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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationWed, 24 Dec 2008 08:13:57 -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/2008/Dec/24/t1230131665vg00i6jejk7bvbw.htm/, Retrieved Fri, 17 May 2024 03:41:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=36610, Retrieved Fri, 17 May 2024 03:41:16 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact202

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]
F RMPD  [Spectral Analysis] [Identification an...] [2008-12-09 22:16:59] [1a689e9ccc515e1757f0522229a687e9]
-   PD    [Spectral Analysis] [Paper Cumulative ...] [2008-12-24 14:53:47] [1a689e9ccc515e1757f0522229a687e9]
-           [Spectral Analysis] [Paper Cumulative ...] [2008-12-24 14:58:31] [1a689e9ccc515e1757f0522229a687e9]
-             [Spectral Analysis] [Paper Cumulative ...] [2008-12-24 15:01:23] [1a689e9ccc515e1757f0522229a687e9]
- RM D          [Variance Reduction Matrix] [Paper Variance Re...] [2008-12-24 15:08:19] [1a689e9ccc515e1757f0522229a687e9]
- RM D            [(Partial) Autocorrelation Function] [Paper Autocorrela...] [2008-12-24 15:11:07] [1a689e9ccc515e1757f0522229a687e9]
-                     [(Partial) Autocorrelation Function] [Paper Autocorrela...] [2008-12-24 15:13:57] [74a138e5b32af267311b5ad4cd13bf7e] [Current]
- RM                    [Spectral Analysis] [Paper Cumulative ...] [2008-12-24 15:16:17] [1a689e9ccc515e1757f0522229a687e9]
-                         [Spectral Analysis] [Paper Cumulative ...] [2008-12-24 15:19:40] [1a689e9ccc515e1757f0522229a687e9]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
103.3
107.9
101
94.6
94.2
92.3
107.1
102.6
103.1
104.1
92.7
87
109.3
113.9
103.3
100.8
97.4
98.9
110.8
103.5
99.8
104.9
95.2
85.7
110
113.7
101.1
103.6
96.2
98.3
119.7
109.4
103.5
118.2
98.7
96.8
121.8
124
119.6
122.5
109.7
111.6
131.2
124.4
116.9
131.8
107.4
111
134
126.2
131.2
130.1
123.1
126.3
148.6
130.1
142.3
154.4
121.6
124.8
143.6
146.9
144.6
137.1
134.7
130.8
153.5
137.6
146.5
156.7
137.6
131.4
147.4
158.5
151.5
142.5
131.3
133.4
136.9
143.2
136.4
145.9
138.8
122.9

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=36610&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=36610&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36610&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
1-0.575819-4.85194e-06
20.0554880.46760.320769
30.1830681.54260.063692
4-0.155114-1.3070.097713
50.0584230.49230.312021
60.0758860.63940.262301
7-0.092139-0.77640.220053
8-0.129376-1.09010.139668
90.3140362.64610.00501
10-0.220474-1.85780.033676
11-0.005178-0.04360.482662
120.0570630.48080.316062
13-0.059012-0.49720.310276
140.1086350.91540.181546
15-0.049447-0.41660.339097
16-0.043712-0.36830.356865
170.0043250.03640.485516
180.1832021.54370.063555
19-0.199339-1.67970.048709
200.0567970.47860.316855
210.0997360.84040.201755
22-0.264756-2.23090.014425
230.3803393.20480.001013
24-0.299386-2.52270.006945
250.0164630.13870.445031
260.158621.33660.092818
27-0.087496-0.73730.231699
28-0.084243-0.70980.240062
290.1503921.26720.104607
30-0.12402-1.0450.149782
310.01490.12550.450223
320.1454691.22570.112172
33-0.222326-1.87340.032568
340.0853480.71920.237204
350.0757990.63870.262539
36-0.110062-0.92740.17843

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.575819 & -4.8519 & 4e-06 \tabularnewline
2 & 0.055488 & 0.4676 & 0.320769 \tabularnewline
3 & 0.183068 & 1.5426 & 0.063692 \tabularnewline
4 & -0.155114 & -1.307 & 0.097713 \tabularnewline
5 & 0.058423 & 0.4923 & 0.312021 \tabularnewline
6 & 0.075886 & 0.6394 & 0.262301 \tabularnewline
7 & -0.092139 & -0.7764 & 0.220053 \tabularnewline
8 & -0.129376 & -1.0901 & 0.139668 \tabularnewline
9 & 0.314036 & 2.6461 & 0.00501 \tabularnewline
10 & -0.220474 & -1.8578 & 0.033676 \tabularnewline
11 & -0.005178 & -0.0436 & 0.482662 \tabularnewline
12 & 0.057063 & 0.4808 & 0.316062 \tabularnewline
13 & -0.059012 & -0.4972 & 0.310276 \tabularnewline
14 & 0.108635 & 0.9154 & 0.181546 \tabularnewline
15 & -0.049447 & -0.4166 & 0.339097 \tabularnewline
16 & -0.043712 & -0.3683 & 0.356865 \tabularnewline
17 & 0.004325 & 0.0364 & 0.485516 \tabularnewline
18 & 0.183202 & 1.5437 & 0.063555 \tabularnewline
19 & -0.199339 & -1.6797 & 0.048709 \tabularnewline
20 & 0.056797 & 0.4786 & 0.316855 \tabularnewline
21 & 0.099736 & 0.8404 & 0.201755 \tabularnewline
22 & -0.264756 & -2.2309 & 0.014425 \tabularnewline
23 & 0.380339 & 3.2048 & 0.001013 \tabularnewline
24 & -0.299386 & -2.5227 & 0.006945 \tabularnewline
25 & 0.016463 & 0.1387 & 0.445031 \tabularnewline
26 & 0.15862 & 1.3366 & 0.092818 \tabularnewline
27 & -0.087496 & -0.7373 & 0.231699 \tabularnewline
28 & -0.084243 & -0.7098 & 0.240062 \tabularnewline
29 & 0.150392 & 1.2672 & 0.104607 \tabularnewline
30 & -0.12402 & -1.045 & 0.149782 \tabularnewline
31 & 0.0149 & 0.1255 & 0.450223 \tabularnewline
32 & 0.145469 & 1.2257 & 0.112172 \tabularnewline
33 & -0.222326 & -1.8734 & 0.032568 \tabularnewline
34 & 0.085348 & 0.7192 & 0.237204 \tabularnewline
35 & 0.075799 & 0.6387 & 0.262539 \tabularnewline
36 & -0.110062 & -0.9274 & 0.17843 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36610&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]-0.575819[/C][C]-4.8519[/C][C]4e-06[/C][/ROW]
[ROW][C]2[/C][C]0.055488[/C][C]0.4676[/C][C]0.320769[/C][/ROW]
[ROW][C]3[/C][C]0.183068[/C][C]1.5426[/C][C]0.063692[/C][/ROW]
[ROW][C]4[/C][C]-0.155114[/C][C]-1.307[/C][C]0.097713[/C][/ROW]
[ROW][C]5[/C][C]0.058423[/C][C]0.4923[/C][C]0.312021[/C][/ROW]
[ROW][C]6[/C][C]0.075886[/C][C]0.6394[/C][C]0.262301[/C][/ROW]
[ROW][C]7[/C][C]-0.092139[/C][C]-0.7764[/C][C]0.220053[/C][/ROW]
[ROW][C]8[/C][C]-0.129376[/C][C]-1.0901[/C][C]0.139668[/C][/ROW]
[ROW][C]9[/C][C]0.314036[/C][C]2.6461[/C][C]0.00501[/C][/ROW]
[ROW][C]10[/C][C]-0.220474[/C][C]-1.8578[/C][C]0.033676[/C][/ROW]
[ROW][C]11[/C][C]-0.005178[/C][C]-0.0436[/C][C]0.482662[/C][/ROW]
[ROW][C]12[/C][C]0.057063[/C][C]0.4808[/C][C]0.316062[/C][/ROW]
[ROW][C]13[/C][C]-0.059012[/C][C]-0.4972[/C][C]0.310276[/C][/ROW]
[ROW][C]14[/C][C]0.108635[/C][C]0.9154[/C][C]0.181546[/C][/ROW]
[ROW][C]15[/C][C]-0.049447[/C][C]-0.4166[/C][C]0.339097[/C][/ROW]
[ROW][C]16[/C][C]-0.043712[/C][C]-0.3683[/C][C]0.356865[/C][/ROW]
[ROW][C]17[/C][C]0.004325[/C][C]0.0364[/C][C]0.485516[/C][/ROW]
[ROW][C]18[/C][C]0.183202[/C][C]1.5437[/C][C]0.063555[/C][/ROW]
[ROW][C]19[/C][C]-0.199339[/C][C]-1.6797[/C][C]0.048709[/C][/ROW]
[ROW][C]20[/C][C]0.056797[/C][C]0.4786[/C][C]0.316855[/C][/ROW]
[ROW][C]21[/C][C]0.099736[/C][C]0.8404[/C][C]0.201755[/C][/ROW]
[ROW][C]22[/C][C]-0.264756[/C][C]-2.2309[/C][C]0.014425[/C][/ROW]
[ROW][C]23[/C][C]0.380339[/C][C]3.2048[/C][C]0.001013[/C][/ROW]
[ROW][C]24[/C][C]-0.299386[/C][C]-2.5227[/C][C]0.006945[/C][/ROW]
[ROW][C]25[/C][C]0.016463[/C][C]0.1387[/C][C]0.445031[/C][/ROW]
[ROW][C]26[/C][C]0.15862[/C][C]1.3366[/C][C]0.092818[/C][/ROW]
[ROW][C]27[/C][C]-0.087496[/C][C]-0.7373[/C][C]0.231699[/C][/ROW]
[ROW][C]28[/C][C]-0.084243[/C][C]-0.7098[/C][C]0.240062[/C][/ROW]
[ROW][C]29[/C][C]0.150392[/C][C]1.2672[/C][C]0.104607[/C][/ROW]
[ROW][C]30[/C][C]-0.12402[/C][C]-1.045[/C][C]0.149782[/C][/ROW]
[ROW][C]31[/C][C]0.0149[/C][C]0.1255[/C][C]0.450223[/C][/ROW]
[ROW][C]32[/C][C]0.145469[/C][C]1.2257[/C][C]0.112172[/C][/ROW]
[ROW][C]33[/C][C]-0.222326[/C][C]-1.8734[/C][C]0.032568[/C][/ROW]
[ROW][C]34[/C][C]0.085348[/C][C]0.7192[/C][C]0.237204[/C][/ROW]
[ROW][C]35[/C][C]0.075799[/C][C]0.6387[/C][C]0.262539[/C][/ROW]
[ROW][C]36[/C][C]-0.110062[/C][C]-0.9274[/C][C]0.17843[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36610&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36610&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
1-0.575819-4.85194e-06
20.0554880.46760.320769
30.1830681.54260.063692
4-0.155114-1.3070.097713
50.0584230.49230.312021
60.0758860.63940.262301
7-0.092139-0.77640.220053
8-0.129376-1.09010.139668
90.3140362.64610.00501
10-0.220474-1.85780.033676
11-0.005178-0.04360.482662
120.0570630.48080.316062
13-0.059012-0.49720.310276
140.1086350.91540.181546
15-0.049447-0.41660.339097
16-0.043712-0.36830.356865
170.0043250.03640.485516
180.1832021.54370.063555
19-0.199339-1.67970.048709
200.0567970.47860.316855
210.0997360.84040.201755
22-0.264756-2.23090.014425
230.3803393.20480.001013
24-0.299386-2.52270.006945
250.0164630.13870.445031
260.158621.33660.092818
27-0.087496-0.73730.231699
28-0.084243-0.70980.240062
290.1503921.26720.104607
30-0.12402-1.0450.149782
310.01490.12550.450223
320.1454691.22570.112172
33-0.222326-1.87340.032568
340.0853480.71920.237204
350.0757990.63870.262539
36-0.110062-0.92740.17843






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.575819-4.85194e-06
2-0.413026-3.48020.00043
3-0.017338-0.14610.442132
40.0160.13480.446569
50.0316490.26670.395243
60.1317161.10990.135402
70.0861330.72580.235182
8-0.281866-2.3750.010126
90.0437030.36820.356892
100.0865640.72940.234079
11-0.017039-0.14360.443123
12-0.15605-1.31490.096387
13-0.093739-0.78990.21612
140.1332641.12290.132631
150.1064620.89710.186359
16-0.003452-0.02910.488438
17-0.038666-0.32580.372766
180.1999121.68450.048239
190.0420550.35440.362059
20-0.089416-0.75340.226841
210.1099640.92660.178644
22-0.187669-1.58130.059124
230.0893270.75270.227064
24-0.07506-0.63250.264555
25-0.058364-0.49180.312195
260.0833270.70210.242447
270.0385250.32460.373211
28-0.122428-1.03160.152882
290.0505080.42560.335847
30-0.034184-0.2880.387076
310.0349570.29460.384596
32-0.053083-0.44730.328015
33-0.09029-0.76080.224648
34-0.044617-0.37590.354038
35-0.011881-0.10010.460271
36-0.095577-0.80530.211655

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.575819 & -4.8519 & 4e-06 \tabularnewline
2 & -0.413026 & -3.4802 & 0.00043 \tabularnewline
3 & -0.017338 & -0.1461 & 0.442132 \tabularnewline
4 & 0.016 & 0.1348 & 0.446569 \tabularnewline
5 & 0.031649 & 0.2667 & 0.395243 \tabularnewline
6 & 0.131716 & 1.1099 & 0.135402 \tabularnewline
7 & 0.086133 & 0.7258 & 0.235182 \tabularnewline
8 & -0.281866 & -2.375 & 0.010126 \tabularnewline
9 & 0.043703 & 0.3682 & 0.356892 \tabularnewline
10 & 0.086564 & 0.7294 & 0.234079 \tabularnewline
11 & -0.017039 & -0.1436 & 0.443123 \tabularnewline
12 & -0.15605 & -1.3149 & 0.096387 \tabularnewline
13 & -0.093739 & -0.7899 & 0.21612 \tabularnewline
14 & 0.133264 & 1.1229 & 0.132631 \tabularnewline
15 & 0.106462 & 0.8971 & 0.186359 \tabularnewline
16 & -0.003452 & -0.0291 & 0.488438 \tabularnewline
17 & -0.038666 & -0.3258 & 0.372766 \tabularnewline
18 & 0.199912 & 1.6845 & 0.048239 \tabularnewline
19 & 0.042055 & 0.3544 & 0.362059 \tabularnewline
20 & -0.089416 & -0.7534 & 0.226841 \tabularnewline
21 & 0.109964 & 0.9266 & 0.178644 \tabularnewline
22 & -0.187669 & -1.5813 & 0.059124 \tabularnewline
23 & 0.089327 & 0.7527 & 0.227064 \tabularnewline
24 & -0.07506 & -0.6325 & 0.264555 \tabularnewline
25 & -0.058364 & -0.4918 & 0.312195 \tabularnewline
26 & 0.083327 & 0.7021 & 0.242447 \tabularnewline
27 & 0.038525 & 0.3246 & 0.373211 \tabularnewline
28 & -0.122428 & -1.0316 & 0.152882 \tabularnewline
29 & 0.050508 & 0.4256 & 0.335847 \tabularnewline
30 & -0.034184 & -0.288 & 0.387076 \tabularnewline
31 & 0.034957 & 0.2946 & 0.384596 \tabularnewline
32 & -0.053083 & -0.4473 & 0.328015 \tabularnewline
33 & -0.09029 & -0.7608 & 0.224648 \tabularnewline
34 & -0.044617 & -0.3759 & 0.354038 \tabularnewline
35 & -0.011881 & -0.1001 & 0.460271 \tabularnewline
36 & -0.095577 & -0.8053 & 0.211655 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36610&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]-0.575819[/C][C]-4.8519[/C][C]4e-06[/C][/ROW]
[ROW][C]2[/C][C]-0.413026[/C][C]-3.4802[/C][C]0.00043[/C][/ROW]
[ROW][C]3[/C][C]-0.017338[/C][C]-0.1461[/C][C]0.442132[/C][/ROW]
[ROW][C]4[/C][C]0.016[/C][C]0.1348[/C][C]0.446569[/C][/ROW]
[ROW][C]5[/C][C]0.031649[/C][C]0.2667[/C][C]0.395243[/C][/ROW]
[ROW][C]6[/C][C]0.131716[/C][C]1.1099[/C][C]0.135402[/C][/ROW]
[ROW][C]7[/C][C]0.086133[/C][C]0.7258[/C][C]0.235182[/C][/ROW]
[ROW][C]8[/C][C]-0.281866[/C][C]-2.375[/C][C]0.010126[/C][/ROW]
[ROW][C]9[/C][C]0.043703[/C][C]0.3682[/C][C]0.356892[/C][/ROW]
[ROW][C]10[/C][C]0.086564[/C][C]0.7294[/C][C]0.234079[/C][/ROW]
[ROW][C]11[/C][C]-0.017039[/C][C]-0.1436[/C][C]0.443123[/C][/ROW]
[ROW][C]12[/C][C]-0.15605[/C][C]-1.3149[/C][C]0.096387[/C][/ROW]
[ROW][C]13[/C][C]-0.093739[/C][C]-0.7899[/C][C]0.21612[/C][/ROW]
[ROW][C]14[/C][C]0.133264[/C][C]1.1229[/C][C]0.132631[/C][/ROW]
[ROW][C]15[/C][C]0.106462[/C][C]0.8971[/C][C]0.186359[/C][/ROW]
[ROW][C]16[/C][C]-0.003452[/C][C]-0.0291[/C][C]0.488438[/C][/ROW]
[ROW][C]17[/C][C]-0.038666[/C][C]-0.3258[/C][C]0.372766[/C][/ROW]
[ROW][C]18[/C][C]0.199912[/C][C]1.6845[/C][C]0.048239[/C][/ROW]
[ROW][C]19[/C][C]0.042055[/C][C]0.3544[/C][C]0.362059[/C][/ROW]
[ROW][C]20[/C][C]-0.089416[/C][C]-0.7534[/C][C]0.226841[/C][/ROW]
[ROW][C]21[/C][C]0.109964[/C][C]0.9266[/C][C]0.178644[/C][/ROW]
[ROW][C]22[/C][C]-0.187669[/C][C]-1.5813[/C][C]0.059124[/C][/ROW]
[ROW][C]23[/C][C]0.089327[/C][C]0.7527[/C][C]0.227064[/C][/ROW]
[ROW][C]24[/C][C]-0.07506[/C][C]-0.6325[/C][C]0.264555[/C][/ROW]
[ROW][C]25[/C][C]-0.058364[/C][C]-0.4918[/C][C]0.312195[/C][/ROW]
[ROW][C]26[/C][C]0.083327[/C][C]0.7021[/C][C]0.242447[/C][/ROW]
[ROW][C]27[/C][C]0.038525[/C][C]0.3246[/C][C]0.373211[/C][/ROW]
[ROW][C]28[/C][C]-0.122428[/C][C]-1.0316[/C][C]0.152882[/C][/ROW]
[ROW][C]29[/C][C]0.050508[/C][C]0.4256[/C][C]0.335847[/C][/ROW]
[ROW][C]30[/C][C]-0.034184[/C][C]-0.288[/C][C]0.387076[/C][/ROW]
[ROW][C]31[/C][C]0.034957[/C][C]0.2946[/C][C]0.384596[/C][/ROW]
[ROW][C]32[/C][C]-0.053083[/C][C]-0.4473[/C][C]0.328015[/C][/ROW]
[ROW][C]33[/C][C]-0.09029[/C][C]-0.7608[/C][C]0.224648[/C][/ROW]
[ROW][C]34[/C][C]-0.044617[/C][C]-0.3759[/C][C]0.354038[/C][/ROW]
[ROW][C]35[/C][C]-0.011881[/C][C]-0.1001[/C][C]0.460271[/C][/ROW]
[ROW][C]36[/C][C]-0.095577[/C][C]-0.8053[/C][C]0.211655[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36610&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36610&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
1-0.575819-4.85194e-06
2-0.413026-3.48020.00043
3-0.017338-0.14610.442132
40.0160.13480.446569
50.0316490.26670.395243
60.1317161.10990.135402
70.0861330.72580.235182
8-0.281866-2.3750.010126
90.0437030.36820.356892
100.0865640.72940.234079
11-0.017039-0.14360.443123
12-0.15605-1.31490.096387
13-0.093739-0.78990.21612
140.1332641.12290.132631
150.1064620.89710.186359
16-0.003452-0.02910.488438
17-0.038666-0.32580.372766
180.1999121.68450.048239
190.0420550.35440.362059
20-0.089416-0.75340.226841
210.1099640.92660.178644
22-0.187669-1.58130.059124
230.0893270.75270.227064
24-0.07506-0.63250.264555
25-0.058364-0.49180.312195
260.0833270.70210.242447
270.0385250.32460.373211
28-0.122428-1.03160.152882
290.0505080.42560.335847
30-0.034184-0.2880.387076
310.0349570.29460.384596
32-0.053083-0.44730.328015
33-0.09029-0.76080.224648
34-0.044617-0.37590.354038
35-0.011881-0.10010.460271
36-0.095577-0.80530.211655


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ;
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 (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='lags',ylab='ACF')
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')