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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 computationSun, 05 Dec 2010 09:31:14 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/05/t1291541403qqzjphc1hfxpjf8.htm/, Retrieved Wed, 01 May 2024 14:43:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=105283, Retrieved Wed, 01 May 2024 14:43:46 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact149

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]
- RMP   [(Partial) Autocorrelation Function] [Unemployment] [2010-11-29 09:05:21] [b98453cac15ba1066b407e146608df68]
-    D    [(Partial) Autocorrelation Function] [] [2010-12-04 15:53:43] [39e83c7b0ac936e906a817a1bb402750]
-   P         [(Partial) Autocorrelation Function] [] [2010-12-05 09:31:14] [558c060a42ec367ec2c020fab85c25c7] [Current]
-   P           [(Partial) Autocorrelation Function] [ws9, autocorrelatie] [2010-12-13 09:24:10] [d946de7cca328fbcf207448a112523ab]
- RMPD          [Univariate Data Series] [] [2010-12-19 15:13:34] [39e83c7b0ac936e906a817a1bb402750]
-   PD            [Univariate Data Series] [AMS (Academic mot...] [2010-12-19 17:32:44] [39e83c7b0ac936e906a817a1bb402750]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0.4754
0.4531
0.469
0.4716
0.4824
0.527
0.5172
0.515
0.5245
0.53
0.4836
0.4663
0.4592
0.4553
0.4217
0.4366
0.4532
0.4743
0.4776
0.4949
0.5069
0.498
0.5213
0.5394
0.6075
0.5919
0.5758
0.5916
0.6474
0.6704
0.7553
0.7891
0.784
0.7007
0.668
0.6102
0.5238
0.4237
0.3983
0.3879
0.3733
0.394
0.3945
0.4324
0.4233
0.455
0.4344
0.4388
0.4561
0.4512
0.4756
0.4704
0.5107
0.5472
0.5537
0.5539
0.5313
0.5371
0.5459
0.5461

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=105283&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=105283&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105283&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
10.9355817.2470
20.8129166.29680
30.649735.03282e-06
40.4710443.64870.000277
50.2784732.1570.017509
60.1102080.85370.198342
7-0.028836-0.22340.412005
8-0.147519-1.14270.128855
9-0.239055-1.85170.034495
10-0.303861-2.35370.010941
11-0.353656-2.73940.004047
12-0.405196-3.13860.001316
13-0.445371-3.44980.000516
14-0.471981-3.6560.000271
15-0.483705-3.74680.000202
16-0.482754-3.73940.000207
17-0.450775-3.49170.000454
18-0.390268-3.0230.001839
19-0.307153-2.37920.010274
20-0.221614-1.71660.045604
21-0.123973-0.96030.170382
22-0.029399-0.22770.410317
230.0491280.38050.352442
240.0940960.72890.23446
250.1229220.95220.17242
260.1266560.98110.165248
270.1059940.8210.20744
280.0755850.58550.280211
290.0469960.3640.358559
300.0252370.19550.422837
310.0135440.10490.458397
320.0167650.12990.448555
330.0330130.25570.399522
340.0488230.37820.353315
350.0613860.47550.318081
360.0677520.52480.300826

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.935581 & 7.247 & 0 \tabularnewline
2 & 0.812916 & 6.2968 & 0 \tabularnewline
3 & 0.64973 & 5.0328 & 2e-06 \tabularnewline
4 & 0.471044 & 3.6487 & 0.000277 \tabularnewline
5 & 0.278473 & 2.157 & 0.017509 \tabularnewline
6 & 0.110208 & 0.8537 & 0.198342 \tabularnewline
7 & -0.028836 & -0.2234 & 0.412005 \tabularnewline
8 & -0.147519 & -1.1427 & 0.128855 \tabularnewline
9 & -0.239055 & -1.8517 & 0.034495 \tabularnewline
10 & -0.303861 & -2.3537 & 0.010941 \tabularnewline
11 & -0.353656 & -2.7394 & 0.004047 \tabularnewline
12 & -0.405196 & -3.1386 & 0.001316 \tabularnewline
13 & -0.445371 & -3.4498 & 0.000516 \tabularnewline
14 & -0.471981 & -3.656 & 0.000271 \tabularnewline
15 & -0.483705 & -3.7468 & 0.000202 \tabularnewline
16 & -0.482754 & -3.7394 & 0.000207 \tabularnewline
17 & -0.450775 & -3.4917 & 0.000454 \tabularnewline
18 & -0.390268 & -3.023 & 0.001839 \tabularnewline
19 & -0.307153 & -2.3792 & 0.010274 \tabularnewline
20 & -0.221614 & -1.7166 & 0.045604 \tabularnewline
21 & -0.123973 & -0.9603 & 0.170382 \tabularnewline
22 & -0.029399 & -0.2277 & 0.410317 \tabularnewline
23 & 0.049128 & 0.3805 & 0.352442 \tabularnewline
24 & 0.094096 & 0.7289 & 0.23446 \tabularnewline
25 & 0.122922 & 0.9522 & 0.17242 \tabularnewline
26 & 0.126656 & 0.9811 & 0.165248 \tabularnewline
27 & 0.105994 & 0.821 & 0.20744 \tabularnewline
28 & 0.075585 & 0.5855 & 0.280211 \tabularnewline
29 & 0.046996 & 0.364 & 0.358559 \tabularnewline
30 & 0.025237 & 0.1955 & 0.422837 \tabularnewline
31 & 0.013544 & 0.1049 & 0.458397 \tabularnewline
32 & 0.016765 & 0.1299 & 0.448555 \tabularnewline
33 & 0.033013 & 0.2557 & 0.399522 \tabularnewline
34 & 0.048823 & 0.3782 & 0.353315 \tabularnewline
35 & 0.061386 & 0.4755 & 0.318081 \tabularnewline
36 & 0.067752 & 0.5248 & 0.300826 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105283&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]0.935581[/C][C]7.247[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.812916[/C][C]6.2968[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.64973[/C][C]5.0328[/C][C]2e-06[/C][/ROW]
[ROW][C]4[/C][C]0.471044[/C][C]3.6487[/C][C]0.000277[/C][/ROW]
[ROW][C]5[/C][C]0.278473[/C][C]2.157[/C][C]0.017509[/C][/ROW]
[ROW][C]6[/C][C]0.110208[/C][C]0.8537[/C][C]0.198342[/C][/ROW]
[ROW][C]7[/C][C]-0.028836[/C][C]-0.2234[/C][C]0.412005[/C][/ROW]
[ROW][C]8[/C][C]-0.147519[/C][C]-1.1427[/C][C]0.128855[/C][/ROW]
[ROW][C]9[/C][C]-0.239055[/C][C]-1.8517[/C][C]0.034495[/C][/ROW]
[ROW][C]10[/C][C]-0.303861[/C][C]-2.3537[/C][C]0.010941[/C][/ROW]
[ROW][C]11[/C][C]-0.353656[/C][C]-2.7394[/C][C]0.004047[/C][/ROW]
[ROW][C]12[/C][C]-0.405196[/C][C]-3.1386[/C][C]0.001316[/C][/ROW]
[ROW][C]13[/C][C]-0.445371[/C][C]-3.4498[/C][C]0.000516[/C][/ROW]
[ROW][C]14[/C][C]-0.471981[/C][C]-3.656[/C][C]0.000271[/C][/ROW]
[ROW][C]15[/C][C]-0.483705[/C][C]-3.7468[/C][C]0.000202[/C][/ROW]
[ROW][C]16[/C][C]-0.482754[/C][C]-3.7394[/C][C]0.000207[/C][/ROW]
[ROW][C]17[/C][C]-0.450775[/C][C]-3.4917[/C][C]0.000454[/C][/ROW]
[ROW][C]18[/C][C]-0.390268[/C][C]-3.023[/C][C]0.001839[/C][/ROW]
[ROW][C]19[/C][C]-0.307153[/C][C]-2.3792[/C][C]0.010274[/C][/ROW]
[ROW][C]20[/C][C]-0.221614[/C][C]-1.7166[/C][C]0.045604[/C][/ROW]
[ROW][C]21[/C][C]-0.123973[/C][C]-0.9603[/C][C]0.170382[/C][/ROW]
[ROW][C]22[/C][C]-0.029399[/C][C]-0.2277[/C][C]0.410317[/C][/ROW]
[ROW][C]23[/C][C]0.049128[/C][C]0.3805[/C][C]0.352442[/C][/ROW]
[ROW][C]24[/C][C]0.094096[/C][C]0.7289[/C][C]0.23446[/C][/ROW]
[ROW][C]25[/C][C]0.122922[/C][C]0.9522[/C][C]0.17242[/C][/ROW]
[ROW][C]26[/C][C]0.126656[/C][C]0.9811[/C][C]0.165248[/C][/ROW]
[ROW][C]27[/C][C]0.105994[/C][C]0.821[/C][C]0.20744[/C][/ROW]
[ROW][C]28[/C][C]0.075585[/C][C]0.5855[/C][C]0.280211[/C][/ROW]
[ROW][C]29[/C][C]0.046996[/C][C]0.364[/C][C]0.358559[/C][/ROW]
[ROW][C]30[/C][C]0.025237[/C][C]0.1955[/C][C]0.422837[/C][/ROW]
[ROW][C]31[/C][C]0.013544[/C][C]0.1049[/C][C]0.458397[/C][/ROW]
[ROW][C]32[/C][C]0.016765[/C][C]0.1299[/C][C]0.448555[/C][/ROW]
[ROW][C]33[/C][C]0.033013[/C][C]0.2557[/C][C]0.399522[/C][/ROW]
[ROW][C]34[/C][C]0.048823[/C][C]0.3782[/C][C]0.353315[/C][/ROW]
[ROW][C]35[/C][C]0.061386[/C][C]0.4755[/C][C]0.318081[/C][/ROW]
[ROW][C]36[/C][C]0.067752[/C][C]0.5248[/C][C]0.300826[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105283&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105283&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
10.9355817.2470
20.8129166.29680
30.649735.03282e-06
40.4710443.64870.000277
50.2784732.1570.017509
60.1102080.85370.198342
7-0.028836-0.22340.412005
8-0.147519-1.14270.128855
9-0.239055-1.85170.034495
10-0.303861-2.35370.010941
11-0.353656-2.73940.004047
12-0.405196-3.13860.001316
13-0.445371-3.44980.000516
14-0.471981-3.6560.000271
15-0.483705-3.74680.000202
16-0.482754-3.73940.000207
17-0.450775-3.49170.000454
18-0.390268-3.0230.001839
19-0.307153-2.37920.010274
20-0.221614-1.71660.045604
21-0.123973-0.96030.170382
22-0.029399-0.22770.410317
230.0491280.38050.352442
240.0940960.72890.23446
250.1229220.95220.17242
260.1266560.98110.165248
270.1059940.8210.20744
280.0755850.58550.280211
290.0469960.3640.358559
300.0252370.19550.422837
310.0135440.10490.458397
320.0167650.12990.448555
330.0330130.25570.399522
340.0488230.37820.353315
350.0613860.47550.318081
360.0677520.52480.300826






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9355817.2470
2-0.500407-3.87610.000133
3-0.248557-1.92530.029467
4-0.051369-0.39790.346056
5-0.205521-1.5920.058325
60.1868241.44710.076532
70.0019250.01490.494078
8-0.212771-1.64810.052278
90.0516430.40.345278
10-0.087566-0.67830.250099
11-0.163439-1.2660.105205
12-0.160513-1.24330.109291
13-0.019163-0.14840.441248
14-0.021719-0.16820.433482
15-0.00897-0.06950.472418
16-0.057318-0.4440.329326
170.0792870.61420.270718
180.0325380.2520.400935
190.0050780.03930.484376
20-0.18085-1.40090.083204
210.0868060.67240.251957
22-0.007315-0.05670.477502
23-0.102147-0.79120.215965
24-0.183306-1.41990.080409
250.047590.36860.356851
26-0.110376-0.8550.197985
27-0.09021-0.69880.2437
280.011080.08580.465946
29-0.089958-0.69680.244307
300.0491770.38090.352304
310.1023590.79290.215489
32-0.159308-1.2340.111009
330.0662680.51330.30481
34-0.050098-0.38810.349673
35-0.034591-0.26790.394833
36-0.065398-0.50660.307157

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.935581 & 7.247 & 0 \tabularnewline
2 & -0.500407 & -3.8761 & 0.000133 \tabularnewline
3 & -0.248557 & -1.9253 & 0.029467 \tabularnewline
4 & -0.051369 & -0.3979 & 0.346056 \tabularnewline
5 & -0.205521 & -1.592 & 0.058325 \tabularnewline
6 & 0.186824 & 1.4471 & 0.076532 \tabularnewline
7 & 0.001925 & 0.0149 & 0.494078 \tabularnewline
8 & -0.212771 & -1.6481 & 0.052278 \tabularnewline
9 & 0.051643 & 0.4 & 0.345278 \tabularnewline
10 & -0.087566 & -0.6783 & 0.250099 \tabularnewline
11 & -0.163439 & -1.266 & 0.105205 \tabularnewline
12 & -0.160513 & -1.2433 & 0.109291 \tabularnewline
13 & -0.019163 & -0.1484 & 0.441248 \tabularnewline
14 & -0.021719 & -0.1682 & 0.433482 \tabularnewline
15 & -0.00897 & -0.0695 & 0.472418 \tabularnewline
16 & -0.057318 & -0.444 & 0.329326 \tabularnewline
17 & 0.079287 & 0.6142 & 0.270718 \tabularnewline
18 & 0.032538 & 0.252 & 0.400935 \tabularnewline
19 & 0.005078 & 0.0393 & 0.484376 \tabularnewline
20 & -0.18085 & -1.4009 & 0.083204 \tabularnewline
21 & 0.086806 & 0.6724 & 0.251957 \tabularnewline
22 & -0.007315 & -0.0567 & 0.477502 \tabularnewline
23 & -0.102147 & -0.7912 & 0.215965 \tabularnewline
24 & -0.183306 & -1.4199 & 0.080409 \tabularnewline
25 & 0.04759 & 0.3686 & 0.356851 \tabularnewline
26 & -0.110376 & -0.855 & 0.197985 \tabularnewline
27 & -0.09021 & -0.6988 & 0.2437 \tabularnewline
28 & 0.01108 & 0.0858 & 0.465946 \tabularnewline
29 & -0.089958 & -0.6968 & 0.244307 \tabularnewline
30 & 0.049177 & 0.3809 & 0.352304 \tabularnewline
31 & 0.102359 & 0.7929 & 0.215489 \tabularnewline
32 & -0.159308 & -1.234 & 0.111009 \tabularnewline
33 & 0.066268 & 0.5133 & 0.30481 \tabularnewline
34 & -0.050098 & -0.3881 & 0.349673 \tabularnewline
35 & -0.034591 & -0.2679 & 0.394833 \tabularnewline
36 & -0.065398 & -0.5066 & 0.307157 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105283&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]0.935581[/C][C]7.247[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.500407[/C][C]-3.8761[/C][C]0.000133[/C][/ROW]
[ROW][C]3[/C][C]-0.248557[/C][C]-1.9253[/C][C]0.029467[/C][/ROW]
[ROW][C]4[/C][C]-0.051369[/C][C]-0.3979[/C][C]0.346056[/C][/ROW]
[ROW][C]5[/C][C]-0.205521[/C][C]-1.592[/C][C]0.058325[/C][/ROW]
[ROW][C]6[/C][C]0.186824[/C][C]1.4471[/C][C]0.076532[/C][/ROW]
[ROW][C]7[/C][C]0.001925[/C][C]0.0149[/C][C]0.494078[/C][/ROW]
[ROW][C]8[/C][C]-0.212771[/C][C]-1.6481[/C][C]0.052278[/C][/ROW]
[ROW][C]9[/C][C]0.051643[/C][C]0.4[/C][C]0.345278[/C][/ROW]
[ROW][C]10[/C][C]-0.087566[/C][C]-0.6783[/C][C]0.250099[/C][/ROW]
[ROW][C]11[/C][C]-0.163439[/C][C]-1.266[/C][C]0.105205[/C][/ROW]
[ROW][C]12[/C][C]-0.160513[/C][C]-1.2433[/C][C]0.109291[/C][/ROW]
[ROW][C]13[/C][C]-0.019163[/C][C]-0.1484[/C][C]0.441248[/C][/ROW]
[ROW][C]14[/C][C]-0.021719[/C][C]-0.1682[/C][C]0.433482[/C][/ROW]
[ROW][C]15[/C][C]-0.00897[/C][C]-0.0695[/C][C]0.472418[/C][/ROW]
[ROW][C]16[/C][C]-0.057318[/C][C]-0.444[/C][C]0.329326[/C][/ROW]
[ROW][C]17[/C][C]0.079287[/C][C]0.6142[/C][C]0.270718[/C][/ROW]
[ROW][C]18[/C][C]0.032538[/C][C]0.252[/C][C]0.400935[/C][/ROW]
[ROW][C]19[/C][C]0.005078[/C][C]0.0393[/C][C]0.484376[/C][/ROW]
[ROW][C]20[/C][C]-0.18085[/C][C]-1.4009[/C][C]0.083204[/C][/ROW]
[ROW][C]21[/C][C]0.086806[/C][C]0.6724[/C][C]0.251957[/C][/ROW]
[ROW][C]22[/C][C]-0.007315[/C][C]-0.0567[/C][C]0.477502[/C][/ROW]
[ROW][C]23[/C][C]-0.102147[/C][C]-0.7912[/C][C]0.215965[/C][/ROW]
[ROW][C]24[/C][C]-0.183306[/C][C]-1.4199[/C][C]0.080409[/C][/ROW]
[ROW][C]25[/C][C]0.04759[/C][C]0.3686[/C][C]0.356851[/C][/ROW]
[ROW][C]26[/C][C]-0.110376[/C][C]-0.855[/C][C]0.197985[/C][/ROW]
[ROW][C]27[/C][C]-0.09021[/C][C]-0.6988[/C][C]0.2437[/C][/ROW]
[ROW][C]28[/C][C]0.01108[/C][C]0.0858[/C][C]0.465946[/C][/ROW]
[ROW][C]29[/C][C]-0.089958[/C][C]-0.6968[/C][C]0.244307[/C][/ROW]
[ROW][C]30[/C][C]0.049177[/C][C]0.3809[/C][C]0.352304[/C][/ROW]
[ROW][C]31[/C][C]0.102359[/C][C]0.7929[/C][C]0.215489[/C][/ROW]
[ROW][C]32[/C][C]-0.159308[/C][C]-1.234[/C][C]0.111009[/C][/ROW]
[ROW][C]33[/C][C]0.066268[/C][C]0.5133[/C][C]0.30481[/C][/ROW]
[ROW][C]34[/C][C]-0.050098[/C][C]-0.3881[/C][C]0.349673[/C][/ROW]
[ROW][C]35[/C][C]-0.034591[/C][C]-0.2679[/C][C]0.394833[/C][/ROW]
[ROW][C]36[/C][C]-0.065398[/C][C]-0.5066[/C][C]0.307157[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105283&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105283&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
10.9355817.2470
2-0.500407-3.87610.000133
3-0.248557-1.92530.029467
4-0.051369-0.39790.346056
5-0.205521-1.5920.058325
60.1868241.44710.076532
70.0019250.01490.494078
8-0.212771-1.64810.052278
90.0516430.40.345278
10-0.087566-0.67830.250099
11-0.163439-1.2660.105205
12-0.160513-1.24330.109291
13-0.019163-0.14840.441248
14-0.021719-0.16820.433482
15-0.00897-0.06950.472418
16-0.057318-0.4440.329326
170.0792870.61420.270718
180.0325380.2520.400935
190.0050780.03930.484376
20-0.18085-1.40090.083204
210.0868060.67240.251957
22-0.007315-0.05670.477502
23-0.102147-0.79120.215965
24-0.183306-1.41990.080409
250.047590.36860.356851
26-0.110376-0.8550.197985
27-0.09021-0.69880.2437
280.011080.08580.465946
29-0.089958-0.69680.244307
300.0491770.38090.352304
310.1023590.79290.215489
32-0.159308-1.2340.111009
330.0662680.51330.30481
34-0.050098-0.38810.349673
35-0.034591-0.26790.394833
36-0.065398-0.50660.307157


Figures (Output of Computation)

Input Parameters & R Code

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