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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 computationSat, 19 Dec 2009 09:21:26 -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/19/t1261239726anfcl51v3n59czh.htm/, Retrieved Fri, 03 May 2024 21:40:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=69668, Retrieved Fri, 03 May 2024 21:40:38 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact131

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 12:26:39] [b98453cac15ba1066b407e146608df68]
- R PD        [(Partial) Autocorrelation Function] [ACF d=2,D=1] [2009-11-27 19:16:14] [fa71ec4c741ffec745cb91dcbd756720]
-   PD            [(Partial) Autocorrelation Function] [d=2,D=2] [2009-12-19 16:21:26] [18c0746232b29e9668aa6bedcb8dd698] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
12.6
15.7
13.2
20.3
12.8
8
0.9
3.6
14.1
21.7
24.5
18.9
13.9
11
5.8
15.5
22.4
31.7
30.3
31.4
20.2
19.7
10.8
13.2
15.1
15.6
15.5
12.7
10.9
10
9.1
10.3
16.9
22
27.6
28.9
31
32.9
38.1
28.8
29
21.8
28.8
25.6
28.2
20.2
17.9
16.3
13.2
8.1
4.5
-0.1
0
2.3
2.8
2.9
0.1
3.5
8.6
13.8

Tables (Output of Computation)





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=69668&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=69668&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69668&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.42143-2.45730.009627
20.4233062.46830.009382
3-0.553668-3.22840.001379
40.1049050.61170.272403
5-0.254529-1.48410.073492
60.2164511.26210.107749
7-0.160242-0.93440.178352
80.2386661.39160.086533
9-0.022316-0.13010.448617
100.0925410.53960.296493
11-0.011256-0.06560.474027
12-0.219296-1.27870.10483
130.0164280.09580.462124
14-0.121732-0.70980.241329
150.1601410.93380.178502
16-0.068939-0.4020.345107
170.1827331.06550.147077
18-0.182004-1.06130.148027
190.266611.55460.064652
20-0.271469-1.58290.061349
210.2813011.64030.055086
22-0.314365-1.8330.037782
230.1986481.15830.127405
24-0.204375-1.19170.120815
250.1847391.07720.144486
26-0.041333-0.2410.405498
270.0795890.46410.322775
28-0.07004-0.40840.342771
29-0.014465-0.08430.466638
30-0.055334-0.32260.374469
310.0238060.13880.445209
320.0159250.09290.463281
330.0010030.00580.497685
34NANANA
35NANANA
36NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.42143 & -2.4573 & 0.009627 \tabularnewline
2 & 0.423306 & 2.4683 & 0.009382 \tabularnewline
3 & -0.553668 & -3.2284 & 0.001379 \tabularnewline
4 & 0.104905 & 0.6117 & 0.272403 \tabularnewline
5 & -0.254529 & -1.4841 & 0.073492 \tabularnewline
6 & 0.216451 & 1.2621 & 0.107749 \tabularnewline
7 & -0.160242 & -0.9344 & 0.178352 \tabularnewline
8 & 0.238666 & 1.3916 & 0.086533 \tabularnewline
9 & -0.022316 & -0.1301 & 0.448617 \tabularnewline
10 & 0.092541 & 0.5396 & 0.296493 \tabularnewline
11 & -0.011256 & -0.0656 & 0.474027 \tabularnewline
12 & -0.219296 & -1.2787 & 0.10483 \tabularnewline
13 & 0.016428 & 0.0958 & 0.462124 \tabularnewline
14 & -0.121732 & -0.7098 & 0.241329 \tabularnewline
15 & 0.160141 & 0.9338 & 0.178502 \tabularnewline
16 & -0.068939 & -0.402 & 0.345107 \tabularnewline
17 & 0.182733 & 1.0655 & 0.147077 \tabularnewline
18 & -0.182004 & -1.0613 & 0.148027 \tabularnewline
19 & 0.26661 & 1.5546 & 0.064652 \tabularnewline
20 & -0.271469 & -1.5829 & 0.061349 \tabularnewline
21 & 0.281301 & 1.6403 & 0.055086 \tabularnewline
22 & -0.314365 & -1.833 & 0.037782 \tabularnewline
23 & 0.198648 & 1.1583 & 0.127405 \tabularnewline
24 & -0.204375 & -1.1917 & 0.120815 \tabularnewline
25 & 0.184739 & 1.0772 & 0.144486 \tabularnewline
26 & -0.041333 & -0.241 & 0.405498 \tabularnewline
27 & 0.079589 & 0.4641 & 0.322775 \tabularnewline
28 & -0.07004 & -0.4084 & 0.342771 \tabularnewline
29 & -0.014465 & -0.0843 & 0.466638 \tabularnewline
30 & -0.055334 & -0.3226 & 0.374469 \tabularnewline
31 & 0.023806 & 0.1388 & 0.445209 \tabularnewline
32 & 0.015925 & 0.0929 & 0.463281 \tabularnewline
33 & 0.001003 & 0.0058 & 0.497685 \tabularnewline
34 & NA & NA & NA \tabularnewline
35 & NA & NA & NA \tabularnewline
36 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69668&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]-0.42143[/C][C]-2.4573[/C][C]0.009627[/C][/ROW]
[ROW][C]2[/C][C]0.423306[/C][C]2.4683[/C][C]0.009382[/C][/ROW]
[ROW][C]3[/C][C]-0.553668[/C][C]-3.2284[/C][C]0.001379[/C][/ROW]
[ROW][C]4[/C][C]0.104905[/C][C]0.6117[/C][C]0.272403[/C][/ROW]
[ROW][C]5[/C][C]-0.254529[/C][C]-1.4841[/C][C]0.073492[/C][/ROW]
[ROW][C]6[/C][C]0.216451[/C][C]1.2621[/C][C]0.107749[/C][/ROW]
[ROW][C]7[/C][C]-0.160242[/C][C]-0.9344[/C][C]0.178352[/C][/ROW]
[ROW][C]8[/C][C]0.238666[/C][C]1.3916[/C][C]0.086533[/C][/ROW]
[ROW][C]9[/C][C]-0.022316[/C][C]-0.1301[/C][C]0.448617[/C][/ROW]
[ROW][C]10[/C][C]0.092541[/C][C]0.5396[/C][C]0.296493[/C][/ROW]
[ROW][C]11[/C][C]-0.011256[/C][C]-0.0656[/C][C]0.474027[/C][/ROW]
[ROW][C]12[/C][C]-0.219296[/C][C]-1.2787[/C][C]0.10483[/C][/ROW]
[ROW][C]13[/C][C]0.016428[/C][C]0.0958[/C][C]0.462124[/C][/ROW]
[ROW][C]14[/C][C]-0.121732[/C][C]-0.7098[/C][C]0.241329[/C][/ROW]
[ROW][C]15[/C][C]0.160141[/C][C]0.9338[/C][C]0.178502[/C][/ROW]
[ROW][C]16[/C][C]-0.068939[/C][C]-0.402[/C][C]0.345107[/C][/ROW]
[ROW][C]17[/C][C]0.182733[/C][C]1.0655[/C][C]0.147077[/C][/ROW]
[ROW][C]18[/C][C]-0.182004[/C][C]-1.0613[/C][C]0.148027[/C][/ROW]
[ROW][C]19[/C][C]0.26661[/C][C]1.5546[/C][C]0.064652[/C][/ROW]
[ROW][C]20[/C][C]-0.271469[/C][C]-1.5829[/C][C]0.061349[/C][/ROW]
[ROW][C]21[/C][C]0.281301[/C][C]1.6403[/C][C]0.055086[/C][/ROW]
[ROW][C]22[/C][C]-0.314365[/C][C]-1.833[/C][C]0.037782[/C][/ROW]
[ROW][C]23[/C][C]0.198648[/C][C]1.1583[/C][C]0.127405[/C][/ROW]
[ROW][C]24[/C][C]-0.204375[/C][C]-1.1917[/C][C]0.120815[/C][/ROW]
[ROW][C]25[/C][C]0.184739[/C][C]1.0772[/C][C]0.144486[/C][/ROW]
[ROW][C]26[/C][C]-0.041333[/C][C]-0.241[/C][C]0.405498[/C][/ROW]
[ROW][C]27[/C][C]0.079589[/C][C]0.4641[/C][C]0.322775[/C][/ROW]
[ROW][C]28[/C][C]-0.07004[/C][C]-0.4084[/C][C]0.342771[/C][/ROW]
[ROW][C]29[/C][C]-0.014465[/C][C]-0.0843[/C][C]0.466638[/C][/ROW]
[ROW][C]30[/C][C]-0.055334[/C][C]-0.3226[/C][C]0.374469[/C][/ROW]
[ROW][C]31[/C][C]0.023806[/C][C]0.1388[/C][C]0.445209[/C][/ROW]
[ROW][C]32[/C][C]0.015925[/C][C]0.0929[/C][C]0.463281[/C][/ROW]
[ROW][C]33[/C][C]0.001003[/C][C]0.0058[/C][C]0.497685[/C][/ROW]
[ROW][C]34[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]35[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]36[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69668&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69668&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
1-0.42143-2.45730.009627
20.4233062.46830.009382
3-0.553668-3.22840.001379
40.1049050.61170.272403
5-0.254529-1.48410.073492
60.2164511.26210.107749
7-0.160242-0.93440.178352
80.2386661.39160.086533
9-0.022316-0.13010.448617
100.0925410.53960.296493
11-0.011256-0.06560.474027
12-0.219296-1.27870.10483
130.0164280.09580.462124
14-0.121732-0.70980.241329
150.1601410.93380.178502
16-0.068939-0.4020.345107
170.1827331.06550.147077
18-0.182004-1.06130.148027
190.266611.55460.064652
20-0.271469-1.58290.061349
210.2813011.64030.055086
22-0.314365-1.8330.037782
230.1986481.15830.127405
24-0.204375-1.19170.120815
250.1847391.07720.144486
26-0.041333-0.2410.405498
270.0795890.46410.322775
28-0.07004-0.40840.342771
29-0.014465-0.08430.466638
30-0.055334-0.32260.374469
310.0238060.13880.445209
320.0159250.09290.463281
330.0010030.00580.497685
34NANANA
35NANANA
36NANANA






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.42143-2.45730.009627
20.2987641.74210.045268
3-0.404096-2.35630.012182
4-0.379915-2.21530.016771
5-0.082064-0.47850.317674
6-0.016105-0.09390.462867
7-0.329889-1.92360.031407
8-0.091005-0.53060.299557
90.2751521.60440.058938
10-0.091506-0.53360.298557
11-0.040299-0.2350.407816
12-0.137336-0.80080.214404
13-0.047315-0.27590.392152
14-0.040006-0.23330.408475
15-0.090745-0.52910.300076
16-0.206611-1.20470.118312
170.0168650.09830.46112
18-0.118987-0.69380.246259
190.0067750.03950.484359
20-0.057957-0.33790.368741
210.1561010.91020.184558
220.0138240.08060.468113
23-0.083869-0.4890.313978
240.0239890.13990.444791
250.0143630.08370.466874
260.1632620.9520.173915
27-0.104907-0.61170.272401
28-0.093046-0.54250.29549
290.0558060.32540.373436
30-0.064708-0.37730.354143
31-0.014763-0.08610.465952
32-0.001598-0.00930.496309
330.1045460.60960.273088
34NANANA
35NANANA
36NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.42143 & -2.4573 & 0.009627 \tabularnewline
2 & 0.298764 & 1.7421 & 0.045268 \tabularnewline
3 & -0.404096 & -2.3563 & 0.012182 \tabularnewline
4 & -0.379915 & -2.2153 & 0.016771 \tabularnewline
5 & -0.082064 & -0.4785 & 0.317674 \tabularnewline
6 & -0.016105 & -0.0939 & 0.462867 \tabularnewline
7 & -0.329889 & -1.9236 & 0.031407 \tabularnewline
8 & -0.091005 & -0.5306 & 0.299557 \tabularnewline
9 & 0.275152 & 1.6044 & 0.058938 \tabularnewline
10 & -0.091506 & -0.5336 & 0.298557 \tabularnewline
11 & -0.040299 & -0.235 & 0.407816 \tabularnewline
12 & -0.137336 & -0.8008 & 0.214404 \tabularnewline
13 & -0.047315 & -0.2759 & 0.392152 \tabularnewline
14 & -0.040006 & -0.2333 & 0.408475 \tabularnewline
15 & -0.090745 & -0.5291 & 0.300076 \tabularnewline
16 & -0.206611 & -1.2047 & 0.118312 \tabularnewline
17 & 0.016865 & 0.0983 & 0.46112 \tabularnewline
18 & -0.118987 & -0.6938 & 0.246259 \tabularnewline
19 & 0.006775 & 0.0395 & 0.484359 \tabularnewline
20 & -0.057957 & -0.3379 & 0.368741 \tabularnewline
21 & 0.156101 & 0.9102 & 0.184558 \tabularnewline
22 & 0.013824 & 0.0806 & 0.468113 \tabularnewline
23 & -0.083869 & -0.489 & 0.313978 \tabularnewline
24 & 0.023989 & 0.1399 & 0.444791 \tabularnewline
25 & 0.014363 & 0.0837 & 0.466874 \tabularnewline
26 & 0.163262 & 0.952 & 0.173915 \tabularnewline
27 & -0.104907 & -0.6117 & 0.272401 \tabularnewline
28 & -0.093046 & -0.5425 & 0.29549 \tabularnewline
29 & 0.055806 & 0.3254 & 0.373436 \tabularnewline
30 & -0.064708 & -0.3773 & 0.354143 \tabularnewline
31 & -0.014763 & -0.0861 & 0.465952 \tabularnewline
32 & -0.001598 & -0.0093 & 0.496309 \tabularnewline
33 & 0.104546 & 0.6096 & 0.273088 \tabularnewline
34 & NA & NA & NA \tabularnewline
35 & NA & NA & NA \tabularnewline
36 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69668&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]-0.42143[/C][C]-2.4573[/C][C]0.009627[/C][/ROW]
[ROW][C]2[/C][C]0.298764[/C][C]1.7421[/C][C]0.045268[/C][/ROW]
[ROW][C]3[/C][C]-0.404096[/C][C]-2.3563[/C][C]0.012182[/C][/ROW]
[ROW][C]4[/C][C]-0.379915[/C][C]-2.2153[/C][C]0.016771[/C][/ROW]
[ROW][C]5[/C][C]-0.082064[/C][C]-0.4785[/C][C]0.317674[/C][/ROW]
[ROW][C]6[/C][C]-0.016105[/C][C]-0.0939[/C][C]0.462867[/C][/ROW]
[ROW][C]7[/C][C]-0.329889[/C][C]-1.9236[/C][C]0.031407[/C][/ROW]
[ROW][C]8[/C][C]-0.091005[/C][C]-0.5306[/C][C]0.299557[/C][/ROW]
[ROW][C]9[/C][C]0.275152[/C][C]1.6044[/C][C]0.058938[/C][/ROW]
[ROW][C]10[/C][C]-0.091506[/C][C]-0.5336[/C][C]0.298557[/C][/ROW]
[ROW][C]11[/C][C]-0.040299[/C][C]-0.235[/C][C]0.407816[/C][/ROW]
[ROW][C]12[/C][C]-0.137336[/C][C]-0.8008[/C][C]0.214404[/C][/ROW]
[ROW][C]13[/C][C]-0.047315[/C][C]-0.2759[/C][C]0.392152[/C][/ROW]
[ROW][C]14[/C][C]-0.040006[/C][C]-0.2333[/C][C]0.408475[/C][/ROW]
[ROW][C]15[/C][C]-0.090745[/C][C]-0.5291[/C][C]0.300076[/C][/ROW]
[ROW][C]16[/C][C]-0.206611[/C][C]-1.2047[/C][C]0.118312[/C][/ROW]
[ROW][C]17[/C][C]0.016865[/C][C]0.0983[/C][C]0.46112[/C][/ROW]
[ROW][C]18[/C][C]-0.118987[/C][C]-0.6938[/C][C]0.246259[/C][/ROW]
[ROW][C]19[/C][C]0.006775[/C][C]0.0395[/C][C]0.484359[/C][/ROW]
[ROW][C]20[/C][C]-0.057957[/C][C]-0.3379[/C][C]0.368741[/C][/ROW]
[ROW][C]21[/C][C]0.156101[/C][C]0.9102[/C][C]0.184558[/C][/ROW]
[ROW][C]22[/C][C]0.013824[/C][C]0.0806[/C][C]0.468113[/C][/ROW]
[ROW][C]23[/C][C]-0.083869[/C][C]-0.489[/C][C]0.313978[/C][/ROW]
[ROW][C]24[/C][C]0.023989[/C][C]0.1399[/C][C]0.444791[/C][/ROW]
[ROW][C]25[/C][C]0.014363[/C][C]0.0837[/C][C]0.466874[/C][/ROW]
[ROW][C]26[/C][C]0.163262[/C][C]0.952[/C][C]0.173915[/C][/ROW]
[ROW][C]27[/C][C]-0.104907[/C][C]-0.6117[/C][C]0.272401[/C][/ROW]
[ROW][C]28[/C][C]-0.093046[/C][C]-0.5425[/C][C]0.29549[/C][/ROW]
[ROW][C]29[/C][C]0.055806[/C][C]0.3254[/C][C]0.373436[/C][/ROW]
[ROW][C]30[/C][C]-0.064708[/C][C]-0.3773[/C][C]0.354143[/C][/ROW]
[ROW][C]31[/C][C]-0.014763[/C][C]-0.0861[/C][C]0.465952[/C][/ROW]
[ROW][C]32[/C][C]-0.001598[/C][C]-0.0093[/C][C]0.496309[/C][/ROW]
[ROW][C]33[/C][C]0.104546[/C][C]0.6096[/C][C]0.273088[/C][/ROW]
[ROW][C]34[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]35[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]36[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69668&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69668&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
1-0.42143-2.45730.009627
20.2987641.74210.045268
3-0.404096-2.35630.012182
4-0.379915-2.21530.016771
5-0.082064-0.47850.317674
6-0.016105-0.09390.462867
7-0.329889-1.92360.031407
8-0.091005-0.53060.299557
90.2751521.60440.058938
10-0.091506-0.53360.298557
11-0.040299-0.2350.407816
12-0.137336-0.80080.214404
13-0.047315-0.27590.392152
14-0.040006-0.23330.408475
15-0.090745-0.52910.300076
16-0.206611-1.20470.118312
170.0168650.09830.46112
18-0.118987-0.69380.246259
190.0067750.03950.484359
20-0.057957-0.33790.368741
210.1561010.91020.184558
220.0138240.08060.468113
23-0.083869-0.4890.313978
240.0239890.13990.444791
250.0143630.08370.466874
260.1632620.9520.173915
27-0.104907-0.61170.272401
28-0.093046-0.54250.29549
290.0558060.32540.373436
30-0.064708-0.37730.354143
31-0.014763-0.08610.465952
32-0.001598-0.00930.496309
330.1045460.60960.273088
34NANANA
35NANANA
36NANANA


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 2 ; par4 = 2 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 2 ; par4 = 2 ; 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')