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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, 25 Nov 2009 11:29:11 -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/25/t1259174050zp8w5xrymmhw432.htm/, Retrieved Wed, 08 May 2024 20:49:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59550, Retrieved Wed, 08 May 2024 20:49:35 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact136

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]
- R  D          [(Partial) Autocorrelation Function] [ACF Link 1] [2009-11-25 18:29:11] [026d431dc78a3ce53a040b5408fc0322] [Current]
-   PD            [(Partial) Autocorrelation Function] [ACF d=0 D=0] [2009-12-02 18:51:07] [1f74ef2f756548f1f3a7b6136ea56d7f]
-    D              [(Partial) Autocorrelation Function] [WS 9 ACF d=0 en D=0] [2009-12-04 13:58:17] [af8eb90b4bf1bcfcc4325c143dbee260]
-   PD                [(Partial) Autocorrelation Function] [] [2009-12-20 15:15:21] [5e6d255681a7853beaa91b62357037a7]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
5250,0
3937,0
4004,0
5560,0
3922,0
3759,0
4138,0
4634,0
3996,0
4308,0
4143,0
4429,0
5219,0
4929,0
5755,0
5592,0
4163,0
4962,0
5208,0
4755,0
4491,0
5732,0
5731,0
5040,0
6102,0
4904,0
5369,0
5578,0
4619,0
4731,0
5011,0
5299,0
4146,0
4625,0
4736,0
4219,0
5116,0
4205,0
4121,0
5103,0
4300,0
4578,0
3809,0
5526,0
4247,0
3830,0
4394,0
4826,0
4409,0
4569,0
4106,0
4794,0
3914,0
3793,0
4405,0
4022,0
4100,0
4788,0
3163,0
3585,0
3903,0

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=59550&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=59550&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59550&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
10.2676342.09030.020384
20.2286181.78560.03957
30.4367053.41080.000577
40.2804092.19010.016177
50.1848881.4440.076925
60.1753371.36940.087944
70.2031471.58660.058884
80.1338821.04570.149923
90.1451881.1340.130625
100.1127610.88070.19097
11-0.047218-0.36880.356782
120.1678661.31110.097373
13-0.040071-0.3130.377689
14-0.009619-0.07510.470179
150.0104710.08180.467543
16-0.118849-0.92820.17847
17-0.105588-0.82470.206386
18-0.038543-0.3010.382207
19-0.11155-0.87120.193521
20-0.197391-1.54170.064162
21-0.02514-0.19630.422496
22-0.09474-0.73990.231087
23-0.177463-1.3860.085392
24-0.034245-0.26750.395007
25-0.115679-0.90350.184912
26-0.104635-0.81720.208491
27-0.091338-0.71340.239167
28-0.137262-1.07210.14396
29-0.15955-1.24610.108742
30-0.119667-0.93460.176832
31-0.176034-1.37490.087101
32-0.202741-1.58350.059245
33-0.093879-0.73320.233117
34-0.183735-1.4350.078195
35-0.202804-1.58390.059188
36-0.044258-0.34570.36539

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.267634 & 2.0903 & 0.020384 \tabularnewline
2 & 0.228618 & 1.7856 & 0.03957 \tabularnewline
3 & 0.436705 & 3.4108 & 0.000577 \tabularnewline
4 & 0.280409 & 2.1901 & 0.016177 \tabularnewline
5 & 0.184888 & 1.444 & 0.076925 \tabularnewline
6 & 0.175337 & 1.3694 & 0.087944 \tabularnewline
7 & 0.203147 & 1.5866 & 0.058884 \tabularnewline
8 & 0.133882 & 1.0457 & 0.149923 \tabularnewline
9 & 0.145188 & 1.134 & 0.130625 \tabularnewline
10 & 0.112761 & 0.8807 & 0.19097 \tabularnewline
11 & -0.047218 & -0.3688 & 0.356782 \tabularnewline
12 & 0.167866 & 1.3111 & 0.097373 \tabularnewline
13 & -0.040071 & -0.313 & 0.377689 \tabularnewline
14 & -0.009619 & -0.0751 & 0.470179 \tabularnewline
15 & 0.010471 & 0.0818 & 0.467543 \tabularnewline
16 & -0.118849 & -0.9282 & 0.17847 \tabularnewline
17 & -0.105588 & -0.8247 & 0.206386 \tabularnewline
18 & -0.038543 & -0.301 & 0.382207 \tabularnewline
19 & -0.11155 & -0.8712 & 0.193521 \tabularnewline
20 & -0.197391 & -1.5417 & 0.064162 \tabularnewline
21 & -0.02514 & -0.1963 & 0.422496 \tabularnewline
22 & -0.09474 & -0.7399 & 0.231087 \tabularnewline
23 & -0.177463 & -1.386 & 0.085392 \tabularnewline
24 & -0.034245 & -0.2675 & 0.395007 \tabularnewline
25 & -0.115679 & -0.9035 & 0.184912 \tabularnewline
26 & -0.104635 & -0.8172 & 0.208491 \tabularnewline
27 & -0.091338 & -0.7134 & 0.239167 \tabularnewline
28 & -0.137262 & -1.0721 & 0.14396 \tabularnewline
29 & -0.15955 & -1.2461 & 0.108742 \tabularnewline
30 & -0.119667 & -0.9346 & 0.176832 \tabularnewline
31 & -0.176034 & -1.3749 & 0.087101 \tabularnewline
32 & -0.202741 & -1.5835 & 0.059245 \tabularnewline
33 & -0.093879 & -0.7332 & 0.233117 \tabularnewline
34 & -0.183735 & -1.435 & 0.078195 \tabularnewline
35 & -0.202804 & -1.5839 & 0.059188 \tabularnewline
36 & -0.044258 & -0.3457 & 0.36539 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59550&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]0.267634[/C][C]2.0903[/C][C]0.020384[/C][/ROW]
[ROW][C]2[/C][C]0.228618[/C][C]1.7856[/C][C]0.03957[/C][/ROW]
[ROW][C]3[/C][C]0.436705[/C][C]3.4108[/C][C]0.000577[/C][/ROW]
[ROW][C]4[/C][C]0.280409[/C][C]2.1901[/C][C]0.016177[/C][/ROW]
[ROW][C]5[/C][C]0.184888[/C][C]1.444[/C][C]0.076925[/C][/ROW]
[ROW][C]6[/C][C]0.175337[/C][C]1.3694[/C][C]0.087944[/C][/ROW]
[ROW][C]7[/C][C]0.203147[/C][C]1.5866[/C][C]0.058884[/C][/ROW]
[ROW][C]8[/C][C]0.133882[/C][C]1.0457[/C][C]0.149923[/C][/ROW]
[ROW][C]9[/C][C]0.145188[/C][C]1.134[/C][C]0.130625[/C][/ROW]
[ROW][C]10[/C][C]0.112761[/C][C]0.8807[/C][C]0.19097[/C][/ROW]
[ROW][C]11[/C][C]-0.047218[/C][C]-0.3688[/C][C]0.356782[/C][/ROW]
[ROW][C]12[/C][C]0.167866[/C][C]1.3111[/C][C]0.097373[/C][/ROW]
[ROW][C]13[/C][C]-0.040071[/C][C]-0.313[/C][C]0.377689[/C][/ROW]
[ROW][C]14[/C][C]-0.009619[/C][C]-0.0751[/C][C]0.470179[/C][/ROW]
[ROW][C]15[/C][C]0.010471[/C][C]0.0818[/C][C]0.467543[/C][/ROW]
[ROW][C]16[/C][C]-0.118849[/C][C]-0.9282[/C][C]0.17847[/C][/ROW]
[ROW][C]17[/C][C]-0.105588[/C][C]-0.8247[/C][C]0.206386[/C][/ROW]
[ROW][C]18[/C][C]-0.038543[/C][C]-0.301[/C][C]0.382207[/C][/ROW]
[ROW][C]19[/C][C]-0.11155[/C][C]-0.8712[/C][C]0.193521[/C][/ROW]
[ROW][C]20[/C][C]-0.197391[/C][C]-1.5417[/C][C]0.064162[/C][/ROW]
[ROW][C]21[/C][C]-0.02514[/C][C]-0.1963[/C][C]0.422496[/C][/ROW]
[ROW][C]22[/C][C]-0.09474[/C][C]-0.7399[/C][C]0.231087[/C][/ROW]
[ROW][C]23[/C][C]-0.177463[/C][C]-1.386[/C][C]0.085392[/C][/ROW]
[ROW][C]24[/C][C]-0.034245[/C][C]-0.2675[/C][C]0.395007[/C][/ROW]
[ROW][C]25[/C][C]-0.115679[/C][C]-0.9035[/C][C]0.184912[/C][/ROW]
[ROW][C]26[/C][C]-0.104635[/C][C]-0.8172[/C][C]0.208491[/C][/ROW]
[ROW][C]27[/C][C]-0.091338[/C][C]-0.7134[/C][C]0.239167[/C][/ROW]
[ROW][C]28[/C][C]-0.137262[/C][C]-1.0721[/C][C]0.14396[/C][/ROW]
[ROW][C]29[/C][C]-0.15955[/C][C]-1.2461[/C][C]0.108742[/C][/ROW]
[ROW][C]30[/C][C]-0.119667[/C][C]-0.9346[/C][C]0.176832[/C][/ROW]
[ROW][C]31[/C][C]-0.176034[/C][C]-1.3749[/C][C]0.087101[/C][/ROW]
[ROW][C]32[/C][C]-0.202741[/C][C]-1.5835[/C][C]0.059245[/C][/ROW]
[ROW][C]33[/C][C]-0.093879[/C][C]-0.7332[/C][C]0.233117[/C][/ROW]
[ROW][C]34[/C][C]-0.183735[/C][C]-1.435[/C][C]0.078195[/C][/ROW]
[ROW][C]35[/C][C]-0.202804[/C][C]-1.5839[/C][C]0.059188[/C][/ROW]
[ROW][C]36[/C][C]-0.044258[/C][C]-0.3457[/C][C]0.36539[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59550&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59550&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
10.2676342.09030.020384
20.2286181.78560.03957
30.4367053.41080.000577
40.2804092.19010.016177
50.1848881.4440.076925
60.1753371.36940.087944
70.2031471.58660.058884
80.1338821.04570.149923
90.1451881.1340.130625
100.1127610.88070.19097
11-0.047218-0.36880.356782
120.1678661.31110.097373
13-0.040071-0.3130.377689
14-0.009619-0.07510.470179
150.0104710.08180.467543
16-0.118849-0.92820.17847
17-0.105588-0.82470.206386
18-0.038543-0.3010.382207
19-0.11155-0.87120.193521
20-0.197391-1.54170.064162
21-0.02514-0.19630.422496
22-0.09474-0.73990.231087
23-0.177463-1.3860.085392
24-0.034245-0.26750.395007
25-0.115679-0.90350.184912
26-0.104635-0.81720.208491
27-0.091338-0.71340.239167
28-0.137262-1.07210.14396
29-0.15955-1.24610.108742
30-0.119667-0.93460.176832
31-0.176034-1.37490.087101
32-0.202741-1.58350.059245
33-0.093879-0.73320.233117
34-0.183735-1.4350.078195
35-0.202804-1.58390.059188
36-0.044258-0.34570.36539






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.2676342.09030.020384
20.1691031.32070.095762
30.3776872.94980.002252
40.1172380.91570.181725
50.0086170.06730.473282
6-0.067174-0.52460.300864
70.0297110.2320.408639
8-0.002975-0.02320.490768
90.0622770.48640.314212
10-0.015785-0.12330.451145
11-0.191348-1.49450.070103
120.1345541.05090.148725
13-0.155139-1.21170.115155
140.0775330.60550.27353
15-0.074824-0.58440.280556
16-0.117093-0.91450.18202
17-0.094615-0.7390.231382
180.0615570.48080.316197
19-0.026003-0.20310.419869
20-0.078294-0.61150.271572
210.0964480.75330.227089
22-0.076082-0.59420.277282
230.048320.37740.353596
24-0.005911-0.04620.481665
250.0035220.02750.489072
26-0.018331-0.14320.443314
27-0.038773-0.30280.381525
28-0.074603-0.58270.281132
29-0.075664-0.5910.278367
30-0.02764-0.21590.414902
31-0.129005-1.00760.158823
32-0.005053-0.03950.484323
33-0.034236-0.26740.395036
34-0.037257-0.2910.386024
35-0.050847-0.39710.34633
360.0666270.52040.302343

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.267634 & 2.0903 & 0.020384 \tabularnewline
2 & 0.169103 & 1.3207 & 0.095762 \tabularnewline
3 & 0.377687 & 2.9498 & 0.002252 \tabularnewline
4 & 0.117238 & 0.9157 & 0.181725 \tabularnewline
5 & 0.008617 & 0.0673 & 0.473282 \tabularnewline
6 & -0.067174 & -0.5246 & 0.300864 \tabularnewline
7 & 0.029711 & 0.232 & 0.408639 \tabularnewline
8 & -0.002975 & -0.0232 & 0.490768 \tabularnewline
9 & 0.062277 & 0.4864 & 0.314212 \tabularnewline
10 & -0.015785 & -0.1233 & 0.451145 \tabularnewline
11 & -0.191348 & -1.4945 & 0.070103 \tabularnewline
12 & 0.134554 & 1.0509 & 0.148725 \tabularnewline
13 & -0.155139 & -1.2117 & 0.115155 \tabularnewline
14 & 0.077533 & 0.6055 & 0.27353 \tabularnewline
15 & -0.074824 & -0.5844 & 0.280556 \tabularnewline
16 & -0.117093 & -0.9145 & 0.18202 \tabularnewline
17 & -0.094615 & -0.739 & 0.231382 \tabularnewline
18 & 0.061557 & 0.4808 & 0.316197 \tabularnewline
19 & -0.026003 & -0.2031 & 0.419869 \tabularnewline
20 & -0.078294 & -0.6115 & 0.271572 \tabularnewline
21 & 0.096448 & 0.7533 & 0.227089 \tabularnewline
22 & -0.076082 & -0.5942 & 0.277282 \tabularnewline
23 & 0.04832 & 0.3774 & 0.353596 \tabularnewline
24 & -0.005911 & -0.0462 & 0.481665 \tabularnewline
25 & 0.003522 & 0.0275 & 0.489072 \tabularnewline
26 & -0.018331 & -0.1432 & 0.443314 \tabularnewline
27 & -0.038773 & -0.3028 & 0.381525 \tabularnewline
28 & -0.074603 & -0.5827 & 0.281132 \tabularnewline
29 & -0.075664 & -0.591 & 0.278367 \tabularnewline
30 & -0.02764 & -0.2159 & 0.414902 \tabularnewline
31 & -0.129005 & -1.0076 & 0.158823 \tabularnewline
32 & -0.005053 & -0.0395 & 0.484323 \tabularnewline
33 & -0.034236 & -0.2674 & 0.395036 \tabularnewline
34 & -0.037257 & -0.291 & 0.386024 \tabularnewline
35 & -0.050847 & -0.3971 & 0.34633 \tabularnewline
36 & 0.066627 & 0.5204 & 0.302343 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59550&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]0.267634[/C][C]2.0903[/C][C]0.020384[/C][/ROW]
[ROW][C]2[/C][C]0.169103[/C][C]1.3207[/C][C]0.095762[/C][/ROW]
[ROW][C]3[/C][C]0.377687[/C][C]2.9498[/C][C]0.002252[/C][/ROW]
[ROW][C]4[/C][C]0.117238[/C][C]0.9157[/C][C]0.181725[/C][/ROW]
[ROW][C]5[/C][C]0.008617[/C][C]0.0673[/C][C]0.473282[/C][/ROW]
[ROW][C]6[/C][C]-0.067174[/C][C]-0.5246[/C][C]0.300864[/C][/ROW]
[ROW][C]7[/C][C]0.029711[/C][C]0.232[/C][C]0.408639[/C][/ROW]
[ROW][C]8[/C][C]-0.002975[/C][C]-0.0232[/C][C]0.490768[/C][/ROW]
[ROW][C]9[/C][C]0.062277[/C][C]0.4864[/C][C]0.314212[/C][/ROW]
[ROW][C]10[/C][C]-0.015785[/C][C]-0.1233[/C][C]0.451145[/C][/ROW]
[ROW][C]11[/C][C]-0.191348[/C][C]-1.4945[/C][C]0.070103[/C][/ROW]
[ROW][C]12[/C][C]0.134554[/C][C]1.0509[/C][C]0.148725[/C][/ROW]
[ROW][C]13[/C][C]-0.155139[/C][C]-1.2117[/C][C]0.115155[/C][/ROW]
[ROW][C]14[/C][C]0.077533[/C][C]0.6055[/C][C]0.27353[/C][/ROW]
[ROW][C]15[/C][C]-0.074824[/C][C]-0.5844[/C][C]0.280556[/C][/ROW]
[ROW][C]16[/C][C]-0.117093[/C][C]-0.9145[/C][C]0.18202[/C][/ROW]
[ROW][C]17[/C][C]-0.094615[/C][C]-0.739[/C][C]0.231382[/C][/ROW]
[ROW][C]18[/C][C]0.061557[/C][C]0.4808[/C][C]0.316197[/C][/ROW]
[ROW][C]19[/C][C]-0.026003[/C][C]-0.2031[/C][C]0.419869[/C][/ROW]
[ROW][C]20[/C][C]-0.078294[/C][C]-0.6115[/C][C]0.271572[/C][/ROW]
[ROW][C]21[/C][C]0.096448[/C][C]0.7533[/C][C]0.227089[/C][/ROW]
[ROW][C]22[/C][C]-0.076082[/C][C]-0.5942[/C][C]0.277282[/C][/ROW]
[ROW][C]23[/C][C]0.04832[/C][C]0.3774[/C][C]0.353596[/C][/ROW]
[ROW][C]24[/C][C]-0.005911[/C][C]-0.0462[/C][C]0.481665[/C][/ROW]
[ROW][C]25[/C][C]0.003522[/C][C]0.0275[/C][C]0.489072[/C][/ROW]
[ROW][C]26[/C][C]-0.018331[/C][C]-0.1432[/C][C]0.443314[/C][/ROW]
[ROW][C]27[/C][C]-0.038773[/C][C]-0.3028[/C][C]0.381525[/C][/ROW]
[ROW][C]28[/C][C]-0.074603[/C][C]-0.5827[/C][C]0.281132[/C][/ROW]
[ROW][C]29[/C][C]-0.075664[/C][C]-0.591[/C][C]0.278367[/C][/ROW]
[ROW][C]30[/C][C]-0.02764[/C][C]-0.2159[/C][C]0.414902[/C][/ROW]
[ROW][C]31[/C][C]-0.129005[/C][C]-1.0076[/C][C]0.158823[/C][/ROW]
[ROW][C]32[/C][C]-0.005053[/C][C]-0.0395[/C][C]0.484323[/C][/ROW]
[ROW][C]33[/C][C]-0.034236[/C][C]-0.2674[/C][C]0.395036[/C][/ROW]
[ROW][C]34[/C][C]-0.037257[/C][C]-0.291[/C][C]0.386024[/C][/ROW]
[ROW][C]35[/C][C]-0.050847[/C][C]-0.3971[/C][C]0.34633[/C][/ROW]
[ROW][C]36[/C][C]0.066627[/C][C]0.5204[/C][C]0.302343[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59550&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59550&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
10.2676342.09030.020384
20.1691031.32070.095762
30.3776872.94980.002252
40.1172380.91570.181725
50.0086170.06730.473282
6-0.067174-0.52460.300864
70.0297110.2320.408639
8-0.002975-0.02320.490768
90.0622770.48640.314212
10-0.015785-0.12330.451145
11-0.191348-1.49450.070103
120.1345541.05090.148725
13-0.155139-1.21170.115155
140.0775330.60550.27353
15-0.074824-0.58440.280556
16-0.117093-0.91450.18202
17-0.094615-0.7390.231382
180.0615570.48080.316197
19-0.026003-0.20310.419869
20-0.078294-0.61150.271572
210.0964480.75330.227089
22-0.076082-0.59420.277282
230.048320.37740.353596
24-0.005911-0.04620.481665
250.0035220.02750.489072
26-0.018331-0.14320.443314
27-0.038773-0.30280.381525
28-0.074603-0.58270.281132
29-0.075664-0.5910.278367
30-0.02764-0.21590.414902
31-0.129005-1.00760.158823
32-0.005053-0.03950.484323
33-0.034236-0.26740.395036
34-0.037257-0.2910.386024
35-0.050847-0.39710.34633
360.0666270.52040.302343


Figures (Output of Computation)

Input Parameters & R Code

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