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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 computationWed, 25 Nov 2009 10:41:01 -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/25/t1259170940xopzes7s3whhqmz.htm/, Retrieved Wed, 08 May 2024 03:22:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59514, Retrieved Wed, 08 May 2024 03:22:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact199

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]
-   P                 [(Partial) Autocorrelation Function] [Model 1: D=0, d=1] [2009-11-25 17:41:01] [d5837f25ec8937f9733a894c487f865c] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
3030.29
2803.47
2767.63
2882.6
2863.36
2897.06
3012.61
3142.95
3032.93
3045.78
3110.52
3013.24
2987.1
2995.55
2833.18
2848.96
2794.83
2845.26
2915.02
2892.63
2604.42
2641.65
2659.81
2638.53
2720.25
2745.88
2735.7
2811.7
2799.43
2555.28
2304.98
2214.95
2065.81
1940.49
2042
1995.37
1946.81
1765.9
1635.25
1833.42
1910.43
1959.67
1969.6
2061.41
2093.48
2120.88
2174.56
2196.72
2350.44
2440.25
2408.64
2472.81
2407.6
2454.62
2448.05
2497.84
2645.64
2756.76
2849.27
2921.44

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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 & 0 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59514&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]0 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=59514&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59514&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 time0 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.2658452.0420.022815
20.0280440.21540.415096
30.1577411.21160.115242
4-0.004965-0.03810.484855
5-0.039569-0.30390.381122
60.070790.54370.294331
70.0641490.49270.312012
80.0563190.43260.333442
90.1214350.93280.177372
100.0011530.00890.49648
11-0.140274-1.07750.142829
120.0803250.6170.269808
13-0.078007-0.59920.275673
14-0.097949-0.75240.227413
150.0950040.72970.234219
160.0012910.00990.496062
170.0702110.53930.295854
180.1013440.77840.219711
19-0.050104-0.38490.350865
20-0.173124-1.32980.094353
210.0433360.33290.370205
220.0300240.23060.409204
23-0.173069-1.32940.094422
24-0.047749-0.36680.357554
25-0.149976-1.1520.126987
26-0.260397-2.00010.025047
27-0.172949-1.32840.094573
28-0.10524-0.80840.211065
29-0.013-0.09990.4604
30-0.004592-0.03530.485992
31-0.008581-0.06590.473834
320.0502270.38580.350517
33-0.005102-0.03920.484437
340.0073580.05650.47756
35-0.037437-0.28760.387346
360.0770990.59220.277987

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.265845 & 2.042 & 0.022815 \tabularnewline
2 & 0.028044 & 0.2154 & 0.415096 \tabularnewline
3 & 0.157741 & 1.2116 & 0.115242 \tabularnewline
4 & -0.004965 & -0.0381 & 0.484855 \tabularnewline
5 & -0.039569 & -0.3039 & 0.381122 \tabularnewline
6 & 0.07079 & 0.5437 & 0.294331 \tabularnewline
7 & 0.064149 & 0.4927 & 0.312012 \tabularnewline
8 & 0.056319 & 0.4326 & 0.333442 \tabularnewline
9 & 0.121435 & 0.9328 & 0.177372 \tabularnewline
10 & 0.001153 & 0.0089 & 0.49648 \tabularnewline
11 & -0.140274 & -1.0775 & 0.142829 \tabularnewline
12 & 0.080325 & 0.617 & 0.269808 \tabularnewline
13 & -0.078007 & -0.5992 & 0.275673 \tabularnewline
14 & -0.097949 & -0.7524 & 0.227413 \tabularnewline
15 & 0.095004 & 0.7297 & 0.234219 \tabularnewline
16 & 0.001291 & 0.0099 & 0.496062 \tabularnewline
17 & 0.070211 & 0.5393 & 0.295854 \tabularnewline
18 & 0.101344 & 0.7784 & 0.219711 \tabularnewline
19 & -0.050104 & -0.3849 & 0.350865 \tabularnewline
20 & -0.173124 & -1.3298 & 0.094353 \tabularnewline
21 & 0.043336 & 0.3329 & 0.370205 \tabularnewline
22 & 0.030024 & 0.2306 & 0.409204 \tabularnewline
23 & -0.173069 & -1.3294 & 0.094422 \tabularnewline
24 & -0.047749 & -0.3668 & 0.357554 \tabularnewline
25 & -0.149976 & -1.152 & 0.126987 \tabularnewline
26 & -0.260397 & -2.0001 & 0.025047 \tabularnewline
27 & -0.172949 & -1.3284 & 0.094573 \tabularnewline
28 & -0.10524 & -0.8084 & 0.211065 \tabularnewline
29 & -0.013 & -0.0999 & 0.4604 \tabularnewline
30 & -0.004592 & -0.0353 & 0.485992 \tabularnewline
31 & -0.008581 & -0.0659 & 0.473834 \tabularnewline
32 & 0.050227 & 0.3858 & 0.350517 \tabularnewline
33 & -0.005102 & -0.0392 & 0.484437 \tabularnewline
34 & 0.007358 & 0.0565 & 0.47756 \tabularnewline
35 & -0.037437 & -0.2876 & 0.387346 \tabularnewline
36 & 0.077099 & 0.5922 & 0.277987 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59514&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]0.265845[/C][C]2.042[/C][C]0.022815[/C][/ROW]
[ROW][C]2[/C][C]0.028044[/C][C]0.2154[/C][C]0.415096[/C][/ROW]
[ROW][C]3[/C][C]0.157741[/C][C]1.2116[/C][C]0.115242[/C][/ROW]
[ROW][C]4[/C][C]-0.004965[/C][C]-0.0381[/C][C]0.484855[/C][/ROW]
[ROW][C]5[/C][C]-0.039569[/C][C]-0.3039[/C][C]0.381122[/C][/ROW]
[ROW][C]6[/C][C]0.07079[/C][C]0.5437[/C][C]0.294331[/C][/ROW]
[ROW][C]7[/C][C]0.064149[/C][C]0.4927[/C][C]0.312012[/C][/ROW]
[ROW][C]8[/C][C]0.056319[/C][C]0.4326[/C][C]0.333442[/C][/ROW]
[ROW][C]9[/C][C]0.121435[/C][C]0.9328[/C][C]0.177372[/C][/ROW]
[ROW][C]10[/C][C]0.001153[/C][C]0.0089[/C][C]0.49648[/C][/ROW]
[ROW][C]11[/C][C]-0.140274[/C][C]-1.0775[/C][C]0.142829[/C][/ROW]
[ROW][C]12[/C][C]0.080325[/C][C]0.617[/C][C]0.269808[/C][/ROW]
[ROW][C]13[/C][C]-0.078007[/C][C]-0.5992[/C][C]0.275673[/C][/ROW]
[ROW][C]14[/C][C]-0.097949[/C][C]-0.7524[/C][C]0.227413[/C][/ROW]
[ROW][C]15[/C][C]0.095004[/C][C]0.7297[/C][C]0.234219[/C][/ROW]
[ROW][C]16[/C][C]0.001291[/C][C]0.0099[/C][C]0.496062[/C][/ROW]
[ROW][C]17[/C][C]0.070211[/C][C]0.5393[/C][C]0.295854[/C][/ROW]
[ROW][C]18[/C][C]0.101344[/C][C]0.7784[/C][C]0.219711[/C][/ROW]
[ROW][C]19[/C][C]-0.050104[/C][C]-0.3849[/C][C]0.350865[/C][/ROW]
[ROW][C]20[/C][C]-0.173124[/C][C]-1.3298[/C][C]0.094353[/C][/ROW]
[ROW][C]21[/C][C]0.043336[/C][C]0.3329[/C][C]0.370205[/C][/ROW]
[ROW][C]22[/C][C]0.030024[/C][C]0.2306[/C][C]0.409204[/C][/ROW]
[ROW][C]23[/C][C]-0.173069[/C][C]-1.3294[/C][C]0.094422[/C][/ROW]
[ROW][C]24[/C][C]-0.047749[/C][C]-0.3668[/C][C]0.357554[/C][/ROW]
[ROW][C]25[/C][C]-0.149976[/C][C]-1.152[/C][C]0.126987[/C][/ROW]
[ROW][C]26[/C][C]-0.260397[/C][C]-2.0001[/C][C]0.025047[/C][/ROW]
[ROW][C]27[/C][C]-0.172949[/C][C]-1.3284[/C][C]0.094573[/C][/ROW]
[ROW][C]28[/C][C]-0.10524[/C][C]-0.8084[/C][C]0.211065[/C][/ROW]
[ROW][C]29[/C][C]-0.013[/C][C]-0.0999[/C][C]0.4604[/C][/ROW]
[ROW][C]30[/C][C]-0.004592[/C][C]-0.0353[/C][C]0.485992[/C][/ROW]
[ROW][C]31[/C][C]-0.008581[/C][C]-0.0659[/C][C]0.473834[/C][/ROW]
[ROW][C]32[/C][C]0.050227[/C][C]0.3858[/C][C]0.350517[/C][/ROW]
[ROW][C]33[/C][C]-0.005102[/C][C]-0.0392[/C][C]0.484437[/C][/ROW]
[ROW][C]34[/C][C]0.007358[/C][C]0.0565[/C][C]0.47756[/C][/ROW]
[ROW][C]35[/C][C]-0.037437[/C][C]-0.2876[/C][C]0.387346[/C][/ROW]
[ROW][C]36[/C][C]0.077099[/C][C]0.5922[/C][C]0.277987[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59514&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59514&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
10.2658452.0420.022815
20.0280440.21540.415096
30.1577411.21160.115242
4-0.004965-0.03810.484855
5-0.039569-0.30390.381122
60.070790.54370.294331
70.0641490.49270.312012
80.0563190.43260.333442
90.1214350.93280.177372
100.0011530.00890.49648
11-0.140274-1.07750.142829
120.0803250.6170.269808
13-0.078007-0.59920.275673
14-0.097949-0.75240.227413
150.0950040.72970.234219
160.0012910.00990.496062
170.0702110.53930.295854
180.1013440.77840.219711
19-0.050104-0.38490.350865
20-0.173124-1.32980.094353
210.0433360.33290.370205
220.0300240.23060.409204
23-0.173069-1.32940.094422
24-0.047749-0.36680.357554
25-0.149976-1.1520.126987
26-0.260397-2.00010.025047
27-0.172949-1.32840.094573
28-0.10524-0.80840.211065
29-0.013-0.09990.4604
30-0.004592-0.03530.485992
31-0.008581-0.06590.473834
320.0502270.38580.350517
33-0.005102-0.03920.484437
340.0073580.05650.47756
35-0.037437-0.28760.387346
360.0770990.59220.277987






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.2658452.0420.022815
2-0.045872-0.35230.362917
30.1748371.34290.092217
4-0.104466-0.80240.212765
50.0004870.00370.498514
60.05940.45630.324939
70.0450290.34590.365334
80.0451850.34710.364886
90.0815920.62670.266631
10-0.072123-0.5540.290842
11-0.133757-1.02740.154211
120.1465971.1260.132356
13-0.161144-1.23780.110352
140.0304060.23360.408069
150.0546820.420.337999
16-0.036724-0.28210.389433
170.1396291.07250.143929
18-0.006481-0.04980.480233
19-0.064313-0.4940.31157
20-0.150548-1.15640.126093
210.1340751.02980.153642
22-0.020405-0.15670.437995
23-0.119787-0.92010.180633
24-0.076843-0.59020.278641
25-0.190295-1.46170.074567
26-0.108243-0.83140.204541
27-0.143537-1.10250.137355
280.0832870.63970.262408
290.0589670.45290.326129
30-0.0295-0.22660.410761
310.0181130.13910.444912
320.1561281.19920.117614
33-0.060889-0.46770.320862
340.0467360.3590.360444
350.0304870.23420.407829
360.0495980.3810.352298

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.265845 & 2.042 & 0.022815 \tabularnewline
2 & -0.045872 & -0.3523 & 0.362917 \tabularnewline
3 & 0.174837 & 1.3429 & 0.092217 \tabularnewline
4 & -0.104466 & -0.8024 & 0.212765 \tabularnewline
5 & 0.000487 & 0.0037 & 0.498514 \tabularnewline
6 & 0.0594 & 0.4563 & 0.324939 \tabularnewline
7 & 0.045029 & 0.3459 & 0.365334 \tabularnewline
8 & 0.045185 & 0.3471 & 0.364886 \tabularnewline
9 & 0.081592 & 0.6267 & 0.266631 \tabularnewline
10 & -0.072123 & -0.554 & 0.290842 \tabularnewline
11 & -0.133757 & -1.0274 & 0.154211 \tabularnewline
12 & 0.146597 & 1.126 & 0.132356 \tabularnewline
13 & -0.161144 & -1.2378 & 0.110352 \tabularnewline
14 & 0.030406 & 0.2336 & 0.408069 \tabularnewline
15 & 0.054682 & 0.42 & 0.337999 \tabularnewline
16 & -0.036724 & -0.2821 & 0.389433 \tabularnewline
17 & 0.139629 & 1.0725 & 0.143929 \tabularnewline
18 & -0.006481 & -0.0498 & 0.480233 \tabularnewline
19 & -0.064313 & -0.494 & 0.31157 \tabularnewline
20 & -0.150548 & -1.1564 & 0.126093 \tabularnewline
21 & 0.134075 & 1.0298 & 0.153642 \tabularnewline
22 & -0.020405 & -0.1567 & 0.437995 \tabularnewline
23 & -0.119787 & -0.9201 & 0.180633 \tabularnewline
24 & -0.076843 & -0.5902 & 0.278641 \tabularnewline
25 & -0.190295 & -1.4617 & 0.074567 \tabularnewline
26 & -0.108243 & -0.8314 & 0.204541 \tabularnewline
27 & -0.143537 & -1.1025 & 0.137355 \tabularnewline
28 & 0.083287 & 0.6397 & 0.262408 \tabularnewline
29 & 0.058967 & 0.4529 & 0.326129 \tabularnewline
30 & -0.0295 & -0.2266 & 0.410761 \tabularnewline
31 & 0.018113 & 0.1391 & 0.444912 \tabularnewline
32 & 0.156128 & 1.1992 & 0.117614 \tabularnewline
33 & -0.060889 & -0.4677 & 0.320862 \tabularnewline
34 & 0.046736 & 0.359 & 0.360444 \tabularnewline
35 & 0.030487 & 0.2342 & 0.407829 \tabularnewline
36 & 0.049598 & 0.381 & 0.352298 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59514&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]0.265845[/C][C]2.042[/C][C]0.022815[/C][/ROW]
[ROW][C]2[/C][C]-0.045872[/C][C]-0.3523[/C][C]0.362917[/C][/ROW]
[ROW][C]3[/C][C]0.174837[/C][C]1.3429[/C][C]0.092217[/C][/ROW]
[ROW][C]4[/C][C]-0.104466[/C][C]-0.8024[/C][C]0.212765[/C][/ROW]
[ROW][C]5[/C][C]0.000487[/C][C]0.0037[/C][C]0.498514[/C][/ROW]
[ROW][C]6[/C][C]0.0594[/C][C]0.4563[/C][C]0.324939[/C][/ROW]
[ROW][C]7[/C][C]0.045029[/C][C]0.3459[/C][C]0.365334[/C][/ROW]
[ROW][C]8[/C][C]0.045185[/C][C]0.3471[/C][C]0.364886[/C][/ROW]
[ROW][C]9[/C][C]0.081592[/C][C]0.6267[/C][C]0.266631[/C][/ROW]
[ROW][C]10[/C][C]-0.072123[/C][C]-0.554[/C][C]0.290842[/C][/ROW]
[ROW][C]11[/C][C]-0.133757[/C][C]-1.0274[/C][C]0.154211[/C][/ROW]
[ROW][C]12[/C][C]0.146597[/C][C]1.126[/C][C]0.132356[/C][/ROW]
[ROW][C]13[/C][C]-0.161144[/C][C]-1.2378[/C][C]0.110352[/C][/ROW]
[ROW][C]14[/C][C]0.030406[/C][C]0.2336[/C][C]0.408069[/C][/ROW]
[ROW][C]15[/C][C]0.054682[/C][C]0.42[/C][C]0.337999[/C][/ROW]
[ROW][C]16[/C][C]-0.036724[/C][C]-0.2821[/C][C]0.389433[/C][/ROW]
[ROW][C]17[/C][C]0.139629[/C][C]1.0725[/C][C]0.143929[/C][/ROW]
[ROW][C]18[/C][C]-0.006481[/C][C]-0.0498[/C][C]0.480233[/C][/ROW]
[ROW][C]19[/C][C]-0.064313[/C][C]-0.494[/C][C]0.31157[/C][/ROW]
[ROW][C]20[/C][C]-0.150548[/C][C]-1.1564[/C][C]0.126093[/C][/ROW]
[ROW][C]21[/C][C]0.134075[/C][C]1.0298[/C][C]0.153642[/C][/ROW]
[ROW][C]22[/C][C]-0.020405[/C][C]-0.1567[/C][C]0.437995[/C][/ROW]
[ROW][C]23[/C][C]-0.119787[/C][C]-0.9201[/C][C]0.180633[/C][/ROW]
[ROW][C]24[/C][C]-0.076843[/C][C]-0.5902[/C][C]0.278641[/C][/ROW]
[ROW][C]25[/C][C]-0.190295[/C][C]-1.4617[/C][C]0.074567[/C][/ROW]
[ROW][C]26[/C][C]-0.108243[/C][C]-0.8314[/C][C]0.204541[/C][/ROW]
[ROW][C]27[/C][C]-0.143537[/C][C]-1.1025[/C][C]0.137355[/C][/ROW]
[ROW][C]28[/C][C]0.083287[/C][C]0.6397[/C][C]0.262408[/C][/ROW]
[ROW][C]29[/C][C]0.058967[/C][C]0.4529[/C][C]0.326129[/C][/ROW]
[ROW][C]30[/C][C]-0.0295[/C][C]-0.2266[/C][C]0.410761[/C][/ROW]
[ROW][C]31[/C][C]0.018113[/C][C]0.1391[/C][C]0.444912[/C][/ROW]
[ROW][C]32[/C][C]0.156128[/C][C]1.1992[/C][C]0.117614[/C][/ROW]
[ROW][C]33[/C][C]-0.060889[/C][C]-0.4677[/C][C]0.320862[/C][/ROW]
[ROW][C]34[/C][C]0.046736[/C][C]0.359[/C][C]0.360444[/C][/ROW]
[ROW][C]35[/C][C]0.030487[/C][C]0.2342[/C][C]0.407829[/C][/ROW]
[ROW][C]36[/C][C]0.049598[/C][C]0.381[/C][C]0.352298[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59514&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59514&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
10.2658452.0420.022815
2-0.045872-0.35230.362917
30.1748371.34290.092217
4-0.104466-0.80240.212765
50.0004870.00370.498514
60.05940.45630.324939
70.0450290.34590.365334
80.0451850.34710.364886
90.0815920.62670.266631
10-0.072123-0.5540.290842
11-0.133757-1.02740.154211
120.1465971.1260.132356
13-0.161144-1.23780.110352
140.0304060.23360.408069
150.0546820.420.337999
16-0.036724-0.28210.389433
170.1396291.07250.143929
18-0.006481-0.04980.480233
19-0.064313-0.4940.31157
20-0.150548-1.15640.126093
210.1340751.02980.153642
22-0.020405-0.15670.437995
23-0.119787-0.92010.180633
24-0.076843-0.59020.278641
25-0.190295-1.46170.074567
26-0.108243-0.83140.204541
27-0.143537-1.10250.137355
280.0832870.63970.262408
290.0589670.45290.326129
30-0.0295-0.22660.410761
310.0181130.13910.444912
320.1561281.19920.117614
33-0.060889-0.46770.320862
340.0467360.3590.360444
350.0304870.23420.407829
360.0495980.3810.352298


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 ;
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')