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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 computationWed, 25 Nov 2009 09:44:29 -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/25/t1259167517rxxandh6bfhrlhx.htm/, Retrieved Tue, 07 May 2024 22:13:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59457, Retrieved Tue, 07 May 2024 22:13:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact136
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [] [2009-11-25 16:44:29] [fd7715938ba69fff5a3edaf7913b7ba1] [Current]
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Dataseries X:
108.8
128.4
121.1
119.5
128.7
108.7
105.5
119.8
111.3
110.6
120.1
97.5
107.7
127.3
117.2
119.8
116.2
111
112.4
130.6
109.1
118.8
123.9
101.6
112.8
128
129.6
125.8
119.5
115.7
113.6
129.7
112
116.8
127
112.1
114.2
121.1
131.6
125
120.4
117.7
117.5
120.6
127.5
112.3
124.5
115.2
104.7
130.9
129.2
113.5
125.6
107.6
107
121.6
110.7
106.3
118.6
104.6
103.5




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=59457&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=59457&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59457&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
10.0207830.14550.442465
20.244181.70930.046865
30.4290263.00320.002099
4-0.056863-0.3980.346164
50.2928652.05010.022865
60.1907051.33490.094033
7-0.115283-0.8070.21179
80.2806241.96440.027586
90.0597830.41850.338712
10-0.097642-0.68350.248756
110.0910430.63730.263449
12-0.134133-0.93890.176186
13-0.018159-0.12710.449685
140.0556050.38920.349395
15-0.055386-0.38770.349957
16-0.018756-0.13130.448041
170.0902270.63160.265294
18-0.035457-0.24820.40251
19-0.143168-1.00220.160591
200.0289170.20240.420214
21-0.043658-0.30560.380601
22-0.115604-0.80920.211148
230.1096760.76770.223165
24-0.217794-1.52460.066899
25-0.052698-0.36890.356902
26-0.01804-0.12630.450012
27-0.140298-0.98210.165441
28-0.154029-1.07820.143111
29-0.116459-0.81520.209448
30-0.198749-1.39120.085219
31-0.078433-0.5490.292738
32-0.157616-1.10330.13764
33-0.200996-1.4070.082873
34-0.061196-0.42840.335129
35-0.131537-0.92080.180844
36-0.099943-0.69960.243741

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.020783 & 0.1455 & 0.442465 \tabularnewline
2 & 0.24418 & 1.7093 & 0.046865 \tabularnewline
3 & 0.429026 & 3.0032 & 0.002099 \tabularnewline
4 & -0.056863 & -0.398 & 0.346164 \tabularnewline
5 & 0.292865 & 2.0501 & 0.022865 \tabularnewline
6 & 0.190705 & 1.3349 & 0.094033 \tabularnewline
7 & -0.115283 & -0.807 & 0.21179 \tabularnewline
8 & 0.280624 & 1.9644 & 0.027586 \tabularnewline
9 & 0.059783 & 0.4185 & 0.338712 \tabularnewline
10 & -0.097642 & -0.6835 & 0.248756 \tabularnewline
11 & 0.091043 & 0.6373 & 0.263449 \tabularnewline
12 & -0.134133 & -0.9389 & 0.176186 \tabularnewline
13 & -0.018159 & -0.1271 & 0.449685 \tabularnewline
14 & 0.055605 & 0.3892 & 0.349395 \tabularnewline
15 & -0.055386 & -0.3877 & 0.349957 \tabularnewline
16 & -0.018756 & -0.1313 & 0.448041 \tabularnewline
17 & 0.090227 & 0.6316 & 0.265294 \tabularnewline
18 & -0.035457 & -0.2482 & 0.40251 \tabularnewline
19 & -0.143168 & -1.0022 & 0.160591 \tabularnewline
20 & 0.028917 & 0.2024 & 0.420214 \tabularnewline
21 & -0.043658 & -0.3056 & 0.380601 \tabularnewline
22 & -0.115604 & -0.8092 & 0.211148 \tabularnewline
23 & 0.109676 & 0.7677 & 0.223165 \tabularnewline
24 & -0.217794 & -1.5246 & 0.066899 \tabularnewline
25 & -0.052698 & -0.3689 & 0.356902 \tabularnewline
26 & -0.01804 & -0.1263 & 0.450012 \tabularnewline
27 & -0.140298 & -0.9821 & 0.165441 \tabularnewline
28 & -0.154029 & -1.0782 & 0.143111 \tabularnewline
29 & -0.116459 & -0.8152 & 0.209448 \tabularnewline
30 & -0.198749 & -1.3912 & 0.085219 \tabularnewline
31 & -0.078433 & -0.549 & 0.292738 \tabularnewline
32 & -0.157616 & -1.1033 & 0.13764 \tabularnewline
33 & -0.200996 & -1.407 & 0.082873 \tabularnewline
34 & -0.061196 & -0.4284 & 0.335129 \tabularnewline
35 & -0.131537 & -0.9208 & 0.180844 \tabularnewline
36 & -0.099943 & -0.6996 & 0.243741 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59457&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]0.020783[/C][C]0.1455[/C][C]0.442465[/C][/ROW]
[ROW][C]2[/C][C]0.24418[/C][C]1.7093[/C][C]0.046865[/C][/ROW]
[ROW][C]3[/C][C]0.429026[/C][C]3.0032[/C][C]0.002099[/C][/ROW]
[ROW][C]4[/C][C]-0.056863[/C][C]-0.398[/C][C]0.346164[/C][/ROW]
[ROW][C]5[/C][C]0.292865[/C][C]2.0501[/C][C]0.022865[/C][/ROW]
[ROW][C]6[/C][C]0.190705[/C][C]1.3349[/C][C]0.094033[/C][/ROW]
[ROW][C]7[/C][C]-0.115283[/C][C]-0.807[/C][C]0.21179[/C][/ROW]
[ROW][C]8[/C][C]0.280624[/C][C]1.9644[/C][C]0.027586[/C][/ROW]
[ROW][C]9[/C][C]0.059783[/C][C]0.4185[/C][C]0.338712[/C][/ROW]
[ROW][C]10[/C][C]-0.097642[/C][C]-0.6835[/C][C]0.248756[/C][/ROW]
[ROW][C]11[/C][C]0.091043[/C][C]0.6373[/C][C]0.263449[/C][/ROW]
[ROW][C]12[/C][C]-0.134133[/C][C]-0.9389[/C][C]0.176186[/C][/ROW]
[ROW][C]13[/C][C]-0.018159[/C][C]-0.1271[/C][C]0.449685[/C][/ROW]
[ROW][C]14[/C][C]0.055605[/C][C]0.3892[/C][C]0.349395[/C][/ROW]
[ROW][C]15[/C][C]-0.055386[/C][C]-0.3877[/C][C]0.349957[/C][/ROW]
[ROW][C]16[/C][C]-0.018756[/C][C]-0.1313[/C][C]0.448041[/C][/ROW]
[ROW][C]17[/C][C]0.090227[/C][C]0.6316[/C][C]0.265294[/C][/ROW]
[ROW][C]18[/C][C]-0.035457[/C][C]-0.2482[/C][C]0.40251[/C][/ROW]
[ROW][C]19[/C][C]-0.143168[/C][C]-1.0022[/C][C]0.160591[/C][/ROW]
[ROW][C]20[/C][C]0.028917[/C][C]0.2024[/C][C]0.420214[/C][/ROW]
[ROW][C]21[/C][C]-0.043658[/C][C]-0.3056[/C][C]0.380601[/C][/ROW]
[ROW][C]22[/C][C]-0.115604[/C][C]-0.8092[/C][C]0.211148[/C][/ROW]
[ROW][C]23[/C][C]0.109676[/C][C]0.7677[/C][C]0.223165[/C][/ROW]
[ROW][C]24[/C][C]-0.217794[/C][C]-1.5246[/C][C]0.066899[/C][/ROW]
[ROW][C]25[/C][C]-0.052698[/C][C]-0.3689[/C][C]0.356902[/C][/ROW]
[ROW][C]26[/C][C]-0.01804[/C][C]-0.1263[/C][C]0.450012[/C][/ROW]
[ROW][C]27[/C][C]-0.140298[/C][C]-0.9821[/C][C]0.165441[/C][/ROW]
[ROW][C]28[/C][C]-0.154029[/C][C]-1.0782[/C][C]0.143111[/C][/ROW]
[ROW][C]29[/C][C]-0.116459[/C][C]-0.8152[/C][C]0.209448[/C][/ROW]
[ROW][C]30[/C][C]-0.198749[/C][C]-1.3912[/C][C]0.085219[/C][/ROW]
[ROW][C]31[/C][C]-0.078433[/C][C]-0.549[/C][C]0.292738[/C][/ROW]
[ROW][C]32[/C][C]-0.157616[/C][C]-1.1033[/C][C]0.13764[/C][/ROW]
[ROW][C]33[/C][C]-0.200996[/C][C]-1.407[/C][C]0.082873[/C][/ROW]
[ROW][C]34[/C][C]-0.061196[/C][C]-0.4284[/C][C]0.335129[/C][/ROW]
[ROW][C]35[/C][C]-0.131537[/C][C]-0.9208[/C][C]0.180844[/C][/ROW]
[ROW][C]36[/C][C]-0.099943[/C][C]-0.6996[/C][C]0.243741[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59457&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59457&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
10.0207830.14550.442465
20.244181.70930.046865
30.4290263.00320.002099
4-0.056863-0.3980.346164
50.2928652.05010.022865
60.1907051.33490.094033
7-0.115283-0.8070.21179
80.2806241.96440.027586
90.0597830.41850.338712
10-0.097642-0.68350.248756
110.0910430.63730.263449
12-0.134133-0.93890.176186
13-0.018159-0.12710.449685
140.0556050.38920.349395
15-0.055386-0.38770.349957
16-0.018756-0.13130.448041
170.0902270.63160.265294
18-0.035457-0.24820.40251
19-0.143168-1.00220.160591
200.0289170.20240.420214
21-0.043658-0.30560.380601
22-0.115604-0.80920.211148
230.1096760.76770.223165
24-0.217794-1.52460.066899
25-0.052698-0.36890.356902
26-0.01804-0.12630.450012
27-0.140298-0.98210.165441
28-0.154029-1.07820.143111
29-0.116459-0.81520.209448
30-0.198749-1.39120.085219
31-0.078433-0.5490.292738
32-0.157616-1.10330.13764
33-0.200996-1.4070.082873
34-0.061196-0.42840.335129
35-0.131537-0.92080.180844
36-0.099943-0.69960.243741







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.0207830.14550.442465
20.2438541.7070.047078
30.4468753.12810.00148
4-0.111605-0.78120.219211
50.0985090.68960.24686
60.0825590.57790.282984
7-0.172162-1.20510.11697
80.0675970.47320.319094
90.0906130.63430.26442
10-0.123956-0.86770.194896
11-0.180339-1.26240.106395
12-0.08706-0.60940.272531
130.0653360.45740.324719
140.049660.34760.364806
150.1345020.94150.17553
16-0.020333-0.14230.4437
170.0596750.41770.338986
180.0144510.10120.459919
19-0.254655-1.78260.040425
20-0.03911-0.27380.392706
210.121190.84830.200191
22-0.100554-0.70390.242421
230.0280140.19610.422672
24-0.132942-0.93060.178313
25-0.047414-0.33190.37069
26-0.106429-0.7450.229915
270.2179181.52540.066791
28-0.149444-1.04610.150323
29-0.180478-1.26330.106222
30-0.081222-0.56860.286127
31-0.042328-0.29630.384127
32-0.062449-0.43710.331964
330.04220.29540.384469
340.0706340.49440.311603
35-0.028705-0.20090.420789
360.0026050.01820.492762

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.020783 & 0.1455 & 0.442465 \tabularnewline
2 & 0.243854 & 1.707 & 0.047078 \tabularnewline
3 & 0.446875 & 3.1281 & 0.00148 \tabularnewline
4 & -0.111605 & -0.7812 & 0.219211 \tabularnewline
5 & 0.098509 & 0.6896 & 0.24686 \tabularnewline
6 & 0.082559 & 0.5779 & 0.282984 \tabularnewline
7 & -0.172162 & -1.2051 & 0.11697 \tabularnewline
8 & 0.067597 & 0.4732 & 0.319094 \tabularnewline
9 & 0.090613 & 0.6343 & 0.26442 \tabularnewline
10 & -0.123956 & -0.8677 & 0.194896 \tabularnewline
11 & -0.180339 & -1.2624 & 0.106395 \tabularnewline
12 & -0.08706 & -0.6094 & 0.272531 \tabularnewline
13 & 0.065336 & 0.4574 & 0.324719 \tabularnewline
14 & 0.04966 & 0.3476 & 0.364806 \tabularnewline
15 & 0.134502 & 0.9415 & 0.17553 \tabularnewline
16 & -0.020333 & -0.1423 & 0.4437 \tabularnewline
17 & 0.059675 & 0.4177 & 0.338986 \tabularnewline
18 & 0.014451 & 0.1012 & 0.459919 \tabularnewline
19 & -0.254655 & -1.7826 & 0.040425 \tabularnewline
20 & -0.03911 & -0.2738 & 0.392706 \tabularnewline
21 & 0.12119 & 0.8483 & 0.200191 \tabularnewline
22 & -0.100554 & -0.7039 & 0.242421 \tabularnewline
23 & 0.028014 & 0.1961 & 0.422672 \tabularnewline
24 & -0.132942 & -0.9306 & 0.178313 \tabularnewline
25 & -0.047414 & -0.3319 & 0.37069 \tabularnewline
26 & -0.106429 & -0.745 & 0.229915 \tabularnewline
27 & 0.217918 & 1.5254 & 0.066791 \tabularnewline
28 & -0.149444 & -1.0461 & 0.150323 \tabularnewline
29 & -0.180478 & -1.2633 & 0.106222 \tabularnewline
30 & -0.081222 & -0.5686 & 0.286127 \tabularnewline
31 & -0.042328 & -0.2963 & 0.384127 \tabularnewline
32 & -0.062449 & -0.4371 & 0.331964 \tabularnewline
33 & 0.0422 & 0.2954 & 0.384469 \tabularnewline
34 & 0.070634 & 0.4944 & 0.311603 \tabularnewline
35 & -0.028705 & -0.2009 & 0.420789 \tabularnewline
36 & 0.002605 & 0.0182 & 0.492762 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59457&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]0.020783[/C][C]0.1455[/C][C]0.442465[/C][/ROW]
[ROW][C]2[/C][C]0.243854[/C][C]1.707[/C][C]0.047078[/C][/ROW]
[ROW][C]3[/C][C]0.446875[/C][C]3.1281[/C][C]0.00148[/C][/ROW]
[ROW][C]4[/C][C]-0.111605[/C][C]-0.7812[/C][C]0.219211[/C][/ROW]
[ROW][C]5[/C][C]0.098509[/C][C]0.6896[/C][C]0.24686[/C][/ROW]
[ROW][C]6[/C][C]0.082559[/C][C]0.5779[/C][C]0.282984[/C][/ROW]
[ROW][C]7[/C][C]-0.172162[/C][C]-1.2051[/C][C]0.11697[/C][/ROW]
[ROW][C]8[/C][C]0.067597[/C][C]0.4732[/C][C]0.319094[/C][/ROW]
[ROW][C]9[/C][C]0.090613[/C][C]0.6343[/C][C]0.26442[/C][/ROW]
[ROW][C]10[/C][C]-0.123956[/C][C]-0.8677[/C][C]0.194896[/C][/ROW]
[ROW][C]11[/C][C]-0.180339[/C][C]-1.2624[/C][C]0.106395[/C][/ROW]
[ROW][C]12[/C][C]-0.08706[/C][C]-0.6094[/C][C]0.272531[/C][/ROW]
[ROW][C]13[/C][C]0.065336[/C][C]0.4574[/C][C]0.324719[/C][/ROW]
[ROW][C]14[/C][C]0.04966[/C][C]0.3476[/C][C]0.364806[/C][/ROW]
[ROW][C]15[/C][C]0.134502[/C][C]0.9415[/C][C]0.17553[/C][/ROW]
[ROW][C]16[/C][C]-0.020333[/C][C]-0.1423[/C][C]0.4437[/C][/ROW]
[ROW][C]17[/C][C]0.059675[/C][C]0.4177[/C][C]0.338986[/C][/ROW]
[ROW][C]18[/C][C]0.014451[/C][C]0.1012[/C][C]0.459919[/C][/ROW]
[ROW][C]19[/C][C]-0.254655[/C][C]-1.7826[/C][C]0.040425[/C][/ROW]
[ROW][C]20[/C][C]-0.03911[/C][C]-0.2738[/C][C]0.392706[/C][/ROW]
[ROW][C]21[/C][C]0.12119[/C][C]0.8483[/C][C]0.200191[/C][/ROW]
[ROW][C]22[/C][C]-0.100554[/C][C]-0.7039[/C][C]0.242421[/C][/ROW]
[ROW][C]23[/C][C]0.028014[/C][C]0.1961[/C][C]0.422672[/C][/ROW]
[ROW][C]24[/C][C]-0.132942[/C][C]-0.9306[/C][C]0.178313[/C][/ROW]
[ROW][C]25[/C][C]-0.047414[/C][C]-0.3319[/C][C]0.37069[/C][/ROW]
[ROW][C]26[/C][C]-0.106429[/C][C]-0.745[/C][C]0.229915[/C][/ROW]
[ROW][C]27[/C][C]0.217918[/C][C]1.5254[/C][C]0.066791[/C][/ROW]
[ROW][C]28[/C][C]-0.149444[/C][C]-1.0461[/C][C]0.150323[/C][/ROW]
[ROW][C]29[/C][C]-0.180478[/C][C]-1.2633[/C][C]0.106222[/C][/ROW]
[ROW][C]30[/C][C]-0.081222[/C][C]-0.5686[/C][C]0.286127[/C][/ROW]
[ROW][C]31[/C][C]-0.042328[/C][C]-0.2963[/C][C]0.384127[/C][/ROW]
[ROW][C]32[/C][C]-0.062449[/C][C]-0.4371[/C][C]0.331964[/C][/ROW]
[ROW][C]33[/C][C]0.0422[/C][C]0.2954[/C][C]0.384469[/C][/ROW]
[ROW][C]34[/C][C]0.070634[/C][C]0.4944[/C][C]0.311603[/C][/ROW]
[ROW][C]35[/C][C]-0.028705[/C][C]-0.2009[/C][C]0.420789[/C][/ROW]
[ROW][C]36[/C][C]0.002605[/C][C]0.0182[/C][C]0.492762[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59457&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59457&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
10.0207830.14550.442465
20.2438541.7070.047078
30.4468753.12810.00148
4-0.111605-0.78120.219211
50.0985090.68960.24686
60.0825590.57790.282984
7-0.172162-1.20510.11697
80.0675970.47320.319094
90.0906130.63430.26442
10-0.123956-0.86770.194896
11-0.180339-1.26240.106395
12-0.08706-0.60940.272531
130.0653360.45740.324719
140.049660.34760.364806
150.1345020.94150.17553
16-0.020333-0.14230.4437
170.0596750.41770.338986
180.0144510.10120.459919
19-0.254655-1.78260.040425
20-0.03911-0.27380.392706
210.121190.84830.200191
22-0.100554-0.70390.242421
230.0280140.19610.422672
24-0.132942-0.93060.178313
25-0.047414-0.33190.37069
26-0.106429-0.7450.229915
270.2179181.52540.066791
28-0.149444-1.04610.150323
29-0.180478-1.26330.106222
30-0.081222-0.56860.286127
31-0.042328-0.29630.384127
32-0.062449-0.43710.331964
330.04220.29540.384469
340.0706340.49440.311603
35-0.028705-0.20090.420789
360.0026050.01820.492762



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