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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, 28 Nov 2009 04:37:11 -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/28/t1259408303mwciv9k9mk9sxvi.htm/, Retrieved Fri, 03 May 2024 13:58:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=61438, Retrieved Fri, 03 May 2024 13:58:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact159

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]
- 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] [c0117c881d5fcd069841276db0c34efe]
-   P             [(Partial) Autocorrelation Function] [Model 1: D=1, d=1] [2009-11-25 17:09:22] [c0117c881d5fcd069841276db0c34efe]
-    D                [(Partial) Autocorrelation Function] [model 1: D=1, d=1] [2009-11-28 11:37:11] [d1818fb1d9a1b0f34f8553ada228d3d5] [Current]
-   PD                  [(Partial) Autocorrelation Function] [model 1: D=0, d=1] [2009-11-28 11:46:39] [4f1a20f787b3465111b61213cdeef1a9]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
107.11
107.57
107.81
108.75
109.43
109.62
109.54
109.53
109.84
109.67
109.79
109.56
110.22
110.40
110.69
110.72
110.89
110.58
110.94
110.91
111.22
111.09
111.00
111.06
111.55
112.32
112.64
112.36
112.04
112.37
112.59
112.89
113.22
112.85
113.06
112.99
113.32
113.74
113.91
114.52
114.96
114.91
115.30
115.44
115.52
116.08
115.94
115.56
115.88
116.66
117.41
117.68
117.85
118.21
118.92
119.03
119.17
118.95
118.92
118.90

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=61438&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=61438&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61438&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
1-0.037036-0.25390.400338
2-0.166434-1.1410.129822
3-0.13391-0.9180.181642
4-0.055739-0.38210.352043
50.2556731.75280.043078
60.0956730.65590.257543
7-0.242441-1.66210.051576
8-0.074485-0.51060.305996
90.0777350.53290.298299
100.0822130.56360.287845
110.2655761.82070.037511
12-0.425654-2.91810.002694
130.0262680.18010.428929
140.1700851.1660.124739
150.0061640.04230.483235
160.0843710.57840.282871
17-0.170319-1.16770.124418
18-0.184804-1.2670.105707
190.1001380.68650.247881
200.2015641.38190.086775
210.0497420.3410.367307
220.0083130.0570.477398
23-0.200468-1.37430.087928
240.0041360.02840.488751
25-0.008912-0.06110.475772
26-0.112642-0.77220.221921
270.0448010.30710.380046
28-0.070609-0.48410.315291
290.0334240.22910.409875
300.0028070.01920.492363
310.0716630.49130.312752
32-0.070488-0.48320.315583
33-0.035724-0.24490.403795
34-0.069463-0.47620.318064
350.0152170.10430.45868
360.0474020.3250.373321

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.037036 & -0.2539 & 0.400338 \tabularnewline
2 & -0.166434 & -1.141 & 0.129822 \tabularnewline
3 & -0.13391 & -0.918 & 0.181642 \tabularnewline
4 & -0.055739 & -0.3821 & 0.352043 \tabularnewline
5 & 0.255673 & 1.7528 & 0.043078 \tabularnewline
6 & 0.095673 & 0.6559 & 0.257543 \tabularnewline
7 & -0.242441 & -1.6621 & 0.051576 \tabularnewline
8 & -0.074485 & -0.5106 & 0.305996 \tabularnewline
9 & 0.077735 & 0.5329 & 0.298299 \tabularnewline
10 & 0.082213 & 0.5636 & 0.287845 \tabularnewline
11 & 0.265576 & 1.8207 & 0.037511 \tabularnewline
12 & -0.425654 & -2.9181 & 0.002694 \tabularnewline
13 & 0.026268 & 0.1801 & 0.428929 \tabularnewline
14 & 0.170085 & 1.166 & 0.124739 \tabularnewline
15 & 0.006164 & 0.0423 & 0.483235 \tabularnewline
16 & 0.084371 & 0.5784 & 0.282871 \tabularnewline
17 & -0.170319 & -1.1677 & 0.124418 \tabularnewline
18 & -0.184804 & -1.267 & 0.105707 \tabularnewline
19 & 0.100138 & 0.6865 & 0.247881 \tabularnewline
20 & 0.201564 & 1.3819 & 0.086775 \tabularnewline
21 & 0.049742 & 0.341 & 0.367307 \tabularnewline
22 & 0.008313 & 0.057 & 0.477398 \tabularnewline
23 & -0.200468 & -1.3743 & 0.087928 \tabularnewline
24 & 0.004136 & 0.0284 & 0.488751 \tabularnewline
25 & -0.008912 & -0.0611 & 0.475772 \tabularnewline
26 & -0.112642 & -0.7722 & 0.221921 \tabularnewline
27 & 0.044801 & 0.3071 & 0.380046 \tabularnewline
28 & -0.070609 & -0.4841 & 0.315291 \tabularnewline
29 & 0.033424 & 0.2291 & 0.409875 \tabularnewline
30 & 0.002807 & 0.0192 & 0.492363 \tabularnewline
31 & 0.071663 & 0.4913 & 0.312752 \tabularnewline
32 & -0.070488 & -0.4832 & 0.315583 \tabularnewline
33 & -0.035724 & -0.2449 & 0.403795 \tabularnewline
34 & -0.069463 & -0.4762 & 0.318064 \tabularnewline
35 & 0.015217 & 0.1043 & 0.45868 \tabularnewline
36 & 0.047402 & 0.325 & 0.373321 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61438&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]-0.037036[/C][C]-0.2539[/C][C]0.400338[/C][/ROW]
[ROW][C]2[/C][C]-0.166434[/C][C]-1.141[/C][C]0.129822[/C][/ROW]
[ROW][C]3[/C][C]-0.13391[/C][C]-0.918[/C][C]0.181642[/C][/ROW]
[ROW][C]4[/C][C]-0.055739[/C][C]-0.3821[/C][C]0.352043[/C][/ROW]
[ROW][C]5[/C][C]0.255673[/C][C]1.7528[/C][C]0.043078[/C][/ROW]
[ROW][C]6[/C][C]0.095673[/C][C]0.6559[/C][C]0.257543[/C][/ROW]
[ROW][C]7[/C][C]-0.242441[/C][C]-1.6621[/C][C]0.051576[/C][/ROW]
[ROW][C]8[/C][C]-0.074485[/C][C]-0.5106[/C][C]0.305996[/C][/ROW]
[ROW][C]9[/C][C]0.077735[/C][C]0.5329[/C][C]0.298299[/C][/ROW]
[ROW][C]10[/C][C]0.082213[/C][C]0.5636[/C][C]0.287845[/C][/ROW]
[ROW][C]11[/C][C]0.265576[/C][C]1.8207[/C][C]0.037511[/C][/ROW]
[ROW][C]12[/C][C]-0.425654[/C][C]-2.9181[/C][C]0.002694[/C][/ROW]
[ROW][C]13[/C][C]0.026268[/C][C]0.1801[/C][C]0.428929[/C][/ROW]
[ROW][C]14[/C][C]0.170085[/C][C]1.166[/C][C]0.124739[/C][/ROW]
[ROW][C]15[/C][C]0.006164[/C][C]0.0423[/C][C]0.483235[/C][/ROW]
[ROW][C]16[/C][C]0.084371[/C][C]0.5784[/C][C]0.282871[/C][/ROW]
[ROW][C]17[/C][C]-0.170319[/C][C]-1.1677[/C][C]0.124418[/C][/ROW]
[ROW][C]18[/C][C]-0.184804[/C][C]-1.267[/C][C]0.105707[/C][/ROW]
[ROW][C]19[/C][C]0.100138[/C][C]0.6865[/C][C]0.247881[/C][/ROW]
[ROW][C]20[/C][C]0.201564[/C][C]1.3819[/C][C]0.086775[/C][/ROW]
[ROW][C]21[/C][C]0.049742[/C][C]0.341[/C][C]0.367307[/C][/ROW]
[ROW][C]22[/C][C]0.008313[/C][C]0.057[/C][C]0.477398[/C][/ROW]
[ROW][C]23[/C][C]-0.200468[/C][C]-1.3743[/C][C]0.087928[/C][/ROW]
[ROW][C]24[/C][C]0.004136[/C][C]0.0284[/C][C]0.488751[/C][/ROW]
[ROW][C]25[/C][C]-0.008912[/C][C]-0.0611[/C][C]0.475772[/C][/ROW]
[ROW][C]26[/C][C]-0.112642[/C][C]-0.7722[/C][C]0.221921[/C][/ROW]
[ROW][C]27[/C][C]0.044801[/C][C]0.3071[/C][C]0.380046[/C][/ROW]
[ROW][C]28[/C][C]-0.070609[/C][C]-0.4841[/C][C]0.315291[/C][/ROW]
[ROW][C]29[/C][C]0.033424[/C][C]0.2291[/C][C]0.409875[/C][/ROW]
[ROW][C]30[/C][C]0.002807[/C][C]0.0192[/C][C]0.492363[/C][/ROW]
[ROW][C]31[/C][C]0.071663[/C][C]0.4913[/C][C]0.312752[/C][/ROW]
[ROW][C]32[/C][C]-0.070488[/C][C]-0.4832[/C][C]0.315583[/C][/ROW]
[ROW][C]33[/C][C]-0.035724[/C][C]-0.2449[/C][C]0.403795[/C][/ROW]
[ROW][C]34[/C][C]-0.069463[/C][C]-0.4762[/C][C]0.318064[/C][/ROW]
[ROW][C]35[/C][C]0.015217[/C][C]0.1043[/C][C]0.45868[/C][/ROW]
[ROW][C]36[/C][C]0.047402[/C][C]0.325[/C][C]0.373321[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61438&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61438&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
1-0.037036-0.25390.400338
2-0.166434-1.1410.129822
3-0.13391-0.9180.181642
4-0.055739-0.38210.352043
50.2556731.75280.043078
60.0956730.65590.257543
7-0.242441-1.66210.051576
8-0.074485-0.51060.305996
90.0777350.53290.298299
100.0822130.56360.287845
110.2655761.82070.037511
12-0.425654-2.91810.002694
130.0262680.18010.428929
140.1700851.1660.124739
150.0061640.04230.483235
160.0843710.57840.282871
17-0.170319-1.16770.124418
18-0.184804-1.2670.105707
190.1001380.68650.247881
200.2015641.38190.086775
210.0497420.3410.367307
220.0083130.0570.477398
23-0.200468-1.37430.087928
240.0041360.02840.488751
25-0.008912-0.06110.475772
26-0.112642-0.77220.221921
270.0448010.30710.380046
28-0.070609-0.48410.315291
290.0334240.22910.409875
300.0028070.01920.492363
310.0716630.49130.312752
32-0.070488-0.48320.315583
33-0.035724-0.24490.403795
34-0.069463-0.47620.318064
350.0152170.10430.45868
360.0474020.3250.373321






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.037036-0.25390.400338
2-0.168036-1.1520.127574
3-0.151823-1.04080.151636
4-0.10509-0.72050.237405
50.2077121.4240.080526
60.0892180.61160.27186
7-0.194153-1.3310.094797
8-0.027688-0.18980.425134
90.0795330.54520.294081
10-0.009598-0.06580.473907
110.238891.63770.054077
12-0.36345-2.49170.00815
130.1882841.29080.101541
140.0918680.62980.265932
15-0.091741-0.62890.266215
160.0355430.24370.404274
17-0.051951-0.35620.361657
18-0.077713-0.53280.29835
19-0.088411-0.60610.273677
200.1715961.17640.122679
210.1184380.8120.21045
22-0.028929-0.19830.421823
230.1105530.75790.226143
24-0.261778-1.79470.03957
25-0.112094-0.76850.223024
26-0.098299-0.67390.251837
27-0.048007-0.32910.371764
280.0477210.32720.372502
290.0381260.26140.397472
30-0.122461-0.83960.202705
310.1076290.73790.232131
32-0.008252-0.05660.477562
33-0.083366-0.57150.285182
34-0.137559-0.94310.175237
350.0435720.29870.383238
36-0.053114-0.36410.358696

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.037036 & -0.2539 & 0.400338 \tabularnewline
2 & -0.168036 & -1.152 & 0.127574 \tabularnewline
3 & -0.151823 & -1.0408 & 0.151636 \tabularnewline
4 & -0.10509 & -0.7205 & 0.237405 \tabularnewline
5 & 0.207712 & 1.424 & 0.080526 \tabularnewline
6 & 0.089218 & 0.6116 & 0.27186 \tabularnewline
7 & -0.194153 & -1.331 & 0.094797 \tabularnewline
8 & -0.027688 & -0.1898 & 0.425134 \tabularnewline
9 & 0.079533 & 0.5452 & 0.294081 \tabularnewline
10 & -0.009598 & -0.0658 & 0.473907 \tabularnewline
11 & 0.23889 & 1.6377 & 0.054077 \tabularnewline
12 & -0.36345 & -2.4917 & 0.00815 \tabularnewline
13 & 0.188284 & 1.2908 & 0.101541 \tabularnewline
14 & 0.091868 & 0.6298 & 0.265932 \tabularnewline
15 & -0.091741 & -0.6289 & 0.266215 \tabularnewline
16 & 0.035543 & 0.2437 & 0.404274 \tabularnewline
17 & -0.051951 & -0.3562 & 0.361657 \tabularnewline
18 & -0.077713 & -0.5328 & 0.29835 \tabularnewline
19 & -0.088411 & -0.6061 & 0.273677 \tabularnewline
20 & 0.171596 & 1.1764 & 0.122679 \tabularnewline
21 & 0.118438 & 0.812 & 0.21045 \tabularnewline
22 & -0.028929 & -0.1983 & 0.421823 \tabularnewline
23 & 0.110553 & 0.7579 & 0.226143 \tabularnewline
24 & -0.261778 & -1.7947 & 0.03957 \tabularnewline
25 & -0.112094 & -0.7685 & 0.223024 \tabularnewline
26 & -0.098299 & -0.6739 & 0.251837 \tabularnewline
27 & -0.048007 & -0.3291 & 0.371764 \tabularnewline
28 & 0.047721 & 0.3272 & 0.372502 \tabularnewline
29 & 0.038126 & 0.2614 & 0.397472 \tabularnewline
30 & -0.122461 & -0.8396 & 0.202705 \tabularnewline
31 & 0.107629 & 0.7379 & 0.232131 \tabularnewline
32 & -0.008252 & -0.0566 & 0.477562 \tabularnewline
33 & -0.083366 & -0.5715 & 0.285182 \tabularnewline
34 & -0.137559 & -0.9431 & 0.175237 \tabularnewline
35 & 0.043572 & 0.2987 & 0.383238 \tabularnewline
36 & -0.053114 & -0.3641 & 0.358696 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61438&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]-0.037036[/C][C]-0.2539[/C][C]0.400338[/C][/ROW]
[ROW][C]2[/C][C]-0.168036[/C][C]-1.152[/C][C]0.127574[/C][/ROW]
[ROW][C]3[/C][C]-0.151823[/C][C]-1.0408[/C][C]0.151636[/C][/ROW]
[ROW][C]4[/C][C]-0.10509[/C][C]-0.7205[/C][C]0.237405[/C][/ROW]
[ROW][C]5[/C][C]0.207712[/C][C]1.424[/C][C]0.080526[/C][/ROW]
[ROW][C]6[/C][C]0.089218[/C][C]0.6116[/C][C]0.27186[/C][/ROW]
[ROW][C]7[/C][C]-0.194153[/C][C]-1.331[/C][C]0.094797[/C][/ROW]
[ROW][C]8[/C][C]-0.027688[/C][C]-0.1898[/C][C]0.425134[/C][/ROW]
[ROW][C]9[/C][C]0.079533[/C][C]0.5452[/C][C]0.294081[/C][/ROW]
[ROW][C]10[/C][C]-0.009598[/C][C]-0.0658[/C][C]0.473907[/C][/ROW]
[ROW][C]11[/C][C]0.23889[/C][C]1.6377[/C][C]0.054077[/C][/ROW]
[ROW][C]12[/C][C]-0.36345[/C][C]-2.4917[/C][C]0.00815[/C][/ROW]
[ROW][C]13[/C][C]0.188284[/C][C]1.2908[/C][C]0.101541[/C][/ROW]
[ROW][C]14[/C][C]0.091868[/C][C]0.6298[/C][C]0.265932[/C][/ROW]
[ROW][C]15[/C][C]-0.091741[/C][C]-0.6289[/C][C]0.266215[/C][/ROW]
[ROW][C]16[/C][C]0.035543[/C][C]0.2437[/C][C]0.404274[/C][/ROW]
[ROW][C]17[/C][C]-0.051951[/C][C]-0.3562[/C][C]0.361657[/C][/ROW]
[ROW][C]18[/C][C]-0.077713[/C][C]-0.5328[/C][C]0.29835[/C][/ROW]
[ROW][C]19[/C][C]-0.088411[/C][C]-0.6061[/C][C]0.273677[/C][/ROW]
[ROW][C]20[/C][C]0.171596[/C][C]1.1764[/C][C]0.122679[/C][/ROW]
[ROW][C]21[/C][C]0.118438[/C][C]0.812[/C][C]0.21045[/C][/ROW]
[ROW][C]22[/C][C]-0.028929[/C][C]-0.1983[/C][C]0.421823[/C][/ROW]
[ROW][C]23[/C][C]0.110553[/C][C]0.7579[/C][C]0.226143[/C][/ROW]
[ROW][C]24[/C][C]-0.261778[/C][C]-1.7947[/C][C]0.03957[/C][/ROW]
[ROW][C]25[/C][C]-0.112094[/C][C]-0.7685[/C][C]0.223024[/C][/ROW]
[ROW][C]26[/C][C]-0.098299[/C][C]-0.6739[/C][C]0.251837[/C][/ROW]
[ROW][C]27[/C][C]-0.048007[/C][C]-0.3291[/C][C]0.371764[/C][/ROW]
[ROW][C]28[/C][C]0.047721[/C][C]0.3272[/C][C]0.372502[/C][/ROW]
[ROW][C]29[/C][C]0.038126[/C][C]0.2614[/C][C]0.397472[/C][/ROW]
[ROW][C]30[/C][C]-0.122461[/C][C]-0.8396[/C][C]0.202705[/C][/ROW]
[ROW][C]31[/C][C]0.107629[/C][C]0.7379[/C][C]0.232131[/C][/ROW]
[ROW][C]32[/C][C]-0.008252[/C][C]-0.0566[/C][C]0.477562[/C][/ROW]
[ROW][C]33[/C][C]-0.083366[/C][C]-0.5715[/C][C]0.285182[/C][/ROW]
[ROW][C]34[/C][C]-0.137559[/C][C]-0.9431[/C][C]0.175237[/C][/ROW]
[ROW][C]35[/C][C]0.043572[/C][C]0.2987[/C][C]0.383238[/C][/ROW]
[ROW][C]36[/C][C]-0.053114[/C][C]-0.3641[/C][C]0.358696[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61438&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61438&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
1-0.037036-0.25390.400338
2-0.168036-1.1520.127574
3-0.151823-1.04080.151636
4-0.10509-0.72050.237405
50.2077121.4240.080526
60.0892180.61160.27186
7-0.194153-1.3310.094797
8-0.027688-0.18980.425134
90.0795330.54520.294081
10-0.009598-0.06580.473907
110.238891.63770.054077
12-0.36345-2.49170.00815
130.1882841.29080.101541
140.0918680.62980.265932
15-0.091741-0.62890.266215
160.0355430.24370.404274
17-0.051951-0.35620.361657
18-0.077713-0.53280.29835
19-0.088411-0.60610.273677
200.1715961.17640.122679
210.1184380.8120.21045
22-0.028929-0.19830.421823
230.1105530.75790.226143
24-0.261778-1.79470.03957
25-0.112094-0.76850.223024
26-0.098299-0.67390.251837
27-0.048007-0.32910.371764
280.0477210.32720.372502
290.0381260.26140.397472
30-0.122461-0.83960.202705
310.1076290.73790.232131
32-0.008252-0.05660.477562
33-0.083366-0.57150.285182
34-0.137559-0.94310.175237
350.0435720.29870.383238
36-0.053114-0.36410.358696


Figures (Output of Computation)

Input Parameters & R Code

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