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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, 24 Dec 2010 14:36:48 +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/24/t1293201291hlc1p2aezr78o9f.htm/, Retrieved Tue, 30 Apr 2024 04:36:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=115012, Retrieved Tue, 30 Apr 2024 04:36:18 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact141

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] [] [2009-11-27 12:15:02] [ebd107afac1bd6180acb277edd05815b]
-    D            [(Partial) Autocorrelation Function] [] [2010-12-24 14:36:48] [817f44ab92560f82acbc5e6c80d9a294] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
19685.6
19601.7
16006.9
17681.2
19790.4
17014.2
17424.5
18908.9
15692.1
15160
15794.3
16032.1
16065
16236.8
12521
14762.1
15446.9
13635
14212.6
15021.7
14134.3
13721.4
14384.5
15638.6
19711.6
20359.8
16141.4
20056.9
20605.5
19325.8
20547.7
19211.2
19009.5
18746.8
16471.5
18957.2
20515.2
18374.4
16192.9
18147.5
19301.4
18344.7
17183.6
19630
17167.2
17428.5
16016.5
18466.5
18406.6
18174.1
14851.9
16260.7
18329.6
18003.8
15903.8
19554.2
16554.2
16198.9
16571.8
17535.2
16198.1

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'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 & 1 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115012&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115012&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115012&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'RServer@AstonUniversity' @ vre.aston.ac.uk






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.5251144.10136.2e-05
20.3429072.67820.004749
30.4952523.8680.000135
40.4387013.42640.00055
50.2561622.00070.024941
60.2655282.07380.021161
70.1000740.78160.218735
80.0845590.66040.255734
9-0.069013-0.5390.295923
10-0.241717-1.88790.031901
11-0.158025-1.23420.110929
120.040730.31810.375744
13-0.259647-2.02790.023472
14-0.388976-3.0380.001751
15-0.285973-2.23350.014596
16-0.243141-1.8990.031149
17-0.292386-2.28360.012945
18-0.25967-2.02810.023462
19-0.258126-2.0160.024104
20-0.176317-1.37710.08676
21-0.247993-1.93690.028697
22-0.279167-2.18040.016549
23-0.101728-0.79450.214985
240.0519020.40540.343312
25-0.069291-0.54120.295177
26-0.147336-1.15070.127167
27-0.053323-0.41650.339265
280.0306730.23960.405735
29-0.013504-0.10550.458176
30-0.001643-0.01280.494903
31-0.008147-0.06360.474738
320.0191210.14930.440889
33-0.033484-0.26150.397286
34-0.047446-0.37060.356122
350.0172190.13450.446732
360.1333871.04180.150812

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.525114 & 4.1013 & 6.2e-05 \tabularnewline
2 & 0.342907 & 2.6782 & 0.004749 \tabularnewline
3 & 0.495252 & 3.868 & 0.000135 \tabularnewline
4 & 0.438701 & 3.4264 & 0.00055 \tabularnewline
5 & 0.256162 & 2.0007 & 0.024941 \tabularnewline
6 & 0.265528 & 2.0738 & 0.021161 \tabularnewline
7 & 0.100074 & 0.7816 & 0.218735 \tabularnewline
8 & 0.084559 & 0.6604 & 0.255734 \tabularnewline
9 & -0.069013 & -0.539 & 0.295923 \tabularnewline
10 & -0.241717 & -1.8879 & 0.031901 \tabularnewline
11 & -0.158025 & -1.2342 & 0.110929 \tabularnewline
12 & 0.04073 & 0.3181 & 0.375744 \tabularnewline
13 & -0.259647 & -2.0279 & 0.023472 \tabularnewline
14 & -0.388976 & -3.038 & 0.001751 \tabularnewline
15 & -0.285973 & -2.2335 & 0.014596 \tabularnewline
16 & -0.243141 & -1.899 & 0.031149 \tabularnewline
17 & -0.292386 & -2.2836 & 0.012945 \tabularnewline
18 & -0.25967 & -2.0281 & 0.023462 \tabularnewline
19 & -0.258126 & -2.016 & 0.024104 \tabularnewline
20 & -0.176317 & -1.3771 & 0.08676 \tabularnewline
21 & -0.247993 & -1.9369 & 0.028697 \tabularnewline
22 & -0.279167 & -2.1804 & 0.016549 \tabularnewline
23 & -0.101728 & -0.7945 & 0.214985 \tabularnewline
24 & 0.051902 & 0.4054 & 0.343312 \tabularnewline
25 & -0.069291 & -0.5412 & 0.295177 \tabularnewline
26 & -0.147336 & -1.1507 & 0.127167 \tabularnewline
27 & -0.053323 & -0.4165 & 0.339265 \tabularnewline
28 & 0.030673 & 0.2396 & 0.405735 \tabularnewline
29 & -0.013504 & -0.1055 & 0.458176 \tabularnewline
30 & -0.001643 & -0.0128 & 0.494903 \tabularnewline
31 & -0.008147 & -0.0636 & 0.474738 \tabularnewline
32 & 0.019121 & 0.1493 & 0.440889 \tabularnewline
33 & -0.033484 & -0.2615 & 0.397286 \tabularnewline
34 & -0.047446 & -0.3706 & 0.356122 \tabularnewline
35 & 0.017219 & 0.1345 & 0.446732 \tabularnewline
36 & 0.133387 & 1.0418 & 0.150812 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115012&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]0.525114[/C][C]4.1013[/C][C]6.2e-05[/C][/ROW]
[ROW][C]2[/C][C]0.342907[/C][C]2.6782[/C][C]0.004749[/C][/ROW]
[ROW][C]3[/C][C]0.495252[/C][C]3.868[/C][C]0.000135[/C][/ROW]
[ROW][C]4[/C][C]0.438701[/C][C]3.4264[/C][C]0.00055[/C][/ROW]
[ROW][C]5[/C][C]0.256162[/C][C]2.0007[/C][C]0.024941[/C][/ROW]
[ROW][C]6[/C][C]0.265528[/C][C]2.0738[/C][C]0.021161[/C][/ROW]
[ROW][C]7[/C][C]0.100074[/C][C]0.7816[/C][C]0.218735[/C][/ROW]
[ROW][C]8[/C][C]0.084559[/C][C]0.6604[/C][C]0.255734[/C][/ROW]
[ROW][C]9[/C][C]-0.069013[/C][C]-0.539[/C][C]0.295923[/C][/ROW]
[ROW][C]10[/C][C]-0.241717[/C][C]-1.8879[/C][C]0.031901[/C][/ROW]
[ROW][C]11[/C][C]-0.158025[/C][C]-1.2342[/C][C]0.110929[/C][/ROW]
[ROW][C]12[/C][C]0.04073[/C][C]0.3181[/C][C]0.375744[/C][/ROW]
[ROW][C]13[/C][C]-0.259647[/C][C]-2.0279[/C][C]0.023472[/C][/ROW]
[ROW][C]14[/C][C]-0.388976[/C][C]-3.038[/C][C]0.001751[/C][/ROW]
[ROW][C]15[/C][C]-0.285973[/C][C]-2.2335[/C][C]0.014596[/C][/ROW]
[ROW][C]16[/C][C]-0.243141[/C][C]-1.899[/C][C]0.031149[/C][/ROW]
[ROW][C]17[/C][C]-0.292386[/C][C]-2.2836[/C][C]0.012945[/C][/ROW]
[ROW][C]18[/C][C]-0.25967[/C][C]-2.0281[/C][C]0.023462[/C][/ROW]
[ROW][C]19[/C][C]-0.258126[/C][C]-2.016[/C][C]0.024104[/C][/ROW]
[ROW][C]20[/C][C]-0.176317[/C][C]-1.3771[/C][C]0.08676[/C][/ROW]
[ROW][C]21[/C][C]-0.247993[/C][C]-1.9369[/C][C]0.028697[/C][/ROW]
[ROW][C]22[/C][C]-0.279167[/C][C]-2.1804[/C][C]0.016549[/C][/ROW]
[ROW][C]23[/C][C]-0.101728[/C][C]-0.7945[/C][C]0.214985[/C][/ROW]
[ROW][C]24[/C][C]0.051902[/C][C]0.4054[/C][C]0.343312[/C][/ROW]
[ROW][C]25[/C][C]-0.069291[/C][C]-0.5412[/C][C]0.295177[/C][/ROW]
[ROW][C]26[/C][C]-0.147336[/C][C]-1.1507[/C][C]0.127167[/C][/ROW]
[ROW][C]27[/C][C]-0.053323[/C][C]-0.4165[/C][C]0.339265[/C][/ROW]
[ROW][C]28[/C][C]0.030673[/C][C]0.2396[/C][C]0.405735[/C][/ROW]
[ROW][C]29[/C][C]-0.013504[/C][C]-0.1055[/C][C]0.458176[/C][/ROW]
[ROW][C]30[/C][C]-0.001643[/C][C]-0.0128[/C][C]0.494903[/C][/ROW]
[ROW][C]31[/C][C]-0.008147[/C][C]-0.0636[/C][C]0.474738[/C][/ROW]
[ROW][C]32[/C][C]0.019121[/C][C]0.1493[/C][C]0.440889[/C][/ROW]
[ROW][C]33[/C][C]-0.033484[/C][C]-0.2615[/C][C]0.397286[/C][/ROW]
[ROW][C]34[/C][C]-0.047446[/C][C]-0.3706[/C][C]0.356122[/C][/ROW]
[ROW][C]35[/C][C]0.017219[/C][C]0.1345[/C][C]0.446732[/C][/ROW]
[ROW][C]36[/C][C]0.133387[/C][C]1.0418[/C][C]0.150812[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115012&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115012&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
10.5251144.10136.2e-05
20.3429072.67820.004749
30.4952523.8680.000135
40.4387013.42640.00055
50.2561622.00070.024941
60.2655282.07380.021161
70.1000740.78160.218735
80.0845590.66040.255734
9-0.069013-0.5390.295923
10-0.241717-1.88790.031901
11-0.158025-1.23420.110929
120.040730.31810.375744
13-0.259647-2.02790.023472
14-0.388976-3.0380.001751
15-0.285973-2.23350.014596
16-0.243141-1.8990.031149
17-0.292386-2.28360.012945
18-0.25967-2.02810.023462
19-0.258126-2.0160.024104
20-0.176317-1.37710.08676
21-0.247993-1.93690.028697
22-0.279167-2.18040.016549
23-0.101728-0.79450.214985
240.0519020.40540.343312
25-0.069291-0.54120.295177
26-0.147336-1.15070.127167
27-0.053323-0.41650.339265
280.0306730.23960.405735
29-0.013504-0.10550.458176
30-0.001643-0.01280.494903
31-0.008147-0.06360.474738
320.0191210.14930.440889
33-0.033484-0.26150.397286
34-0.047446-0.37060.356122
350.0172190.13450.446732
360.1333871.04180.150812






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.5251144.10136.2e-05
20.0927320.72430.235837
30.3943993.08040.00155
40.0765170.59760.276153
5-0.072855-0.5690.285717
60.0208170.16260.435692
7-0.304924-2.38150.010188
80.0629890.4920.312257
9-0.352717-2.75480.003865
10-0.208125-1.62550.054605
110.0849240.66330.254826
120.3681362.87520.002776
13-0.125152-0.97750.166099
14-0.197456-1.54220.064101
15-0.208286-1.62680.054471
16-0.040676-0.31770.375902
170.083440.65170.258526
18-0.039869-0.31140.378283
190.0381990.29830.383228
200.0154830.12090.452075
21-0.006207-0.04850.480747
22-0.031402-0.24530.403539
23-0.021181-0.16540.434576
24-0.040025-0.31260.377824
250.0174590.13640.445992
26-0.13574-1.06020.146626
27-0.042626-0.33290.370167
28-0.049723-0.38830.349555
29-0.060658-0.47380.318683
300.0428990.33510.369367
31-0.150617-1.17640.122012
320.0187040.14610.442169
330.0130380.10180.459612
340.1294761.01120.157948
35-0.087887-0.68640.247525
360.0104620.08170.467571

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.525114 & 4.1013 & 6.2e-05 \tabularnewline
2 & 0.092732 & 0.7243 & 0.235837 \tabularnewline
3 & 0.394399 & 3.0804 & 0.00155 \tabularnewline
4 & 0.076517 & 0.5976 & 0.276153 \tabularnewline
5 & -0.072855 & -0.569 & 0.285717 \tabularnewline
6 & 0.020817 & 0.1626 & 0.435692 \tabularnewline
7 & -0.304924 & -2.3815 & 0.010188 \tabularnewline
8 & 0.062989 & 0.492 & 0.312257 \tabularnewline
9 & -0.352717 & -2.7548 & 0.003865 \tabularnewline
10 & -0.208125 & -1.6255 & 0.054605 \tabularnewline
11 & 0.084924 & 0.6633 & 0.254826 \tabularnewline
12 & 0.368136 & 2.8752 & 0.002776 \tabularnewline
13 & -0.125152 & -0.9775 & 0.166099 \tabularnewline
14 & -0.197456 & -1.5422 & 0.064101 \tabularnewline
15 & -0.208286 & -1.6268 & 0.054471 \tabularnewline
16 & -0.040676 & -0.3177 & 0.375902 \tabularnewline
17 & 0.08344 & 0.6517 & 0.258526 \tabularnewline
18 & -0.039869 & -0.3114 & 0.378283 \tabularnewline
19 & 0.038199 & 0.2983 & 0.383228 \tabularnewline
20 & 0.015483 & 0.1209 & 0.452075 \tabularnewline
21 & -0.006207 & -0.0485 & 0.480747 \tabularnewline
22 & -0.031402 & -0.2453 & 0.403539 \tabularnewline
23 & -0.021181 & -0.1654 & 0.434576 \tabularnewline
24 & -0.040025 & -0.3126 & 0.377824 \tabularnewline
25 & 0.017459 & 0.1364 & 0.445992 \tabularnewline
26 & -0.13574 & -1.0602 & 0.146626 \tabularnewline
27 & -0.042626 & -0.3329 & 0.370167 \tabularnewline
28 & -0.049723 & -0.3883 & 0.349555 \tabularnewline
29 & -0.060658 & -0.4738 & 0.318683 \tabularnewline
30 & 0.042899 & 0.3351 & 0.369367 \tabularnewline
31 & -0.150617 & -1.1764 & 0.122012 \tabularnewline
32 & 0.018704 & 0.1461 & 0.442169 \tabularnewline
33 & 0.013038 & 0.1018 & 0.459612 \tabularnewline
34 & 0.129476 & 1.0112 & 0.157948 \tabularnewline
35 & -0.087887 & -0.6864 & 0.247525 \tabularnewline
36 & 0.010462 & 0.0817 & 0.467571 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115012&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]0.525114[/C][C]4.1013[/C][C]6.2e-05[/C][/ROW]
[ROW][C]2[/C][C]0.092732[/C][C]0.7243[/C][C]0.235837[/C][/ROW]
[ROW][C]3[/C][C]0.394399[/C][C]3.0804[/C][C]0.00155[/C][/ROW]
[ROW][C]4[/C][C]0.076517[/C][C]0.5976[/C][C]0.276153[/C][/ROW]
[ROW][C]5[/C][C]-0.072855[/C][C]-0.569[/C][C]0.285717[/C][/ROW]
[ROW][C]6[/C][C]0.020817[/C][C]0.1626[/C][C]0.435692[/C][/ROW]
[ROW][C]7[/C][C]-0.304924[/C][C]-2.3815[/C][C]0.010188[/C][/ROW]
[ROW][C]8[/C][C]0.062989[/C][C]0.492[/C][C]0.312257[/C][/ROW]
[ROW][C]9[/C][C]-0.352717[/C][C]-2.7548[/C][C]0.003865[/C][/ROW]
[ROW][C]10[/C][C]-0.208125[/C][C]-1.6255[/C][C]0.054605[/C][/ROW]
[ROW][C]11[/C][C]0.084924[/C][C]0.6633[/C][C]0.254826[/C][/ROW]
[ROW][C]12[/C][C]0.368136[/C][C]2.8752[/C][C]0.002776[/C][/ROW]
[ROW][C]13[/C][C]-0.125152[/C][C]-0.9775[/C][C]0.166099[/C][/ROW]
[ROW][C]14[/C][C]-0.197456[/C][C]-1.5422[/C][C]0.064101[/C][/ROW]
[ROW][C]15[/C][C]-0.208286[/C][C]-1.6268[/C][C]0.054471[/C][/ROW]
[ROW][C]16[/C][C]-0.040676[/C][C]-0.3177[/C][C]0.375902[/C][/ROW]
[ROW][C]17[/C][C]0.08344[/C][C]0.6517[/C][C]0.258526[/C][/ROW]
[ROW][C]18[/C][C]-0.039869[/C][C]-0.3114[/C][C]0.378283[/C][/ROW]
[ROW][C]19[/C][C]0.038199[/C][C]0.2983[/C][C]0.383228[/C][/ROW]
[ROW][C]20[/C][C]0.015483[/C][C]0.1209[/C][C]0.452075[/C][/ROW]
[ROW][C]21[/C][C]-0.006207[/C][C]-0.0485[/C][C]0.480747[/C][/ROW]
[ROW][C]22[/C][C]-0.031402[/C][C]-0.2453[/C][C]0.403539[/C][/ROW]
[ROW][C]23[/C][C]-0.021181[/C][C]-0.1654[/C][C]0.434576[/C][/ROW]
[ROW][C]24[/C][C]-0.040025[/C][C]-0.3126[/C][C]0.377824[/C][/ROW]
[ROW][C]25[/C][C]0.017459[/C][C]0.1364[/C][C]0.445992[/C][/ROW]
[ROW][C]26[/C][C]-0.13574[/C][C]-1.0602[/C][C]0.146626[/C][/ROW]
[ROW][C]27[/C][C]-0.042626[/C][C]-0.3329[/C][C]0.370167[/C][/ROW]
[ROW][C]28[/C][C]-0.049723[/C][C]-0.3883[/C][C]0.349555[/C][/ROW]
[ROW][C]29[/C][C]-0.060658[/C][C]-0.4738[/C][C]0.318683[/C][/ROW]
[ROW][C]30[/C][C]0.042899[/C][C]0.3351[/C][C]0.369367[/C][/ROW]
[ROW][C]31[/C][C]-0.150617[/C][C]-1.1764[/C][C]0.122012[/C][/ROW]
[ROW][C]32[/C][C]0.018704[/C][C]0.1461[/C][C]0.442169[/C][/ROW]
[ROW][C]33[/C][C]0.013038[/C][C]0.1018[/C][C]0.459612[/C][/ROW]
[ROW][C]34[/C][C]0.129476[/C][C]1.0112[/C][C]0.157948[/C][/ROW]
[ROW][C]35[/C][C]-0.087887[/C][C]-0.6864[/C][C]0.247525[/C][/ROW]
[ROW][C]36[/C][C]0.010462[/C][C]0.0817[/C][C]0.467571[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115012&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115012&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
10.5251144.10136.2e-05
20.0927320.72430.235837
30.3943993.08040.00155
40.0765170.59760.276153
5-0.072855-0.5690.285717
60.0208170.16260.435692
7-0.304924-2.38150.010188
80.0629890.4920.312257
9-0.352717-2.75480.003865
10-0.208125-1.62550.054605
110.0849240.66330.254826
120.3681362.87520.002776
13-0.125152-0.97750.166099
14-0.197456-1.54220.064101
15-0.208286-1.62680.054471
16-0.040676-0.31770.375902
170.083440.65170.258526
18-0.039869-0.31140.378283
190.0381990.29830.383228
200.0154830.12090.452075
21-0.006207-0.04850.480747
22-0.031402-0.24530.403539
23-0.021181-0.16540.434576
24-0.040025-0.31260.377824
250.0174590.13640.445992
26-0.13574-1.06020.146626
27-0.042626-0.33290.370167
28-0.049723-0.38830.349555
29-0.060658-0.47380.318683
300.0428990.33510.369367
31-0.150617-1.17640.122012
320.0187040.14610.442169
330.0130380.10180.459612
340.1294761.01120.157948
35-0.087887-0.68640.247525
360.0104620.08170.467571


Figures (Output of Computation)

Input Parameters & R Code

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