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Description of Statistical Computation

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, 02 Dec 2009 11:00:55 -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/02/t12597768770qy29b0s5vm1q2s.htm/, Retrieved Sat, 27 Apr 2024 17:24:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62498, Retrieved Sat, 27 Apr 2024 17:24:49 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact156

Tree of Dependent Computations

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] [WS8 berekening4 TVD] [2009-11-25 11:42:02] [42ad1186d39724f834063794eac7cea3]
-                 [(Partial) Autocorrelation Function] [TG 6] [2009-12-02 18:00:55] [81cf732ffd29c90ba583bd04c2d9af10] [Current]
- R                 [(Partial) Autocorrelation Function] [WorkShop9 (SHW)] [2009-12-04 14:39:26] [37daf76adc256428993ec4063536c760]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
101.3
106.3
94
102.8
102
105.1
92.4
81.4
105.8
120.3
100.7
88.8
94.3
99.9
103.4
103.3
98.8
104.2
91.2
74.7
108.5
114.5
96.9
89.6
97.1
100.3
122.6
115.4
109
129.1
102.8
96.2
127.7
128.9
126.5
119.8
113.2
114.1
134.1
130
121.8
132.1
105.3
103
117.1
126.3
138.1
119.5
138
135.5
178.6
162.2
176.9
204.9
132.2
142.5
164.3
174.9
175.4
143

Tables (Output of Computation)





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=62498&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=62498&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62498&T=0

As an alternative you can also use a QR Code:  
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
1-0.378363-2.59390.006307
2-0.075628-0.51850.303277
30.2225251.52560.066911
4-0.108158-0.74150.231042
50.1497471.02660.154929
6-0.16752-1.14850.128296
70.0414180.28390.388848
8-0.083472-0.57230.284939
9-0.07763-0.53220.298545
10-0.030525-0.20930.41757
11-0.029654-0.20330.419891
12-0.034945-0.23960.405853
13-0.076692-0.52580.300758
140.0787390.53980.29594
15-0.020649-0.14160.444015
16-0.076845-0.52680.300396
170.1028240.70490.242167
180.0047670.03270.487033
190.0664450.45550.325415
20-0.11143-0.76390.224365
210.0951390.65220.258712
220.0505840.34680.36515
23-0.034854-0.23890.406093
240.124930.85650.19804
25-0.158022-1.08330.142092
260.1250750.85750.197769
270.0054940.03770.485056
28-0.079341-0.54390.29453
290.0354430.2430.404536
30-0.021028-0.14420.442996
31-0.052384-0.35910.360555
320.0258230.1770.430122
33-0.013193-0.09040.464158
34-0.041161-0.28220.38952
350.0079970.05480.478254
360.0459360.31490.377107

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.378363 & -2.5939 & 0.006307 \tabularnewline
2 & -0.075628 & -0.5185 & 0.303277 \tabularnewline
3 & 0.222525 & 1.5256 & 0.066911 \tabularnewline
4 & -0.108158 & -0.7415 & 0.231042 \tabularnewline
5 & 0.149747 & 1.0266 & 0.154929 \tabularnewline
6 & -0.16752 & -1.1485 & 0.128296 \tabularnewline
7 & 0.041418 & 0.2839 & 0.388848 \tabularnewline
8 & -0.083472 & -0.5723 & 0.284939 \tabularnewline
9 & -0.07763 & -0.5322 & 0.298545 \tabularnewline
10 & -0.030525 & -0.2093 & 0.41757 \tabularnewline
11 & -0.029654 & -0.2033 & 0.419891 \tabularnewline
12 & -0.034945 & -0.2396 & 0.405853 \tabularnewline
13 & -0.076692 & -0.5258 & 0.300758 \tabularnewline
14 & 0.078739 & 0.5398 & 0.29594 \tabularnewline
15 & -0.020649 & -0.1416 & 0.444015 \tabularnewline
16 & -0.076845 & -0.5268 & 0.300396 \tabularnewline
17 & 0.102824 & 0.7049 & 0.242167 \tabularnewline
18 & 0.004767 & 0.0327 & 0.487033 \tabularnewline
19 & 0.066445 & 0.4555 & 0.325415 \tabularnewline
20 & -0.11143 & -0.7639 & 0.224365 \tabularnewline
21 & 0.095139 & 0.6522 & 0.258712 \tabularnewline
22 & 0.050584 & 0.3468 & 0.36515 \tabularnewline
23 & -0.034854 & -0.2389 & 0.406093 \tabularnewline
24 & 0.12493 & 0.8565 & 0.19804 \tabularnewline
25 & -0.158022 & -1.0833 & 0.142092 \tabularnewline
26 & 0.125075 & 0.8575 & 0.197769 \tabularnewline
27 & 0.005494 & 0.0377 & 0.485056 \tabularnewline
28 & -0.079341 & -0.5439 & 0.29453 \tabularnewline
29 & 0.035443 & 0.243 & 0.404536 \tabularnewline
30 & -0.021028 & -0.1442 & 0.442996 \tabularnewline
31 & -0.052384 & -0.3591 & 0.360555 \tabularnewline
32 & 0.025823 & 0.177 & 0.430122 \tabularnewline
33 & -0.013193 & -0.0904 & 0.464158 \tabularnewline
34 & -0.041161 & -0.2822 & 0.38952 \tabularnewline
35 & 0.007997 & 0.0548 & 0.478254 \tabularnewline
36 & 0.045936 & 0.3149 & 0.377107 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62498&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]-0.378363[/C][C]-2.5939[/C][C]0.006307[/C][/ROW]
[ROW][C]2[/C][C]-0.075628[/C][C]-0.5185[/C][C]0.303277[/C][/ROW]
[ROW][C]3[/C][C]0.222525[/C][C]1.5256[/C][C]0.066911[/C][/ROW]
[ROW][C]4[/C][C]-0.108158[/C][C]-0.7415[/C][C]0.231042[/C][/ROW]
[ROW][C]5[/C][C]0.149747[/C][C]1.0266[/C][C]0.154929[/C][/ROW]
[ROW][C]6[/C][C]-0.16752[/C][C]-1.1485[/C][C]0.128296[/C][/ROW]
[ROW][C]7[/C][C]0.041418[/C][C]0.2839[/C][C]0.388848[/C][/ROW]
[ROW][C]8[/C][C]-0.083472[/C][C]-0.5723[/C][C]0.284939[/C][/ROW]
[ROW][C]9[/C][C]-0.07763[/C][C]-0.5322[/C][C]0.298545[/C][/ROW]
[ROW][C]10[/C][C]-0.030525[/C][C]-0.2093[/C][C]0.41757[/C][/ROW]
[ROW][C]11[/C][C]-0.029654[/C][C]-0.2033[/C][C]0.419891[/C][/ROW]
[ROW][C]12[/C][C]-0.034945[/C][C]-0.2396[/C][C]0.405853[/C][/ROW]
[ROW][C]13[/C][C]-0.076692[/C][C]-0.5258[/C][C]0.300758[/C][/ROW]
[ROW][C]14[/C][C]0.078739[/C][C]0.5398[/C][C]0.29594[/C][/ROW]
[ROW][C]15[/C][C]-0.020649[/C][C]-0.1416[/C][C]0.444015[/C][/ROW]
[ROW][C]16[/C][C]-0.076845[/C][C]-0.5268[/C][C]0.300396[/C][/ROW]
[ROW][C]17[/C][C]0.102824[/C][C]0.7049[/C][C]0.242167[/C][/ROW]
[ROW][C]18[/C][C]0.004767[/C][C]0.0327[/C][C]0.487033[/C][/ROW]
[ROW][C]19[/C][C]0.066445[/C][C]0.4555[/C][C]0.325415[/C][/ROW]
[ROW][C]20[/C][C]-0.11143[/C][C]-0.7639[/C][C]0.224365[/C][/ROW]
[ROW][C]21[/C][C]0.095139[/C][C]0.6522[/C][C]0.258712[/C][/ROW]
[ROW][C]22[/C][C]0.050584[/C][C]0.3468[/C][C]0.36515[/C][/ROW]
[ROW][C]23[/C][C]-0.034854[/C][C]-0.2389[/C][C]0.406093[/C][/ROW]
[ROW][C]24[/C][C]0.12493[/C][C]0.8565[/C][C]0.19804[/C][/ROW]
[ROW][C]25[/C][C]-0.158022[/C][C]-1.0833[/C][C]0.142092[/C][/ROW]
[ROW][C]26[/C][C]0.125075[/C][C]0.8575[/C][C]0.197769[/C][/ROW]
[ROW][C]27[/C][C]0.005494[/C][C]0.0377[/C][C]0.485056[/C][/ROW]
[ROW][C]28[/C][C]-0.079341[/C][C]-0.5439[/C][C]0.29453[/C][/ROW]
[ROW][C]29[/C][C]0.035443[/C][C]0.243[/C][C]0.404536[/C][/ROW]
[ROW][C]30[/C][C]-0.021028[/C][C]-0.1442[/C][C]0.442996[/C][/ROW]
[ROW][C]31[/C][C]-0.052384[/C][C]-0.3591[/C][C]0.360555[/C][/ROW]
[ROW][C]32[/C][C]0.025823[/C][C]0.177[/C][C]0.430122[/C][/ROW]
[ROW][C]33[/C][C]-0.013193[/C][C]-0.0904[/C][C]0.464158[/C][/ROW]
[ROW][C]34[/C][C]-0.041161[/C][C]-0.2822[/C][C]0.38952[/C][/ROW]
[ROW][C]35[/C][C]0.007997[/C][C]0.0548[/C][C]0.478254[/C][/ROW]
[ROW][C]36[/C][C]0.045936[/C][C]0.3149[/C][C]0.377107[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62498&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62498&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.378363-2.59390.006307
2-0.075628-0.51850.303277
30.2225251.52560.066911
4-0.108158-0.74150.231042
50.1497471.02660.154929
6-0.16752-1.14850.128296
70.0414180.28390.388848
8-0.083472-0.57230.284939
9-0.07763-0.53220.298545
10-0.030525-0.20930.41757
11-0.029654-0.20330.419891
12-0.034945-0.23960.405853
13-0.076692-0.52580.300758
140.0787390.53980.29594
15-0.020649-0.14160.444015
16-0.076845-0.52680.300396
170.1028240.70490.242167
180.0047670.03270.487033
190.0664450.45550.325415
20-0.11143-0.76390.224365
210.0951390.65220.258712
220.0505840.34680.36515
23-0.034854-0.23890.406093
240.124930.85650.19804
25-0.158022-1.08330.142092
260.1250750.85750.197769
270.0054940.03770.485056
28-0.079341-0.54390.29453
290.0354430.2430.404536
30-0.021028-0.14420.442996
31-0.052384-0.35910.360555
320.0258230.1770.430122
33-0.013193-0.09040.464158
34-0.041161-0.28220.38952
350.0079970.05480.478254
360.0459360.31490.377107






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.378363-2.59390.006307
2-0.255342-1.75050.043276
30.1123520.77020.222504
40.0232490.15940.437024
50.2064341.41520.081795
6-0.096671-0.66270.255366
7-0.033992-0.2330.408372
8-0.229937-1.57640.060825
9-0.179956-1.23370.111721
10-0.246202-1.68790.049031
11-0.083373-0.57160.285166
12-0.102982-0.7060.241833
13-0.077293-0.52990.29934
14-0.008669-0.05940.47643
150.0091390.06270.475153
16-0.146919-1.00720.159491
17-0.080121-0.54930.292706
18-0.103907-0.71230.239885
190.0210060.1440.443054
20-0.198177-1.35860.090374
21-0.064378-0.44140.330491
22-0.114466-0.78470.218272
230.0043380.02970.488201
240.0786090.53890.296245
25-0.05842-0.40050.345299
26-0.007568-0.05190.47942
270.0004890.00340.49867
28-0.071756-0.49190.312527
29-0.117533-0.80580.212218
30-0.033424-0.22910.409877
31-0.120664-0.82720.206142
32-0.001805-0.01240.495091
33-0.004054-0.02780.488973
340.0385530.26430.396351
35-0.016042-0.110.456447
360.0808380.55420.291035

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.378363 & -2.5939 & 0.006307 \tabularnewline
2 & -0.255342 & -1.7505 & 0.043276 \tabularnewline
3 & 0.112352 & 0.7702 & 0.222504 \tabularnewline
4 & 0.023249 & 0.1594 & 0.437024 \tabularnewline
5 & 0.206434 & 1.4152 & 0.081795 \tabularnewline
6 & -0.096671 & -0.6627 & 0.255366 \tabularnewline
7 & -0.033992 & -0.233 & 0.408372 \tabularnewline
8 & -0.229937 & -1.5764 & 0.060825 \tabularnewline
9 & -0.179956 & -1.2337 & 0.111721 \tabularnewline
10 & -0.246202 & -1.6879 & 0.049031 \tabularnewline
11 & -0.083373 & -0.5716 & 0.285166 \tabularnewline
12 & -0.102982 & -0.706 & 0.241833 \tabularnewline
13 & -0.077293 & -0.5299 & 0.29934 \tabularnewline
14 & -0.008669 & -0.0594 & 0.47643 \tabularnewline
15 & 0.009139 & 0.0627 & 0.475153 \tabularnewline
16 & -0.146919 & -1.0072 & 0.159491 \tabularnewline
17 & -0.080121 & -0.5493 & 0.292706 \tabularnewline
18 & -0.103907 & -0.7123 & 0.239885 \tabularnewline
19 & 0.021006 & 0.144 & 0.443054 \tabularnewline
20 & -0.198177 & -1.3586 & 0.090374 \tabularnewline
21 & -0.064378 & -0.4414 & 0.330491 \tabularnewline
22 & -0.114466 & -0.7847 & 0.218272 \tabularnewline
23 & 0.004338 & 0.0297 & 0.488201 \tabularnewline
24 & 0.078609 & 0.5389 & 0.296245 \tabularnewline
25 & -0.05842 & -0.4005 & 0.345299 \tabularnewline
26 & -0.007568 & -0.0519 & 0.47942 \tabularnewline
27 & 0.000489 & 0.0034 & 0.49867 \tabularnewline
28 & -0.071756 & -0.4919 & 0.312527 \tabularnewline
29 & -0.117533 & -0.8058 & 0.212218 \tabularnewline
30 & -0.033424 & -0.2291 & 0.409877 \tabularnewline
31 & -0.120664 & -0.8272 & 0.206142 \tabularnewline
32 & -0.001805 & -0.0124 & 0.495091 \tabularnewline
33 & -0.004054 & -0.0278 & 0.488973 \tabularnewline
34 & 0.038553 & 0.2643 & 0.396351 \tabularnewline
35 & -0.016042 & -0.11 & 0.456447 \tabularnewline
36 & 0.080838 & 0.5542 & 0.291035 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62498&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]-0.378363[/C][C]-2.5939[/C][C]0.006307[/C][/ROW]
[ROW][C]2[/C][C]-0.255342[/C][C]-1.7505[/C][C]0.043276[/C][/ROW]
[ROW][C]3[/C][C]0.112352[/C][C]0.7702[/C][C]0.222504[/C][/ROW]
[ROW][C]4[/C][C]0.023249[/C][C]0.1594[/C][C]0.437024[/C][/ROW]
[ROW][C]5[/C][C]0.206434[/C][C]1.4152[/C][C]0.081795[/C][/ROW]
[ROW][C]6[/C][C]-0.096671[/C][C]-0.6627[/C][C]0.255366[/C][/ROW]
[ROW][C]7[/C][C]-0.033992[/C][C]-0.233[/C][C]0.408372[/C][/ROW]
[ROW][C]8[/C][C]-0.229937[/C][C]-1.5764[/C][C]0.060825[/C][/ROW]
[ROW][C]9[/C][C]-0.179956[/C][C]-1.2337[/C][C]0.111721[/C][/ROW]
[ROW][C]10[/C][C]-0.246202[/C][C]-1.6879[/C][C]0.049031[/C][/ROW]
[ROW][C]11[/C][C]-0.083373[/C][C]-0.5716[/C][C]0.285166[/C][/ROW]
[ROW][C]12[/C][C]-0.102982[/C][C]-0.706[/C][C]0.241833[/C][/ROW]
[ROW][C]13[/C][C]-0.077293[/C][C]-0.5299[/C][C]0.29934[/C][/ROW]
[ROW][C]14[/C][C]-0.008669[/C][C]-0.0594[/C][C]0.47643[/C][/ROW]
[ROW][C]15[/C][C]0.009139[/C][C]0.0627[/C][C]0.475153[/C][/ROW]
[ROW][C]16[/C][C]-0.146919[/C][C]-1.0072[/C][C]0.159491[/C][/ROW]
[ROW][C]17[/C][C]-0.080121[/C][C]-0.5493[/C][C]0.292706[/C][/ROW]
[ROW][C]18[/C][C]-0.103907[/C][C]-0.7123[/C][C]0.239885[/C][/ROW]
[ROW][C]19[/C][C]0.021006[/C][C]0.144[/C][C]0.443054[/C][/ROW]
[ROW][C]20[/C][C]-0.198177[/C][C]-1.3586[/C][C]0.090374[/C][/ROW]
[ROW][C]21[/C][C]-0.064378[/C][C]-0.4414[/C][C]0.330491[/C][/ROW]
[ROW][C]22[/C][C]-0.114466[/C][C]-0.7847[/C][C]0.218272[/C][/ROW]
[ROW][C]23[/C][C]0.004338[/C][C]0.0297[/C][C]0.488201[/C][/ROW]
[ROW][C]24[/C][C]0.078609[/C][C]0.5389[/C][C]0.296245[/C][/ROW]
[ROW][C]25[/C][C]-0.05842[/C][C]-0.4005[/C][C]0.345299[/C][/ROW]
[ROW][C]26[/C][C]-0.007568[/C][C]-0.0519[/C][C]0.47942[/C][/ROW]
[ROW][C]27[/C][C]0.000489[/C][C]0.0034[/C][C]0.49867[/C][/ROW]
[ROW][C]28[/C][C]-0.071756[/C][C]-0.4919[/C][C]0.312527[/C][/ROW]
[ROW][C]29[/C][C]-0.117533[/C][C]-0.8058[/C][C]0.212218[/C][/ROW]
[ROW][C]30[/C][C]-0.033424[/C][C]-0.2291[/C][C]0.409877[/C][/ROW]
[ROW][C]31[/C][C]-0.120664[/C][C]-0.8272[/C][C]0.206142[/C][/ROW]
[ROW][C]32[/C][C]-0.001805[/C][C]-0.0124[/C][C]0.495091[/C][/ROW]
[ROW][C]33[/C][C]-0.004054[/C][C]-0.0278[/C][C]0.488973[/C][/ROW]
[ROW][C]34[/C][C]0.038553[/C][C]0.2643[/C][C]0.396351[/C][/ROW]
[ROW][C]35[/C][C]-0.016042[/C][C]-0.11[/C][C]0.456447[/C][/ROW]
[ROW][C]36[/C][C]0.080838[/C][C]0.5542[/C][C]0.291035[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62498&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62498&T=2

As an alternative you can also use a QR Code:  
QR Code


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

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.378363-2.59390.006307
2-0.255342-1.75050.043276
30.1123520.77020.222504
40.0232490.15940.437024
50.2064341.41520.081795
6-0.096671-0.66270.255366
7-0.033992-0.2330.408372
8-0.229937-1.57640.060825
9-0.179956-1.23370.111721
10-0.246202-1.68790.049031
11-0.083373-0.57160.285166
12-0.102982-0.7060.241833
13-0.077293-0.52990.29934
14-0.008669-0.05940.47643
150.0091390.06270.475153
16-0.146919-1.00720.159491
17-0.080121-0.54930.292706
18-0.103907-0.71230.239885
190.0210060.1440.443054
20-0.198177-1.35860.090374
21-0.064378-0.44140.330491
22-0.114466-0.78470.218272
230.0043380.02970.488201
240.0786090.53890.296245
25-0.05842-0.40050.345299
26-0.007568-0.05190.47942
270.0004890.00340.49867
28-0.071756-0.49190.312527
29-0.117533-0.80580.212218
30-0.033424-0.22910.409877
31-0.120664-0.82720.206142
32-0.001805-0.01240.495091
33-0.004054-0.02780.488973
340.0385530.26430.396351
35-0.016042-0.110.456447
360.0808380.55420.291035


Figures (Output of Computation)

Input Parameters & R Code

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 ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
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')