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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 computationTue, 29 Dec 2009 14:03:02 -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/Dec/29/t1262120683q58c38fbz2s9uws.htm/, Retrieved Fri, 03 May 2024 07:21:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=71197, Retrieved Fri, 03 May 2024 07:21:24 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact125

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]
-   PD        [(Partial) Autocorrelation Function] [ACF] [2009-12-26 11:04:38] [f15cf5036ae52d4243ad71d4fb151dbe]
-   PD            [(Partial) Autocorrelation Function] [Paper correlatie] [2009-12-29 21:03:02] [1aecede37375310a889a187dca5e5c0a] [Current]
-   P               [(Partial) Autocorrelation Function] [Paper d=1 D=0] [2009-12-29 21:16:53] [f15cf5036ae52d4243ad71d4fb151dbe]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
10001.60
10411.75
10673.38
10539.51
10723.78
10682.06
10283.19
10377.18
10486.64
10545.38
10554.27
10532.54
10324.31
10695.25
10827.81
10872.48
10971.19
11145.65
11234.68
11333.88
10997.97
11036.89
11257.35
11533.59
11963.12
12185.15
12377.62
12512.89
12631.48
12268.53
12754.80
13407.75
13480.21
13673.28
13239.71
13557.69
13901.28
13200.58
13406.97
12538.12
12419.57
12193.88
12656.63
12812.48
12056.67
11322.38
11530.75
11114.08
9181.73
8614.55
8595.56
8396.20
7690.50
7235.47
7992.12
8398.37
8593.01
8679.75
9374.63
9634.97

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=71197&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=71197&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71197&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
10.9538787.38870
20.8903556.89670
30.8232586.37690
40.7418285.74620
50.6359834.92633e-06
60.5154693.99289e-05
70.4016563.11120.001426
80.2949452.28460.012943
90.1863761.44370.077017
100.0792450.61380.270824
11-0.014314-0.11090.456043
12-0.104731-0.81120.210217
13-0.181785-1.40810.08213
14-0.244762-1.89590.031395
15-0.306352-2.3730.010433
16-0.355307-2.75220.003909
17-0.394074-3.05250.00169
18-0.418956-3.24520.000961
19-0.438488-3.39650.000608
20-0.455025-3.52460.000409
21-0.466319-3.61210.000311
22-0.45775-3.54570.000383
23-0.442565-3.42810.000552
24-0.421432-3.26440.000907
25-0.396732-3.07310.001592
26-0.36788-2.84960.002995
27-0.327575-2.53740.006893
28-0.288712-2.23640.014529
29-0.254493-1.97130.026654
30-0.229158-1.77510.040481
31-0.202798-1.57090.060736
32-0.169137-1.31010.097573
33-0.137177-1.06260.146118
34-0.108816-0.84290.20132
35-0.085327-0.66090.25559
36-0.057012-0.44160.33018

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.953878 & 7.3887 & 0 \tabularnewline
2 & 0.890355 & 6.8967 & 0 \tabularnewline
3 & 0.823258 & 6.3769 & 0 \tabularnewline
4 & 0.741828 & 5.7462 & 0 \tabularnewline
5 & 0.635983 & 4.9263 & 3e-06 \tabularnewline
6 & 0.515469 & 3.9928 & 9e-05 \tabularnewline
7 & 0.401656 & 3.1112 & 0.001426 \tabularnewline
8 & 0.294945 & 2.2846 & 0.012943 \tabularnewline
9 & 0.186376 & 1.4437 & 0.077017 \tabularnewline
10 & 0.079245 & 0.6138 & 0.270824 \tabularnewline
11 & -0.014314 & -0.1109 & 0.456043 \tabularnewline
12 & -0.104731 & -0.8112 & 0.210217 \tabularnewline
13 & -0.181785 & -1.4081 & 0.08213 \tabularnewline
14 & -0.244762 & -1.8959 & 0.031395 \tabularnewline
15 & -0.306352 & -2.373 & 0.010433 \tabularnewline
16 & -0.355307 & -2.7522 & 0.003909 \tabularnewline
17 & -0.394074 & -3.0525 & 0.00169 \tabularnewline
18 & -0.418956 & -3.2452 & 0.000961 \tabularnewline
19 & -0.438488 & -3.3965 & 0.000608 \tabularnewline
20 & -0.455025 & -3.5246 & 0.000409 \tabularnewline
21 & -0.466319 & -3.6121 & 0.000311 \tabularnewline
22 & -0.45775 & -3.5457 & 0.000383 \tabularnewline
23 & -0.442565 & -3.4281 & 0.000552 \tabularnewline
24 & -0.421432 & -3.2644 & 0.000907 \tabularnewline
25 & -0.396732 & -3.0731 & 0.001592 \tabularnewline
26 & -0.36788 & -2.8496 & 0.002995 \tabularnewline
27 & -0.327575 & -2.5374 & 0.006893 \tabularnewline
28 & -0.288712 & -2.2364 & 0.014529 \tabularnewline
29 & -0.254493 & -1.9713 & 0.026654 \tabularnewline
30 & -0.229158 & -1.7751 & 0.040481 \tabularnewline
31 & -0.202798 & -1.5709 & 0.060736 \tabularnewline
32 & -0.169137 & -1.3101 & 0.097573 \tabularnewline
33 & -0.137177 & -1.0626 & 0.146118 \tabularnewline
34 & -0.108816 & -0.8429 & 0.20132 \tabularnewline
35 & -0.085327 & -0.6609 & 0.25559 \tabularnewline
36 & -0.057012 & -0.4416 & 0.33018 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71197&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]0.953878[/C][C]7.3887[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.890355[/C][C]6.8967[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.823258[/C][C]6.3769[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.741828[/C][C]5.7462[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.635983[/C][C]4.9263[/C][C]3e-06[/C][/ROW]
[ROW][C]6[/C][C]0.515469[/C][C]3.9928[/C][C]9e-05[/C][/ROW]
[ROW][C]7[/C][C]0.401656[/C][C]3.1112[/C][C]0.001426[/C][/ROW]
[ROW][C]8[/C][C]0.294945[/C][C]2.2846[/C][C]0.012943[/C][/ROW]
[ROW][C]9[/C][C]0.186376[/C][C]1.4437[/C][C]0.077017[/C][/ROW]
[ROW][C]10[/C][C]0.079245[/C][C]0.6138[/C][C]0.270824[/C][/ROW]
[ROW][C]11[/C][C]-0.014314[/C][C]-0.1109[/C][C]0.456043[/C][/ROW]
[ROW][C]12[/C][C]-0.104731[/C][C]-0.8112[/C][C]0.210217[/C][/ROW]
[ROW][C]13[/C][C]-0.181785[/C][C]-1.4081[/C][C]0.08213[/C][/ROW]
[ROW][C]14[/C][C]-0.244762[/C][C]-1.8959[/C][C]0.031395[/C][/ROW]
[ROW][C]15[/C][C]-0.306352[/C][C]-2.373[/C][C]0.010433[/C][/ROW]
[ROW][C]16[/C][C]-0.355307[/C][C]-2.7522[/C][C]0.003909[/C][/ROW]
[ROW][C]17[/C][C]-0.394074[/C][C]-3.0525[/C][C]0.00169[/C][/ROW]
[ROW][C]18[/C][C]-0.418956[/C][C]-3.2452[/C][C]0.000961[/C][/ROW]
[ROW][C]19[/C][C]-0.438488[/C][C]-3.3965[/C][C]0.000608[/C][/ROW]
[ROW][C]20[/C][C]-0.455025[/C][C]-3.5246[/C][C]0.000409[/C][/ROW]
[ROW][C]21[/C][C]-0.466319[/C][C]-3.6121[/C][C]0.000311[/C][/ROW]
[ROW][C]22[/C][C]-0.45775[/C][C]-3.5457[/C][C]0.000383[/C][/ROW]
[ROW][C]23[/C][C]-0.442565[/C][C]-3.4281[/C][C]0.000552[/C][/ROW]
[ROW][C]24[/C][C]-0.421432[/C][C]-3.2644[/C][C]0.000907[/C][/ROW]
[ROW][C]25[/C][C]-0.396732[/C][C]-3.0731[/C][C]0.001592[/C][/ROW]
[ROW][C]26[/C][C]-0.36788[/C][C]-2.8496[/C][C]0.002995[/C][/ROW]
[ROW][C]27[/C][C]-0.327575[/C][C]-2.5374[/C][C]0.006893[/C][/ROW]
[ROW][C]28[/C][C]-0.288712[/C][C]-2.2364[/C][C]0.014529[/C][/ROW]
[ROW][C]29[/C][C]-0.254493[/C][C]-1.9713[/C][C]0.026654[/C][/ROW]
[ROW][C]30[/C][C]-0.229158[/C][C]-1.7751[/C][C]0.040481[/C][/ROW]
[ROW][C]31[/C][C]-0.202798[/C][C]-1.5709[/C][C]0.060736[/C][/ROW]
[ROW][C]32[/C][C]-0.169137[/C][C]-1.3101[/C][C]0.097573[/C][/ROW]
[ROW][C]33[/C][C]-0.137177[/C][C]-1.0626[/C][C]0.146118[/C][/ROW]
[ROW][C]34[/C][C]-0.108816[/C][C]-0.8429[/C][C]0.20132[/C][/ROW]
[ROW][C]35[/C][C]-0.085327[/C][C]-0.6609[/C][C]0.25559[/C][/ROW]
[ROW][C]36[/C][C]-0.057012[/C][C]-0.4416[/C][C]0.33018[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71197&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71197&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
10.9538787.38870
20.8903556.89670
30.8232586.37690
40.7418285.74620
50.6359834.92633e-06
60.5154693.99289e-05
70.4016563.11120.001426
80.2949452.28460.012943
90.1863761.44370.077017
100.0792450.61380.270824
11-0.014314-0.11090.456043
12-0.104731-0.81120.210217
13-0.181785-1.40810.08213
14-0.244762-1.89590.031395
15-0.306352-2.3730.010433
16-0.355307-2.75220.003909
17-0.394074-3.05250.00169
18-0.418956-3.24520.000961
19-0.438488-3.39650.000608
20-0.455025-3.52460.000409
21-0.466319-3.61210.000311
22-0.45775-3.54570.000383
23-0.442565-3.42810.000552
24-0.421432-3.26440.000907
25-0.396732-3.07310.001592
26-0.36788-2.84960.002995
27-0.327575-2.53740.006893
28-0.288712-2.23640.014529
29-0.254493-1.97130.026654
30-0.229158-1.77510.040481
31-0.202798-1.57090.060736
32-0.169137-1.31010.097573
33-0.137177-1.06260.146118
34-0.108816-0.84290.20132
35-0.085327-0.66090.25559
36-0.057012-0.44160.33018






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9538787.38870
2-0.216693-1.67850.049226
3-0.039216-0.30380.38118
4-0.196053-1.51860.067055
5-0.285961-2.2150.015283
6-0.183662-1.42260.08001
70.0395240.30620.380274
80.0375540.29090.38607
9-0.034861-0.270.39403
10-0.034117-0.26430.39624
110.0136540.10580.458063
12-0.168987-1.3090.097768
130.0506830.39260.348006
140.0302090.2340.407891
15-0.154863-1.19960.117513
160.0318450.24670.403004
17-0.049237-0.38140.352132
180.0031260.02420.49038
19-0.065932-0.51070.305716
20-0.051695-0.40040.345131
21-0.088856-0.68830.246967
220.1074060.8320.204365
23-0.002242-0.01740.493102
240.0463650.35910.360374
25-0.072422-0.5610.288452
26-0.046682-0.36160.359462
270.0044530.03450.4863
28-0.069637-0.53940.295803
29-0.045332-0.35110.363358
30-0.161643-1.25210.107699
31-0.012832-0.09940.460579
320.0940010.72810.234683
330.010430.08080.467939
340.060290.4670.321093
35-0.066975-0.51880.30291
36-0.044949-0.34820.364464

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.953878 & 7.3887 & 0 \tabularnewline
2 & -0.216693 & -1.6785 & 0.049226 \tabularnewline
3 & -0.039216 & -0.3038 & 0.38118 \tabularnewline
4 & -0.196053 & -1.5186 & 0.067055 \tabularnewline
5 & -0.285961 & -2.215 & 0.015283 \tabularnewline
6 & -0.183662 & -1.4226 & 0.08001 \tabularnewline
7 & 0.039524 & 0.3062 & 0.380274 \tabularnewline
8 & 0.037554 & 0.2909 & 0.38607 \tabularnewline
9 & -0.034861 & -0.27 & 0.39403 \tabularnewline
10 & -0.034117 & -0.2643 & 0.39624 \tabularnewline
11 & 0.013654 & 0.1058 & 0.458063 \tabularnewline
12 & -0.168987 & -1.309 & 0.097768 \tabularnewline
13 & 0.050683 & 0.3926 & 0.348006 \tabularnewline
14 & 0.030209 & 0.234 & 0.407891 \tabularnewline
15 & -0.154863 & -1.1996 & 0.117513 \tabularnewline
16 & 0.031845 & 0.2467 & 0.403004 \tabularnewline
17 & -0.049237 & -0.3814 & 0.352132 \tabularnewline
18 & 0.003126 & 0.0242 & 0.49038 \tabularnewline
19 & -0.065932 & -0.5107 & 0.305716 \tabularnewline
20 & -0.051695 & -0.4004 & 0.345131 \tabularnewline
21 & -0.088856 & -0.6883 & 0.246967 \tabularnewline
22 & 0.107406 & 0.832 & 0.204365 \tabularnewline
23 & -0.002242 & -0.0174 & 0.493102 \tabularnewline
24 & 0.046365 & 0.3591 & 0.360374 \tabularnewline
25 & -0.072422 & -0.561 & 0.288452 \tabularnewline
26 & -0.046682 & -0.3616 & 0.359462 \tabularnewline
27 & 0.004453 & 0.0345 & 0.4863 \tabularnewline
28 & -0.069637 & -0.5394 & 0.295803 \tabularnewline
29 & -0.045332 & -0.3511 & 0.363358 \tabularnewline
30 & -0.161643 & -1.2521 & 0.107699 \tabularnewline
31 & -0.012832 & -0.0994 & 0.460579 \tabularnewline
32 & 0.094001 & 0.7281 & 0.234683 \tabularnewline
33 & 0.01043 & 0.0808 & 0.467939 \tabularnewline
34 & 0.06029 & 0.467 & 0.321093 \tabularnewline
35 & -0.066975 & -0.5188 & 0.30291 \tabularnewline
36 & -0.044949 & -0.3482 & 0.364464 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71197&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]0.953878[/C][C]7.3887[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.216693[/C][C]-1.6785[/C][C]0.049226[/C][/ROW]
[ROW][C]3[/C][C]-0.039216[/C][C]-0.3038[/C][C]0.38118[/C][/ROW]
[ROW][C]4[/C][C]-0.196053[/C][C]-1.5186[/C][C]0.067055[/C][/ROW]
[ROW][C]5[/C][C]-0.285961[/C][C]-2.215[/C][C]0.015283[/C][/ROW]
[ROW][C]6[/C][C]-0.183662[/C][C]-1.4226[/C][C]0.08001[/C][/ROW]
[ROW][C]7[/C][C]0.039524[/C][C]0.3062[/C][C]0.380274[/C][/ROW]
[ROW][C]8[/C][C]0.037554[/C][C]0.2909[/C][C]0.38607[/C][/ROW]
[ROW][C]9[/C][C]-0.034861[/C][C]-0.27[/C][C]0.39403[/C][/ROW]
[ROW][C]10[/C][C]-0.034117[/C][C]-0.2643[/C][C]0.39624[/C][/ROW]
[ROW][C]11[/C][C]0.013654[/C][C]0.1058[/C][C]0.458063[/C][/ROW]
[ROW][C]12[/C][C]-0.168987[/C][C]-1.309[/C][C]0.097768[/C][/ROW]
[ROW][C]13[/C][C]0.050683[/C][C]0.3926[/C][C]0.348006[/C][/ROW]
[ROW][C]14[/C][C]0.030209[/C][C]0.234[/C][C]0.407891[/C][/ROW]
[ROW][C]15[/C][C]-0.154863[/C][C]-1.1996[/C][C]0.117513[/C][/ROW]
[ROW][C]16[/C][C]0.031845[/C][C]0.2467[/C][C]0.403004[/C][/ROW]
[ROW][C]17[/C][C]-0.049237[/C][C]-0.3814[/C][C]0.352132[/C][/ROW]
[ROW][C]18[/C][C]0.003126[/C][C]0.0242[/C][C]0.49038[/C][/ROW]
[ROW][C]19[/C][C]-0.065932[/C][C]-0.5107[/C][C]0.305716[/C][/ROW]
[ROW][C]20[/C][C]-0.051695[/C][C]-0.4004[/C][C]0.345131[/C][/ROW]
[ROW][C]21[/C][C]-0.088856[/C][C]-0.6883[/C][C]0.246967[/C][/ROW]
[ROW][C]22[/C][C]0.107406[/C][C]0.832[/C][C]0.204365[/C][/ROW]
[ROW][C]23[/C][C]-0.002242[/C][C]-0.0174[/C][C]0.493102[/C][/ROW]
[ROW][C]24[/C][C]0.046365[/C][C]0.3591[/C][C]0.360374[/C][/ROW]
[ROW][C]25[/C][C]-0.072422[/C][C]-0.561[/C][C]0.288452[/C][/ROW]
[ROW][C]26[/C][C]-0.046682[/C][C]-0.3616[/C][C]0.359462[/C][/ROW]
[ROW][C]27[/C][C]0.004453[/C][C]0.0345[/C][C]0.4863[/C][/ROW]
[ROW][C]28[/C][C]-0.069637[/C][C]-0.5394[/C][C]0.295803[/C][/ROW]
[ROW][C]29[/C][C]-0.045332[/C][C]-0.3511[/C][C]0.363358[/C][/ROW]
[ROW][C]30[/C][C]-0.161643[/C][C]-1.2521[/C][C]0.107699[/C][/ROW]
[ROW][C]31[/C][C]-0.012832[/C][C]-0.0994[/C][C]0.460579[/C][/ROW]
[ROW][C]32[/C][C]0.094001[/C][C]0.7281[/C][C]0.234683[/C][/ROW]
[ROW][C]33[/C][C]0.01043[/C][C]0.0808[/C][C]0.467939[/C][/ROW]
[ROW][C]34[/C][C]0.06029[/C][C]0.467[/C][C]0.321093[/C][/ROW]
[ROW][C]35[/C][C]-0.066975[/C][C]-0.5188[/C][C]0.30291[/C][/ROW]
[ROW][C]36[/C][C]-0.044949[/C][C]-0.3482[/C][C]0.364464[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71197&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71197&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
10.9538787.38870
2-0.216693-1.67850.049226
3-0.039216-0.30380.38118
4-0.196053-1.51860.067055
5-0.285961-2.2150.015283
6-0.183662-1.42260.08001
70.0395240.30620.380274
80.0375540.29090.38607
9-0.034861-0.270.39403
10-0.034117-0.26430.39624
110.0136540.10580.458063
12-0.168987-1.3090.097768
130.0506830.39260.348006
140.0302090.2340.407891
15-0.154863-1.19960.117513
160.0318450.24670.403004
17-0.049237-0.38140.352132
180.0031260.02420.49038
19-0.065932-0.51070.305716
20-0.051695-0.40040.345131
21-0.088856-0.68830.246967
220.1074060.8320.204365
23-0.002242-0.01740.493102
240.0463650.35910.360374
25-0.072422-0.5610.288452
26-0.046682-0.36160.359462
270.0044530.03450.4863
28-0.069637-0.53940.295803
29-0.045332-0.35110.363358
30-0.161643-1.25210.107699
31-0.012832-0.09940.460579
320.0940010.72810.234683
330.010430.08080.467939
340.060290.4670.321093
35-0.066975-0.51880.30291
36-0.044949-0.34820.364464


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')