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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 13:29:11 -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/t1259094661kxixp7ehzg4jd7t.htm/, Retrieved Mon, 22 Jul 2024 20:48:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59268, Retrieved Mon, 22 Jul 2024 20:48:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact190
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 12:19:56] [b98453cac15ba1066b407e146608df68]
-    D          [(Partial) Autocorrelation Function] [ws 8] [2009-11-24 20:29:11] [f7d3e79b917995ba1c8c80042fc22ef9] [Current]
-   PD            [(Partial) Autocorrelation Function] [ws 8] [2009-11-25 16:54:58] [b5908418e3090fddbd22f5f0f774653d]
-   PD            [(Partial) Autocorrelation Function] [ws 8] [2009-11-25 17:07:43] [b5908418e3090fddbd22f5f0f774653d]
-   PD              [(Partial) Autocorrelation Function] [WS8] [2009-11-27 15:28:25] [37a8d600db9abe09a2528d150ccff095]
-   P               [(Partial) Autocorrelation Function] [ws 9] [2009-12-03 17:03:35] [b5908418e3090fddbd22f5f0f774653d]
-   P               [(Partial) Autocorrelation Function] [ws 9] [2009-12-03 17:05:32] [b5908418e3090fddbd22f5f0f774653d]
-   PD            [(Partial) Autocorrelation Function] [ws 8] [2009-11-25 17:10:44] [b5908418e3090fddbd22f5f0f774653d]
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Dataseries X:
9,3
9,3
8,7
8,2
8,3
8,5
8,6
8,5
8,2
8,1
7,9
8,6
8,7
8,7
8,5
8,4
8,5
8,7
8,7
8,6
8,5
8,3
8
8,2
8,1
8,1
8
7,9
7,9
8
8
7,9
8
7,7
7,2
7,5
7,3
7
7
7
7,2
7,3
7,1
6,8
6,4
6,1
6,5
7,7
7,9
7,5
6,9
6,6
6,9
7,7
8
8
7,7
7,3
7,4
8,1




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=59268&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=59268&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59268&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.8829116.1170
20.6379574.41992.8e-05
30.4072682.82160.003465
40.2803441.94230.028992
50.2617231.81330.038022
60.2827971.95930.027951
70.2694351.86670.034029
80.1908781.32240.096144
90.059820.41440.340198
10-0.074376-0.51530.304358
11-0.188512-1.3060.09888
12-0.263157-1.82320.037251
13-0.279231-1.93460.029474
14-0.255501-1.77020.041526
15-0.227637-1.57710.060669
16-0.228117-1.58040.060287
17-0.252587-1.750.043256
18-0.275083-1.90580.031335
19-0.286101-1.98220.026601
20-0.277631-1.92350.030181
21-0.26429-1.83110.036652
22-0.273056-1.89180.03228
23-0.282874-1.95980.027919
24-0.273279-1.89330.032175
25-0.236225-1.63660.054126
26-0.189354-1.31190.0979
27-0.158703-1.09950.138511
28-0.145362-1.00710.159469
29-0.126706-0.87780.1922
30-0.089449-0.61970.269186
31-0.024253-0.1680.433632
320.0367530.25460.400046
330.0659460.45690.324906
340.0716660.49650.310898
350.0816670.56580.287081
360.1072250.74290.230589

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.882911 & 6.117 & 0 \tabularnewline
2 & 0.637957 & 4.4199 & 2.8e-05 \tabularnewline
3 & 0.407268 & 2.8216 & 0.003465 \tabularnewline
4 & 0.280344 & 1.9423 & 0.028992 \tabularnewline
5 & 0.261723 & 1.8133 & 0.038022 \tabularnewline
6 & 0.282797 & 1.9593 & 0.027951 \tabularnewline
7 & 0.269435 & 1.8667 & 0.034029 \tabularnewline
8 & 0.190878 & 1.3224 & 0.096144 \tabularnewline
9 & 0.05982 & 0.4144 & 0.340198 \tabularnewline
10 & -0.074376 & -0.5153 & 0.304358 \tabularnewline
11 & -0.188512 & -1.306 & 0.09888 \tabularnewline
12 & -0.263157 & -1.8232 & 0.037251 \tabularnewline
13 & -0.279231 & -1.9346 & 0.029474 \tabularnewline
14 & -0.255501 & -1.7702 & 0.041526 \tabularnewline
15 & -0.227637 & -1.5771 & 0.060669 \tabularnewline
16 & -0.228117 & -1.5804 & 0.060287 \tabularnewline
17 & -0.252587 & -1.75 & 0.043256 \tabularnewline
18 & -0.275083 & -1.9058 & 0.031335 \tabularnewline
19 & -0.286101 & -1.9822 & 0.026601 \tabularnewline
20 & -0.277631 & -1.9235 & 0.030181 \tabularnewline
21 & -0.26429 & -1.8311 & 0.036652 \tabularnewline
22 & -0.273056 & -1.8918 & 0.03228 \tabularnewline
23 & -0.282874 & -1.9598 & 0.027919 \tabularnewline
24 & -0.273279 & -1.8933 & 0.032175 \tabularnewline
25 & -0.236225 & -1.6366 & 0.054126 \tabularnewline
26 & -0.189354 & -1.3119 & 0.0979 \tabularnewline
27 & -0.158703 & -1.0995 & 0.138511 \tabularnewline
28 & -0.145362 & -1.0071 & 0.159469 \tabularnewline
29 & -0.126706 & -0.8778 & 0.1922 \tabularnewline
30 & -0.089449 & -0.6197 & 0.269186 \tabularnewline
31 & -0.024253 & -0.168 & 0.433632 \tabularnewline
32 & 0.036753 & 0.2546 & 0.400046 \tabularnewline
33 & 0.065946 & 0.4569 & 0.324906 \tabularnewline
34 & 0.071666 & 0.4965 & 0.310898 \tabularnewline
35 & 0.081667 & 0.5658 & 0.287081 \tabularnewline
36 & 0.107225 & 0.7429 & 0.230589 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59268&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]0.882911[/C][C]6.117[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.637957[/C][C]4.4199[/C][C]2.8e-05[/C][/ROW]
[ROW][C]3[/C][C]0.407268[/C][C]2.8216[/C][C]0.003465[/C][/ROW]
[ROW][C]4[/C][C]0.280344[/C][C]1.9423[/C][C]0.028992[/C][/ROW]
[ROW][C]5[/C][C]0.261723[/C][C]1.8133[/C][C]0.038022[/C][/ROW]
[ROW][C]6[/C][C]0.282797[/C][C]1.9593[/C][C]0.027951[/C][/ROW]
[ROW][C]7[/C][C]0.269435[/C][C]1.8667[/C][C]0.034029[/C][/ROW]
[ROW][C]8[/C][C]0.190878[/C][C]1.3224[/C][C]0.096144[/C][/ROW]
[ROW][C]9[/C][C]0.05982[/C][C]0.4144[/C][C]0.340198[/C][/ROW]
[ROW][C]10[/C][C]-0.074376[/C][C]-0.5153[/C][C]0.304358[/C][/ROW]
[ROW][C]11[/C][C]-0.188512[/C][C]-1.306[/C][C]0.09888[/C][/ROW]
[ROW][C]12[/C][C]-0.263157[/C][C]-1.8232[/C][C]0.037251[/C][/ROW]
[ROW][C]13[/C][C]-0.279231[/C][C]-1.9346[/C][C]0.029474[/C][/ROW]
[ROW][C]14[/C][C]-0.255501[/C][C]-1.7702[/C][C]0.041526[/C][/ROW]
[ROW][C]15[/C][C]-0.227637[/C][C]-1.5771[/C][C]0.060669[/C][/ROW]
[ROW][C]16[/C][C]-0.228117[/C][C]-1.5804[/C][C]0.060287[/C][/ROW]
[ROW][C]17[/C][C]-0.252587[/C][C]-1.75[/C][C]0.043256[/C][/ROW]
[ROW][C]18[/C][C]-0.275083[/C][C]-1.9058[/C][C]0.031335[/C][/ROW]
[ROW][C]19[/C][C]-0.286101[/C][C]-1.9822[/C][C]0.026601[/C][/ROW]
[ROW][C]20[/C][C]-0.277631[/C][C]-1.9235[/C][C]0.030181[/C][/ROW]
[ROW][C]21[/C][C]-0.26429[/C][C]-1.8311[/C][C]0.036652[/C][/ROW]
[ROW][C]22[/C][C]-0.273056[/C][C]-1.8918[/C][C]0.03228[/C][/ROW]
[ROW][C]23[/C][C]-0.282874[/C][C]-1.9598[/C][C]0.027919[/C][/ROW]
[ROW][C]24[/C][C]-0.273279[/C][C]-1.8933[/C][C]0.032175[/C][/ROW]
[ROW][C]25[/C][C]-0.236225[/C][C]-1.6366[/C][C]0.054126[/C][/ROW]
[ROW][C]26[/C][C]-0.189354[/C][C]-1.3119[/C][C]0.0979[/C][/ROW]
[ROW][C]27[/C][C]-0.158703[/C][C]-1.0995[/C][C]0.138511[/C][/ROW]
[ROW][C]28[/C][C]-0.145362[/C][C]-1.0071[/C][C]0.159469[/C][/ROW]
[ROW][C]29[/C][C]-0.126706[/C][C]-0.8778[/C][C]0.1922[/C][/ROW]
[ROW][C]30[/C][C]-0.089449[/C][C]-0.6197[/C][C]0.269186[/C][/ROW]
[ROW][C]31[/C][C]-0.024253[/C][C]-0.168[/C][C]0.433632[/C][/ROW]
[ROW][C]32[/C][C]0.036753[/C][C]0.2546[/C][C]0.400046[/C][/ROW]
[ROW][C]33[/C][C]0.065946[/C][C]0.4569[/C][C]0.324906[/C][/ROW]
[ROW][C]34[/C][C]0.071666[/C][C]0.4965[/C][C]0.310898[/C][/ROW]
[ROW][C]35[/C][C]0.081667[/C][C]0.5658[/C][C]0.287081[/C][/ROW]
[ROW][C]36[/C][C]0.107225[/C][C]0.7429[/C][C]0.230589[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59268&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59268&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
10.8829116.1170
20.6379574.41992.8e-05
30.4072682.82160.003465
40.2803441.94230.028992
50.2617231.81330.038022
60.2827971.95930.027951
70.2694351.86670.034029
80.1908781.32240.096144
90.059820.41440.340198
10-0.074376-0.51530.304358
11-0.188512-1.3060.09888
12-0.263157-1.82320.037251
13-0.279231-1.93460.029474
14-0.255501-1.77020.041526
15-0.227637-1.57710.060669
16-0.228117-1.58040.060287
17-0.252587-1.750.043256
18-0.275083-1.90580.031335
19-0.286101-1.98220.026601
20-0.277631-1.92350.030181
21-0.26429-1.83110.036652
22-0.273056-1.89180.03228
23-0.282874-1.95980.027919
24-0.273279-1.89330.032175
25-0.236225-1.63660.054126
26-0.189354-1.31190.0979
27-0.158703-1.09950.138511
28-0.145362-1.00710.159469
29-0.126706-0.87780.1922
30-0.089449-0.61970.269186
31-0.024253-0.1680.433632
320.0367530.25460.400046
330.0659460.45690.324906
340.0716660.49650.310898
350.0816670.56580.287081
360.1072250.74290.230589







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8829116.1170
2-0.642156-4.4492.6e-05
30.3803382.63510.005647
40.1447991.00320.160398
50.0365480.25320.400592
6-0.127934-0.88630.189924
7-0.071579-0.49590.31111
8-0.070082-0.48550.314752
9-0.136743-0.94740.174094
10-0.014533-0.10070.460109
11-0.258352-1.78990.039889
120.0696780.48270.315737
130.1131330.78380.218503
14-0.111526-0.77270.221751
15-0.043863-0.30390.381263
16-0.05686-0.39390.347685
170.1333210.92370.180138
18-0.052082-0.36080.359902
19-0.149416-1.03520.152886
200.0076150.05280.479071
21-0.151023-1.04630.150328
22-0.119447-0.82760.206009
230.1307290.90570.184804
24-0.111314-0.77120.222182
250.0103520.07170.47156
26-0.065756-0.45560.325377
270.0051270.03550.485906
28-0.002689-0.01860.492608
290.1278590.88580.190062
30-0.034798-0.24110.405257
310.0194150.13450.446781
32-0.112427-0.77890.219927
33-0.037641-0.26080.397688
340.0693560.48050.316523
350.0306820.21260.41628
36-0.109069-0.75570.226775

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.882911 & 6.117 & 0 \tabularnewline
2 & -0.642156 & -4.449 & 2.6e-05 \tabularnewline
3 & 0.380338 & 2.6351 & 0.005647 \tabularnewline
4 & 0.144799 & 1.0032 & 0.160398 \tabularnewline
5 & 0.036548 & 0.2532 & 0.400592 \tabularnewline
6 & -0.127934 & -0.8863 & 0.189924 \tabularnewline
7 & -0.071579 & -0.4959 & 0.31111 \tabularnewline
8 & -0.070082 & -0.4855 & 0.314752 \tabularnewline
9 & -0.136743 & -0.9474 & 0.174094 \tabularnewline
10 & -0.014533 & -0.1007 & 0.460109 \tabularnewline
11 & -0.258352 & -1.7899 & 0.039889 \tabularnewline
12 & 0.069678 & 0.4827 & 0.315737 \tabularnewline
13 & 0.113133 & 0.7838 & 0.218503 \tabularnewline
14 & -0.111526 & -0.7727 & 0.221751 \tabularnewline
15 & -0.043863 & -0.3039 & 0.381263 \tabularnewline
16 & -0.05686 & -0.3939 & 0.347685 \tabularnewline
17 & 0.133321 & 0.9237 & 0.180138 \tabularnewline
18 & -0.052082 & -0.3608 & 0.359902 \tabularnewline
19 & -0.149416 & -1.0352 & 0.152886 \tabularnewline
20 & 0.007615 & 0.0528 & 0.479071 \tabularnewline
21 & -0.151023 & -1.0463 & 0.150328 \tabularnewline
22 & -0.119447 & -0.8276 & 0.206009 \tabularnewline
23 & 0.130729 & 0.9057 & 0.184804 \tabularnewline
24 & -0.111314 & -0.7712 & 0.222182 \tabularnewline
25 & 0.010352 & 0.0717 & 0.47156 \tabularnewline
26 & -0.065756 & -0.4556 & 0.325377 \tabularnewline
27 & 0.005127 & 0.0355 & 0.485906 \tabularnewline
28 & -0.002689 & -0.0186 & 0.492608 \tabularnewline
29 & 0.127859 & 0.8858 & 0.190062 \tabularnewline
30 & -0.034798 & -0.2411 & 0.405257 \tabularnewline
31 & 0.019415 & 0.1345 & 0.446781 \tabularnewline
32 & -0.112427 & -0.7789 & 0.219927 \tabularnewline
33 & -0.037641 & -0.2608 & 0.397688 \tabularnewline
34 & 0.069356 & 0.4805 & 0.316523 \tabularnewline
35 & 0.030682 & 0.2126 & 0.41628 \tabularnewline
36 & -0.109069 & -0.7557 & 0.226775 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59268&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]0.882911[/C][C]6.117[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.642156[/C][C]-4.449[/C][C]2.6e-05[/C][/ROW]
[ROW][C]3[/C][C]0.380338[/C][C]2.6351[/C][C]0.005647[/C][/ROW]
[ROW][C]4[/C][C]0.144799[/C][C]1.0032[/C][C]0.160398[/C][/ROW]
[ROW][C]5[/C][C]0.036548[/C][C]0.2532[/C][C]0.400592[/C][/ROW]
[ROW][C]6[/C][C]-0.127934[/C][C]-0.8863[/C][C]0.189924[/C][/ROW]
[ROW][C]7[/C][C]-0.071579[/C][C]-0.4959[/C][C]0.31111[/C][/ROW]
[ROW][C]8[/C][C]-0.070082[/C][C]-0.4855[/C][C]0.314752[/C][/ROW]
[ROW][C]9[/C][C]-0.136743[/C][C]-0.9474[/C][C]0.174094[/C][/ROW]
[ROW][C]10[/C][C]-0.014533[/C][C]-0.1007[/C][C]0.460109[/C][/ROW]
[ROW][C]11[/C][C]-0.258352[/C][C]-1.7899[/C][C]0.039889[/C][/ROW]
[ROW][C]12[/C][C]0.069678[/C][C]0.4827[/C][C]0.315737[/C][/ROW]
[ROW][C]13[/C][C]0.113133[/C][C]0.7838[/C][C]0.218503[/C][/ROW]
[ROW][C]14[/C][C]-0.111526[/C][C]-0.7727[/C][C]0.221751[/C][/ROW]
[ROW][C]15[/C][C]-0.043863[/C][C]-0.3039[/C][C]0.381263[/C][/ROW]
[ROW][C]16[/C][C]-0.05686[/C][C]-0.3939[/C][C]0.347685[/C][/ROW]
[ROW][C]17[/C][C]0.133321[/C][C]0.9237[/C][C]0.180138[/C][/ROW]
[ROW][C]18[/C][C]-0.052082[/C][C]-0.3608[/C][C]0.359902[/C][/ROW]
[ROW][C]19[/C][C]-0.149416[/C][C]-1.0352[/C][C]0.152886[/C][/ROW]
[ROW][C]20[/C][C]0.007615[/C][C]0.0528[/C][C]0.479071[/C][/ROW]
[ROW][C]21[/C][C]-0.151023[/C][C]-1.0463[/C][C]0.150328[/C][/ROW]
[ROW][C]22[/C][C]-0.119447[/C][C]-0.8276[/C][C]0.206009[/C][/ROW]
[ROW][C]23[/C][C]0.130729[/C][C]0.9057[/C][C]0.184804[/C][/ROW]
[ROW][C]24[/C][C]-0.111314[/C][C]-0.7712[/C][C]0.222182[/C][/ROW]
[ROW][C]25[/C][C]0.010352[/C][C]0.0717[/C][C]0.47156[/C][/ROW]
[ROW][C]26[/C][C]-0.065756[/C][C]-0.4556[/C][C]0.325377[/C][/ROW]
[ROW][C]27[/C][C]0.005127[/C][C]0.0355[/C][C]0.485906[/C][/ROW]
[ROW][C]28[/C][C]-0.002689[/C][C]-0.0186[/C][C]0.492608[/C][/ROW]
[ROW][C]29[/C][C]0.127859[/C][C]0.8858[/C][C]0.190062[/C][/ROW]
[ROW][C]30[/C][C]-0.034798[/C][C]-0.2411[/C][C]0.405257[/C][/ROW]
[ROW][C]31[/C][C]0.019415[/C][C]0.1345[/C][C]0.446781[/C][/ROW]
[ROW][C]32[/C][C]-0.112427[/C][C]-0.7789[/C][C]0.219927[/C][/ROW]
[ROW][C]33[/C][C]-0.037641[/C][C]-0.2608[/C][C]0.397688[/C][/ROW]
[ROW][C]34[/C][C]0.069356[/C][C]0.4805[/C][C]0.316523[/C][/ROW]
[ROW][C]35[/C][C]0.030682[/C][C]0.2126[/C][C]0.41628[/C][/ROW]
[ROW][C]36[/C][C]-0.109069[/C][C]-0.7557[/C][C]0.226775[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59268&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59268&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
10.8829116.1170
2-0.642156-4.4492.6e-05
30.3803382.63510.005647
40.1447991.00320.160398
50.0365480.25320.400592
6-0.127934-0.88630.189924
7-0.071579-0.49590.31111
8-0.070082-0.48550.314752
9-0.136743-0.94740.174094
10-0.014533-0.10070.460109
11-0.258352-1.78990.039889
120.0696780.48270.315737
130.1131330.78380.218503
14-0.111526-0.77270.221751
15-0.043863-0.30390.381263
16-0.05686-0.39390.347685
170.1333210.92370.180138
18-0.052082-0.36080.359902
19-0.149416-1.03520.152886
200.0076150.05280.479071
21-0.151023-1.04630.150328
22-0.119447-0.82760.206009
230.1307290.90570.184804
24-0.111314-0.77120.222182
250.0103520.07170.47156
26-0.065756-0.45560.325377
270.0051270.03550.485906
28-0.002689-0.01860.492608
290.1278590.88580.190062
30-0.034798-0.24110.405257
310.0194150.13450.446781
32-0.112427-0.77890.219927
33-0.037641-0.26080.397688
340.0693560.48050.316523
350.0306820.21260.41628
36-0.109069-0.75570.226775



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')