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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 07:11:22 -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/t1259417541ijm5gwngreqq012.htm/, Retrieved Fri, 03 May 2024 13:30:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=61470, Retrieved Fri, 03 May 2024 13:30:02 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact122

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]
-   PD        [(Partial) Autocorrelation Function] [] [2009-11-28 14:08:05] [74be16979710d4c4e7c6647856088456]
-   P             [(Partial) Autocorrelation Function] [] [2009-11-28 14:11:22] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
95,5
76,7
79,4
55,2
60
64,8
82,3
210,5
106
80,8
97,3
189,5
90
69,3
87,3
57,4
56,2
61,6
77,7
177,2
97,6
81,6
96,8
191,3
106
75,1
72
63,5
57,4
62,3
79,4
178,1
109,3
85,2
102,7
193,7
108,4
73,4
85,9
58,5
58,6
62,7
77,5
180,5
102,2
82,6
97,8
197,8
93,8
72,4
77,7
58,7
53,1
64,3
76,4
188,4
105,5
79,8
96,1
202,5

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'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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61470&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61470&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61470&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'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.482613-3.30860.000902
2-0.000992-0.00680.497301
30.0046010.03150.487486
40.1554031.06540.146071
5-0.353846-2.42580.009583
60.0983890.67450.251641
70.1675981.1490.128186
8-0.144899-0.99340.162806
90.1195950.81990.208205
10-0.052281-0.35840.360816
110.1438110.98590.164611
12-0.26454-1.81360.038064
130.1421850.97480.167332
14-0.018584-0.12740.44958
150.0083820.05750.477209
16-0.074895-0.51350.305019
170.0412820.2830.389204
180.1064120.72950.23465
19-0.175849-1.20560.117011
200.1272960.87270.193633
21-0.112024-0.7680.223164
220.080340.55080.292196
230.0009990.00680.497282
24-0.010724-0.07350.470851
25-0.032318-0.22160.412809
260.0337130.23110.409109
270.0040130.02750.489084
28-0.088325-0.60550.273872
290.1461051.00160.160822
30-0.152806-1.04760.150093
310.1294930.88780.189595
32-0.029871-0.20480.419313
330.0418270.28670.387782
34-0.113016-0.77480.22117
350.1135920.77870.220017
36-0.110698-0.75890.225848

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.482613 & -3.3086 & 0.000902 \tabularnewline
2 & -0.000992 & -0.0068 & 0.497301 \tabularnewline
3 & 0.004601 & 0.0315 & 0.487486 \tabularnewline
4 & 0.155403 & 1.0654 & 0.146071 \tabularnewline
5 & -0.353846 & -2.4258 & 0.009583 \tabularnewline
6 & 0.098389 & 0.6745 & 0.251641 \tabularnewline
7 & 0.167598 & 1.149 & 0.128186 \tabularnewline
8 & -0.144899 & -0.9934 & 0.162806 \tabularnewline
9 & 0.119595 & 0.8199 & 0.208205 \tabularnewline
10 & -0.052281 & -0.3584 & 0.360816 \tabularnewline
11 & 0.143811 & 0.9859 & 0.164611 \tabularnewline
12 & -0.26454 & -1.8136 & 0.038064 \tabularnewline
13 & 0.142185 & 0.9748 & 0.167332 \tabularnewline
14 & -0.018584 & -0.1274 & 0.44958 \tabularnewline
15 & 0.008382 & 0.0575 & 0.477209 \tabularnewline
16 & -0.074895 & -0.5135 & 0.305019 \tabularnewline
17 & 0.041282 & 0.283 & 0.389204 \tabularnewline
18 & 0.106412 & 0.7295 & 0.23465 \tabularnewline
19 & -0.175849 & -1.2056 & 0.117011 \tabularnewline
20 & 0.127296 & 0.8727 & 0.193633 \tabularnewline
21 & -0.112024 & -0.768 & 0.223164 \tabularnewline
22 & 0.08034 & 0.5508 & 0.292196 \tabularnewline
23 & 0.000999 & 0.0068 & 0.497282 \tabularnewline
24 & -0.010724 & -0.0735 & 0.470851 \tabularnewline
25 & -0.032318 & -0.2216 & 0.412809 \tabularnewline
26 & 0.033713 & 0.2311 & 0.409109 \tabularnewline
27 & 0.004013 & 0.0275 & 0.489084 \tabularnewline
28 & -0.088325 & -0.6055 & 0.273872 \tabularnewline
29 & 0.146105 & 1.0016 & 0.160822 \tabularnewline
30 & -0.152806 & -1.0476 & 0.150093 \tabularnewline
31 & 0.129493 & 0.8878 & 0.189595 \tabularnewline
32 & -0.029871 & -0.2048 & 0.419313 \tabularnewline
33 & 0.041827 & 0.2867 & 0.387782 \tabularnewline
34 & -0.113016 & -0.7748 & 0.22117 \tabularnewline
35 & 0.113592 & 0.7787 & 0.220017 \tabularnewline
36 & -0.110698 & -0.7589 & 0.225848 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61470&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]-0.482613[/C][C]-3.3086[/C][C]0.000902[/C][/ROW]
[ROW][C]2[/C][C]-0.000992[/C][C]-0.0068[/C][C]0.497301[/C][/ROW]
[ROW][C]3[/C][C]0.004601[/C][C]0.0315[/C][C]0.487486[/C][/ROW]
[ROW][C]4[/C][C]0.155403[/C][C]1.0654[/C][C]0.146071[/C][/ROW]
[ROW][C]5[/C][C]-0.353846[/C][C]-2.4258[/C][C]0.009583[/C][/ROW]
[ROW][C]6[/C][C]0.098389[/C][C]0.6745[/C][C]0.251641[/C][/ROW]
[ROW][C]7[/C][C]0.167598[/C][C]1.149[/C][C]0.128186[/C][/ROW]
[ROW][C]8[/C][C]-0.144899[/C][C]-0.9934[/C][C]0.162806[/C][/ROW]
[ROW][C]9[/C][C]0.119595[/C][C]0.8199[/C][C]0.208205[/C][/ROW]
[ROW][C]10[/C][C]-0.052281[/C][C]-0.3584[/C][C]0.360816[/C][/ROW]
[ROW][C]11[/C][C]0.143811[/C][C]0.9859[/C][C]0.164611[/C][/ROW]
[ROW][C]12[/C][C]-0.26454[/C][C]-1.8136[/C][C]0.038064[/C][/ROW]
[ROW][C]13[/C][C]0.142185[/C][C]0.9748[/C][C]0.167332[/C][/ROW]
[ROW][C]14[/C][C]-0.018584[/C][C]-0.1274[/C][C]0.44958[/C][/ROW]
[ROW][C]15[/C][C]0.008382[/C][C]0.0575[/C][C]0.477209[/C][/ROW]
[ROW][C]16[/C][C]-0.074895[/C][C]-0.5135[/C][C]0.305019[/C][/ROW]
[ROW][C]17[/C][C]0.041282[/C][C]0.283[/C][C]0.389204[/C][/ROW]
[ROW][C]18[/C][C]0.106412[/C][C]0.7295[/C][C]0.23465[/C][/ROW]
[ROW][C]19[/C][C]-0.175849[/C][C]-1.2056[/C][C]0.117011[/C][/ROW]
[ROW][C]20[/C][C]0.127296[/C][C]0.8727[/C][C]0.193633[/C][/ROW]
[ROW][C]21[/C][C]-0.112024[/C][C]-0.768[/C][C]0.223164[/C][/ROW]
[ROW][C]22[/C][C]0.08034[/C][C]0.5508[/C][C]0.292196[/C][/ROW]
[ROW][C]23[/C][C]0.000999[/C][C]0.0068[/C][C]0.497282[/C][/ROW]
[ROW][C]24[/C][C]-0.010724[/C][C]-0.0735[/C][C]0.470851[/C][/ROW]
[ROW][C]25[/C][C]-0.032318[/C][C]-0.2216[/C][C]0.412809[/C][/ROW]
[ROW][C]26[/C][C]0.033713[/C][C]0.2311[/C][C]0.409109[/C][/ROW]
[ROW][C]27[/C][C]0.004013[/C][C]0.0275[/C][C]0.489084[/C][/ROW]
[ROW][C]28[/C][C]-0.088325[/C][C]-0.6055[/C][C]0.273872[/C][/ROW]
[ROW][C]29[/C][C]0.146105[/C][C]1.0016[/C][C]0.160822[/C][/ROW]
[ROW][C]30[/C][C]-0.152806[/C][C]-1.0476[/C][C]0.150093[/C][/ROW]
[ROW][C]31[/C][C]0.129493[/C][C]0.8878[/C][C]0.189595[/C][/ROW]
[ROW][C]32[/C][C]-0.029871[/C][C]-0.2048[/C][C]0.419313[/C][/ROW]
[ROW][C]33[/C][C]0.041827[/C][C]0.2867[/C][C]0.387782[/C][/ROW]
[ROW][C]34[/C][C]-0.113016[/C][C]-0.7748[/C][C]0.22117[/C][/ROW]
[ROW][C]35[/C][C]0.113592[/C][C]0.7787[/C][C]0.220017[/C][/ROW]
[ROW][C]36[/C][C]-0.110698[/C][C]-0.7589[/C][C]0.225848[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61470&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61470&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
1-0.482613-3.30860.000902
2-0.000992-0.00680.497301
30.0046010.03150.487486
40.1554031.06540.146071
5-0.353846-2.42580.009583
60.0983890.67450.251641
70.1675981.1490.128186
8-0.144899-0.99340.162806
90.1195950.81990.208205
10-0.052281-0.35840.360816
110.1438110.98590.164611
12-0.26454-1.81360.038064
130.1421850.97480.167332
14-0.018584-0.12740.44958
150.0083820.05750.477209
16-0.074895-0.51350.305019
170.0412820.2830.389204
180.1064120.72950.23465
19-0.175849-1.20560.117011
200.1272960.87270.193633
21-0.112024-0.7680.223164
220.080340.55080.292196
230.0009990.00680.497282
24-0.010724-0.07350.470851
25-0.032318-0.22160.412809
260.0337130.23110.409109
270.0040130.02750.489084
28-0.088325-0.60550.273872
290.1461051.00160.160822
30-0.152806-1.04760.150093
310.1294930.88780.189595
32-0.029871-0.20480.419313
330.0418270.28670.387782
34-0.113016-0.77480.22117
350.1135920.77870.220017
36-0.110698-0.75890.225848






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.482613-3.30860.000902
2-0.304931-2.09050.021004
3-0.205801-1.41090.08243
40.0883030.60540.273921
5-0.309718-2.12330.019511
6-0.352008-2.41320.009882
7-0.080294-0.55050.292302
8-0.16631-1.14020.129998
90.0918270.62950.266023
10-0.078543-0.53850.296399
110.1028010.70480.242216
12-0.057037-0.3910.348773
13-0.067099-0.460.323815
140.0717650.4920.312507
150.044260.30340.381449
160.0160680.11020.456378
17-0.155287-1.06460.146249
18-0.005703-0.03910.484489
19-0.070969-0.48650.314422
20-0.016288-0.11170.455782
21-0.154236-1.05740.147869
22-0.202467-1.3880.085834
230.0881850.60460.274187
24-0.069963-0.47960.316853
25-0.059655-0.4090.342208
26-0.079588-0.54560.293952
27-0.080605-0.55260.291577
28-0.032547-0.22310.412201
290.0066230.04540.481988
30-0.095712-0.65620.257458
31-0.021486-0.14730.441763
320.0377210.25860.398535
330.0405280.27780.391174
340.0007790.00530.49788
350.0804570.55160.291922
36-0.10917-0.74840.228965

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.482613 & -3.3086 & 0.000902 \tabularnewline
2 & -0.304931 & -2.0905 & 0.021004 \tabularnewline
3 & -0.205801 & -1.4109 & 0.08243 \tabularnewline
4 & 0.088303 & 0.6054 & 0.273921 \tabularnewline
5 & -0.309718 & -2.1233 & 0.019511 \tabularnewline
6 & -0.352008 & -2.4132 & 0.009882 \tabularnewline
7 & -0.080294 & -0.5505 & 0.292302 \tabularnewline
8 & -0.16631 & -1.1402 & 0.129998 \tabularnewline
9 & 0.091827 & 0.6295 & 0.266023 \tabularnewline
10 & -0.078543 & -0.5385 & 0.296399 \tabularnewline
11 & 0.102801 & 0.7048 & 0.242216 \tabularnewline
12 & -0.057037 & -0.391 & 0.348773 \tabularnewline
13 & -0.067099 & -0.46 & 0.323815 \tabularnewline
14 & 0.071765 & 0.492 & 0.312507 \tabularnewline
15 & 0.04426 & 0.3034 & 0.381449 \tabularnewline
16 & 0.016068 & 0.1102 & 0.456378 \tabularnewline
17 & -0.155287 & -1.0646 & 0.146249 \tabularnewline
18 & -0.005703 & -0.0391 & 0.484489 \tabularnewline
19 & -0.070969 & -0.4865 & 0.314422 \tabularnewline
20 & -0.016288 & -0.1117 & 0.455782 \tabularnewline
21 & -0.154236 & -1.0574 & 0.147869 \tabularnewline
22 & -0.202467 & -1.388 & 0.085834 \tabularnewline
23 & 0.088185 & 0.6046 & 0.274187 \tabularnewline
24 & -0.069963 & -0.4796 & 0.316853 \tabularnewline
25 & -0.059655 & -0.409 & 0.342208 \tabularnewline
26 & -0.079588 & -0.5456 & 0.293952 \tabularnewline
27 & -0.080605 & -0.5526 & 0.291577 \tabularnewline
28 & -0.032547 & -0.2231 & 0.412201 \tabularnewline
29 & 0.006623 & 0.0454 & 0.481988 \tabularnewline
30 & -0.095712 & -0.6562 & 0.257458 \tabularnewline
31 & -0.021486 & -0.1473 & 0.441763 \tabularnewline
32 & 0.037721 & 0.2586 & 0.398535 \tabularnewline
33 & 0.040528 & 0.2778 & 0.391174 \tabularnewline
34 & 0.000779 & 0.0053 & 0.49788 \tabularnewline
35 & 0.080457 & 0.5516 & 0.291922 \tabularnewline
36 & -0.10917 & -0.7484 & 0.228965 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61470&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]-0.482613[/C][C]-3.3086[/C][C]0.000902[/C][/ROW]
[ROW][C]2[/C][C]-0.304931[/C][C]-2.0905[/C][C]0.021004[/C][/ROW]
[ROW][C]3[/C][C]-0.205801[/C][C]-1.4109[/C][C]0.08243[/C][/ROW]
[ROW][C]4[/C][C]0.088303[/C][C]0.6054[/C][C]0.273921[/C][/ROW]
[ROW][C]5[/C][C]-0.309718[/C][C]-2.1233[/C][C]0.019511[/C][/ROW]
[ROW][C]6[/C][C]-0.352008[/C][C]-2.4132[/C][C]0.009882[/C][/ROW]
[ROW][C]7[/C][C]-0.080294[/C][C]-0.5505[/C][C]0.292302[/C][/ROW]
[ROW][C]8[/C][C]-0.16631[/C][C]-1.1402[/C][C]0.129998[/C][/ROW]
[ROW][C]9[/C][C]0.091827[/C][C]0.6295[/C][C]0.266023[/C][/ROW]
[ROW][C]10[/C][C]-0.078543[/C][C]-0.5385[/C][C]0.296399[/C][/ROW]
[ROW][C]11[/C][C]0.102801[/C][C]0.7048[/C][C]0.242216[/C][/ROW]
[ROW][C]12[/C][C]-0.057037[/C][C]-0.391[/C][C]0.348773[/C][/ROW]
[ROW][C]13[/C][C]-0.067099[/C][C]-0.46[/C][C]0.323815[/C][/ROW]
[ROW][C]14[/C][C]0.071765[/C][C]0.492[/C][C]0.312507[/C][/ROW]
[ROW][C]15[/C][C]0.04426[/C][C]0.3034[/C][C]0.381449[/C][/ROW]
[ROW][C]16[/C][C]0.016068[/C][C]0.1102[/C][C]0.456378[/C][/ROW]
[ROW][C]17[/C][C]-0.155287[/C][C]-1.0646[/C][C]0.146249[/C][/ROW]
[ROW][C]18[/C][C]-0.005703[/C][C]-0.0391[/C][C]0.484489[/C][/ROW]
[ROW][C]19[/C][C]-0.070969[/C][C]-0.4865[/C][C]0.314422[/C][/ROW]
[ROW][C]20[/C][C]-0.016288[/C][C]-0.1117[/C][C]0.455782[/C][/ROW]
[ROW][C]21[/C][C]-0.154236[/C][C]-1.0574[/C][C]0.147869[/C][/ROW]
[ROW][C]22[/C][C]-0.202467[/C][C]-1.388[/C][C]0.085834[/C][/ROW]
[ROW][C]23[/C][C]0.088185[/C][C]0.6046[/C][C]0.274187[/C][/ROW]
[ROW][C]24[/C][C]-0.069963[/C][C]-0.4796[/C][C]0.316853[/C][/ROW]
[ROW][C]25[/C][C]-0.059655[/C][C]-0.409[/C][C]0.342208[/C][/ROW]
[ROW][C]26[/C][C]-0.079588[/C][C]-0.5456[/C][C]0.293952[/C][/ROW]
[ROW][C]27[/C][C]-0.080605[/C][C]-0.5526[/C][C]0.291577[/C][/ROW]
[ROW][C]28[/C][C]-0.032547[/C][C]-0.2231[/C][C]0.412201[/C][/ROW]
[ROW][C]29[/C][C]0.006623[/C][C]0.0454[/C][C]0.481988[/C][/ROW]
[ROW][C]30[/C][C]-0.095712[/C][C]-0.6562[/C][C]0.257458[/C][/ROW]
[ROW][C]31[/C][C]-0.021486[/C][C]-0.1473[/C][C]0.441763[/C][/ROW]
[ROW][C]32[/C][C]0.037721[/C][C]0.2586[/C][C]0.398535[/C][/ROW]
[ROW][C]33[/C][C]0.040528[/C][C]0.2778[/C][C]0.391174[/C][/ROW]
[ROW][C]34[/C][C]0.000779[/C][C]0.0053[/C][C]0.49788[/C][/ROW]
[ROW][C]35[/C][C]0.080457[/C][C]0.5516[/C][C]0.291922[/C][/ROW]
[ROW][C]36[/C][C]-0.10917[/C][C]-0.7484[/C][C]0.228965[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61470&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61470&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
1-0.482613-3.30860.000902
2-0.304931-2.09050.021004
3-0.205801-1.41090.08243
40.0883030.60540.273921
5-0.309718-2.12330.019511
6-0.352008-2.41320.009882
7-0.080294-0.55050.292302
8-0.16631-1.14020.129998
90.0918270.62950.266023
10-0.078543-0.53850.296399
110.1028010.70480.242216
12-0.057037-0.3910.348773
13-0.067099-0.460.323815
140.0717650.4920.312507
150.044260.30340.381449
160.0160680.11020.456378
17-0.155287-1.06460.146249
18-0.005703-0.03910.484489
19-0.070969-0.48650.314422
20-0.016288-0.11170.455782
21-0.154236-1.05740.147869
22-0.202467-1.3880.085834
230.0881850.60460.274187
24-0.069963-0.47960.316853
25-0.059655-0.4090.342208
26-0.079588-0.54560.293952
27-0.080605-0.55260.291577
28-0.032547-0.22310.412201
290.0066230.04540.481988
30-0.095712-0.65620.257458
31-0.021486-0.14730.441763
320.0377210.25860.398535
330.0405280.27780.391174
340.0007790.00530.49788
350.0804570.55160.291922
36-0.10917-0.74840.228965


Figures (Output of Computation)

Input Parameters & R Code

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