FreeStatistics.org

Free Statistics

of Irreproducible Research!

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, 12 Dec 2009 13:45:42 -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/Dec/12/t1260650795zlirjbd5qt8ziwa.htm/, Retrieved Mon, 29 Apr 2024 11:49:29 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=67142, Retrieved Mon, 29 Apr 2024 11:49:29 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact121

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] [] [2009-11-26 23:50:07] [0e3da40906c04c6abfe5eb434331b3f1]
-   P             [(Partial) Autocorrelation Function] [] [2009-12-12 20:45:42] [90c9838c596c9c0a7d0d4c412ffe5b98] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
6802.96
7132.68
7073.29
7264.5
7105.33
7218.71
7225.72
7354.25
7745.46
8070.26
8366.33
8667.51
8854.34
9218.1
9332.9
9358.31
9248.66
9401.2
9652.04
9957.38
10110.63
10169.26
10343.78
10750.21
11337.5
11786.96
12083.04
12007.74
11745.93
11051.51
11445.9
11924.88
12247.63
12690.91
12910.7
13202.12
13654.67
13862.82
13523.93
14211.17
14510.35
14289.23
14111.82
13086.59
13351.54
13747.69
12855.61
12926.93
12121.95
11731.65
11639.51
12163.78
12029.53
11234.18
9852.13
9709.04
9332.75
7108.6
6691.49
6143.05

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'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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67142&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67142&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67142&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'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.9109397.05610
20.8225346.37130
30.7281485.64020
40.6650665.15162e-06
50.5953314.61141.1e-05
60.5184314.01578.4e-05
70.4566153.53690.000394
80.40353.12550.001367
90.3518912.72570.004198
100.2917312.25970.01374
110.2331751.80620.037954
120.1721811.33370.093671
130.1208630.93620.176461
140.071040.55030.292088
150.0251190.19460.423194
16-0.027272-0.21130.416704
17-0.088279-0.68380.248365
18-0.134596-1.04260.150664
19-0.170286-1.3190.096085
20-0.199731-1.54710.063548
21-0.228019-1.76620.041223
22-0.260288-2.01620.024132
23-0.282444-2.18780.016295
24-0.297577-2.3050.01232
25-0.306587-2.37480.010386
26-0.314092-2.43290.008987
27-0.317952-2.46280.008336
28-0.325736-2.52310.00715
29-0.341896-2.64830.005161
30-0.370879-2.87280.002809
31-0.399771-3.09660.001487
32-0.410879-3.18270.001156
33-0.410925-3.1830.001155
34-0.39807-3.08340.001545
35-0.380041-2.94380.002303
36-0.35752-2.76930.003732

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.910939 & 7.0561 & 0 \tabularnewline
2 & 0.822534 & 6.3713 & 0 \tabularnewline
3 & 0.728148 & 5.6402 & 0 \tabularnewline
4 & 0.665066 & 5.1516 & 2e-06 \tabularnewline
5 & 0.595331 & 4.6114 & 1.1e-05 \tabularnewline
6 & 0.518431 & 4.0157 & 8.4e-05 \tabularnewline
7 & 0.456615 & 3.5369 & 0.000394 \tabularnewline
8 & 0.4035 & 3.1255 & 0.001367 \tabularnewline
9 & 0.351891 & 2.7257 & 0.004198 \tabularnewline
10 & 0.291731 & 2.2597 & 0.01374 \tabularnewline
11 & 0.233175 & 1.8062 & 0.037954 \tabularnewline
12 & 0.172181 & 1.3337 & 0.093671 \tabularnewline
13 & 0.120863 & 0.9362 & 0.176461 \tabularnewline
14 & 0.07104 & 0.5503 & 0.292088 \tabularnewline
15 & 0.025119 & 0.1946 & 0.423194 \tabularnewline
16 & -0.027272 & -0.2113 & 0.416704 \tabularnewline
17 & -0.088279 & -0.6838 & 0.248365 \tabularnewline
18 & -0.134596 & -1.0426 & 0.150664 \tabularnewline
19 & -0.170286 & -1.319 & 0.096085 \tabularnewline
20 & -0.199731 & -1.5471 & 0.063548 \tabularnewline
21 & -0.228019 & -1.7662 & 0.041223 \tabularnewline
22 & -0.260288 & -2.0162 & 0.024132 \tabularnewline
23 & -0.282444 & -2.1878 & 0.016295 \tabularnewline
24 & -0.297577 & -2.305 & 0.01232 \tabularnewline
25 & -0.306587 & -2.3748 & 0.010386 \tabularnewline
26 & -0.314092 & -2.4329 & 0.008987 \tabularnewline
27 & -0.317952 & -2.4628 & 0.008336 \tabularnewline
28 & -0.325736 & -2.5231 & 0.00715 \tabularnewline
29 & -0.341896 & -2.6483 & 0.005161 \tabularnewline
30 & -0.370879 & -2.8728 & 0.002809 \tabularnewline
31 & -0.399771 & -3.0966 & 0.001487 \tabularnewline
32 & -0.410879 & -3.1827 & 0.001156 \tabularnewline
33 & -0.410925 & -3.183 & 0.001155 \tabularnewline
34 & -0.39807 & -3.0834 & 0.001545 \tabularnewline
35 & -0.380041 & -2.9438 & 0.002303 \tabularnewline
36 & -0.35752 & -2.7693 & 0.003732 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67142&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]0.910939[/C][C]7.0561[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.822534[/C][C]6.3713[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.728148[/C][C]5.6402[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.665066[/C][C]5.1516[/C][C]2e-06[/C][/ROW]
[ROW][C]5[/C][C]0.595331[/C][C]4.6114[/C][C]1.1e-05[/C][/ROW]
[ROW][C]6[/C][C]0.518431[/C][C]4.0157[/C][C]8.4e-05[/C][/ROW]
[ROW][C]7[/C][C]0.456615[/C][C]3.5369[/C][C]0.000394[/C][/ROW]
[ROW][C]8[/C][C]0.4035[/C][C]3.1255[/C][C]0.001367[/C][/ROW]
[ROW][C]9[/C][C]0.351891[/C][C]2.7257[/C][C]0.004198[/C][/ROW]
[ROW][C]10[/C][C]0.291731[/C][C]2.2597[/C][C]0.01374[/C][/ROW]
[ROW][C]11[/C][C]0.233175[/C][C]1.8062[/C][C]0.037954[/C][/ROW]
[ROW][C]12[/C][C]0.172181[/C][C]1.3337[/C][C]0.093671[/C][/ROW]
[ROW][C]13[/C][C]0.120863[/C][C]0.9362[/C][C]0.176461[/C][/ROW]
[ROW][C]14[/C][C]0.07104[/C][C]0.5503[/C][C]0.292088[/C][/ROW]
[ROW][C]15[/C][C]0.025119[/C][C]0.1946[/C][C]0.423194[/C][/ROW]
[ROW][C]16[/C][C]-0.027272[/C][C]-0.2113[/C][C]0.416704[/C][/ROW]
[ROW][C]17[/C][C]-0.088279[/C][C]-0.6838[/C][C]0.248365[/C][/ROW]
[ROW][C]18[/C][C]-0.134596[/C][C]-1.0426[/C][C]0.150664[/C][/ROW]
[ROW][C]19[/C][C]-0.170286[/C][C]-1.319[/C][C]0.096085[/C][/ROW]
[ROW][C]20[/C][C]-0.199731[/C][C]-1.5471[/C][C]0.063548[/C][/ROW]
[ROW][C]21[/C][C]-0.228019[/C][C]-1.7662[/C][C]0.041223[/C][/ROW]
[ROW][C]22[/C][C]-0.260288[/C][C]-2.0162[/C][C]0.024132[/C][/ROW]
[ROW][C]23[/C][C]-0.282444[/C][C]-2.1878[/C][C]0.016295[/C][/ROW]
[ROW][C]24[/C][C]-0.297577[/C][C]-2.305[/C][C]0.01232[/C][/ROW]
[ROW][C]25[/C][C]-0.306587[/C][C]-2.3748[/C][C]0.010386[/C][/ROW]
[ROW][C]26[/C][C]-0.314092[/C][C]-2.4329[/C][C]0.008987[/C][/ROW]
[ROW][C]27[/C][C]-0.317952[/C][C]-2.4628[/C][C]0.008336[/C][/ROW]
[ROW][C]28[/C][C]-0.325736[/C][C]-2.5231[/C][C]0.00715[/C][/ROW]
[ROW][C]29[/C][C]-0.341896[/C][C]-2.6483[/C][C]0.005161[/C][/ROW]
[ROW][C]30[/C][C]-0.370879[/C][C]-2.8728[/C][C]0.002809[/C][/ROW]
[ROW][C]31[/C][C]-0.399771[/C][C]-3.0966[/C][C]0.001487[/C][/ROW]
[ROW][C]32[/C][C]-0.410879[/C][C]-3.1827[/C][C]0.001156[/C][/ROW]
[ROW][C]33[/C][C]-0.410925[/C][C]-3.183[/C][C]0.001155[/C][/ROW]
[ROW][C]34[/C][C]-0.39807[/C][C]-3.0834[/C][C]0.001545[/C][/ROW]
[ROW][C]35[/C][C]-0.380041[/C][C]-2.9438[/C][C]0.002303[/C][/ROW]
[ROW][C]36[/C][C]-0.35752[/C][C]-2.7693[/C][C]0.003732[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67142&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67142&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
10.9109397.05610
20.8225346.37130
30.7281485.64020
40.6650665.15162e-06
50.5953314.61141.1e-05
60.5184314.01578.4e-05
70.4566153.53690.000394
80.40353.12550.001367
90.3518912.72570.004198
100.2917312.25970.01374
110.2331751.80620.037954
120.1721811.33370.093671
130.1208630.93620.176461
140.071040.55030.292088
150.0251190.19460.423194
16-0.027272-0.21130.416704
17-0.088279-0.68380.248365
18-0.134596-1.04260.150664
19-0.170286-1.3190.096085
20-0.199731-1.54710.063548
21-0.228019-1.76620.041223
22-0.260288-2.01620.024132
23-0.282444-2.18780.016295
24-0.297577-2.3050.01232
25-0.306587-2.37480.010386
26-0.314092-2.43290.008987
27-0.317952-2.46280.008336
28-0.325736-2.52310.00715
29-0.341896-2.64830.005161
30-0.370879-2.87280.002809
31-0.399771-3.09660.001487
32-0.410879-3.18270.001156
33-0.410925-3.1830.001155
34-0.39807-3.08340.001545
35-0.380041-2.94380.002303
36-0.35752-2.76930.003732






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9109397.05610
2-0.042752-0.33120.370841
3-0.083695-0.64830.259633
40.1305951.01160.157899
5-0.078575-0.60860.272531
6-0.100581-0.77910.219493
70.0770540.59690.276423
8-0.002135-0.01650.493431
9-0.059344-0.45970.323706
10-0.055413-0.42920.334647
11-0.024214-0.18760.425926
12-0.076054-0.58910.278998
130.0003710.00290.498859
14-0.020673-0.16010.436656
15-0.036133-0.27990.390264
16-0.079725-0.61750.269606
17-0.105979-0.82090.207473
180.0298580.23130.408944
190.0054160.0420.483337
20-0.038695-0.29970.38271
21-0.005099-0.03950.484313
22-0.066594-0.51580.303932
23-0.013564-0.10510.458337
240.0062040.04810.480916
25-0.002259-0.01750.493048
26-0.011335-0.08780.465165
27-0.006409-0.04960.480286
28-0.068868-0.53340.297848
29-0.102207-0.79170.215829
30-0.11122-0.86150.196194
31-0.05603-0.4340.332919
320.0462050.35790.360835
330.001260.00980.496123
340.0100170.07760.469207
350.0188810.14620.442108
36-0.017345-0.13440.446786

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.910939 & 7.0561 & 0 \tabularnewline
2 & -0.042752 & -0.3312 & 0.370841 \tabularnewline
3 & -0.083695 & -0.6483 & 0.259633 \tabularnewline
4 & 0.130595 & 1.0116 & 0.157899 \tabularnewline
5 & -0.078575 & -0.6086 & 0.272531 \tabularnewline
6 & -0.100581 & -0.7791 & 0.219493 \tabularnewline
7 & 0.077054 & 0.5969 & 0.276423 \tabularnewline
8 & -0.002135 & -0.0165 & 0.493431 \tabularnewline
9 & -0.059344 & -0.4597 & 0.323706 \tabularnewline
10 & -0.055413 & -0.4292 & 0.334647 \tabularnewline
11 & -0.024214 & -0.1876 & 0.425926 \tabularnewline
12 & -0.076054 & -0.5891 & 0.278998 \tabularnewline
13 & 0.000371 & 0.0029 & 0.498859 \tabularnewline
14 & -0.020673 & -0.1601 & 0.436656 \tabularnewline
15 & -0.036133 & -0.2799 & 0.390264 \tabularnewline
16 & -0.079725 & -0.6175 & 0.269606 \tabularnewline
17 & -0.105979 & -0.8209 & 0.207473 \tabularnewline
18 & 0.029858 & 0.2313 & 0.408944 \tabularnewline
19 & 0.005416 & 0.042 & 0.483337 \tabularnewline
20 & -0.038695 & -0.2997 & 0.38271 \tabularnewline
21 & -0.005099 & -0.0395 & 0.484313 \tabularnewline
22 & -0.066594 & -0.5158 & 0.303932 \tabularnewline
23 & -0.013564 & -0.1051 & 0.458337 \tabularnewline
24 & 0.006204 & 0.0481 & 0.480916 \tabularnewline
25 & -0.002259 & -0.0175 & 0.493048 \tabularnewline
26 & -0.011335 & -0.0878 & 0.465165 \tabularnewline
27 & -0.006409 & -0.0496 & 0.480286 \tabularnewline
28 & -0.068868 & -0.5334 & 0.297848 \tabularnewline
29 & -0.102207 & -0.7917 & 0.215829 \tabularnewline
30 & -0.11122 & -0.8615 & 0.196194 \tabularnewline
31 & -0.05603 & -0.434 & 0.332919 \tabularnewline
32 & 0.046205 & 0.3579 & 0.360835 \tabularnewline
33 & 0.00126 & 0.0098 & 0.496123 \tabularnewline
34 & 0.010017 & 0.0776 & 0.469207 \tabularnewline
35 & 0.018881 & 0.1462 & 0.442108 \tabularnewline
36 & -0.017345 & -0.1344 & 0.446786 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67142&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]0.910939[/C][C]7.0561[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.042752[/C][C]-0.3312[/C][C]0.370841[/C][/ROW]
[ROW][C]3[/C][C]-0.083695[/C][C]-0.6483[/C][C]0.259633[/C][/ROW]
[ROW][C]4[/C][C]0.130595[/C][C]1.0116[/C][C]0.157899[/C][/ROW]
[ROW][C]5[/C][C]-0.078575[/C][C]-0.6086[/C][C]0.272531[/C][/ROW]
[ROW][C]6[/C][C]-0.100581[/C][C]-0.7791[/C][C]0.219493[/C][/ROW]
[ROW][C]7[/C][C]0.077054[/C][C]0.5969[/C][C]0.276423[/C][/ROW]
[ROW][C]8[/C][C]-0.002135[/C][C]-0.0165[/C][C]0.493431[/C][/ROW]
[ROW][C]9[/C][C]-0.059344[/C][C]-0.4597[/C][C]0.323706[/C][/ROW]
[ROW][C]10[/C][C]-0.055413[/C][C]-0.4292[/C][C]0.334647[/C][/ROW]
[ROW][C]11[/C][C]-0.024214[/C][C]-0.1876[/C][C]0.425926[/C][/ROW]
[ROW][C]12[/C][C]-0.076054[/C][C]-0.5891[/C][C]0.278998[/C][/ROW]
[ROW][C]13[/C][C]0.000371[/C][C]0.0029[/C][C]0.498859[/C][/ROW]
[ROW][C]14[/C][C]-0.020673[/C][C]-0.1601[/C][C]0.436656[/C][/ROW]
[ROW][C]15[/C][C]-0.036133[/C][C]-0.2799[/C][C]0.390264[/C][/ROW]
[ROW][C]16[/C][C]-0.079725[/C][C]-0.6175[/C][C]0.269606[/C][/ROW]
[ROW][C]17[/C][C]-0.105979[/C][C]-0.8209[/C][C]0.207473[/C][/ROW]
[ROW][C]18[/C][C]0.029858[/C][C]0.2313[/C][C]0.408944[/C][/ROW]
[ROW][C]19[/C][C]0.005416[/C][C]0.042[/C][C]0.483337[/C][/ROW]
[ROW][C]20[/C][C]-0.038695[/C][C]-0.2997[/C][C]0.38271[/C][/ROW]
[ROW][C]21[/C][C]-0.005099[/C][C]-0.0395[/C][C]0.484313[/C][/ROW]
[ROW][C]22[/C][C]-0.066594[/C][C]-0.5158[/C][C]0.303932[/C][/ROW]
[ROW][C]23[/C][C]-0.013564[/C][C]-0.1051[/C][C]0.458337[/C][/ROW]
[ROW][C]24[/C][C]0.006204[/C][C]0.0481[/C][C]0.480916[/C][/ROW]
[ROW][C]25[/C][C]-0.002259[/C][C]-0.0175[/C][C]0.493048[/C][/ROW]
[ROW][C]26[/C][C]-0.011335[/C][C]-0.0878[/C][C]0.465165[/C][/ROW]
[ROW][C]27[/C][C]-0.006409[/C][C]-0.0496[/C][C]0.480286[/C][/ROW]
[ROW][C]28[/C][C]-0.068868[/C][C]-0.5334[/C][C]0.297848[/C][/ROW]
[ROW][C]29[/C][C]-0.102207[/C][C]-0.7917[/C][C]0.215829[/C][/ROW]
[ROW][C]30[/C][C]-0.11122[/C][C]-0.8615[/C][C]0.196194[/C][/ROW]
[ROW][C]31[/C][C]-0.05603[/C][C]-0.434[/C][C]0.332919[/C][/ROW]
[ROW][C]32[/C][C]0.046205[/C][C]0.3579[/C][C]0.360835[/C][/ROW]
[ROW][C]33[/C][C]0.00126[/C][C]0.0098[/C][C]0.496123[/C][/ROW]
[ROW][C]34[/C][C]0.010017[/C][C]0.0776[/C][C]0.469207[/C][/ROW]
[ROW][C]35[/C][C]0.018881[/C][C]0.1462[/C][C]0.442108[/C][/ROW]
[ROW][C]36[/C][C]-0.017345[/C][C]-0.1344[/C][C]0.446786[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67142&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67142&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
10.9109397.05610
2-0.042752-0.33120.370841
3-0.083695-0.64830.259633
40.1305951.01160.157899
5-0.078575-0.60860.272531
6-0.100581-0.77910.219493
70.0770540.59690.276423
8-0.002135-0.01650.493431
9-0.059344-0.45970.323706
10-0.055413-0.42920.334647
11-0.024214-0.18760.425926
12-0.076054-0.58910.278998
130.0003710.00290.498859
14-0.020673-0.16010.436656
15-0.036133-0.27990.390264
16-0.079725-0.61750.269606
17-0.105979-0.82090.207473
180.0298580.23130.408944
190.0054160.0420.483337
20-0.038695-0.29970.38271
21-0.005099-0.03950.484313
22-0.066594-0.51580.303932
23-0.013564-0.10510.458337
240.0062040.04810.480916
25-0.002259-0.01750.493048
26-0.011335-0.08780.465165
27-0.006409-0.04960.480286
28-0.068868-0.53340.297848
29-0.102207-0.79170.215829
30-0.11122-0.86150.196194
31-0.05603-0.4340.332919
320.0462050.35790.360835
330.001260.00980.496123
340.0100170.07760.469207
350.0188810.14620.442108
36-0.017345-0.13440.446786


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = 0.0 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = 0.0 ; par3 = 0 ; 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')