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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, 30 Nov 2009 04:42:11 -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/Nov/30/t1259581368aqez461ktfu4ig6.htm/, Retrieved Wed, 01 May 2024 19:58:57 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=61726, Retrieved Wed, 01 May 2024 19:58:57 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact143

Tree of Dependent Computations

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] [ACF D=d=o, lambda=1] [2009-11-30 11:39:52] [005293453b571dbccb80b45226e44173]
-   P             [(Partial) Autocorrelation Function] [ACF D=lambda=1, d=0] [2009-11-30 11:42:11] [b02b8a83db8a631da1ab9c106b4cdcf2] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
244.576
241.572
240.541
236.089
236.997
264.579
270.349
269.645
267.037
258.113
262.813
267.413
267.366
264.777
258.863
254.844
254.868
277.267
285.351
286.602
283.042
276.687
277.915
277.128
277.103
275.037
270.150
267.140
264.993
287.259
291.186
292.300
288.186
281.477
282.656
280.190
280.408
276.836
275.216
274.352
271.311
289.802
290.726
292.300
278.506
269.826
265.861
269.034
264.176
255.198
253.353
246.057
235.372
258.556
260.993
254.663
250.643
243.422
247.105
248.541
245.039
237.080
237.085
225.554
226.839
247.934
248.333
246.969
245.098
246.263
255.765
264.319
268.347
273.046
273.963
267.430
271.993
292.710
295.881

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'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=61726&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=61726&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61726&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'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.9292377.60610
20.8568337.01350
30.7726846.32470
40.6770325.54170
50.580764.75375e-06
60.4846883.96739e-05
70.3968863.24870.000907
80.315632.58350.005983
90.2388481.95510.027375
100.1648341.34920.090903
110.1114680.91240.182413
120.0499280.40870.34204
130.003490.02860.488648
14-0.048578-0.39760.346084
15-0.11017-0.90180.185202
16-0.155872-1.27590.103204
17-0.20448-1.67370.049422
18-0.2542-2.08070.020643
19-0.294853-2.41350.009271
20-0.333496-2.72980.004045
21-0.370758-3.03480.001712
22-0.388844-3.18280.001106
23-0.403757-3.30490.000764
24-0.392109-3.20950.001021
25-0.386516-3.16380.001171
26-0.371053-3.03720.0017
27-0.347361-2.84330.002957
28-0.330417-2.70460.004331
29-0.319093-2.61190.005552
30-0.301881-2.4710.008012
31-0.287359-2.35210.010806
32-0.278611-2.28050.012882
33-0.253361-2.07390.02097
34-0.232862-1.90610.030467
35-0.208293-1.7050.046418
36-0.207692-1.70.046881

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.929237 & 7.6061 & 0 \tabularnewline
2 & 0.856833 & 7.0135 & 0 \tabularnewline
3 & 0.772684 & 6.3247 & 0 \tabularnewline
4 & 0.677032 & 5.5417 & 0 \tabularnewline
5 & 0.58076 & 4.7537 & 5e-06 \tabularnewline
6 & 0.484688 & 3.9673 & 9e-05 \tabularnewline
7 & 0.396886 & 3.2487 & 0.000907 \tabularnewline
8 & 0.31563 & 2.5835 & 0.005983 \tabularnewline
9 & 0.238848 & 1.9551 & 0.027375 \tabularnewline
10 & 0.164834 & 1.3492 & 0.090903 \tabularnewline
11 & 0.111468 & 0.9124 & 0.182413 \tabularnewline
12 & 0.049928 & 0.4087 & 0.34204 \tabularnewline
13 & 0.00349 & 0.0286 & 0.488648 \tabularnewline
14 & -0.048578 & -0.3976 & 0.346084 \tabularnewline
15 & -0.11017 & -0.9018 & 0.185202 \tabularnewline
16 & -0.155872 & -1.2759 & 0.103204 \tabularnewline
17 & -0.20448 & -1.6737 & 0.049422 \tabularnewline
18 & -0.2542 & -2.0807 & 0.020643 \tabularnewline
19 & -0.294853 & -2.4135 & 0.009271 \tabularnewline
20 & -0.333496 & -2.7298 & 0.004045 \tabularnewline
21 & -0.370758 & -3.0348 & 0.001712 \tabularnewline
22 & -0.388844 & -3.1828 & 0.001106 \tabularnewline
23 & -0.403757 & -3.3049 & 0.000764 \tabularnewline
24 & -0.392109 & -3.2095 & 0.001021 \tabularnewline
25 & -0.386516 & -3.1638 & 0.001171 \tabularnewline
26 & -0.371053 & -3.0372 & 0.0017 \tabularnewline
27 & -0.347361 & -2.8433 & 0.002957 \tabularnewline
28 & -0.330417 & -2.7046 & 0.004331 \tabularnewline
29 & -0.319093 & -2.6119 & 0.005552 \tabularnewline
30 & -0.301881 & -2.471 & 0.008012 \tabularnewline
31 & -0.287359 & -2.3521 & 0.010806 \tabularnewline
32 & -0.278611 & -2.2805 & 0.012882 \tabularnewline
33 & -0.253361 & -2.0739 & 0.02097 \tabularnewline
34 & -0.232862 & -1.9061 & 0.030467 \tabularnewline
35 & -0.208293 & -1.705 & 0.046418 \tabularnewline
36 & -0.207692 & -1.7 & 0.046881 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61726&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]0.929237[/C][C]7.6061[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.856833[/C][C]7.0135[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.772684[/C][C]6.3247[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.677032[/C][C]5.5417[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.58076[/C][C]4.7537[/C][C]5e-06[/C][/ROW]
[ROW][C]6[/C][C]0.484688[/C][C]3.9673[/C][C]9e-05[/C][/ROW]
[ROW][C]7[/C][C]0.396886[/C][C]3.2487[/C][C]0.000907[/C][/ROW]
[ROW][C]8[/C][C]0.31563[/C][C]2.5835[/C][C]0.005983[/C][/ROW]
[ROW][C]9[/C][C]0.238848[/C][C]1.9551[/C][C]0.027375[/C][/ROW]
[ROW][C]10[/C][C]0.164834[/C][C]1.3492[/C][C]0.090903[/C][/ROW]
[ROW][C]11[/C][C]0.111468[/C][C]0.9124[/C][C]0.182413[/C][/ROW]
[ROW][C]12[/C][C]0.049928[/C][C]0.4087[/C][C]0.34204[/C][/ROW]
[ROW][C]13[/C][C]0.00349[/C][C]0.0286[/C][C]0.488648[/C][/ROW]
[ROW][C]14[/C][C]-0.048578[/C][C]-0.3976[/C][C]0.346084[/C][/ROW]
[ROW][C]15[/C][C]-0.11017[/C][C]-0.9018[/C][C]0.185202[/C][/ROW]
[ROW][C]16[/C][C]-0.155872[/C][C]-1.2759[/C][C]0.103204[/C][/ROW]
[ROW][C]17[/C][C]-0.20448[/C][C]-1.6737[/C][C]0.049422[/C][/ROW]
[ROW][C]18[/C][C]-0.2542[/C][C]-2.0807[/C][C]0.020643[/C][/ROW]
[ROW][C]19[/C][C]-0.294853[/C][C]-2.4135[/C][C]0.009271[/C][/ROW]
[ROW][C]20[/C][C]-0.333496[/C][C]-2.7298[/C][C]0.004045[/C][/ROW]
[ROW][C]21[/C][C]-0.370758[/C][C]-3.0348[/C][C]0.001712[/C][/ROW]
[ROW][C]22[/C][C]-0.388844[/C][C]-3.1828[/C][C]0.001106[/C][/ROW]
[ROW][C]23[/C][C]-0.403757[/C][C]-3.3049[/C][C]0.000764[/C][/ROW]
[ROW][C]24[/C][C]-0.392109[/C][C]-3.2095[/C][C]0.001021[/C][/ROW]
[ROW][C]25[/C][C]-0.386516[/C][C]-3.1638[/C][C]0.001171[/C][/ROW]
[ROW][C]26[/C][C]-0.371053[/C][C]-3.0372[/C][C]0.0017[/C][/ROW]
[ROW][C]27[/C][C]-0.347361[/C][C]-2.8433[/C][C]0.002957[/C][/ROW]
[ROW][C]28[/C][C]-0.330417[/C][C]-2.7046[/C][C]0.004331[/C][/ROW]
[ROW][C]29[/C][C]-0.319093[/C][C]-2.6119[/C][C]0.005552[/C][/ROW]
[ROW][C]30[/C][C]-0.301881[/C][C]-2.471[/C][C]0.008012[/C][/ROW]
[ROW][C]31[/C][C]-0.287359[/C][C]-2.3521[/C][C]0.010806[/C][/ROW]
[ROW][C]32[/C][C]-0.278611[/C][C]-2.2805[/C][C]0.012882[/C][/ROW]
[ROW][C]33[/C][C]-0.253361[/C][C]-2.0739[/C][C]0.02097[/C][/ROW]
[ROW][C]34[/C][C]-0.232862[/C][C]-1.9061[/C][C]0.030467[/C][/ROW]
[ROW][C]35[/C][C]-0.208293[/C][C]-1.705[/C][C]0.046418[/C][/ROW]
[ROW][C]36[/C][C]-0.207692[/C][C]-1.7[/C][C]0.046881[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61726&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61726&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
10.9292377.60610
20.8568337.01350
30.7726846.32470
40.6770325.54170
50.580764.75375e-06
60.4846883.96739e-05
70.3968863.24870.000907
80.315632.58350.005983
90.2388481.95510.027375
100.1648341.34920.090903
110.1114680.91240.182413
120.0499280.40870.34204
130.003490.02860.488648
14-0.048578-0.39760.346084
15-0.11017-0.90180.185202
16-0.155872-1.27590.103204
17-0.20448-1.67370.049422
18-0.2542-2.08070.020643
19-0.294853-2.41350.009271
20-0.333496-2.72980.004045
21-0.370758-3.03480.001712
22-0.388844-3.18280.001106
23-0.403757-3.30490.000764
24-0.392109-3.20950.001021
25-0.386516-3.16380.001171
26-0.371053-3.03720.0017
27-0.347361-2.84330.002957
28-0.330417-2.70460.004331
29-0.319093-2.61190.005552
30-0.301881-2.4710.008012
31-0.287359-2.35210.010806
32-0.278611-2.28050.012882
33-0.253361-2.07390.02097
34-0.232862-1.90610.030467
35-0.208293-1.7050.046418
36-0.207692-1.70.046881






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9292377.60610
2-0.048694-0.39860.345736
3-0.125103-1.0240.154756
4-0.132134-1.08160.141663
5-0.056123-0.45940.323722
6-0.047548-0.38920.349183
70.0045570.03730.485177
8-0.012931-0.10580.458009
9-0.037566-0.30750.379711
10-0.058408-0.47810.317072
110.0811230.6640.254478
12-0.120258-0.98440.164241
130.0348090.28490.38829
14-0.109327-0.89490.187028
15-0.138028-1.12980.131294
160.0455750.3730.355147
17-0.05637-0.46140.322999
18-0.079412-0.650.258952
19-0.00547-0.04480.482211
20-0.058994-0.48290.315376
21-0.060539-0.49550.310923
220.0565980.46330.322333
23-0.013754-0.11260.455349
240.1058180.86620.194748
25-0.12042-0.98570.163918
260.0330310.27040.393853
27-0.02333-0.1910.424566
28-0.058572-0.47940.316598
29-0.078364-0.64140.261714
300.0021750.01780.492924
31-0.028647-0.23450.407663
32-0.044646-0.36540.357967
330.0773690.63330.26435
340.0079150.06480.474268
35-0.056566-0.4630.322427
36-0.216386-1.77120.040538

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.929237 & 7.6061 & 0 \tabularnewline
2 & -0.048694 & -0.3986 & 0.345736 \tabularnewline
3 & -0.125103 & -1.024 & 0.154756 \tabularnewline
4 & -0.132134 & -1.0816 & 0.141663 \tabularnewline
5 & -0.056123 & -0.4594 & 0.323722 \tabularnewline
6 & -0.047548 & -0.3892 & 0.349183 \tabularnewline
7 & 0.004557 & 0.0373 & 0.485177 \tabularnewline
8 & -0.012931 & -0.1058 & 0.458009 \tabularnewline
9 & -0.037566 & -0.3075 & 0.379711 \tabularnewline
10 & -0.058408 & -0.4781 & 0.317072 \tabularnewline
11 & 0.081123 & 0.664 & 0.254478 \tabularnewline
12 & -0.120258 & -0.9844 & 0.164241 \tabularnewline
13 & 0.034809 & 0.2849 & 0.38829 \tabularnewline
14 & -0.109327 & -0.8949 & 0.187028 \tabularnewline
15 & -0.138028 & -1.1298 & 0.131294 \tabularnewline
16 & 0.045575 & 0.373 & 0.355147 \tabularnewline
17 & -0.05637 & -0.4614 & 0.322999 \tabularnewline
18 & -0.079412 & -0.65 & 0.258952 \tabularnewline
19 & -0.00547 & -0.0448 & 0.482211 \tabularnewline
20 & -0.058994 & -0.4829 & 0.315376 \tabularnewline
21 & -0.060539 & -0.4955 & 0.310923 \tabularnewline
22 & 0.056598 & 0.4633 & 0.322333 \tabularnewline
23 & -0.013754 & -0.1126 & 0.455349 \tabularnewline
24 & 0.105818 & 0.8662 & 0.194748 \tabularnewline
25 & -0.12042 & -0.9857 & 0.163918 \tabularnewline
26 & 0.033031 & 0.2704 & 0.393853 \tabularnewline
27 & -0.02333 & -0.191 & 0.424566 \tabularnewline
28 & -0.058572 & -0.4794 & 0.316598 \tabularnewline
29 & -0.078364 & -0.6414 & 0.261714 \tabularnewline
30 & 0.002175 & 0.0178 & 0.492924 \tabularnewline
31 & -0.028647 & -0.2345 & 0.407663 \tabularnewline
32 & -0.044646 & -0.3654 & 0.357967 \tabularnewline
33 & 0.077369 & 0.6333 & 0.26435 \tabularnewline
34 & 0.007915 & 0.0648 & 0.474268 \tabularnewline
35 & -0.056566 & -0.463 & 0.322427 \tabularnewline
36 & -0.216386 & -1.7712 & 0.040538 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61726&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]0.929237[/C][C]7.6061[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.048694[/C][C]-0.3986[/C][C]0.345736[/C][/ROW]
[ROW][C]3[/C][C]-0.125103[/C][C]-1.024[/C][C]0.154756[/C][/ROW]
[ROW][C]4[/C][C]-0.132134[/C][C]-1.0816[/C][C]0.141663[/C][/ROW]
[ROW][C]5[/C][C]-0.056123[/C][C]-0.4594[/C][C]0.323722[/C][/ROW]
[ROW][C]6[/C][C]-0.047548[/C][C]-0.3892[/C][C]0.349183[/C][/ROW]
[ROW][C]7[/C][C]0.004557[/C][C]0.0373[/C][C]0.485177[/C][/ROW]
[ROW][C]8[/C][C]-0.012931[/C][C]-0.1058[/C][C]0.458009[/C][/ROW]
[ROW][C]9[/C][C]-0.037566[/C][C]-0.3075[/C][C]0.379711[/C][/ROW]
[ROW][C]10[/C][C]-0.058408[/C][C]-0.4781[/C][C]0.317072[/C][/ROW]
[ROW][C]11[/C][C]0.081123[/C][C]0.664[/C][C]0.254478[/C][/ROW]
[ROW][C]12[/C][C]-0.120258[/C][C]-0.9844[/C][C]0.164241[/C][/ROW]
[ROW][C]13[/C][C]0.034809[/C][C]0.2849[/C][C]0.38829[/C][/ROW]
[ROW][C]14[/C][C]-0.109327[/C][C]-0.8949[/C][C]0.187028[/C][/ROW]
[ROW][C]15[/C][C]-0.138028[/C][C]-1.1298[/C][C]0.131294[/C][/ROW]
[ROW][C]16[/C][C]0.045575[/C][C]0.373[/C][C]0.355147[/C][/ROW]
[ROW][C]17[/C][C]-0.05637[/C][C]-0.4614[/C][C]0.322999[/C][/ROW]
[ROW][C]18[/C][C]-0.079412[/C][C]-0.65[/C][C]0.258952[/C][/ROW]
[ROW][C]19[/C][C]-0.00547[/C][C]-0.0448[/C][C]0.482211[/C][/ROW]
[ROW][C]20[/C][C]-0.058994[/C][C]-0.4829[/C][C]0.315376[/C][/ROW]
[ROW][C]21[/C][C]-0.060539[/C][C]-0.4955[/C][C]0.310923[/C][/ROW]
[ROW][C]22[/C][C]0.056598[/C][C]0.4633[/C][C]0.322333[/C][/ROW]
[ROW][C]23[/C][C]-0.013754[/C][C]-0.1126[/C][C]0.455349[/C][/ROW]
[ROW][C]24[/C][C]0.105818[/C][C]0.8662[/C][C]0.194748[/C][/ROW]
[ROW][C]25[/C][C]-0.12042[/C][C]-0.9857[/C][C]0.163918[/C][/ROW]
[ROW][C]26[/C][C]0.033031[/C][C]0.2704[/C][C]0.393853[/C][/ROW]
[ROW][C]27[/C][C]-0.02333[/C][C]-0.191[/C][C]0.424566[/C][/ROW]
[ROW][C]28[/C][C]-0.058572[/C][C]-0.4794[/C][C]0.316598[/C][/ROW]
[ROW][C]29[/C][C]-0.078364[/C][C]-0.6414[/C][C]0.261714[/C][/ROW]
[ROW][C]30[/C][C]0.002175[/C][C]0.0178[/C][C]0.492924[/C][/ROW]
[ROW][C]31[/C][C]-0.028647[/C][C]-0.2345[/C][C]0.407663[/C][/ROW]
[ROW][C]32[/C][C]-0.044646[/C][C]-0.3654[/C][C]0.357967[/C][/ROW]
[ROW][C]33[/C][C]0.077369[/C][C]0.6333[/C][C]0.26435[/C][/ROW]
[ROW][C]34[/C][C]0.007915[/C][C]0.0648[/C][C]0.474268[/C][/ROW]
[ROW][C]35[/C][C]-0.056566[/C][C]-0.463[/C][C]0.322427[/C][/ROW]
[ROW][C]36[/C][C]-0.216386[/C][C]-1.7712[/C][C]0.040538[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61726&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61726&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
10.9292377.60610
2-0.048694-0.39860.345736
3-0.125103-1.0240.154756
4-0.132134-1.08160.141663
5-0.056123-0.45940.323722
6-0.047548-0.38920.349183
70.0045570.03730.485177
8-0.012931-0.10580.458009
9-0.037566-0.30750.379711
10-0.058408-0.47810.317072
110.0811230.6640.254478
12-0.120258-0.98440.164241
130.0348090.28490.38829
14-0.109327-0.89490.187028
15-0.138028-1.12980.131294
160.0455750.3730.355147
17-0.05637-0.46140.322999
18-0.079412-0.650.258952
19-0.00547-0.04480.482211
20-0.058994-0.48290.315376
21-0.060539-0.49550.310923
220.0565980.46330.322333
23-0.013754-0.11260.455349
240.1058180.86620.194748
25-0.12042-0.98570.163918
260.0330310.27040.393853
27-0.02333-0.1910.424566
28-0.058572-0.47940.316598
29-0.078364-0.64140.261714
300.0021750.01780.492924
31-0.028647-0.23450.407663
32-0.044646-0.36540.357967
330.0773690.63330.26435
340.0079150.06480.474268
35-0.056566-0.4630.322427
36-0.216386-1.77120.040538


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; 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')