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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 computationThu, 10 Dec 2009 12:37:57 -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/10/t12604739086levmp63kapz94k.htm/, Retrieved Thu, 28 Mar 2024 16:43:57 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=65753, Retrieved Thu, 28 Mar 2024 16:43:57 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact104
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] [DSHW-WS8-ACF1.1] [2009-11-27 14:52:40] [f15cfb7053d35072d573abca87df96a0]
-   PD          [(Partial) Autocorrelation Function] [DSHW-WS9-ACF1] [2009-12-04 14:49:16] [f15cfb7053d35072d573abca87df96a0]
-                   [(Partial) Autocorrelation Function] [PAPER] [2009-12-10 19:37:57] [db49399df1e4a3dbe31268849cebfd7f] [Current]
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Dataseries X:
7.8
7.8
7.8
7.5
7.5
7.1
7.5
7.5
7.6
7.7
7.7
7.9
8.1
8.2
8.2
8.2
7.9
7.3
6.9
6.6
6.7
6.9
7
7.1
7.2
7.1
6.9
7
6.8
6.4
6.7
6.6
6.4
6.3
6.2
6.5
6.8
6.8
6.4
6.1
5.8
6.1
7.2
7.3
6.9
6.1
5.8
6.2
7.1
7.7
7.9
7.7
7.4
7.5
8
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=65753&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=65753&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65753&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
10.4121663.05670.001725
2-0.16243-1.20460.116756
3-0.520192-3.85790.000151
4-0.417374-3.09530.001545
50.0669240.49630.310823
60.4153643.08040.001612
70.3047462.26010.013899
8-0.071291-0.52870.299567
9-0.267366-1.98280.026194
10-0.283741-2.10430.019969
110.0072690.05390.478602
120.3082952.28640.013053
130.1377281.02140.155763
140.0645960.47910.316898
15-0.007628-0.05660.477547
16-0.098361-0.72950.234407
17-0.073384-0.54420.29424
18-0.011274-0.08360.466836
19-0.009931-0.07370.470777
20-0.009585-0.07110.471796
210.0536680.3980.34608
22-0.015598-0.11570.454165
23-0.059092-0.43820.331464
24-0.044688-0.33140.370794
25-0.147956-1.09730.138653
260.0276970.20540.419006
270.1256830.93210.177681
280.1043880.77420.221076
290.0429110.31820.375754
30-0.071367-0.52930.299373
31-0.148863-1.1040.137201
32-0.160231-1.18830.11991
33-0.031377-0.23270.40843
340.0249940.18540.426815
350.0801930.59470.277232
360.0660430.48980.313116

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.412166 & 3.0567 & 0.001725 \tabularnewline
2 & -0.16243 & -1.2046 & 0.116756 \tabularnewline
3 & -0.520192 & -3.8579 & 0.000151 \tabularnewline
4 & -0.417374 & -3.0953 & 0.001545 \tabularnewline
5 & 0.066924 & 0.4963 & 0.310823 \tabularnewline
6 & 0.415364 & 3.0804 & 0.001612 \tabularnewline
7 & 0.304746 & 2.2601 & 0.013899 \tabularnewline
8 & -0.071291 & -0.5287 & 0.299567 \tabularnewline
9 & -0.267366 & -1.9828 & 0.026194 \tabularnewline
10 & -0.283741 & -2.1043 & 0.019969 \tabularnewline
11 & 0.007269 & 0.0539 & 0.478602 \tabularnewline
12 & 0.308295 & 2.2864 & 0.013053 \tabularnewline
13 & 0.137728 & 1.0214 & 0.155763 \tabularnewline
14 & 0.064596 & 0.4791 & 0.316898 \tabularnewline
15 & -0.007628 & -0.0566 & 0.477547 \tabularnewline
16 & -0.098361 & -0.7295 & 0.234407 \tabularnewline
17 & -0.073384 & -0.5442 & 0.29424 \tabularnewline
18 & -0.011274 & -0.0836 & 0.466836 \tabularnewline
19 & -0.009931 & -0.0737 & 0.470777 \tabularnewline
20 & -0.009585 & -0.0711 & 0.471796 \tabularnewline
21 & 0.053668 & 0.398 & 0.34608 \tabularnewline
22 & -0.015598 & -0.1157 & 0.454165 \tabularnewline
23 & -0.059092 & -0.4382 & 0.331464 \tabularnewline
24 & -0.044688 & -0.3314 & 0.370794 \tabularnewline
25 & -0.147956 & -1.0973 & 0.138653 \tabularnewline
26 & 0.027697 & 0.2054 & 0.419006 \tabularnewline
27 & 0.125683 & 0.9321 & 0.177681 \tabularnewline
28 & 0.104388 & 0.7742 & 0.221076 \tabularnewline
29 & 0.042911 & 0.3182 & 0.375754 \tabularnewline
30 & -0.071367 & -0.5293 & 0.299373 \tabularnewline
31 & -0.148863 & -1.104 & 0.137201 \tabularnewline
32 & -0.160231 & -1.1883 & 0.11991 \tabularnewline
33 & -0.031377 & -0.2327 & 0.40843 \tabularnewline
34 & 0.024994 & 0.1854 & 0.426815 \tabularnewline
35 & 0.080193 & 0.5947 & 0.277232 \tabularnewline
36 & 0.066043 & 0.4898 & 0.313116 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65753&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]0.412166[/C][C]3.0567[/C][C]0.001725[/C][/ROW]
[ROW][C]2[/C][C]-0.16243[/C][C]-1.2046[/C][C]0.116756[/C][/ROW]
[ROW][C]3[/C][C]-0.520192[/C][C]-3.8579[/C][C]0.000151[/C][/ROW]
[ROW][C]4[/C][C]-0.417374[/C][C]-3.0953[/C][C]0.001545[/C][/ROW]
[ROW][C]5[/C][C]0.066924[/C][C]0.4963[/C][C]0.310823[/C][/ROW]
[ROW][C]6[/C][C]0.415364[/C][C]3.0804[/C][C]0.001612[/C][/ROW]
[ROW][C]7[/C][C]0.304746[/C][C]2.2601[/C][C]0.013899[/C][/ROW]
[ROW][C]8[/C][C]-0.071291[/C][C]-0.5287[/C][C]0.299567[/C][/ROW]
[ROW][C]9[/C][C]-0.267366[/C][C]-1.9828[/C][C]0.026194[/C][/ROW]
[ROW][C]10[/C][C]-0.283741[/C][C]-2.1043[/C][C]0.019969[/C][/ROW]
[ROW][C]11[/C][C]0.007269[/C][C]0.0539[/C][C]0.478602[/C][/ROW]
[ROW][C]12[/C][C]0.308295[/C][C]2.2864[/C][C]0.013053[/C][/ROW]
[ROW][C]13[/C][C]0.137728[/C][C]1.0214[/C][C]0.155763[/C][/ROW]
[ROW][C]14[/C][C]0.064596[/C][C]0.4791[/C][C]0.316898[/C][/ROW]
[ROW][C]15[/C][C]-0.007628[/C][C]-0.0566[/C][C]0.477547[/C][/ROW]
[ROW][C]16[/C][C]-0.098361[/C][C]-0.7295[/C][C]0.234407[/C][/ROW]
[ROW][C]17[/C][C]-0.073384[/C][C]-0.5442[/C][C]0.29424[/C][/ROW]
[ROW][C]18[/C][C]-0.011274[/C][C]-0.0836[/C][C]0.466836[/C][/ROW]
[ROW][C]19[/C][C]-0.009931[/C][C]-0.0737[/C][C]0.470777[/C][/ROW]
[ROW][C]20[/C][C]-0.009585[/C][C]-0.0711[/C][C]0.471796[/C][/ROW]
[ROW][C]21[/C][C]0.053668[/C][C]0.398[/C][C]0.34608[/C][/ROW]
[ROW][C]22[/C][C]-0.015598[/C][C]-0.1157[/C][C]0.454165[/C][/ROW]
[ROW][C]23[/C][C]-0.059092[/C][C]-0.4382[/C][C]0.331464[/C][/ROW]
[ROW][C]24[/C][C]-0.044688[/C][C]-0.3314[/C][C]0.370794[/C][/ROW]
[ROW][C]25[/C][C]-0.147956[/C][C]-1.0973[/C][C]0.138653[/C][/ROW]
[ROW][C]26[/C][C]0.027697[/C][C]0.2054[/C][C]0.419006[/C][/ROW]
[ROW][C]27[/C][C]0.125683[/C][C]0.9321[/C][C]0.177681[/C][/ROW]
[ROW][C]28[/C][C]0.104388[/C][C]0.7742[/C][C]0.221076[/C][/ROW]
[ROW][C]29[/C][C]0.042911[/C][C]0.3182[/C][C]0.375754[/C][/ROW]
[ROW][C]30[/C][C]-0.071367[/C][C]-0.5293[/C][C]0.299373[/C][/ROW]
[ROW][C]31[/C][C]-0.148863[/C][C]-1.104[/C][C]0.137201[/C][/ROW]
[ROW][C]32[/C][C]-0.160231[/C][C]-1.1883[/C][C]0.11991[/C][/ROW]
[ROW][C]33[/C][C]-0.031377[/C][C]-0.2327[/C][C]0.40843[/C][/ROW]
[ROW][C]34[/C][C]0.024994[/C][C]0.1854[/C][C]0.426815[/C][/ROW]
[ROW][C]35[/C][C]0.080193[/C][C]0.5947[/C][C]0.277232[/C][/ROW]
[ROW][C]36[/C][C]0.066043[/C][C]0.4898[/C][C]0.313116[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=65753&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65753&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
10.4121663.05670.001725
2-0.16243-1.20460.116756
3-0.520192-3.85790.000151
4-0.417374-3.09530.001545
50.0669240.49630.310823
60.4153643.08040.001612
70.3047462.26010.013899
8-0.071291-0.52870.299567
9-0.267366-1.98280.026194
10-0.283741-2.10430.019969
110.0072690.05390.478602
120.3082952.28640.013053
130.1377281.02140.155763
140.0645960.47910.316898
15-0.007628-0.05660.477547
16-0.098361-0.72950.234407
17-0.073384-0.54420.29424
18-0.011274-0.08360.466836
19-0.009931-0.07370.470777
20-0.009585-0.07110.471796
210.0536680.3980.34608
22-0.015598-0.11570.454165
23-0.059092-0.43820.331464
24-0.044688-0.33140.370794
25-0.147956-1.09730.138653
260.0276970.20540.419006
270.1256830.93210.177681
280.1043880.77420.221076
290.0429110.31820.375754
30-0.071367-0.52930.299373
31-0.148863-1.1040.137201
32-0.160231-1.18830.11991
33-0.031377-0.23270.40843
340.0249940.18540.426815
350.0801930.59470.277232
360.0660430.48980.313116







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.4121663.05670.001725
2-0.400317-2.96880.002211
3-0.375055-2.78150.003699
4-0.117719-0.8730.193221
50.195681.45120.076202
60.1214210.90050.185894
7-0.121334-0.89980.186066
8-0.130838-0.97030.168068
90.1259370.9340.177199
10-0.074726-0.55420.290851
110.0197980.14680.441902
120.1373561.01870.156412
13-0.2465-1.82810.036481
140.2678541.98650.025987
150.2411791.78860.039591
16-0.158685-1.17680.122164
17-0.122793-0.91070.183224
180.0898350.66620.254023
190.0718010.53250.298266
20-0.129651-0.96150.17025
21-0.06074-0.45050.327075
220.0198330.14710.441801
23-0.109951-0.81540.209175
240.0215070.15950.436929
25-0.1069-0.79280.215652
26-0.009217-0.06840.472876
27-0.028432-0.21090.41689
280.0833470.61810.269525
290.0417050.30930.379135
30-0.162071-1.20190.117266
310.0033660.0250.490086
32-0.05919-0.4390.331203
33-0.128786-0.95510.171853
34-0.008311-0.06160.475537
35-0.008821-0.06540.47404
36-0.035514-0.26340.396622

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.412166 & 3.0567 & 0.001725 \tabularnewline
2 & -0.400317 & -2.9688 & 0.002211 \tabularnewline
3 & -0.375055 & -2.7815 & 0.003699 \tabularnewline
4 & -0.117719 & -0.873 & 0.193221 \tabularnewline
5 & 0.19568 & 1.4512 & 0.076202 \tabularnewline
6 & 0.121421 & 0.9005 & 0.185894 \tabularnewline
7 & -0.121334 & -0.8998 & 0.186066 \tabularnewline
8 & -0.130838 & -0.9703 & 0.168068 \tabularnewline
9 & 0.125937 & 0.934 & 0.177199 \tabularnewline
10 & -0.074726 & -0.5542 & 0.290851 \tabularnewline
11 & 0.019798 & 0.1468 & 0.441902 \tabularnewline
12 & 0.137356 & 1.0187 & 0.156412 \tabularnewline
13 & -0.2465 & -1.8281 & 0.036481 \tabularnewline
14 & 0.267854 & 1.9865 & 0.025987 \tabularnewline
15 & 0.241179 & 1.7886 & 0.039591 \tabularnewline
16 & -0.158685 & -1.1768 & 0.122164 \tabularnewline
17 & -0.122793 & -0.9107 & 0.183224 \tabularnewline
18 & 0.089835 & 0.6662 & 0.254023 \tabularnewline
19 & 0.071801 & 0.5325 & 0.298266 \tabularnewline
20 & -0.129651 & -0.9615 & 0.17025 \tabularnewline
21 & -0.06074 & -0.4505 & 0.327075 \tabularnewline
22 & 0.019833 & 0.1471 & 0.441801 \tabularnewline
23 & -0.109951 & -0.8154 & 0.209175 \tabularnewline
24 & 0.021507 & 0.1595 & 0.436929 \tabularnewline
25 & -0.1069 & -0.7928 & 0.215652 \tabularnewline
26 & -0.009217 & -0.0684 & 0.472876 \tabularnewline
27 & -0.028432 & -0.2109 & 0.41689 \tabularnewline
28 & 0.083347 & 0.6181 & 0.269525 \tabularnewline
29 & 0.041705 & 0.3093 & 0.379135 \tabularnewline
30 & -0.162071 & -1.2019 & 0.117266 \tabularnewline
31 & 0.003366 & 0.025 & 0.490086 \tabularnewline
32 & -0.05919 & -0.439 & 0.331203 \tabularnewline
33 & -0.128786 & -0.9551 & 0.171853 \tabularnewline
34 & -0.008311 & -0.0616 & 0.475537 \tabularnewline
35 & -0.008821 & -0.0654 & 0.47404 \tabularnewline
36 & -0.035514 & -0.2634 & 0.396622 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65753&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]0.412166[/C][C]3.0567[/C][C]0.001725[/C][/ROW]
[ROW][C]2[/C][C]-0.400317[/C][C]-2.9688[/C][C]0.002211[/C][/ROW]
[ROW][C]3[/C][C]-0.375055[/C][C]-2.7815[/C][C]0.003699[/C][/ROW]
[ROW][C]4[/C][C]-0.117719[/C][C]-0.873[/C][C]0.193221[/C][/ROW]
[ROW][C]5[/C][C]0.19568[/C][C]1.4512[/C][C]0.076202[/C][/ROW]
[ROW][C]6[/C][C]0.121421[/C][C]0.9005[/C][C]0.185894[/C][/ROW]
[ROW][C]7[/C][C]-0.121334[/C][C]-0.8998[/C][C]0.186066[/C][/ROW]
[ROW][C]8[/C][C]-0.130838[/C][C]-0.9703[/C][C]0.168068[/C][/ROW]
[ROW][C]9[/C][C]0.125937[/C][C]0.934[/C][C]0.177199[/C][/ROW]
[ROW][C]10[/C][C]-0.074726[/C][C]-0.5542[/C][C]0.290851[/C][/ROW]
[ROW][C]11[/C][C]0.019798[/C][C]0.1468[/C][C]0.441902[/C][/ROW]
[ROW][C]12[/C][C]0.137356[/C][C]1.0187[/C][C]0.156412[/C][/ROW]
[ROW][C]13[/C][C]-0.2465[/C][C]-1.8281[/C][C]0.036481[/C][/ROW]
[ROW][C]14[/C][C]0.267854[/C][C]1.9865[/C][C]0.025987[/C][/ROW]
[ROW][C]15[/C][C]0.241179[/C][C]1.7886[/C][C]0.039591[/C][/ROW]
[ROW][C]16[/C][C]-0.158685[/C][C]-1.1768[/C][C]0.122164[/C][/ROW]
[ROW][C]17[/C][C]-0.122793[/C][C]-0.9107[/C][C]0.183224[/C][/ROW]
[ROW][C]18[/C][C]0.089835[/C][C]0.6662[/C][C]0.254023[/C][/ROW]
[ROW][C]19[/C][C]0.071801[/C][C]0.5325[/C][C]0.298266[/C][/ROW]
[ROW][C]20[/C][C]-0.129651[/C][C]-0.9615[/C][C]0.17025[/C][/ROW]
[ROW][C]21[/C][C]-0.06074[/C][C]-0.4505[/C][C]0.327075[/C][/ROW]
[ROW][C]22[/C][C]0.019833[/C][C]0.1471[/C][C]0.441801[/C][/ROW]
[ROW][C]23[/C][C]-0.109951[/C][C]-0.8154[/C][C]0.209175[/C][/ROW]
[ROW][C]24[/C][C]0.021507[/C][C]0.1595[/C][C]0.436929[/C][/ROW]
[ROW][C]25[/C][C]-0.1069[/C][C]-0.7928[/C][C]0.215652[/C][/ROW]
[ROW][C]26[/C][C]-0.009217[/C][C]-0.0684[/C][C]0.472876[/C][/ROW]
[ROW][C]27[/C][C]-0.028432[/C][C]-0.2109[/C][C]0.41689[/C][/ROW]
[ROW][C]28[/C][C]0.083347[/C][C]0.6181[/C][C]0.269525[/C][/ROW]
[ROW][C]29[/C][C]0.041705[/C][C]0.3093[/C][C]0.379135[/C][/ROW]
[ROW][C]30[/C][C]-0.162071[/C][C]-1.2019[/C][C]0.117266[/C][/ROW]
[ROW][C]31[/C][C]0.003366[/C][C]0.025[/C][C]0.490086[/C][/ROW]
[ROW][C]32[/C][C]-0.05919[/C][C]-0.439[/C][C]0.331203[/C][/ROW]
[ROW][C]33[/C][C]-0.128786[/C][C]-0.9551[/C][C]0.171853[/C][/ROW]
[ROW][C]34[/C][C]-0.008311[/C][C]-0.0616[/C][C]0.475537[/C][/ROW]
[ROW][C]35[/C][C]-0.008821[/C][C]-0.0654[/C][C]0.47404[/C][/ROW]
[ROW][C]36[/C][C]-0.035514[/C][C]-0.2634[/C][C]0.396622[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=65753&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65753&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
10.4121663.05670.001725
2-0.400317-2.96880.002211
3-0.375055-2.78150.003699
4-0.117719-0.8730.193221
50.195681.45120.076202
60.1214210.90050.185894
7-0.121334-0.89980.186066
8-0.130838-0.97030.168068
90.1259370.9340.177199
10-0.074726-0.55420.290851
110.0197980.14680.441902
120.1373561.01870.156412
13-0.2465-1.82810.036481
140.2678541.98650.025987
150.2411791.78860.039591
16-0.158685-1.17680.122164
17-0.122793-0.91070.183224
180.0898350.66620.254023
190.0718010.53250.298266
20-0.129651-0.96150.17025
21-0.06074-0.45050.327075
220.0198330.14710.441801
23-0.109951-0.81540.209175
240.0215070.15950.436929
25-0.1069-0.79280.215652
26-0.009217-0.06840.472876
27-0.028432-0.21090.41689
280.0833470.61810.269525
290.0417050.30930.379135
30-0.162071-1.20190.117266
310.0033660.0250.490086
32-0.05919-0.4390.331203
33-0.128786-0.95510.171853
34-0.008311-0.06160.475537
35-0.008821-0.06540.47404
36-0.035514-0.26340.396622



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