Free Statistics

of Irreproducible Research!

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 03:04:18 -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/t12590570981v8tjxgwpj70ae3.htm/, Retrieved Fri, 14 Jun 2024 19:56:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=58972, Retrieved Fri, 14 Jun 2024 19:56:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact232
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 12:26:39] [b98453cac15ba1066b407e146608df68]
-    D          [(Partial) Autocorrelation Function] [] [2009-11-24 10:04:18] [2ffc7e281e02b99889abd2ccc65ed6c3] [Current]
-    D            [(Partial) Autocorrelation Function] [] [2009-12-18 11:21:56] [fef2f8976fa1eef1b54e2cee317fe737]
Feedback Forum

Post a new message
Dataseries X:
95.1
97
112.7
102.9
97.4
111.4
87.4
96.8
114.1
110.3
103.9
101.6
94.6
95.9
104.7
102.8
98.1
113.9
80.9
95.7
113.2
105.9
108.8
102.3
99
100.7
115.5
100.7
109.9
114.6
85.4
100.5
114.8
116.5
112.9
102
106
105.3
118.8
106.1
109.3
117.2
92.5
104.2
112.5
122.4
113.3
100
110.7
112.8
109.8
117.3
109.1
115.9
96.0




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=58972&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=58972&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=58972&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
1-0.653552-4.23556.1e-05
20.0888740.5760.283855
30.1742681.12940.132572
4-0.091083-0.59030.27908
5-0.130821-0.84780.200672
60.2461671.59530.059066
7-0.137715-0.89250.188606
8-0.07929-0.51390.305023
90.1931811.2520.108757
10-0.134311-0.87040.194505
110.0337820.21890.413882
12-0.017779-0.11520.454409
130.0582990.37780.353734
14-0.112316-0.72790.235359
150.1160930.75240.228012
16-0.085959-0.55710.290216
170.0332890.21570.415119
180.0554470.35930.360572
19-0.105337-0.68270.249284
200.0237040.15360.439323
210.1285360.8330.204777
22-0.271415-1.7590.042933
230.3326882.15610.018427
24-0.254968-1.65240.052957
250.0550970.35710.361415
260.0803210.52050.302711
27-0.011949-0.07740.46932
28-0.124532-0.80710.21209
290.1444340.9360.177302
30-0.046754-0.3030.381693
31-0.084624-0.54840.293152
320.1480790.95970.171359
33-0.096991-0.62860.266517
340.0443060.28710.38771
35-0.055485-0.35960.36048
360.098720.63980.262896

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.653552 & -4.2355 & 6.1e-05 \tabularnewline
2 & 0.088874 & 0.576 & 0.283855 \tabularnewline
3 & 0.174268 & 1.1294 & 0.132572 \tabularnewline
4 & -0.091083 & -0.5903 & 0.27908 \tabularnewline
5 & -0.130821 & -0.8478 & 0.200672 \tabularnewline
6 & 0.246167 & 1.5953 & 0.059066 \tabularnewline
7 & -0.137715 & -0.8925 & 0.188606 \tabularnewline
8 & -0.07929 & -0.5139 & 0.305023 \tabularnewline
9 & 0.193181 & 1.252 & 0.108757 \tabularnewline
10 & -0.134311 & -0.8704 & 0.194505 \tabularnewline
11 & 0.033782 & 0.2189 & 0.413882 \tabularnewline
12 & -0.017779 & -0.1152 & 0.454409 \tabularnewline
13 & 0.058299 & 0.3778 & 0.353734 \tabularnewline
14 & -0.112316 & -0.7279 & 0.235359 \tabularnewline
15 & 0.116093 & 0.7524 & 0.228012 \tabularnewline
16 & -0.085959 & -0.5571 & 0.290216 \tabularnewline
17 & 0.033289 & 0.2157 & 0.415119 \tabularnewline
18 & 0.055447 & 0.3593 & 0.360572 \tabularnewline
19 & -0.105337 & -0.6827 & 0.249284 \tabularnewline
20 & 0.023704 & 0.1536 & 0.439323 \tabularnewline
21 & 0.128536 & 0.833 & 0.204777 \tabularnewline
22 & -0.271415 & -1.759 & 0.042933 \tabularnewline
23 & 0.332688 & 2.1561 & 0.018427 \tabularnewline
24 & -0.254968 & -1.6524 & 0.052957 \tabularnewline
25 & 0.055097 & 0.3571 & 0.361415 \tabularnewline
26 & 0.080321 & 0.5205 & 0.302711 \tabularnewline
27 & -0.011949 & -0.0774 & 0.46932 \tabularnewline
28 & -0.124532 & -0.8071 & 0.21209 \tabularnewline
29 & 0.144434 & 0.936 & 0.177302 \tabularnewline
30 & -0.046754 & -0.303 & 0.381693 \tabularnewline
31 & -0.084624 & -0.5484 & 0.293152 \tabularnewline
32 & 0.148079 & 0.9597 & 0.171359 \tabularnewline
33 & -0.096991 & -0.6286 & 0.266517 \tabularnewline
34 & 0.044306 & 0.2871 & 0.38771 \tabularnewline
35 & -0.055485 & -0.3596 & 0.36048 \tabularnewline
36 & 0.09872 & 0.6398 & 0.262896 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=58972&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]-0.653552[/C][C]-4.2355[/C][C]6.1e-05[/C][/ROW]
[ROW][C]2[/C][C]0.088874[/C][C]0.576[/C][C]0.283855[/C][/ROW]
[ROW][C]3[/C][C]0.174268[/C][C]1.1294[/C][C]0.132572[/C][/ROW]
[ROW][C]4[/C][C]-0.091083[/C][C]-0.5903[/C][C]0.27908[/C][/ROW]
[ROW][C]5[/C][C]-0.130821[/C][C]-0.8478[/C][C]0.200672[/C][/ROW]
[ROW][C]6[/C][C]0.246167[/C][C]1.5953[/C][C]0.059066[/C][/ROW]
[ROW][C]7[/C][C]-0.137715[/C][C]-0.8925[/C][C]0.188606[/C][/ROW]
[ROW][C]8[/C][C]-0.07929[/C][C]-0.5139[/C][C]0.305023[/C][/ROW]
[ROW][C]9[/C][C]0.193181[/C][C]1.252[/C][C]0.108757[/C][/ROW]
[ROW][C]10[/C][C]-0.134311[/C][C]-0.8704[/C][C]0.194505[/C][/ROW]
[ROW][C]11[/C][C]0.033782[/C][C]0.2189[/C][C]0.413882[/C][/ROW]
[ROW][C]12[/C][C]-0.017779[/C][C]-0.1152[/C][C]0.454409[/C][/ROW]
[ROW][C]13[/C][C]0.058299[/C][C]0.3778[/C][C]0.353734[/C][/ROW]
[ROW][C]14[/C][C]-0.112316[/C][C]-0.7279[/C][C]0.235359[/C][/ROW]
[ROW][C]15[/C][C]0.116093[/C][C]0.7524[/C][C]0.228012[/C][/ROW]
[ROW][C]16[/C][C]-0.085959[/C][C]-0.5571[/C][C]0.290216[/C][/ROW]
[ROW][C]17[/C][C]0.033289[/C][C]0.2157[/C][C]0.415119[/C][/ROW]
[ROW][C]18[/C][C]0.055447[/C][C]0.3593[/C][C]0.360572[/C][/ROW]
[ROW][C]19[/C][C]-0.105337[/C][C]-0.6827[/C][C]0.249284[/C][/ROW]
[ROW][C]20[/C][C]0.023704[/C][C]0.1536[/C][C]0.439323[/C][/ROW]
[ROW][C]21[/C][C]0.128536[/C][C]0.833[/C][C]0.204777[/C][/ROW]
[ROW][C]22[/C][C]-0.271415[/C][C]-1.759[/C][C]0.042933[/C][/ROW]
[ROW][C]23[/C][C]0.332688[/C][C]2.1561[/C][C]0.018427[/C][/ROW]
[ROW][C]24[/C][C]-0.254968[/C][C]-1.6524[/C][C]0.052957[/C][/ROW]
[ROW][C]25[/C][C]0.055097[/C][C]0.3571[/C][C]0.361415[/C][/ROW]
[ROW][C]26[/C][C]0.080321[/C][C]0.5205[/C][C]0.302711[/C][/ROW]
[ROW][C]27[/C][C]-0.011949[/C][C]-0.0774[/C][C]0.46932[/C][/ROW]
[ROW][C]28[/C][C]-0.124532[/C][C]-0.8071[/C][C]0.21209[/C][/ROW]
[ROW][C]29[/C][C]0.144434[/C][C]0.936[/C][C]0.177302[/C][/ROW]
[ROW][C]30[/C][C]-0.046754[/C][C]-0.303[/C][C]0.381693[/C][/ROW]
[ROW][C]31[/C][C]-0.084624[/C][C]-0.5484[/C][C]0.293152[/C][/ROW]
[ROW][C]32[/C][C]0.148079[/C][C]0.9597[/C][C]0.171359[/C][/ROW]
[ROW][C]33[/C][C]-0.096991[/C][C]-0.6286[/C][C]0.266517[/C][/ROW]
[ROW][C]34[/C][C]0.044306[/C][C]0.2871[/C][C]0.38771[/C][/ROW]
[ROW][C]35[/C][C]-0.055485[/C][C]-0.3596[/C][C]0.36048[/C][/ROW]
[ROW][C]36[/C][C]0.09872[/C][C]0.6398[/C][C]0.262896[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=58972&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=58972&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
1-0.653552-4.23556.1e-05
20.0888740.5760.283855
30.1742681.12940.132572
4-0.091083-0.59030.27908
5-0.130821-0.84780.200672
60.2461671.59530.059066
7-0.137715-0.89250.188606
8-0.07929-0.51390.305023
90.1931811.2520.108757
10-0.134311-0.87040.194505
110.0337820.21890.413882
12-0.017779-0.11520.454409
130.0582990.37780.353734
14-0.112316-0.72790.235359
150.1160930.75240.228012
16-0.085959-0.55710.290216
170.0332890.21570.415119
180.0554470.35930.360572
19-0.105337-0.68270.249284
200.0237040.15360.439323
210.1285360.8330.204777
22-0.271415-1.7590.042933
230.3326882.15610.018427
24-0.254968-1.65240.052957
250.0550970.35710.361415
260.0803210.52050.302711
27-0.011949-0.07740.46932
28-0.124532-0.80710.21209
290.1444340.9360.177302
30-0.046754-0.3030.381693
31-0.084624-0.54840.293152
320.1480790.95970.171359
33-0.096991-0.62860.266517
340.0443060.28710.38771
35-0.055485-0.35960.36048
360.098720.63980.262896







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.653552-4.23556.1e-05
2-0.590459-3.82660.000213
3-0.319578-2.07110.022265
4-0.011697-0.07580.469967
5-0.174106-1.12830.132791
6-0.039225-0.25420.400289
70.0930410.6030.274883
8-0.049537-0.3210.374887
9-0.000831-0.00540.497863
10-0.015944-0.10330.459097
110.1022490.66260.255589
12-0.045232-0.29310.385429
13-0.035652-0.23110.409197
14-0.100498-0.65130.259199
15-0.06991-0.45310.326415
16-0.1373-0.88980.18932
17-0.134533-0.87190.194117
180.0876130.56780.286597
190.0463230.30020.38275
20-0.138889-0.90010.186598
210.0670060.43430.333164
22-0.246091-1.59490.059122
230.1078360.69890.244246
24-0.077149-0.50.309848
25-0.135752-0.87980.191994
26-0.118745-0.76960.222936
27-0.005399-0.0350.486127
280.0334020.21650.414836
29-0.070288-0.45550.325542
30-0.039344-0.2550.399991
31-0.063185-0.40950.342131
32-0.076417-0.49520.311507
33-0.040053-0.25960.398232
340.055960.36270.359339
350.0481060.31180.378381
36-0.069224-0.44860.328006

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.653552 & -4.2355 & 6.1e-05 \tabularnewline
2 & -0.590459 & -3.8266 & 0.000213 \tabularnewline
3 & -0.319578 & -2.0711 & 0.022265 \tabularnewline
4 & -0.011697 & -0.0758 & 0.469967 \tabularnewline
5 & -0.174106 & -1.1283 & 0.132791 \tabularnewline
6 & -0.039225 & -0.2542 & 0.400289 \tabularnewline
7 & 0.093041 & 0.603 & 0.274883 \tabularnewline
8 & -0.049537 & -0.321 & 0.374887 \tabularnewline
9 & -0.000831 & -0.0054 & 0.497863 \tabularnewline
10 & -0.015944 & -0.1033 & 0.459097 \tabularnewline
11 & 0.102249 & 0.6626 & 0.255589 \tabularnewline
12 & -0.045232 & -0.2931 & 0.385429 \tabularnewline
13 & -0.035652 & -0.2311 & 0.409197 \tabularnewline
14 & -0.100498 & -0.6513 & 0.259199 \tabularnewline
15 & -0.06991 & -0.4531 & 0.326415 \tabularnewline
16 & -0.1373 & -0.8898 & 0.18932 \tabularnewline
17 & -0.134533 & -0.8719 & 0.194117 \tabularnewline
18 & 0.087613 & 0.5678 & 0.286597 \tabularnewline
19 & 0.046323 & 0.3002 & 0.38275 \tabularnewline
20 & -0.138889 & -0.9001 & 0.186598 \tabularnewline
21 & 0.067006 & 0.4343 & 0.333164 \tabularnewline
22 & -0.246091 & -1.5949 & 0.059122 \tabularnewline
23 & 0.107836 & 0.6989 & 0.244246 \tabularnewline
24 & -0.077149 & -0.5 & 0.309848 \tabularnewline
25 & -0.135752 & -0.8798 & 0.191994 \tabularnewline
26 & -0.118745 & -0.7696 & 0.222936 \tabularnewline
27 & -0.005399 & -0.035 & 0.486127 \tabularnewline
28 & 0.033402 & 0.2165 & 0.414836 \tabularnewline
29 & -0.070288 & -0.4555 & 0.325542 \tabularnewline
30 & -0.039344 & -0.255 & 0.399991 \tabularnewline
31 & -0.063185 & -0.4095 & 0.342131 \tabularnewline
32 & -0.076417 & -0.4952 & 0.311507 \tabularnewline
33 & -0.040053 & -0.2596 & 0.398232 \tabularnewline
34 & 0.05596 & 0.3627 & 0.359339 \tabularnewline
35 & 0.048106 & 0.3118 & 0.378381 \tabularnewline
36 & -0.069224 & -0.4486 & 0.328006 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=58972&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]-0.653552[/C][C]-4.2355[/C][C]6.1e-05[/C][/ROW]
[ROW][C]2[/C][C]-0.590459[/C][C]-3.8266[/C][C]0.000213[/C][/ROW]
[ROW][C]3[/C][C]-0.319578[/C][C]-2.0711[/C][C]0.022265[/C][/ROW]
[ROW][C]4[/C][C]-0.011697[/C][C]-0.0758[/C][C]0.469967[/C][/ROW]
[ROW][C]5[/C][C]-0.174106[/C][C]-1.1283[/C][C]0.132791[/C][/ROW]
[ROW][C]6[/C][C]-0.039225[/C][C]-0.2542[/C][C]0.400289[/C][/ROW]
[ROW][C]7[/C][C]0.093041[/C][C]0.603[/C][C]0.274883[/C][/ROW]
[ROW][C]8[/C][C]-0.049537[/C][C]-0.321[/C][C]0.374887[/C][/ROW]
[ROW][C]9[/C][C]-0.000831[/C][C]-0.0054[/C][C]0.497863[/C][/ROW]
[ROW][C]10[/C][C]-0.015944[/C][C]-0.1033[/C][C]0.459097[/C][/ROW]
[ROW][C]11[/C][C]0.102249[/C][C]0.6626[/C][C]0.255589[/C][/ROW]
[ROW][C]12[/C][C]-0.045232[/C][C]-0.2931[/C][C]0.385429[/C][/ROW]
[ROW][C]13[/C][C]-0.035652[/C][C]-0.2311[/C][C]0.409197[/C][/ROW]
[ROW][C]14[/C][C]-0.100498[/C][C]-0.6513[/C][C]0.259199[/C][/ROW]
[ROW][C]15[/C][C]-0.06991[/C][C]-0.4531[/C][C]0.326415[/C][/ROW]
[ROW][C]16[/C][C]-0.1373[/C][C]-0.8898[/C][C]0.18932[/C][/ROW]
[ROW][C]17[/C][C]-0.134533[/C][C]-0.8719[/C][C]0.194117[/C][/ROW]
[ROW][C]18[/C][C]0.087613[/C][C]0.5678[/C][C]0.286597[/C][/ROW]
[ROW][C]19[/C][C]0.046323[/C][C]0.3002[/C][C]0.38275[/C][/ROW]
[ROW][C]20[/C][C]-0.138889[/C][C]-0.9001[/C][C]0.186598[/C][/ROW]
[ROW][C]21[/C][C]0.067006[/C][C]0.4343[/C][C]0.333164[/C][/ROW]
[ROW][C]22[/C][C]-0.246091[/C][C]-1.5949[/C][C]0.059122[/C][/ROW]
[ROW][C]23[/C][C]0.107836[/C][C]0.6989[/C][C]0.244246[/C][/ROW]
[ROW][C]24[/C][C]-0.077149[/C][C]-0.5[/C][C]0.309848[/C][/ROW]
[ROW][C]25[/C][C]-0.135752[/C][C]-0.8798[/C][C]0.191994[/C][/ROW]
[ROW][C]26[/C][C]-0.118745[/C][C]-0.7696[/C][C]0.222936[/C][/ROW]
[ROW][C]27[/C][C]-0.005399[/C][C]-0.035[/C][C]0.486127[/C][/ROW]
[ROW][C]28[/C][C]0.033402[/C][C]0.2165[/C][C]0.414836[/C][/ROW]
[ROW][C]29[/C][C]-0.070288[/C][C]-0.4555[/C][C]0.325542[/C][/ROW]
[ROW][C]30[/C][C]-0.039344[/C][C]-0.255[/C][C]0.399991[/C][/ROW]
[ROW][C]31[/C][C]-0.063185[/C][C]-0.4095[/C][C]0.342131[/C][/ROW]
[ROW][C]32[/C][C]-0.076417[/C][C]-0.4952[/C][C]0.311507[/C][/ROW]
[ROW][C]33[/C][C]-0.040053[/C][C]-0.2596[/C][C]0.398232[/C][/ROW]
[ROW][C]34[/C][C]0.05596[/C][C]0.3627[/C][C]0.359339[/C][/ROW]
[ROW][C]35[/C][C]0.048106[/C][C]0.3118[/C][C]0.378381[/C][/ROW]
[ROW][C]36[/C][C]-0.069224[/C][C]-0.4486[/C][C]0.328006[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=58972&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=58972&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
1-0.653552-4.23556.1e-05
2-0.590459-3.82660.000213
3-0.319578-2.07110.022265
4-0.011697-0.07580.469967
5-0.174106-1.12830.132791
6-0.039225-0.25420.400289
70.0930410.6030.274883
8-0.049537-0.3210.374887
9-0.000831-0.00540.497863
10-0.015944-0.10330.459097
110.1022490.66260.255589
12-0.045232-0.29310.385429
13-0.035652-0.23110.409197
14-0.100498-0.65130.259199
15-0.06991-0.45310.326415
16-0.1373-0.88980.18932
17-0.134533-0.87190.194117
180.0876130.56780.286597
190.0463230.30020.38275
20-0.138889-0.90010.186598
210.0670060.43430.333164
22-0.246091-1.59490.059122
230.1078360.69890.244246
24-0.077149-0.50.309848
25-0.135752-0.87980.191994
26-0.118745-0.76960.222936
27-0.005399-0.0350.486127
280.0334020.21650.414836
29-0.070288-0.45550.325542
30-0.039344-0.2550.399991
31-0.063185-0.40950.342131
32-0.076417-0.49520.311507
33-0.040053-0.25960.398232
340.055960.36270.359339
350.0481060.31180.378381
36-0.069224-0.44860.328006



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