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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 computationWed, 25 Nov 2009 09:54:24 -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/25/t1259168127vupmwgks9kpruk3.htm/, Retrieved Tue, 07 May 2024 19:34:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59464, Retrieved Tue, 07 May 2024 19:34:49 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact226
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]
- R  D        [(Partial) Autocorrelation Function] [Model 1 (autocorr...] [2009-11-25 16:46:20] [c0117c881d5fcd069841276db0c34efe]
-   PD            [(Partial) Autocorrelation Function] [Model 1: D=1] [2009-11-25 16:54:24] [d5837f25ec8937f9733a894c487f865c] [Current]
-   P               [(Partial) Autocorrelation Function] [Model 1: D=1, d=1] [2009-11-25 17:09:22] [c0117c881d5fcd069841276db0c34efe]
-   P                 [(Partial) Autocorrelation Function] [Model 1: D=0, d=1] [2009-11-25 17:41:01] [c0117c881d5fcd069841276db0c34efe]
-   PD                [(Partial) Autocorrelation Function] [] [2009-11-28 11:25:31] [4f1a20f787b3465111b61213cdeef1a9]
-    D                [(Partial) Autocorrelation Function] [model 1: D=1, d=1] [2009-11-28 11:37:11] [4f1a20f787b3465111b61213cdeef1a9]
-   PD                  [(Partial) Autocorrelation Function] [model 1: D=0, d=1] [2009-11-28 11:46:39] [4f1a20f787b3465111b61213cdeef1a9]
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Dataseries X:
3030.29
2803.47
2767.63
2882.6
2863.36
2897.06
3012.61
3142.95
3032.93
3045.78
3110.52
3013.24
2987.1
2995.55
2833.18
2848.96
2794.83
2845.26
2915.02
2892.63
2604.42
2641.65
2659.81
2638.53
2720.25
2745.88
2735.7
2811.7
2799.43
2555.28
2304.98
2214.95
2065.81
1940.49
2042
1995.37
1946.81
1765.9
1635.25
1833.42
1910.43
1959.67
1969.6
2061.41
2093.48
2120.88
2174.56
2196.72
2350.44
2440.25
2408.64
2472.81
2407.6
2454.62
2448.05
2497.84
2645.64
2756.76
2849.27
2921.44




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59464&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]1 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=59464&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59464&T=0

As an alternative you can also use a 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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.9323076.45920
20.8298365.74930
30.7198424.98724e-06
40.6162884.26984.6e-05
50.5225573.62040.000353
60.4310622.98650.002217
70.3417412.36770.010989
80.2479571.71790.046131
90.1337570.92670.17936
100.0086630.060.476194
11-0.103617-0.71790.238156
12-0.1835-1.27130.10487
13-0.221734-1.53620.065525
14-0.246794-1.70980.046877
15-0.277526-1.92280.030227
16-0.312401-2.16440.01772
17-0.344026-2.38350.010577
18-0.370973-2.57020.006662
19-0.384586-2.66450.005235
20-0.372893-2.58350.006441
21-0.340288-2.35760.011259
22-0.300684-2.08320.021291
23-0.27603-1.91240.030902
24-0.263866-1.82810.036875
25-0.254664-1.76440.042017
26-0.238914-1.65520.0522
27-0.210827-1.46070.075313
28-0.183392-1.27060.105001
29-0.139319-0.96520.169633
30-0.093563-0.64820.259964
31-0.066562-0.46120.323384
32-0.063217-0.4380.331682
33-0.065617-0.45460.325719
34-0.06536-0.45280.326357
35-0.052382-0.36290.359132
36-0.040471-0.28040.390192

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.932307 & 6.4592 & 0 \tabularnewline
2 & 0.829836 & 5.7493 & 0 \tabularnewline
3 & 0.719842 & 4.9872 & 4e-06 \tabularnewline
4 & 0.616288 & 4.2698 & 4.6e-05 \tabularnewline
5 & 0.522557 & 3.6204 & 0.000353 \tabularnewline
6 & 0.431062 & 2.9865 & 0.002217 \tabularnewline
7 & 0.341741 & 2.3677 & 0.010989 \tabularnewline
8 & 0.247957 & 1.7179 & 0.046131 \tabularnewline
9 & 0.133757 & 0.9267 & 0.17936 \tabularnewline
10 & 0.008663 & 0.06 & 0.476194 \tabularnewline
11 & -0.103617 & -0.7179 & 0.238156 \tabularnewline
12 & -0.1835 & -1.2713 & 0.10487 \tabularnewline
13 & -0.221734 & -1.5362 & 0.065525 \tabularnewline
14 & -0.246794 & -1.7098 & 0.046877 \tabularnewline
15 & -0.277526 & -1.9228 & 0.030227 \tabularnewline
16 & -0.312401 & -2.1644 & 0.01772 \tabularnewline
17 & -0.344026 & -2.3835 & 0.010577 \tabularnewline
18 & -0.370973 & -2.5702 & 0.006662 \tabularnewline
19 & -0.384586 & -2.6645 & 0.005235 \tabularnewline
20 & -0.372893 & -2.5835 & 0.006441 \tabularnewline
21 & -0.340288 & -2.3576 & 0.011259 \tabularnewline
22 & -0.300684 & -2.0832 & 0.021291 \tabularnewline
23 & -0.27603 & -1.9124 & 0.030902 \tabularnewline
24 & -0.263866 & -1.8281 & 0.036875 \tabularnewline
25 & -0.254664 & -1.7644 & 0.042017 \tabularnewline
26 & -0.238914 & -1.6552 & 0.0522 \tabularnewline
27 & -0.210827 & -1.4607 & 0.075313 \tabularnewline
28 & -0.183392 & -1.2706 & 0.105001 \tabularnewline
29 & -0.139319 & -0.9652 & 0.169633 \tabularnewline
30 & -0.093563 & -0.6482 & 0.259964 \tabularnewline
31 & -0.066562 & -0.4612 & 0.323384 \tabularnewline
32 & -0.063217 & -0.438 & 0.331682 \tabularnewline
33 & -0.065617 & -0.4546 & 0.325719 \tabularnewline
34 & -0.06536 & -0.4528 & 0.326357 \tabularnewline
35 & -0.052382 & -0.3629 & 0.359132 \tabularnewline
36 & -0.040471 & -0.2804 & 0.390192 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59464&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]0.932307[/C][C]6.4592[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.829836[/C][C]5.7493[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.719842[/C][C]4.9872[/C][C]4e-06[/C][/ROW]
[ROW][C]4[/C][C]0.616288[/C][C]4.2698[/C][C]4.6e-05[/C][/ROW]
[ROW][C]5[/C][C]0.522557[/C][C]3.6204[/C][C]0.000353[/C][/ROW]
[ROW][C]6[/C][C]0.431062[/C][C]2.9865[/C][C]0.002217[/C][/ROW]
[ROW][C]7[/C][C]0.341741[/C][C]2.3677[/C][C]0.010989[/C][/ROW]
[ROW][C]8[/C][C]0.247957[/C][C]1.7179[/C][C]0.046131[/C][/ROW]
[ROW][C]9[/C][C]0.133757[/C][C]0.9267[/C][C]0.17936[/C][/ROW]
[ROW][C]10[/C][C]0.008663[/C][C]0.06[/C][C]0.476194[/C][/ROW]
[ROW][C]11[/C][C]-0.103617[/C][C]-0.7179[/C][C]0.238156[/C][/ROW]
[ROW][C]12[/C][C]-0.1835[/C][C]-1.2713[/C][C]0.10487[/C][/ROW]
[ROW][C]13[/C][C]-0.221734[/C][C]-1.5362[/C][C]0.065525[/C][/ROW]
[ROW][C]14[/C][C]-0.246794[/C][C]-1.7098[/C][C]0.046877[/C][/ROW]
[ROW][C]15[/C][C]-0.277526[/C][C]-1.9228[/C][C]0.030227[/C][/ROW]
[ROW][C]16[/C][C]-0.312401[/C][C]-2.1644[/C][C]0.01772[/C][/ROW]
[ROW][C]17[/C][C]-0.344026[/C][C]-2.3835[/C][C]0.010577[/C][/ROW]
[ROW][C]18[/C][C]-0.370973[/C][C]-2.5702[/C][C]0.006662[/C][/ROW]
[ROW][C]19[/C][C]-0.384586[/C][C]-2.6645[/C][C]0.005235[/C][/ROW]
[ROW][C]20[/C][C]-0.372893[/C][C]-2.5835[/C][C]0.006441[/C][/ROW]
[ROW][C]21[/C][C]-0.340288[/C][C]-2.3576[/C][C]0.011259[/C][/ROW]
[ROW][C]22[/C][C]-0.300684[/C][C]-2.0832[/C][C]0.021291[/C][/ROW]
[ROW][C]23[/C][C]-0.27603[/C][C]-1.9124[/C][C]0.030902[/C][/ROW]
[ROW][C]24[/C][C]-0.263866[/C][C]-1.8281[/C][C]0.036875[/C][/ROW]
[ROW][C]25[/C][C]-0.254664[/C][C]-1.7644[/C][C]0.042017[/C][/ROW]
[ROW][C]26[/C][C]-0.238914[/C][C]-1.6552[/C][C]0.0522[/C][/ROW]
[ROW][C]27[/C][C]-0.210827[/C][C]-1.4607[/C][C]0.075313[/C][/ROW]
[ROW][C]28[/C][C]-0.183392[/C][C]-1.2706[/C][C]0.105001[/C][/ROW]
[ROW][C]29[/C][C]-0.139319[/C][C]-0.9652[/C][C]0.169633[/C][/ROW]
[ROW][C]30[/C][C]-0.093563[/C][C]-0.6482[/C][C]0.259964[/C][/ROW]
[ROW][C]31[/C][C]-0.066562[/C][C]-0.4612[/C][C]0.323384[/C][/ROW]
[ROW][C]32[/C][C]-0.063217[/C][C]-0.438[/C][C]0.331682[/C][/ROW]
[ROW][C]33[/C][C]-0.065617[/C][C]-0.4546[/C][C]0.325719[/C][/ROW]
[ROW][C]34[/C][C]-0.06536[/C][C]-0.4528[/C][C]0.326357[/C][/ROW]
[ROW][C]35[/C][C]-0.052382[/C][C]-0.3629[/C][C]0.359132[/C][/ROW]
[ROW][C]36[/C][C]-0.040471[/C][C]-0.2804[/C][C]0.390192[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59464&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59464&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.9323076.45920
20.8298365.74930
30.7198424.98724e-06
40.6162884.26984.6e-05
50.5225573.62040.000353
60.4310622.98650.002217
70.3417412.36770.010989
80.2479571.71790.046131
90.1337570.92670.17936
100.0086630.060.476194
11-0.103617-0.71790.238156
12-0.1835-1.27130.10487
13-0.221734-1.53620.065525
14-0.246794-1.70980.046877
15-0.277526-1.92280.030227
16-0.312401-2.16440.01772
17-0.344026-2.38350.010577
18-0.370973-2.57020.006662
19-0.384586-2.66450.005235
20-0.372893-2.58350.006441
21-0.340288-2.35760.011259
22-0.300684-2.08320.021291
23-0.27603-1.91240.030902
24-0.263866-1.82810.036875
25-0.254664-1.76440.042017
26-0.238914-1.65520.0522
27-0.210827-1.46070.075313
28-0.183392-1.27060.105001
29-0.139319-0.96520.169633
30-0.093563-0.64820.259964
31-0.066562-0.46120.323384
32-0.063217-0.4380.331682
33-0.065617-0.45460.325719
34-0.06536-0.45280.326357
35-0.052382-0.36290.359132
36-0.040471-0.28040.390192







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9323076.45920
2-0.300901-2.08470.02122
3-0.051143-0.35430.362323
40.0018570.01290.494893
5-0.010874-0.07530.47013
6-0.078915-0.54670.293545
7-0.047363-0.32810.372117
8-0.106567-0.73830.231959
9-0.23078-1.59890.058204
10-0.122352-0.84770.200411
110.0239750.16610.434386
120.0985520.68280.249012
130.1405260.97360.167571
14-0.087673-0.60740.273218
15-0.14137-0.97940.166137
16-0.057915-0.40120.34501
170.0147230.1020.459589
18-0.027374-0.18970.425191
190.008980.06220.475325
200.0511980.35470.362181
21-0.038339-0.26560.395836
22-0.05116-0.35450.362277
23-0.093252-0.64610.260656
240.0061150.04240.483192
250.0175170.12140.451956
26-0.006491-0.0450.482158
27-0.01026-0.07110.471813
28-0.123019-0.85230.199141
290.1342790.93030.178433
30-0.006989-0.04840.48079
31-0.097461-0.67520.251385
32-0.08483-0.58770.279738
330.0267350.18520.426918
34-0.056453-0.39110.348721
350.0036890.02560.489857
36-0.050077-0.34690.365075

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.932307 & 6.4592 & 0 \tabularnewline
2 & -0.300901 & -2.0847 & 0.02122 \tabularnewline
3 & -0.051143 & -0.3543 & 0.362323 \tabularnewline
4 & 0.001857 & 0.0129 & 0.494893 \tabularnewline
5 & -0.010874 & -0.0753 & 0.47013 \tabularnewline
6 & -0.078915 & -0.5467 & 0.293545 \tabularnewline
7 & -0.047363 & -0.3281 & 0.372117 \tabularnewline
8 & -0.106567 & -0.7383 & 0.231959 \tabularnewline
9 & -0.23078 & -1.5989 & 0.058204 \tabularnewline
10 & -0.122352 & -0.8477 & 0.200411 \tabularnewline
11 & 0.023975 & 0.1661 & 0.434386 \tabularnewline
12 & 0.098552 & 0.6828 & 0.249012 \tabularnewline
13 & 0.140526 & 0.9736 & 0.167571 \tabularnewline
14 & -0.087673 & -0.6074 & 0.273218 \tabularnewline
15 & -0.14137 & -0.9794 & 0.166137 \tabularnewline
16 & -0.057915 & -0.4012 & 0.34501 \tabularnewline
17 & 0.014723 & 0.102 & 0.459589 \tabularnewline
18 & -0.027374 & -0.1897 & 0.425191 \tabularnewline
19 & 0.00898 & 0.0622 & 0.475325 \tabularnewline
20 & 0.051198 & 0.3547 & 0.362181 \tabularnewline
21 & -0.038339 & -0.2656 & 0.395836 \tabularnewline
22 & -0.05116 & -0.3545 & 0.362277 \tabularnewline
23 & -0.093252 & -0.6461 & 0.260656 \tabularnewline
24 & 0.006115 & 0.0424 & 0.483192 \tabularnewline
25 & 0.017517 & 0.1214 & 0.451956 \tabularnewline
26 & -0.006491 & -0.045 & 0.482158 \tabularnewline
27 & -0.01026 & -0.0711 & 0.471813 \tabularnewline
28 & -0.123019 & -0.8523 & 0.199141 \tabularnewline
29 & 0.134279 & 0.9303 & 0.178433 \tabularnewline
30 & -0.006989 & -0.0484 & 0.48079 \tabularnewline
31 & -0.097461 & -0.6752 & 0.251385 \tabularnewline
32 & -0.08483 & -0.5877 & 0.279738 \tabularnewline
33 & 0.026735 & 0.1852 & 0.426918 \tabularnewline
34 & -0.056453 & -0.3911 & 0.348721 \tabularnewline
35 & 0.003689 & 0.0256 & 0.489857 \tabularnewline
36 & -0.050077 & -0.3469 & 0.365075 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59464&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]0.932307[/C][C]6.4592[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.300901[/C][C]-2.0847[/C][C]0.02122[/C][/ROW]
[ROW][C]3[/C][C]-0.051143[/C][C]-0.3543[/C][C]0.362323[/C][/ROW]
[ROW][C]4[/C][C]0.001857[/C][C]0.0129[/C][C]0.494893[/C][/ROW]
[ROW][C]5[/C][C]-0.010874[/C][C]-0.0753[/C][C]0.47013[/C][/ROW]
[ROW][C]6[/C][C]-0.078915[/C][C]-0.5467[/C][C]0.293545[/C][/ROW]
[ROW][C]7[/C][C]-0.047363[/C][C]-0.3281[/C][C]0.372117[/C][/ROW]
[ROW][C]8[/C][C]-0.106567[/C][C]-0.7383[/C][C]0.231959[/C][/ROW]
[ROW][C]9[/C][C]-0.23078[/C][C]-1.5989[/C][C]0.058204[/C][/ROW]
[ROW][C]10[/C][C]-0.122352[/C][C]-0.8477[/C][C]0.200411[/C][/ROW]
[ROW][C]11[/C][C]0.023975[/C][C]0.1661[/C][C]0.434386[/C][/ROW]
[ROW][C]12[/C][C]0.098552[/C][C]0.6828[/C][C]0.249012[/C][/ROW]
[ROW][C]13[/C][C]0.140526[/C][C]0.9736[/C][C]0.167571[/C][/ROW]
[ROW][C]14[/C][C]-0.087673[/C][C]-0.6074[/C][C]0.273218[/C][/ROW]
[ROW][C]15[/C][C]-0.14137[/C][C]-0.9794[/C][C]0.166137[/C][/ROW]
[ROW][C]16[/C][C]-0.057915[/C][C]-0.4012[/C][C]0.34501[/C][/ROW]
[ROW][C]17[/C][C]0.014723[/C][C]0.102[/C][C]0.459589[/C][/ROW]
[ROW][C]18[/C][C]-0.027374[/C][C]-0.1897[/C][C]0.425191[/C][/ROW]
[ROW][C]19[/C][C]0.00898[/C][C]0.0622[/C][C]0.475325[/C][/ROW]
[ROW][C]20[/C][C]0.051198[/C][C]0.3547[/C][C]0.362181[/C][/ROW]
[ROW][C]21[/C][C]-0.038339[/C][C]-0.2656[/C][C]0.395836[/C][/ROW]
[ROW][C]22[/C][C]-0.05116[/C][C]-0.3545[/C][C]0.362277[/C][/ROW]
[ROW][C]23[/C][C]-0.093252[/C][C]-0.6461[/C][C]0.260656[/C][/ROW]
[ROW][C]24[/C][C]0.006115[/C][C]0.0424[/C][C]0.483192[/C][/ROW]
[ROW][C]25[/C][C]0.017517[/C][C]0.1214[/C][C]0.451956[/C][/ROW]
[ROW][C]26[/C][C]-0.006491[/C][C]-0.045[/C][C]0.482158[/C][/ROW]
[ROW][C]27[/C][C]-0.01026[/C][C]-0.0711[/C][C]0.471813[/C][/ROW]
[ROW][C]28[/C][C]-0.123019[/C][C]-0.8523[/C][C]0.199141[/C][/ROW]
[ROW][C]29[/C][C]0.134279[/C][C]0.9303[/C][C]0.178433[/C][/ROW]
[ROW][C]30[/C][C]-0.006989[/C][C]-0.0484[/C][C]0.48079[/C][/ROW]
[ROW][C]31[/C][C]-0.097461[/C][C]-0.6752[/C][C]0.251385[/C][/ROW]
[ROW][C]32[/C][C]-0.08483[/C][C]-0.5877[/C][C]0.279738[/C][/ROW]
[ROW][C]33[/C][C]0.026735[/C][C]0.1852[/C][C]0.426918[/C][/ROW]
[ROW][C]34[/C][C]-0.056453[/C][C]-0.3911[/C][C]0.348721[/C][/ROW]
[ROW][C]35[/C][C]0.003689[/C][C]0.0256[/C][C]0.489857[/C][/ROW]
[ROW][C]36[/C][C]-0.050077[/C][C]-0.3469[/C][C]0.365075[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59464&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59464&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9323076.45920
2-0.300901-2.08470.02122
3-0.051143-0.35430.362323
40.0018570.01290.494893
5-0.010874-0.07530.47013
6-0.078915-0.54670.293545
7-0.047363-0.32810.372117
8-0.106567-0.73830.231959
9-0.23078-1.59890.058204
10-0.122352-0.84770.200411
110.0239750.16610.434386
120.0985520.68280.249012
130.1405260.97360.167571
14-0.087673-0.60740.273218
15-0.14137-0.97940.166137
16-0.057915-0.40120.34501
170.0147230.1020.459589
18-0.027374-0.18970.425191
190.008980.06220.475325
200.0511980.35470.362181
21-0.038339-0.26560.395836
22-0.05116-0.35450.362277
23-0.093252-0.64610.260656
240.0061150.04240.483192
250.0175170.12140.451956
26-0.006491-0.0450.482158
27-0.01026-0.07110.471813
28-0.123019-0.85230.199141
290.1342790.93030.178433
30-0.006989-0.04840.48079
31-0.097461-0.67520.251385
32-0.08483-0.58770.279738
330.0267350.18520.426918
34-0.056453-0.39110.348721
350.0036890.02560.489857
36-0.050077-0.34690.365075



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')