[/C][C]0.123064[/C][C]1.1346[/C][C]0.129868[/C][/ROW]
[ROW][C]26[/C][C]-0.062041[/C][C]-0.572[/C][C]0.284418[/C][/ROW]
[ROW][C]27[/C][C]0.045901[/C][C]0.4232[/C][C]0.336615[/C][/ROW]
[ROW][C]28[/C][C]-0.114518[/C][C]-1.0558[/C][C]0.147024[/C][/ROW]
[ROW][C]29[/C][C]0.015588[/C][C]0.1437[/C][C]0.443033[/C][/ROW]
[ROW][C]30[/C][C]-0.136172[/C][C]-1.2554[/C][C]0.106379[/C][/ROW]
[ROW][C]31[/C][C]0.150166[/C][C]1.3845[/C][C]0.08492[/C][/ROW]
[ROW][C]32[/C][C]-0.100638[/C][C]-0.9278[/C][C]0.178061[/C][/ROW]
[ROW][C]33[/C][C]-0.014401[/C][C]-0.1328[/C][C]0.447345[/C][/ROW]
[ROW][C]34[/C][C]-0.005736[/C][C]-0.0529[/C][C]0.478974[/C][/ROW]
[ROW][C]35[/C][C]0.073677[/C][C]0.6793[/C][C]0.249406[/C][/ROW]
[ROW][C]36[/C][C]0.104162[/C][C]0.9603[/C][C]0.169807[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30902&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30902&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
10.3595383.31480.000675
20.0792360.73050.233541
30.4533694.17993.5e-05
4-0.171629-1.58230.058643
50.3090262.84910.002749
60.2471022.27820.012613
7-0.113711-1.04840.148721
80.0043310.03990.484121
90.0491010.45270.325962
10-0.191573-1.76620.040475
110.2245672.07040.020724
120.3991733.68020.000204
13-0.140109-1.29170.099975
14-0.234495-2.16190.016717
15-0.14282-1.31670.095734
16-0.078857-0.7270.234604
17-0.014838-0.13680.445758
18-0.069026-0.63640.263118
190.0391880.36130.359387
20-0.031494-0.29040.386125
21-0.024223-0.22330.411908
220.0073630.06790.473018
230.099570.9180.180612
24-0.071321-0.65750.256303
250.1230641.13460.129868
26-0.062041-0.5720.284418
270.0459010.42320.336615
28-0.114518-1.05580.147024
290.0155880.14370.443033
30-0.136172-1.25540.106379
310.1501661.38450.08492
32-0.100638-0.92780.178061
33-0.014401-0.13280.447345
34-0.005736-0.05290.478974
350.0736770.67930.249406
360.1041620.96030.169807


Figures (Output of Computation)

Input Parameters & R Code

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