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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 computationFri, 17 Dec 2010 12:25:43 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/17/t1292588661yqxwtu9dux8mg9x.htm/, Retrieved Wed, 01 May 2024 22:35:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=111424, Retrieved Wed, 01 May 2024 22:35:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact163

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]
-    D        [(Partial) Autocorrelation Function] [Model 1 (d = 0, D...] [2009-11-24 17:27:24] [ee7c2e7343f5b1451e62c5c16ec521f1]
-    D          [(Partial) Autocorrelation Function] [Methode 1 (D=0, d=0)] [2009-11-27 12:01:23] [76ab39dc7a55316678260825bd5ad46c]
-    D            [(Partial) Autocorrelation Function] [methode 1 (d=0 D= 0)] [2009-11-27 20:21:42] [4b453aa14d54730625f8d3de5f1f6d82]
-    D              [(Partial) Autocorrelation Function] [koffie en thee] [2009-12-16 19:04:55] [7773f496f69461f4a67891f0ef752622]
-    D                [(Partial) Autocorrelation Function] [Appelen Jonagold ...] [2009-12-17 16:51:16] [7773f496f69461f4a67891f0ef752622]
-    D                  [(Partial) Autocorrelation Function] [biefstuk 3] [2010-12-14 15:31:38] [3df61981e9f4dafed65341be376c4457]
- R  D                    [(Partial) Autocorrelation Function] [restaurant 2] [2010-12-17 12:15:05] [3df61981e9f4dafed65341be376c4457]
-   PD                        [(Partial) Autocorrelation Function] [restaurant 3] [2010-12-17 12:25:43] [6e52d1bada9435d33ddf990b22ee4b00] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
15.13
15.25
15.33
15.36
15.4
15.4
15.41
15.47
15.54
15.55
15.59
15.65
15.75
15.86
15.89
15.94
15.93
15.95
15.99
15.99
16.06
16.08
16.07
16.11
16.15
16.15
16.18
16.3
16.42
16.49
16.5
16.58
16.64
16.66
16.81
16.91
16.92
16.95
17.11
17.16
17.16
17.27
17.34
17.39
17.43
17.45
17.5
17.56
17.62
17.7
17.72
17.71
17.74
17.75
17.78
17.8

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'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=111424&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=111424&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=111424&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'RServer@AstonUniversity' @ vre.aston.ac.uk






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.1686041.25040.108224
2-0.217788-1.61520.056
30.1550541.14990.127579
40.0575830.4270.335506
5-0.11893-0.8820.190806
60.0032010.02370.490572
70.2038941.51210.068114
8-0.070586-0.52350.301372
9-0.194464-1.44220.077461
100.0147310.10930.456701
110.1371621.01720.156751
12-0.168286-1.2480.108651
13-0.195677-1.45120.076205
140.1486961.10280.137467
150.0365810.27130.393591
16-0.119026-0.88270.190615
17-0.171384-1.2710.104536
18-0.103688-0.7690.2226
19-0.092688-0.68740.247362
20-0.034075-0.25270.400718
210.03160.23440.407791
22-0.097799-0.72530.235672
23-0.113687-0.84310.201405
24-0.172027-1.27580.103697
25-0.0639-0.47390.318726
260.1075850.79790.214188
270.0588080.43610.332224
280.0015290.01130.495497
29-0.023041-0.17090.432473
300.0857260.63580.263785
310.0574150.42580.335958
32-0.05594-0.41490.339927
330.0470050.34860.36436
340.1200620.89040.188563
350.0074880.05550.477959
360.0716020.5310.298773

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.168604 & 1.2504 & 0.108224 \tabularnewline
2 & -0.217788 & -1.6152 & 0.056 \tabularnewline
3 & 0.155054 & 1.1499 & 0.127579 \tabularnewline
4 & 0.057583 & 0.427 & 0.335506 \tabularnewline
5 & -0.11893 & -0.882 & 0.190806 \tabularnewline
6 & 0.003201 & 0.0237 & 0.490572 \tabularnewline
7 & 0.203894 & 1.5121 & 0.068114 \tabularnewline
8 & -0.070586 & -0.5235 & 0.301372 \tabularnewline
9 & -0.194464 & -1.4422 & 0.077461 \tabularnewline
10 & 0.014731 & 0.1093 & 0.456701 \tabularnewline
11 & 0.137162 & 1.0172 & 0.156751 \tabularnewline
12 & -0.168286 & -1.248 & 0.108651 \tabularnewline
13 & -0.195677 & -1.4512 & 0.076205 \tabularnewline
14 & 0.148696 & 1.1028 & 0.137467 \tabularnewline
15 & 0.036581 & 0.2713 & 0.393591 \tabularnewline
16 & -0.119026 & -0.8827 & 0.190615 \tabularnewline
17 & -0.171384 & -1.271 & 0.104536 \tabularnewline
18 & -0.103688 & -0.769 & 0.2226 \tabularnewline
19 & -0.092688 & -0.6874 & 0.247362 \tabularnewline
20 & -0.034075 & -0.2527 & 0.400718 \tabularnewline
21 & 0.0316 & 0.2344 & 0.407791 \tabularnewline
22 & -0.097799 & -0.7253 & 0.235672 \tabularnewline
23 & -0.113687 & -0.8431 & 0.201405 \tabularnewline
24 & -0.172027 & -1.2758 & 0.103697 \tabularnewline
25 & -0.0639 & -0.4739 & 0.318726 \tabularnewline
26 & 0.107585 & 0.7979 & 0.214188 \tabularnewline
27 & 0.058808 & 0.4361 & 0.332224 \tabularnewline
28 & 0.001529 & 0.0113 & 0.495497 \tabularnewline
29 & -0.023041 & -0.1709 & 0.432473 \tabularnewline
30 & 0.085726 & 0.6358 & 0.263785 \tabularnewline
31 & 0.057415 & 0.4258 & 0.335958 \tabularnewline
32 & -0.05594 & -0.4149 & 0.339927 \tabularnewline
33 & 0.047005 & 0.3486 & 0.36436 \tabularnewline
34 & 0.120062 & 0.8904 & 0.188563 \tabularnewline
35 & 0.007488 & 0.0555 & 0.477959 \tabularnewline
36 & 0.071602 & 0.531 & 0.298773 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=111424&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]0.168604[/C][C]1.2504[/C][C]0.108224[/C][/ROW]
[ROW][C]2[/C][C]-0.217788[/C][C]-1.6152[/C][C]0.056[/C][/ROW]
[ROW][C]3[/C][C]0.155054[/C][C]1.1499[/C][C]0.127579[/C][/ROW]
[ROW][C]4[/C][C]0.057583[/C][C]0.427[/C][C]0.335506[/C][/ROW]
[ROW][C]5[/C][C]-0.11893[/C][C]-0.882[/C][C]0.190806[/C][/ROW]
[ROW][C]6[/C][C]0.003201[/C][C]0.0237[/C][C]0.490572[/C][/ROW]
[ROW][C]7[/C][C]0.203894[/C][C]1.5121[/C][C]0.068114[/C][/ROW]
[ROW][C]8[/C][C]-0.070586[/C][C]-0.5235[/C][C]0.301372[/C][/ROW]
[ROW][C]9[/C][C]-0.194464[/C][C]-1.4422[/C][C]0.077461[/C][/ROW]
[ROW][C]10[/C][C]0.014731[/C][C]0.1093[/C][C]0.456701[/C][/ROW]
[ROW][C]11[/C][C]0.137162[/C][C]1.0172[/C][C]0.156751[/C][/ROW]
[ROW][C]12[/C][C]-0.168286[/C][C]-1.248[/C][C]0.108651[/C][/ROW]
[ROW][C]13[/C][C]-0.195677[/C][C]-1.4512[/C][C]0.076205[/C][/ROW]
[ROW][C]14[/C][C]0.148696[/C][C]1.1028[/C][C]0.137467[/C][/ROW]
[ROW][C]15[/C][C]0.036581[/C][C]0.2713[/C][C]0.393591[/C][/ROW]
[ROW][C]16[/C][C]-0.119026[/C][C]-0.8827[/C][C]0.190615[/C][/ROW]
[ROW][C]17[/C][C]-0.171384[/C][C]-1.271[/C][C]0.104536[/C][/ROW]
[ROW][C]18[/C][C]-0.103688[/C][C]-0.769[/C][C]0.2226[/C][/ROW]
[ROW][C]19[/C][C]-0.092688[/C][C]-0.6874[/C][C]0.247362[/C][/ROW]
[ROW][C]20[/C][C]-0.034075[/C][C]-0.2527[/C][C]0.400718[/C][/ROW]
[ROW][C]21[/C][C]0.0316[/C][C]0.2344[/C][C]0.407791[/C][/ROW]
[ROW][C]22[/C][C]-0.097799[/C][C]-0.7253[/C][C]0.235672[/C][/ROW]
[ROW][C]23[/C][C]-0.113687[/C][C]-0.8431[/C][C]0.201405[/C][/ROW]
[ROW][C]24[/C][C]-0.172027[/C][C]-1.2758[/C][C]0.103697[/C][/ROW]
[ROW][C]25[/C][C]-0.0639[/C][C]-0.4739[/C][C]0.318726[/C][/ROW]
[ROW][C]26[/C][C]0.107585[/C][C]0.7979[/C][C]0.214188[/C][/ROW]
[ROW][C]27[/C][C]0.058808[/C][C]0.4361[/C][C]0.332224[/C][/ROW]
[ROW][C]28[/C][C]0.001529[/C][C]0.0113[/C][C]0.495497[/C][/ROW]
[ROW][C]29[/C][C]-0.023041[/C][C]-0.1709[/C][C]0.432473[/C][/ROW]
[ROW][C]30[/C][C]0.085726[/C][C]0.6358[/C][C]0.263785[/C][/ROW]
[ROW][C]31[/C][C]0.057415[/C][C]0.4258[/C][C]0.335958[/C][/ROW]
[ROW][C]32[/C][C]-0.05594[/C][C]-0.4149[/C][C]0.339927[/C][/ROW]
[ROW][C]33[/C][C]0.047005[/C][C]0.3486[/C][C]0.36436[/C][/ROW]
[ROW][C]34[/C][C]0.120062[/C][C]0.8904[/C][C]0.188563[/C][/ROW]
[ROW][C]35[/C][C]0.007488[/C][C]0.0555[/C][C]0.477959[/C][/ROW]
[ROW][C]36[/C][C]0.071602[/C][C]0.531[/C][C]0.298773[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=111424&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=111424&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
10.1686041.25040.108224
2-0.217788-1.61520.056
30.1550541.14990.127579
40.0575830.4270.335506
5-0.11893-0.8820.190806
60.0032010.02370.490572
70.2038941.51210.068114
8-0.070586-0.52350.301372
9-0.194464-1.44220.077461
100.0147310.10930.456701
110.1371621.01720.156751
12-0.168286-1.2480.108651
13-0.195677-1.45120.076205
140.1486961.10280.137467
150.0365810.27130.393591
16-0.119026-0.88270.190615
17-0.171384-1.2710.104536
18-0.103688-0.7690.2226
19-0.092688-0.68740.247362
20-0.034075-0.25270.400718
210.03160.23440.407791
22-0.097799-0.72530.235672
23-0.113687-0.84310.201405
24-0.172027-1.27580.103697
25-0.0639-0.47390.318726
260.1075850.79790.214188
270.0588080.43610.332224
280.0015290.01130.495497
29-0.023041-0.17090.432473
300.0857260.63580.263785
310.0574150.42580.335958
32-0.05594-0.41490.339927
330.0470050.34860.36436
340.1200620.89040.188563
350.0074880.05550.477959
360.0716020.5310.298773






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1686041.25040.108224
2-0.253419-1.87940.032746
30.2681621.98870.025857
4-0.116697-0.86540.195277
50.0024670.01830.492734
6-0.015148-0.11230.45548
70.2006121.48780.071261
8-0.183066-1.35770.090059
9-0.027615-0.20480.419243
10-0.078332-0.58090.281831
110.1846051.36910.088272
12-0.280262-2.07850.021172
130.0206980.15350.439284
14-0.009527-0.07070.471964
150.0961330.71290.239448
16-0.078835-0.58470.280585
17-0.249064-1.84710.035057
18-0.112928-0.83750.202969
19-0.010423-0.07730.469335
200.1008450.74790.228858
21-0.173914-1.28980.101262
22-0.144519-1.07180.14425
23-0.043137-0.31990.375122
24-0.114592-0.84980.19955
25-0.104649-0.77610.220508
260.0258130.19140.424444
270.0127910.09490.462385
280.0650430.48240.315728
29-0.159697-1.18430.120685
300.038580.28610.387932
31-0.013536-0.10040.460203
32-0.012898-0.09570.462072
33-0.006641-0.04920.480449
34-0.061921-0.45920.323942
35-0.016211-0.12020.452371
360.1286730.95430.172063

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.168604 & 1.2504 & 0.108224 \tabularnewline
2 & -0.253419 & -1.8794 & 0.032746 \tabularnewline
3 & 0.268162 & 1.9887 & 0.025857 \tabularnewline
4 & -0.116697 & -0.8654 & 0.195277 \tabularnewline
5 & 0.002467 & 0.0183 & 0.492734 \tabularnewline
6 & -0.015148 & -0.1123 & 0.45548 \tabularnewline
7 & 0.200612 & 1.4878 & 0.071261 \tabularnewline
8 & -0.183066 & -1.3577 & 0.090059 \tabularnewline
9 & -0.027615 & -0.2048 & 0.419243 \tabularnewline
10 & -0.078332 & -0.5809 & 0.281831 \tabularnewline
11 & 0.184605 & 1.3691 & 0.088272 \tabularnewline
12 & -0.280262 & -2.0785 & 0.021172 \tabularnewline
13 & 0.020698 & 0.1535 & 0.439284 \tabularnewline
14 & -0.009527 & -0.0707 & 0.471964 \tabularnewline
15 & 0.096133 & 0.7129 & 0.239448 \tabularnewline
16 & -0.078835 & -0.5847 & 0.280585 \tabularnewline
17 & -0.249064 & -1.8471 & 0.035057 \tabularnewline
18 & -0.112928 & -0.8375 & 0.202969 \tabularnewline
19 & -0.010423 & -0.0773 & 0.469335 \tabularnewline
20 & 0.100845 & 0.7479 & 0.228858 \tabularnewline
21 & -0.173914 & -1.2898 & 0.101262 \tabularnewline
22 & -0.144519 & -1.0718 & 0.14425 \tabularnewline
23 & -0.043137 & -0.3199 & 0.375122 \tabularnewline
24 & -0.114592 & -0.8498 & 0.19955 \tabularnewline
25 & -0.104649 & -0.7761 & 0.220508 \tabularnewline
26 & 0.025813 & 0.1914 & 0.424444 \tabularnewline
27 & 0.012791 & 0.0949 & 0.462385 \tabularnewline
28 & 0.065043 & 0.4824 & 0.315728 \tabularnewline
29 & -0.159697 & -1.1843 & 0.120685 \tabularnewline
30 & 0.03858 & 0.2861 & 0.387932 \tabularnewline
31 & -0.013536 & -0.1004 & 0.460203 \tabularnewline
32 & -0.012898 & -0.0957 & 0.462072 \tabularnewline
33 & -0.006641 & -0.0492 & 0.480449 \tabularnewline
34 & -0.061921 & -0.4592 & 0.323942 \tabularnewline
35 & -0.016211 & -0.1202 & 0.452371 \tabularnewline
36 & 0.128673 & 0.9543 & 0.172063 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=111424&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]0.168604[/C][C]1.2504[/C][C]0.108224[/C][/ROW]
[ROW][C]2[/C][C]-0.253419[/C][C]-1.8794[/C][C]0.032746[/C][/ROW]
[ROW][C]3[/C][C]0.268162[/C][C]1.9887[/C][C]0.025857[/C][/ROW]
[ROW][C]4[/C][C]-0.116697[/C][C]-0.8654[/C][C]0.195277[/C][/ROW]
[ROW][C]5[/C][C]0.002467[/C][C]0.0183[/C][C]0.492734[/C][/ROW]
[ROW][C]6[/C][C]-0.015148[/C][C]-0.1123[/C][C]0.45548[/C][/ROW]
[ROW][C]7[/C][C]0.200612[/C][C]1.4878[/C][C]0.071261[/C][/ROW]
[ROW][C]8[/C][C]-0.183066[/C][C]-1.3577[/C][C]0.090059[/C][/ROW]
[ROW][C]9[/C][C]-0.027615[/C][C]-0.2048[/C][C]0.419243[/C][/ROW]
[ROW][C]10[/C][C]-0.078332[/C][C]-0.5809[/C][C]0.281831[/C][/ROW]
[ROW][C]11[/C][C]0.184605[/C][C]1.3691[/C][C]0.088272[/C][/ROW]
[ROW][C]12[/C][C]-0.280262[/C][C]-2.0785[/C][C]0.021172[/C][/ROW]
[ROW][C]13[/C][C]0.020698[/C][C]0.1535[/C][C]0.439284[/C][/ROW]
[ROW][C]14[/C][C]-0.009527[/C][C]-0.0707[/C][C]0.471964[/C][/ROW]
[ROW][C]15[/C][C]0.096133[/C][C]0.7129[/C][C]0.239448[/C][/ROW]
[ROW][C]16[/C][C]-0.078835[/C][C]-0.5847[/C][C]0.280585[/C][/ROW]
[ROW][C]17[/C][C]-0.249064[/C][C]-1.8471[/C][C]0.035057[/C][/ROW]
[ROW][C]18[/C][C]-0.112928[/C][C]-0.8375[/C][C]0.202969[/C][/ROW]
[ROW][C]19[/C][C]-0.010423[/C][C]-0.0773[/C][C]0.469335[/C][/ROW]
[ROW][C]20[/C][C]0.100845[/C][C]0.7479[/C][C]0.228858[/C][/ROW]
[ROW][C]21[/C][C]-0.173914[/C][C]-1.2898[/C][C]0.101262[/C][/ROW]
[ROW][C]22[/C][C]-0.144519[/C][C]-1.0718[/C][C]0.14425[/C][/ROW]
[ROW][C]23[/C][C]-0.043137[/C][C]-0.3199[/C][C]0.375122[/C][/ROW]
[ROW][C]24[/C][C]-0.114592[/C][C]-0.8498[/C][C]0.19955[/C][/ROW]
[ROW][C]25[/C][C]-0.104649[/C][C]-0.7761[/C][C]0.220508[/C][/ROW]
[ROW][C]26[/C][C]0.025813[/C][C]0.1914[/C][C]0.424444[/C][/ROW]
[ROW][C]27[/C][C]0.012791[/C][C]0.0949[/C][C]0.462385[/C][/ROW]
[ROW][C]28[/C][C]0.065043[/C][C]0.4824[/C][C]0.315728[/C][/ROW]
[ROW][C]29[/C][C]-0.159697[/C][C]-1.1843[/C][C]0.120685[/C][/ROW]
[ROW][C]30[/C][C]0.03858[/C][C]0.2861[/C][C]0.387932[/C][/ROW]
[ROW][C]31[/C][C]-0.013536[/C][C]-0.1004[/C][C]0.460203[/C][/ROW]
[ROW][C]32[/C][C]-0.012898[/C][C]-0.0957[/C][C]0.462072[/C][/ROW]
[ROW][C]33[/C][C]-0.006641[/C][C]-0.0492[/C][C]0.480449[/C][/ROW]
[ROW][C]34[/C][C]-0.061921[/C][C]-0.4592[/C][C]0.323942[/C][/ROW]
[ROW][C]35[/C][C]-0.016211[/C][C]-0.1202[/C][C]0.452371[/C][/ROW]
[ROW][C]36[/C][C]0.128673[/C][C]0.9543[/C][C]0.172063[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=111424&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=111424&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
10.1686041.25040.108224
2-0.253419-1.87940.032746
30.2681621.98870.025857
4-0.116697-0.86540.195277
50.0024670.01830.492734
6-0.015148-0.11230.45548
70.2006121.48780.071261
8-0.183066-1.35770.090059
9-0.027615-0.20480.419243
10-0.078332-0.58090.281831
110.1846051.36910.088272
12-0.280262-2.07850.021172
130.0206980.15350.439284
14-0.009527-0.07070.471964
150.0961330.71290.239448
16-0.078835-0.58470.280585
17-0.249064-1.84710.035057
18-0.112928-0.83750.202969
19-0.010423-0.07730.469335
200.1008450.74790.228858
21-0.173914-1.28980.101262
22-0.144519-1.07180.14425
23-0.043137-0.31990.375122
24-0.114592-0.84980.19955
25-0.104649-0.77610.220508
260.0258130.19140.424444
270.0127910.09490.462385
280.0650430.48240.315728
29-0.159697-1.18430.120685
300.038580.28610.387932
31-0.013536-0.10040.460203
32-0.012898-0.09570.462072
33-0.006641-0.04920.480449
34-0.061921-0.45920.323942
35-0.016211-0.12020.452371
360.1286730.95430.172063


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = MA ; 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')