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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 computationMon, 19 Dec 2011 13:47:21 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/19/t1324320491nm368wrilcm41g4.htm/, Retrieved Wed, 15 May 2024 18:38:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=157613, Retrieved Wed, 15 May 2024 18:38:01 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact183

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]
- RMP   [(Partial) Autocorrelation Function] [Unemployment] [2010-11-29 09:09:37] [b98453cac15ba1066b407e146608df68]
- R PD    [(Partial) Autocorrelation Function] [autocorrelatie d=...] [2011-12-07 13:53:53] [141ef847e2c5f8e947fe4eabcb0cf143]
- RM        [Spectral Analysis] [CP D=1] [2011-12-07 14:00:06] [141ef847e2c5f8e947fe4eabcb0cf143]
- RM D        [Variance Reduction Matrix] [VRM] [2011-12-07 14:12:57] [141ef847e2c5f8e947fe4eabcb0cf143]
- RMPD            [(Partial) Autocorrelation Function] [ACF] [2011-12-19 18:47:21] [1a4698f17d8e7f554418314cf0e4bd67] [Current]
- R P               [(Partial) Autocorrelation Function] [AFC d=1 D=1] [2011-12-19 19:04:58] [141ef847e2c5f8e947fe4eabcb0cf143]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
114.7
108
101.3
108.4
105.6
120.4
107.6
111.4
122.1
104.8
103.2
112.3
123.1
115.5
106.3
119.9
119.5
120.9
127.5
116.6
126.7
110.6
100.4
125.2
125
105.2
102.7
94.2
97
111.1
102
97.3
109.8
98.9
93.2
115.2
115
107
104.1
106
110.8
127.8
116.9
113.8
131.6
106.1
107.2
127.4
123
121.8
117.6
118.4
121.8
141.9
122.1
132.2
131.6
108.8
120.4
134.7

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'AstonUniversity' @ aston.wessa.net

\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 & 'AstonUniversity' @ aston.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=157613&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]'AstonUniversity' @ aston.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=157613&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=157613&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'AstonUniversity' @ aston.wessa.net






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.3926693.04160.001744
20.1770621.37150.087661
30.425373.29490.000828
40.2419571.87420.032888
50.2870152.22320.01499
60.356412.76070.00382
70.1134890.87910.191431
80.0893850.69240.245688
90.0252670.19570.422745
10-0.237506-1.83970.035379
110.0079610.06170.475516
120.2378791.84260.035164
13-0.208728-1.61680.055584
14-0.307307-2.38040.010244
15-0.132166-1.02380.15503
16-0.258807-2.00470.024756
17-0.130749-1.01280.157616
18-0.040431-0.31320.377615
19-0.22425-1.7370.043757
20-0.14801-1.14650.128073
21-0.175278-1.35770.089822
22-0.357056-2.76570.003768
23-0.059741-0.46280.322608
240.1051310.81430.209335
25-0.168474-1.3050.098439
26-0.141589-1.09670.138567
27-0.075285-0.58320.280988
28-0.108847-0.84310.201254
290.0552720.42810.335042
300.0532410.41240.340758
31-0.020594-0.15950.436899
320.0691390.53550.297125
330.0194020.15030.440521
34-0.051284-0.39720.346298
350.1601031.24020.109873
360.204981.58780.058797

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.392669 & 3.0416 & 0.001744 \tabularnewline
2 & 0.177062 & 1.3715 & 0.087661 \tabularnewline
3 & 0.42537 & 3.2949 & 0.000828 \tabularnewline
4 & 0.241957 & 1.8742 & 0.032888 \tabularnewline
5 & 0.287015 & 2.2232 & 0.01499 \tabularnewline
6 & 0.35641 & 2.7607 & 0.00382 \tabularnewline
7 & 0.113489 & 0.8791 & 0.191431 \tabularnewline
8 & 0.089385 & 0.6924 & 0.245688 \tabularnewline
9 & 0.025267 & 0.1957 & 0.422745 \tabularnewline
10 & -0.237506 & -1.8397 & 0.035379 \tabularnewline
11 & 0.007961 & 0.0617 & 0.475516 \tabularnewline
12 & 0.237879 & 1.8426 & 0.035164 \tabularnewline
13 & -0.208728 & -1.6168 & 0.055584 \tabularnewline
14 & -0.307307 & -2.3804 & 0.010244 \tabularnewline
15 & -0.132166 & -1.0238 & 0.15503 \tabularnewline
16 & -0.258807 & -2.0047 & 0.024756 \tabularnewline
17 & -0.130749 & -1.0128 & 0.157616 \tabularnewline
18 & -0.040431 & -0.3132 & 0.377615 \tabularnewline
19 & -0.22425 & -1.737 & 0.043757 \tabularnewline
20 & -0.14801 & -1.1465 & 0.128073 \tabularnewline
21 & -0.175278 & -1.3577 & 0.089822 \tabularnewline
22 & -0.357056 & -2.7657 & 0.003768 \tabularnewline
23 & -0.059741 & -0.4628 & 0.322608 \tabularnewline
24 & 0.105131 & 0.8143 & 0.209335 \tabularnewline
25 & -0.168474 & -1.305 & 0.098439 \tabularnewline
26 & -0.141589 & -1.0967 & 0.138567 \tabularnewline
27 & -0.075285 & -0.5832 & 0.280988 \tabularnewline
28 & -0.108847 & -0.8431 & 0.201254 \tabularnewline
29 & 0.055272 & 0.4281 & 0.335042 \tabularnewline
30 & 0.053241 & 0.4124 & 0.340758 \tabularnewline
31 & -0.020594 & -0.1595 & 0.436899 \tabularnewline
32 & 0.069139 & 0.5355 & 0.297125 \tabularnewline
33 & 0.019402 & 0.1503 & 0.440521 \tabularnewline
34 & -0.051284 & -0.3972 & 0.346298 \tabularnewline
35 & 0.160103 & 1.2402 & 0.109873 \tabularnewline
36 & 0.20498 & 1.5878 & 0.058797 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=157613&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]0.392669[/C][C]3.0416[/C][C]0.001744[/C][/ROW]
[ROW][C]2[/C][C]0.177062[/C][C]1.3715[/C][C]0.087661[/C][/ROW]
[ROW][C]3[/C][C]0.42537[/C][C]3.2949[/C][C]0.000828[/C][/ROW]
[ROW][C]4[/C][C]0.241957[/C][C]1.8742[/C][C]0.032888[/C][/ROW]
[ROW][C]5[/C][C]0.287015[/C][C]2.2232[/C][C]0.01499[/C][/ROW]
[ROW][C]6[/C][C]0.35641[/C][C]2.7607[/C][C]0.00382[/C][/ROW]
[ROW][C]7[/C][C]0.113489[/C][C]0.8791[/C][C]0.191431[/C][/ROW]
[ROW][C]8[/C][C]0.089385[/C][C]0.6924[/C][C]0.245688[/C][/ROW]
[ROW][C]9[/C][C]0.025267[/C][C]0.1957[/C][C]0.422745[/C][/ROW]
[ROW][C]10[/C][C]-0.237506[/C][C]-1.8397[/C][C]0.035379[/C][/ROW]
[ROW][C]11[/C][C]0.007961[/C][C]0.0617[/C][C]0.475516[/C][/ROW]
[ROW][C]12[/C][C]0.237879[/C][C]1.8426[/C][C]0.035164[/C][/ROW]
[ROW][C]13[/C][C]-0.208728[/C][C]-1.6168[/C][C]0.055584[/C][/ROW]
[ROW][C]14[/C][C]-0.307307[/C][C]-2.3804[/C][C]0.010244[/C][/ROW]
[ROW][C]15[/C][C]-0.132166[/C][C]-1.0238[/C][C]0.15503[/C][/ROW]
[ROW][C]16[/C][C]-0.258807[/C][C]-2.0047[/C][C]0.024756[/C][/ROW]
[ROW][C]17[/C][C]-0.130749[/C][C]-1.0128[/C][C]0.157616[/C][/ROW]
[ROW][C]18[/C][C]-0.040431[/C][C]-0.3132[/C][C]0.377615[/C][/ROW]
[ROW][C]19[/C][C]-0.22425[/C][C]-1.737[/C][C]0.043757[/C][/ROW]
[ROW][C]20[/C][C]-0.14801[/C][C]-1.1465[/C][C]0.128073[/C][/ROW]
[ROW][C]21[/C][C]-0.175278[/C][C]-1.3577[/C][C]0.089822[/C][/ROW]
[ROW][C]22[/C][C]-0.357056[/C][C]-2.7657[/C][C]0.003768[/C][/ROW]
[ROW][C]23[/C][C]-0.059741[/C][C]-0.4628[/C][C]0.322608[/C][/ROW]
[ROW][C]24[/C][C]0.105131[/C][C]0.8143[/C][C]0.209335[/C][/ROW]
[ROW][C]25[/C][C]-0.168474[/C][C]-1.305[/C][C]0.098439[/C][/ROW]
[ROW][C]26[/C][C]-0.141589[/C][C]-1.0967[/C][C]0.138567[/C][/ROW]
[ROW][C]27[/C][C]-0.075285[/C][C]-0.5832[/C][C]0.280988[/C][/ROW]
[ROW][C]28[/C][C]-0.108847[/C][C]-0.8431[/C][C]0.201254[/C][/ROW]
[ROW][C]29[/C][C]0.055272[/C][C]0.4281[/C][C]0.335042[/C][/ROW]
[ROW][C]30[/C][C]0.053241[/C][C]0.4124[/C][C]0.340758[/C][/ROW]
[ROW][C]31[/C][C]-0.020594[/C][C]-0.1595[/C][C]0.436899[/C][/ROW]
[ROW][C]32[/C][C]0.069139[/C][C]0.5355[/C][C]0.297125[/C][/ROW]
[ROW][C]33[/C][C]0.019402[/C][C]0.1503[/C][C]0.440521[/C][/ROW]
[ROW][C]34[/C][C]-0.051284[/C][C]-0.3972[/C][C]0.346298[/C][/ROW]
[ROW][C]35[/C][C]0.160103[/C][C]1.2402[/C][C]0.109873[/C][/ROW]
[ROW][C]36[/C][C]0.20498[/C][C]1.5878[/C][C]0.058797[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=157613&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=157613&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
10.3926693.04160.001744
20.1770621.37150.087661
30.425373.29490.000828
40.2419571.87420.032888
50.2870152.22320.01499
60.356412.76070.00382
70.1134890.87910.191431
80.0893850.69240.245688
90.0252670.19570.422745
10-0.237506-1.83970.035379
110.0079610.06170.475516
120.2378791.84260.035164
13-0.208728-1.61680.055584
14-0.307307-2.38040.010244
15-0.132166-1.02380.15503
16-0.258807-2.00470.024756
17-0.130749-1.01280.157616
18-0.040431-0.31320.377615
19-0.22425-1.7370.043757
20-0.14801-1.14650.128073
21-0.175278-1.35770.089822
22-0.357056-2.76570.003768
23-0.059741-0.46280.322608
240.1051310.81430.209335
25-0.168474-1.3050.098439
26-0.141589-1.09670.138567
27-0.075285-0.58320.280988
28-0.108847-0.84310.201254
290.0552720.42810.335042
300.0532410.41240.340758
31-0.020594-0.15950.436899
320.0691390.53550.297125
330.0194020.15030.440521
34-0.051284-0.39720.346298
350.1601031.24020.109873
360.204981.58780.058797






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3926693.04160.001744
20.0270430.20950.417394
30.4106813.18110.001162
4-0.076996-0.59640.276574
50.2885742.23530.014566
60.0247990.19210.424158
7-0.082807-0.64140.261845
8-0.085313-0.66080.255625
9-0.244348-1.89270.031612
10-0.374665-2.90210.002588
110.1313691.01760.156481
120.334412.59030.006009
13-0.207001-1.60340.057047
14-0.181218-1.40370.082781
15-0.038871-0.30110.382193
16-0.028294-0.21920.413633
170.0567750.43980.330839
180.0631990.48950.313123
19-0.031576-0.24460.403805
20-0.015391-0.11920.45275
210.0080690.06250.475186
22-0.139691-1.0820.141781
23-0.088966-0.68910.246699
240.0352570.27310.392858
250.1017480.78810.216861
260.0503380.38990.348989
27-0.068978-0.53430.297554
280.0315360.24430.403926
29-0.043106-0.33390.369811
30-0.067818-0.52530.300649
310.0385490.29860.38314
32-0.011253-0.08720.465414
330.1053170.81580.208926
340.1165630.90290.185097
35-0.001184-0.00920.496355
36-0.144757-1.12130.133317

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.392669 & 3.0416 & 0.001744 \tabularnewline
2 & 0.027043 & 0.2095 & 0.417394 \tabularnewline
3 & 0.410681 & 3.1811 & 0.001162 \tabularnewline
4 & -0.076996 & -0.5964 & 0.276574 \tabularnewline
5 & 0.288574 & 2.2353 & 0.014566 \tabularnewline
6 & 0.024799 & 0.1921 & 0.424158 \tabularnewline
7 & -0.082807 & -0.6414 & 0.261845 \tabularnewline
8 & -0.085313 & -0.6608 & 0.255625 \tabularnewline
9 & -0.244348 & -1.8927 & 0.031612 \tabularnewline
10 & -0.374665 & -2.9021 & 0.002588 \tabularnewline
11 & 0.131369 & 1.0176 & 0.156481 \tabularnewline
12 & 0.33441 & 2.5903 & 0.006009 \tabularnewline
13 & -0.207001 & -1.6034 & 0.057047 \tabularnewline
14 & -0.181218 & -1.4037 & 0.082781 \tabularnewline
15 & -0.038871 & -0.3011 & 0.382193 \tabularnewline
16 & -0.028294 & -0.2192 & 0.413633 \tabularnewline
17 & 0.056775 & 0.4398 & 0.330839 \tabularnewline
18 & 0.063199 & 0.4895 & 0.313123 \tabularnewline
19 & -0.031576 & -0.2446 & 0.403805 \tabularnewline
20 & -0.015391 & -0.1192 & 0.45275 \tabularnewline
21 & 0.008069 & 0.0625 & 0.475186 \tabularnewline
22 & -0.139691 & -1.082 & 0.141781 \tabularnewline
23 & -0.088966 & -0.6891 & 0.246699 \tabularnewline
24 & 0.035257 & 0.2731 & 0.392858 \tabularnewline
25 & 0.101748 & 0.7881 & 0.216861 \tabularnewline
26 & 0.050338 & 0.3899 & 0.348989 \tabularnewline
27 & -0.068978 & -0.5343 & 0.297554 \tabularnewline
28 & 0.031536 & 0.2443 & 0.403926 \tabularnewline
29 & -0.043106 & -0.3339 & 0.369811 \tabularnewline
30 & -0.067818 & -0.5253 & 0.300649 \tabularnewline
31 & 0.038549 & 0.2986 & 0.38314 \tabularnewline
32 & -0.011253 & -0.0872 & 0.465414 \tabularnewline
33 & 0.105317 & 0.8158 & 0.208926 \tabularnewline
34 & 0.116563 & 0.9029 & 0.185097 \tabularnewline
35 & -0.001184 & -0.0092 & 0.496355 \tabularnewline
36 & -0.144757 & -1.1213 & 0.133317 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=157613&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]0.392669[/C][C]3.0416[/C][C]0.001744[/C][/ROW]
[ROW][C]2[/C][C]0.027043[/C][C]0.2095[/C][C]0.417394[/C][/ROW]
[ROW][C]3[/C][C]0.410681[/C][C]3.1811[/C][C]0.001162[/C][/ROW]
[ROW][C]4[/C][C]-0.076996[/C][C]-0.5964[/C][C]0.276574[/C][/ROW]
[ROW][C]5[/C][C]0.288574[/C][C]2.2353[/C][C]0.014566[/C][/ROW]
[ROW][C]6[/C][C]0.024799[/C][C]0.1921[/C][C]0.424158[/C][/ROW]
[ROW][C]7[/C][C]-0.082807[/C][C]-0.6414[/C][C]0.261845[/C][/ROW]
[ROW][C]8[/C][C]-0.085313[/C][C]-0.6608[/C][C]0.255625[/C][/ROW]
[ROW][C]9[/C][C]-0.244348[/C][C]-1.8927[/C][C]0.031612[/C][/ROW]
[ROW][C]10[/C][C]-0.374665[/C][C]-2.9021[/C][C]0.002588[/C][/ROW]
[ROW][C]11[/C][C]0.131369[/C][C]1.0176[/C][C]0.156481[/C][/ROW]
[ROW][C]12[/C][C]0.33441[/C][C]2.5903[/C][C]0.006009[/C][/ROW]
[ROW][C]13[/C][C]-0.207001[/C][C]-1.6034[/C][C]0.057047[/C][/ROW]
[ROW][C]14[/C][C]-0.181218[/C][C]-1.4037[/C][C]0.082781[/C][/ROW]
[ROW][C]15[/C][C]-0.038871[/C][C]-0.3011[/C][C]0.382193[/C][/ROW]
[ROW][C]16[/C][C]-0.028294[/C][C]-0.2192[/C][C]0.413633[/C][/ROW]
[ROW][C]17[/C][C]0.056775[/C][C]0.4398[/C][C]0.330839[/C][/ROW]
[ROW][C]18[/C][C]0.063199[/C][C]0.4895[/C][C]0.313123[/C][/ROW]
[ROW][C]19[/C][C]-0.031576[/C][C]-0.2446[/C][C]0.403805[/C][/ROW]
[ROW][C]20[/C][C]-0.015391[/C][C]-0.1192[/C][C]0.45275[/C][/ROW]
[ROW][C]21[/C][C]0.008069[/C][C]0.0625[/C][C]0.475186[/C][/ROW]
[ROW][C]22[/C][C]-0.139691[/C][C]-1.082[/C][C]0.141781[/C][/ROW]
[ROW][C]23[/C][C]-0.088966[/C][C]-0.6891[/C][C]0.246699[/C][/ROW]
[ROW][C]24[/C][C]0.035257[/C][C]0.2731[/C][C]0.392858[/C][/ROW]
[ROW][C]25[/C][C]0.101748[/C][C]0.7881[/C][C]0.216861[/C][/ROW]
[ROW][C]26[/C][C]0.050338[/C][C]0.3899[/C][C]0.348989[/C][/ROW]
[ROW][C]27[/C][C]-0.068978[/C][C]-0.5343[/C][C]0.297554[/C][/ROW]
[ROW][C]28[/C][C]0.031536[/C][C]0.2443[/C][C]0.403926[/C][/ROW]
[ROW][C]29[/C][C]-0.043106[/C][C]-0.3339[/C][C]0.369811[/C][/ROW]
[ROW][C]30[/C][C]-0.067818[/C][C]-0.5253[/C][C]0.300649[/C][/ROW]
[ROW][C]31[/C][C]0.038549[/C][C]0.2986[/C][C]0.38314[/C][/ROW]
[ROW][C]32[/C][C]-0.011253[/C][C]-0.0872[/C][C]0.465414[/C][/ROW]
[ROW][C]33[/C][C]0.105317[/C][C]0.8158[/C][C]0.208926[/C][/ROW]
[ROW][C]34[/C][C]0.116563[/C][C]0.9029[/C][C]0.185097[/C][/ROW]
[ROW][C]35[/C][C]-0.001184[/C][C]-0.0092[/C][C]0.496355[/C][/ROW]
[ROW][C]36[/C][C]-0.144757[/C][C]-1.1213[/C][C]0.133317[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=157613&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=157613&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
10.3926693.04160.001744
20.0270430.20950.417394
30.4106813.18110.001162
4-0.076996-0.59640.276574
50.2885742.23530.014566
60.0247990.19210.424158
7-0.082807-0.64140.261845
8-0.085313-0.66080.255625
9-0.244348-1.89270.031612
10-0.374665-2.90210.002588
110.1313691.01760.156481
120.334412.59030.006009
13-0.207001-1.60340.057047
14-0.181218-1.40370.082781
15-0.038871-0.30110.382193
16-0.028294-0.21920.413633
170.0567750.43980.330839
180.0631990.48950.313123
19-0.031576-0.24460.403805
20-0.015391-0.11920.45275
210.0080690.06250.475186
22-0.139691-1.0820.141781
23-0.088966-0.68910.246699
240.0352570.27310.392858
250.1017480.78810.216861
260.0503380.38990.348989
27-0.068978-0.53430.297554
280.0315360.24430.403926
29-0.043106-0.33390.369811
30-0.067818-0.52530.300649
310.0385490.29860.38314
32-0.011253-0.08720.465414
330.1053170.81580.208926
340.1165630.90290.185097
35-0.001184-0.00920.496355
36-0.144757-1.12130.133317


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 ; par8 = ;
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 (par8 != '') par8 <- as.numeric(par8)
ox <- x
if (par8 == '') {
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
} else {
x <- log(x,base=par8)
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='picts.png')
op <- par(mfrow=c(2,1))
plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')
if (par8=='') {
mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
} else {
mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
}
plot(x,type='l', main=mytitle,xlab='time',ylab='value')
par(op)
dev.off()
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)
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')