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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 computationTue, 24 Nov 2009 09:20:41 -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/24/t1259079756oojz2t3gbsbgf0c.htm/, Retrieved Fri, 29 Mar 2024 05:51:17 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59147, Retrieved Fri, 29 Mar 2024 05:51:17 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsws8ma1.3
Estimated Impact114
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] [] [2009-11-24 16:20:41] [9ea4b07b6662a0f40f92decdf1e3b5d5] [Current]
-   PD            [(Partial) Autocorrelation Function] [] [2009-11-26 16:27:14] [1e83ffa964db6f7ea6ccc4e7b5acbbff]
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Dataseries X:
2756.76
2849.27
2921.44
2981.85
3080.58
3106.22
3119.31
3061.26
3097.31
3161.69
3257.16
3277.01
3295.32
3363.99
3494.17
3667.03
3813.06
3917.96
3895.51
3801.06
3570.12
3701.61
3862.27
3970.1
4138.52
4199.75
4290.89
4443.91
4502.64
4356.98
4591.27
4696.96
4621.4
4562.84
4202.52
4296.49
4435.23
4105.18
4116.68
3844.49
3720.98
3674.4
3857.62
3801.06
3504.37
3032.6
3047.03
2962.34
2197.82
2014.45
1862.83
1905.41
1810.99
1670.07
1864.44
2052.02
2029.6
2070.83
2293.41
2443.27




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=59147&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=59147&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59147&T=0

As an alternative you can also use a 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
10.9670056.69960
20.9238536.40060
30.8758816.06830
40.8173145.66250
50.7558845.23692e-06
60.6758554.68251.2e-05
70.5891244.08168.4e-05
80.512213.54870.000439
90.433673.00460.002109
100.3541742.45380.008908
110.2742961.90040.031699
120.1858471.28760.102031
130.1134960.78630.217772
140.0471860.32690.372576
15-0.025105-0.17390.431326
16-0.093862-0.65030.2593
17-0.159399-1.10440.137473
18-0.210307-1.45710.075807
19-0.252554-1.74970.043277
20-0.299672-2.07620.021627
21-0.342845-2.37530.010788
22-0.376828-2.61070.006009
23-0.395469-2.73990.004302
24-0.404723-2.8040.003632
25-0.409286-2.83560.003338
26-0.409319-2.83580.003336
27-0.404514-2.80260.003646
28-0.395053-2.7370.004334
29-0.386266-2.67610.005079
30-0.378469-2.62210.005837
31-0.369964-2.56320.006781
32-0.355133-2.46040.008763
33-0.336813-2.33350.011929
34-0.312276-2.16350.017755
35-0.294705-2.04180.023345
36-0.275815-1.91090.031

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.967005 & 6.6996 & 0 \tabularnewline
2 & 0.923853 & 6.4006 & 0 \tabularnewline
3 & 0.875881 & 6.0683 & 0 \tabularnewline
4 & 0.817314 & 5.6625 & 0 \tabularnewline
5 & 0.755884 & 5.2369 & 2e-06 \tabularnewline
6 & 0.675855 & 4.6825 & 1.2e-05 \tabularnewline
7 & 0.589124 & 4.0816 & 8.4e-05 \tabularnewline
8 & 0.51221 & 3.5487 & 0.000439 \tabularnewline
9 & 0.43367 & 3.0046 & 0.002109 \tabularnewline
10 & 0.354174 & 2.4538 & 0.008908 \tabularnewline
11 & 0.274296 & 1.9004 & 0.031699 \tabularnewline
12 & 0.185847 & 1.2876 & 0.102031 \tabularnewline
13 & 0.113496 & 0.7863 & 0.217772 \tabularnewline
14 & 0.047186 & 0.3269 & 0.372576 \tabularnewline
15 & -0.025105 & -0.1739 & 0.431326 \tabularnewline
16 & -0.093862 & -0.6503 & 0.2593 \tabularnewline
17 & -0.159399 & -1.1044 & 0.137473 \tabularnewline
18 & -0.210307 & -1.4571 & 0.075807 \tabularnewline
19 & -0.252554 & -1.7497 & 0.043277 \tabularnewline
20 & -0.299672 & -2.0762 & 0.021627 \tabularnewline
21 & -0.342845 & -2.3753 & 0.010788 \tabularnewline
22 & -0.376828 & -2.6107 & 0.006009 \tabularnewline
23 & -0.395469 & -2.7399 & 0.004302 \tabularnewline
24 & -0.404723 & -2.804 & 0.003632 \tabularnewline
25 & -0.409286 & -2.8356 & 0.003338 \tabularnewline
26 & -0.409319 & -2.8358 & 0.003336 \tabularnewline
27 & -0.404514 & -2.8026 & 0.003646 \tabularnewline
28 & -0.395053 & -2.737 & 0.004334 \tabularnewline
29 & -0.386266 & -2.6761 & 0.005079 \tabularnewline
30 & -0.378469 & -2.6221 & 0.005837 \tabularnewline
31 & -0.369964 & -2.5632 & 0.006781 \tabularnewline
32 & -0.355133 & -2.4604 & 0.008763 \tabularnewline
33 & -0.336813 & -2.3335 & 0.011929 \tabularnewline
34 & -0.312276 & -2.1635 & 0.017755 \tabularnewline
35 & -0.294705 & -2.0418 & 0.023345 \tabularnewline
36 & -0.275815 & -1.9109 & 0.031 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59147&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]0.967005[/C][C]6.6996[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.923853[/C][C]6.4006[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.875881[/C][C]6.0683[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.817314[/C][C]5.6625[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.755884[/C][C]5.2369[/C][C]2e-06[/C][/ROW]
[ROW][C]6[/C][C]0.675855[/C][C]4.6825[/C][C]1.2e-05[/C][/ROW]
[ROW][C]7[/C][C]0.589124[/C][C]4.0816[/C][C]8.4e-05[/C][/ROW]
[ROW][C]8[/C][C]0.51221[/C][C]3.5487[/C][C]0.000439[/C][/ROW]
[ROW][C]9[/C][C]0.43367[/C][C]3.0046[/C][C]0.002109[/C][/ROW]
[ROW][C]10[/C][C]0.354174[/C][C]2.4538[/C][C]0.008908[/C][/ROW]
[ROW][C]11[/C][C]0.274296[/C][C]1.9004[/C][C]0.031699[/C][/ROW]
[ROW][C]12[/C][C]0.185847[/C][C]1.2876[/C][C]0.102031[/C][/ROW]
[ROW][C]13[/C][C]0.113496[/C][C]0.7863[/C][C]0.217772[/C][/ROW]
[ROW][C]14[/C][C]0.047186[/C][C]0.3269[/C][C]0.372576[/C][/ROW]
[ROW][C]15[/C][C]-0.025105[/C][C]-0.1739[/C][C]0.431326[/C][/ROW]
[ROW][C]16[/C][C]-0.093862[/C][C]-0.6503[/C][C]0.2593[/C][/ROW]
[ROW][C]17[/C][C]-0.159399[/C][C]-1.1044[/C][C]0.137473[/C][/ROW]
[ROW][C]18[/C][C]-0.210307[/C][C]-1.4571[/C][C]0.075807[/C][/ROW]
[ROW][C]19[/C][C]-0.252554[/C][C]-1.7497[/C][C]0.043277[/C][/ROW]
[ROW][C]20[/C][C]-0.299672[/C][C]-2.0762[/C][C]0.021627[/C][/ROW]
[ROW][C]21[/C][C]-0.342845[/C][C]-2.3753[/C][C]0.010788[/C][/ROW]
[ROW][C]22[/C][C]-0.376828[/C][C]-2.6107[/C][C]0.006009[/C][/ROW]
[ROW][C]23[/C][C]-0.395469[/C][C]-2.7399[/C][C]0.004302[/C][/ROW]
[ROW][C]24[/C][C]-0.404723[/C][C]-2.804[/C][C]0.003632[/C][/ROW]
[ROW][C]25[/C][C]-0.409286[/C][C]-2.8356[/C][C]0.003338[/C][/ROW]
[ROW][C]26[/C][C]-0.409319[/C][C]-2.8358[/C][C]0.003336[/C][/ROW]
[ROW][C]27[/C][C]-0.404514[/C][C]-2.8026[/C][C]0.003646[/C][/ROW]
[ROW][C]28[/C][C]-0.395053[/C][C]-2.737[/C][C]0.004334[/C][/ROW]
[ROW][C]29[/C][C]-0.386266[/C][C]-2.6761[/C][C]0.005079[/C][/ROW]
[ROW][C]30[/C][C]-0.378469[/C][C]-2.6221[/C][C]0.005837[/C][/ROW]
[ROW][C]31[/C][C]-0.369964[/C][C]-2.5632[/C][C]0.006781[/C][/ROW]
[ROW][C]32[/C][C]-0.355133[/C][C]-2.4604[/C][C]0.008763[/C][/ROW]
[ROW][C]33[/C][C]-0.336813[/C][C]-2.3335[/C][C]0.011929[/C][/ROW]
[ROW][C]34[/C][C]-0.312276[/C][C]-2.1635[/C][C]0.017755[/C][/ROW]
[ROW][C]35[/C][C]-0.294705[/C][C]-2.0418[/C][C]0.023345[/C][/ROW]
[ROW][C]36[/C][C]-0.275815[/C][C]-1.9109[/C][C]0.031[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59147&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59147&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.9670056.69960
20.9238536.40060
30.8758816.06830
40.8173145.66250
50.7558845.23692e-06
60.6758554.68251.2e-05
70.5891244.08168.4e-05
80.512213.54870.000439
90.433673.00460.002109
100.3541742.45380.008908
110.2742961.90040.031699
120.1858471.28760.102031
130.1134960.78630.217772
140.0471860.32690.372576
15-0.025105-0.17390.431326
16-0.093862-0.65030.2593
17-0.159399-1.10440.137473
18-0.210307-1.45710.075807
19-0.252554-1.74970.043277
20-0.299672-2.07620.021627
21-0.342845-2.37530.010788
22-0.376828-2.61070.006009
23-0.395469-2.73990.004302
24-0.404723-2.8040.003632
25-0.409286-2.83560.003338
26-0.409319-2.83580.003336
27-0.404514-2.80260.003646
28-0.395053-2.7370.004334
29-0.386266-2.67610.005079
30-0.378469-2.62210.005837
31-0.369964-2.56320.006781
32-0.355133-2.46040.008763
33-0.336813-2.33350.011929
34-0.312276-2.16350.017755
35-0.294705-2.04180.023345
36-0.275815-1.91090.031







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9670056.69960
2-0.173263-1.20040.117938
3-0.075165-0.52080.302465
4-0.176376-1.2220.113843
5-0.033223-0.23020.409466
6-0.322369-2.23340.015108
7-0.073153-0.50680.307302
80.1418990.98310.165243
9-0.042242-0.29270.385521
10-0.06576-0.45560.325367
11-0.032323-0.22390.411877
12-0.186176-1.28990.101639
130.1542831.06890.14523
14-0.035745-0.24760.402732
15-0.14101-0.97690.166748
16-0.058049-0.40220.344669
170.0389580.26990.394193
180.0949710.6580.256848
19-0.085285-0.59090.278689
20-0.09715-0.67310.252064
21-0.012604-0.08730.465388
220.0088940.06160.47556
230.1535211.06360.14641
24-0.06896-0.47780.317493
250.0902520.62530.267373
260.0206860.14330.44332
27-0.127542-0.88360.190648
28-0.113666-0.78750.217431
29-0.14157-0.98080.165798
300.0395080.27370.392736
310.0189270.13110.448112
320.0310140.21490.41539
330.0083430.05780.477074
340.1049690.72720.235304
35-0.108376-0.75090.228203
36-0.048404-0.33540.36941

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.967005 & 6.6996 & 0 \tabularnewline
2 & -0.173263 & -1.2004 & 0.117938 \tabularnewline
3 & -0.075165 & -0.5208 & 0.302465 \tabularnewline
4 & -0.176376 & -1.222 & 0.113843 \tabularnewline
5 & -0.033223 & -0.2302 & 0.409466 \tabularnewline
6 & -0.322369 & -2.2334 & 0.015108 \tabularnewline
7 & -0.073153 & -0.5068 & 0.307302 \tabularnewline
8 & 0.141899 & 0.9831 & 0.165243 \tabularnewline
9 & -0.042242 & -0.2927 & 0.385521 \tabularnewline
10 & -0.06576 & -0.4556 & 0.325367 \tabularnewline
11 & -0.032323 & -0.2239 & 0.411877 \tabularnewline
12 & -0.186176 & -1.2899 & 0.101639 \tabularnewline
13 & 0.154283 & 1.0689 & 0.14523 \tabularnewline
14 & -0.035745 & -0.2476 & 0.402732 \tabularnewline
15 & -0.14101 & -0.9769 & 0.166748 \tabularnewline
16 & -0.058049 & -0.4022 & 0.344669 \tabularnewline
17 & 0.038958 & 0.2699 & 0.394193 \tabularnewline
18 & 0.094971 & 0.658 & 0.256848 \tabularnewline
19 & -0.085285 & -0.5909 & 0.278689 \tabularnewline
20 & -0.09715 & -0.6731 & 0.252064 \tabularnewline
21 & -0.012604 & -0.0873 & 0.465388 \tabularnewline
22 & 0.008894 & 0.0616 & 0.47556 \tabularnewline
23 & 0.153521 & 1.0636 & 0.14641 \tabularnewline
24 & -0.06896 & -0.4778 & 0.317493 \tabularnewline
25 & 0.090252 & 0.6253 & 0.267373 \tabularnewline
26 & 0.020686 & 0.1433 & 0.44332 \tabularnewline
27 & -0.127542 & -0.8836 & 0.190648 \tabularnewline
28 & -0.113666 & -0.7875 & 0.217431 \tabularnewline
29 & -0.14157 & -0.9808 & 0.165798 \tabularnewline
30 & 0.039508 & 0.2737 & 0.392736 \tabularnewline
31 & 0.018927 & 0.1311 & 0.448112 \tabularnewline
32 & 0.031014 & 0.2149 & 0.41539 \tabularnewline
33 & 0.008343 & 0.0578 & 0.477074 \tabularnewline
34 & 0.104969 & 0.7272 & 0.235304 \tabularnewline
35 & -0.108376 & -0.7509 & 0.228203 \tabularnewline
36 & -0.048404 & -0.3354 & 0.36941 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59147&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]0.967005[/C][C]6.6996[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.173263[/C][C]-1.2004[/C][C]0.117938[/C][/ROW]
[ROW][C]3[/C][C]-0.075165[/C][C]-0.5208[/C][C]0.302465[/C][/ROW]
[ROW][C]4[/C][C]-0.176376[/C][C]-1.222[/C][C]0.113843[/C][/ROW]
[ROW][C]5[/C][C]-0.033223[/C][C]-0.2302[/C][C]0.409466[/C][/ROW]
[ROW][C]6[/C][C]-0.322369[/C][C]-2.2334[/C][C]0.015108[/C][/ROW]
[ROW][C]7[/C][C]-0.073153[/C][C]-0.5068[/C][C]0.307302[/C][/ROW]
[ROW][C]8[/C][C]0.141899[/C][C]0.9831[/C][C]0.165243[/C][/ROW]
[ROW][C]9[/C][C]-0.042242[/C][C]-0.2927[/C][C]0.385521[/C][/ROW]
[ROW][C]10[/C][C]-0.06576[/C][C]-0.4556[/C][C]0.325367[/C][/ROW]
[ROW][C]11[/C][C]-0.032323[/C][C]-0.2239[/C][C]0.411877[/C][/ROW]
[ROW][C]12[/C][C]-0.186176[/C][C]-1.2899[/C][C]0.101639[/C][/ROW]
[ROW][C]13[/C][C]0.154283[/C][C]1.0689[/C][C]0.14523[/C][/ROW]
[ROW][C]14[/C][C]-0.035745[/C][C]-0.2476[/C][C]0.402732[/C][/ROW]
[ROW][C]15[/C][C]-0.14101[/C][C]-0.9769[/C][C]0.166748[/C][/ROW]
[ROW][C]16[/C][C]-0.058049[/C][C]-0.4022[/C][C]0.344669[/C][/ROW]
[ROW][C]17[/C][C]0.038958[/C][C]0.2699[/C][C]0.394193[/C][/ROW]
[ROW][C]18[/C][C]0.094971[/C][C]0.658[/C][C]0.256848[/C][/ROW]
[ROW][C]19[/C][C]-0.085285[/C][C]-0.5909[/C][C]0.278689[/C][/ROW]
[ROW][C]20[/C][C]-0.09715[/C][C]-0.6731[/C][C]0.252064[/C][/ROW]
[ROW][C]21[/C][C]-0.012604[/C][C]-0.0873[/C][C]0.465388[/C][/ROW]
[ROW][C]22[/C][C]0.008894[/C][C]0.0616[/C][C]0.47556[/C][/ROW]
[ROW][C]23[/C][C]0.153521[/C][C]1.0636[/C][C]0.14641[/C][/ROW]
[ROW][C]24[/C][C]-0.06896[/C][C]-0.4778[/C][C]0.317493[/C][/ROW]
[ROW][C]25[/C][C]0.090252[/C][C]0.6253[/C][C]0.267373[/C][/ROW]
[ROW][C]26[/C][C]0.020686[/C][C]0.1433[/C][C]0.44332[/C][/ROW]
[ROW][C]27[/C][C]-0.127542[/C][C]-0.8836[/C][C]0.190648[/C][/ROW]
[ROW][C]28[/C][C]-0.113666[/C][C]-0.7875[/C][C]0.217431[/C][/ROW]
[ROW][C]29[/C][C]-0.14157[/C][C]-0.9808[/C][C]0.165798[/C][/ROW]
[ROW][C]30[/C][C]0.039508[/C][C]0.2737[/C][C]0.392736[/C][/ROW]
[ROW][C]31[/C][C]0.018927[/C][C]0.1311[/C][C]0.448112[/C][/ROW]
[ROW][C]32[/C][C]0.031014[/C][C]0.2149[/C][C]0.41539[/C][/ROW]
[ROW][C]33[/C][C]0.008343[/C][C]0.0578[/C][C]0.477074[/C][/ROW]
[ROW][C]34[/C][C]0.104969[/C][C]0.7272[/C][C]0.235304[/C][/ROW]
[ROW][C]35[/C][C]-0.108376[/C][C]-0.7509[/C][C]0.228203[/C][/ROW]
[ROW][C]36[/C][C]-0.048404[/C][C]-0.3354[/C][C]0.36941[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59147&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59147&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9670056.69960
2-0.173263-1.20040.117938
3-0.075165-0.52080.302465
4-0.176376-1.2220.113843
5-0.033223-0.23020.409466
6-0.322369-2.23340.015108
7-0.073153-0.50680.307302
80.1418990.98310.165243
9-0.042242-0.29270.385521
10-0.06576-0.45560.325367
11-0.032323-0.22390.411877
12-0.186176-1.28990.101639
130.1542831.06890.14523
14-0.035745-0.24760.402732
15-0.14101-0.97690.166748
16-0.058049-0.40220.344669
170.0389580.26990.394193
180.0949710.6580.256848
19-0.085285-0.59090.278689
20-0.09715-0.67310.252064
21-0.012604-0.08730.465388
220.0088940.06160.47556
230.1535211.06360.14641
24-0.06896-0.47780.317493
250.0902520.62530.267373
260.0206860.14330.44332
27-0.127542-0.88360.190648
28-0.113666-0.78750.217431
29-0.14157-0.98080.165798
300.0395080.27370.392736
310.0189270.13110.448112
320.0310140.21490.41539
330.0083430.05780.477074
340.1049690.72720.235304
35-0.108376-0.75090.228203
36-0.048404-0.33540.36941



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