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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 computationSun, 20 Dec 2009 01:24:43 -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/20/t1261297604hxny6klv28g8d6s.htm/, Retrieved Sat, 27 Apr 2024 08:09:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=69794, Retrieved Sat, 27 Apr 2024 08:09:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact162

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 12:26:39] [b98453cac15ba1066b407e146608df68]
-    D        [(Partial) Autocorrelation Function] [] [2009-11-23 15:32:19] [5d885a68c2332cc44f6191ec94766bfa]
-    D            [(Partial) Autocorrelation Function] [] [2009-12-20 08:24:43] [2b679e8ec54382eeb0ec0b6bb527570a] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
101.09
102.71
102.11
101.68
101.7
101.53
101.76
101.15
100.92
100.73
100.55
102.15
100.79
99.93
100.03
100.25
99.6
100.16
100.49
99.72
100.14
98.48
100.38
101.45
98.42
98.6
100.06
98.62
100.84
100.02
97.95
98.32
98.27
97.22
99.28
100.38
99.02
100.32
99.81
100.6
101.19
100.47
101.77
102.32
102.39
101.16
100.63
101.48
101.44
100.09
100.7
100.78
99.81
98.45
98.49
97.48
97.91
96.94
98.53
96.82
95.76

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69794&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]2 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=69794&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69794&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.311205-2.41060.009504
2-0.221042-1.71220.046014
30.289022.23870.014447
4-0.182628-1.41460.081173
50.0167840.130.448496
60.2307651.78750.039454
7-0.189899-1.4710.073265
80.1262490.97790.166019
90.110780.85810.197127
10-0.28813-2.23180.014686
110.1085990.84120.201787
120.114170.88440.190016
13-0.243011-1.88240.03232
140.0929110.71970.237256
15-0.044548-0.34510.365625
16-0.01992-0.15430.438945
170.1631311.26360.105629
18-0.197577-1.53040.065584
19-0.003304-0.02560.489833
20-0.037912-0.29370.385014
210.0255470.19790.421901
220.0437960.33920.367806
23-0.108266-0.83860.202505
240.0846370.65560.257296
250.0126980.09840.460988
26-0.088822-0.6880.247049
27-0.032603-0.25250.400744
280.0670120.51910.302811
29-0.03681-0.28510.388264
300.0466330.36120.359601
31-0.064419-0.4990.309807
32-0.018694-0.14480.442675
330.103310.80020.213365
34-0.073816-0.57180.284804
35-0.049127-0.38050.352445
360.1638451.26910.104647

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.311205 & -2.4106 & 0.009504 \tabularnewline
2 & -0.221042 & -1.7122 & 0.046014 \tabularnewline
3 & 0.28902 & 2.2387 & 0.014447 \tabularnewline
4 & -0.182628 & -1.4146 & 0.081173 \tabularnewline
5 & 0.016784 & 0.13 & 0.448496 \tabularnewline
6 & 0.230765 & 1.7875 & 0.039454 \tabularnewline
7 & -0.189899 & -1.471 & 0.073265 \tabularnewline
8 & 0.126249 & 0.9779 & 0.166019 \tabularnewline
9 & 0.11078 & 0.8581 & 0.197127 \tabularnewline
10 & -0.28813 & -2.2318 & 0.014686 \tabularnewline
11 & 0.108599 & 0.8412 & 0.201787 \tabularnewline
12 & 0.11417 & 0.8844 & 0.190016 \tabularnewline
13 & -0.243011 & -1.8824 & 0.03232 \tabularnewline
14 & 0.092911 & 0.7197 & 0.237256 \tabularnewline
15 & -0.044548 & -0.3451 & 0.365625 \tabularnewline
16 & -0.01992 & -0.1543 & 0.438945 \tabularnewline
17 & 0.163131 & 1.2636 & 0.105629 \tabularnewline
18 & -0.197577 & -1.5304 & 0.065584 \tabularnewline
19 & -0.003304 & -0.0256 & 0.489833 \tabularnewline
20 & -0.037912 & -0.2937 & 0.385014 \tabularnewline
21 & 0.025547 & 0.1979 & 0.421901 \tabularnewline
22 & 0.043796 & 0.3392 & 0.367806 \tabularnewline
23 & -0.108266 & -0.8386 & 0.202505 \tabularnewline
24 & 0.084637 & 0.6556 & 0.257296 \tabularnewline
25 & 0.012698 & 0.0984 & 0.460988 \tabularnewline
26 & -0.088822 & -0.688 & 0.247049 \tabularnewline
27 & -0.032603 & -0.2525 & 0.400744 \tabularnewline
28 & 0.067012 & 0.5191 & 0.302811 \tabularnewline
29 & -0.03681 & -0.2851 & 0.388264 \tabularnewline
30 & 0.046633 & 0.3612 & 0.359601 \tabularnewline
31 & -0.064419 & -0.499 & 0.309807 \tabularnewline
32 & -0.018694 & -0.1448 & 0.442675 \tabularnewline
33 & 0.10331 & 0.8002 & 0.213365 \tabularnewline
34 & -0.073816 & -0.5718 & 0.284804 \tabularnewline
35 & -0.049127 & -0.3805 & 0.352445 \tabularnewline
36 & 0.163845 & 1.2691 & 0.104647 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69794&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]-0.311205[/C][C]-2.4106[/C][C]0.009504[/C][/ROW]
[ROW][C]2[/C][C]-0.221042[/C][C]-1.7122[/C][C]0.046014[/C][/ROW]
[ROW][C]3[/C][C]0.28902[/C][C]2.2387[/C][C]0.014447[/C][/ROW]
[ROW][C]4[/C][C]-0.182628[/C][C]-1.4146[/C][C]0.081173[/C][/ROW]
[ROW][C]5[/C][C]0.016784[/C][C]0.13[/C][C]0.448496[/C][/ROW]
[ROW][C]6[/C][C]0.230765[/C][C]1.7875[/C][C]0.039454[/C][/ROW]
[ROW][C]7[/C][C]-0.189899[/C][C]-1.471[/C][C]0.073265[/C][/ROW]
[ROW][C]8[/C][C]0.126249[/C][C]0.9779[/C][C]0.166019[/C][/ROW]
[ROW][C]9[/C][C]0.11078[/C][C]0.8581[/C][C]0.197127[/C][/ROW]
[ROW][C]10[/C][C]-0.28813[/C][C]-2.2318[/C][C]0.014686[/C][/ROW]
[ROW][C]11[/C][C]0.108599[/C][C]0.8412[/C][C]0.201787[/C][/ROW]
[ROW][C]12[/C][C]0.11417[/C][C]0.8844[/C][C]0.190016[/C][/ROW]
[ROW][C]13[/C][C]-0.243011[/C][C]-1.8824[/C][C]0.03232[/C][/ROW]
[ROW][C]14[/C][C]0.092911[/C][C]0.7197[/C][C]0.237256[/C][/ROW]
[ROW][C]15[/C][C]-0.044548[/C][C]-0.3451[/C][C]0.365625[/C][/ROW]
[ROW][C]16[/C][C]-0.01992[/C][C]-0.1543[/C][C]0.438945[/C][/ROW]
[ROW][C]17[/C][C]0.163131[/C][C]1.2636[/C][C]0.105629[/C][/ROW]
[ROW][C]18[/C][C]-0.197577[/C][C]-1.5304[/C][C]0.065584[/C][/ROW]
[ROW][C]19[/C][C]-0.003304[/C][C]-0.0256[/C][C]0.489833[/C][/ROW]
[ROW][C]20[/C][C]-0.037912[/C][C]-0.2937[/C][C]0.385014[/C][/ROW]
[ROW][C]21[/C][C]0.025547[/C][C]0.1979[/C][C]0.421901[/C][/ROW]
[ROW][C]22[/C][C]0.043796[/C][C]0.3392[/C][C]0.367806[/C][/ROW]
[ROW][C]23[/C][C]-0.108266[/C][C]-0.8386[/C][C]0.202505[/C][/ROW]
[ROW][C]24[/C][C]0.084637[/C][C]0.6556[/C][C]0.257296[/C][/ROW]
[ROW][C]25[/C][C]0.012698[/C][C]0.0984[/C][C]0.460988[/C][/ROW]
[ROW][C]26[/C][C]-0.088822[/C][C]-0.688[/C][C]0.247049[/C][/ROW]
[ROW][C]27[/C][C]-0.032603[/C][C]-0.2525[/C][C]0.400744[/C][/ROW]
[ROW][C]28[/C][C]0.067012[/C][C]0.5191[/C][C]0.302811[/C][/ROW]
[ROW][C]29[/C][C]-0.03681[/C][C]-0.2851[/C][C]0.388264[/C][/ROW]
[ROW][C]30[/C][C]0.046633[/C][C]0.3612[/C][C]0.359601[/C][/ROW]
[ROW][C]31[/C][C]-0.064419[/C][C]-0.499[/C][C]0.309807[/C][/ROW]
[ROW][C]32[/C][C]-0.018694[/C][C]-0.1448[/C][C]0.442675[/C][/ROW]
[ROW][C]33[/C][C]0.10331[/C][C]0.8002[/C][C]0.213365[/C][/ROW]
[ROW][C]34[/C][C]-0.073816[/C][C]-0.5718[/C][C]0.284804[/C][/ROW]
[ROW][C]35[/C][C]-0.049127[/C][C]-0.3805[/C][C]0.352445[/C][/ROW]
[ROW][C]36[/C][C]0.163845[/C][C]1.2691[/C][C]0.104647[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69794&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69794&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
1-0.311205-2.41060.009504
2-0.221042-1.71220.046014
30.289022.23870.014447
4-0.182628-1.41460.081173
50.0167840.130.448496
60.2307651.78750.039454
7-0.189899-1.4710.073265
80.1262490.97790.166019
90.110780.85810.197127
10-0.28813-2.23180.014686
110.1085990.84120.201787
120.114170.88440.190016
13-0.243011-1.88240.03232
140.0929110.71970.237256
15-0.044548-0.34510.365625
16-0.01992-0.15430.438945
170.1631311.26360.105629
18-0.197577-1.53040.065584
19-0.003304-0.02560.489833
20-0.037912-0.29370.385014
210.0255470.19790.421901
220.0437960.33920.367806
23-0.108266-0.83860.202505
240.0846370.65560.257296
250.0126980.09840.460988
26-0.088822-0.6880.247049
27-0.032603-0.25250.400744
280.0670120.51910.302811
29-0.03681-0.28510.388264
300.0466330.36120.359601
31-0.064419-0.4990.309807
32-0.018694-0.14480.442675
330.103310.80020.213365
34-0.073816-0.57180.284804
35-0.049127-0.38050.352445
360.1638451.26910.104647






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.311205-2.41060.009504
2-0.351979-2.72640.004191
30.1092950.84660.200293
4-0.135287-1.04790.149438
50.026970.20890.417614
60.1753411.35820.089746
70.0052550.04070.483834
80.178961.38620.085406
90.1384281.07230.143948
10-0.116393-0.90160.185443
11-0.067495-0.52280.301515
12-0.016835-0.13040.448342
13-0.1688-1.30750.098012
14-0.138314-1.07140.144145
15-0.223753-1.73320.0441
160.0100080.07750.469232
170.1162670.90060.185701
18-0.022559-0.17470.430935
190.1010140.78250.218514
20-0.198932-1.54090.064297
210.0966230.74840.22856
220.026260.20340.419751
23-0.161758-1.2530.107538
240.0459610.3560.36154
25-0.077796-0.60260.274521
260.0419620.3250.373142
27-0.098132-0.76010.225077
28-0.057354-0.44430.329224
29-0.001646-0.01270.494935
300.014710.11390.454833
31-0.068722-0.53230.298236
320.0048660.03770.485029
33-0.091099-0.70560.241568
340.0201470.15610.438254
35-0.000435-0.00340.498661
360.0849310.65790.256569

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.311205 & -2.4106 & 0.009504 \tabularnewline
2 & -0.351979 & -2.7264 & 0.004191 \tabularnewline
3 & 0.109295 & 0.8466 & 0.200293 \tabularnewline
4 & -0.135287 & -1.0479 & 0.149438 \tabularnewline
5 & 0.02697 & 0.2089 & 0.417614 \tabularnewline
6 & 0.175341 & 1.3582 & 0.089746 \tabularnewline
7 & 0.005255 & 0.0407 & 0.483834 \tabularnewline
8 & 0.17896 & 1.3862 & 0.085406 \tabularnewline
9 & 0.138428 & 1.0723 & 0.143948 \tabularnewline
10 & -0.116393 & -0.9016 & 0.185443 \tabularnewline
11 & -0.067495 & -0.5228 & 0.301515 \tabularnewline
12 & -0.016835 & -0.1304 & 0.448342 \tabularnewline
13 & -0.1688 & -1.3075 & 0.098012 \tabularnewline
14 & -0.138314 & -1.0714 & 0.144145 \tabularnewline
15 & -0.223753 & -1.7332 & 0.0441 \tabularnewline
16 & 0.010008 & 0.0775 & 0.469232 \tabularnewline
17 & 0.116267 & 0.9006 & 0.185701 \tabularnewline
18 & -0.022559 & -0.1747 & 0.430935 \tabularnewline
19 & 0.101014 & 0.7825 & 0.218514 \tabularnewline
20 & -0.198932 & -1.5409 & 0.064297 \tabularnewline
21 & 0.096623 & 0.7484 & 0.22856 \tabularnewline
22 & 0.02626 & 0.2034 & 0.419751 \tabularnewline
23 & -0.161758 & -1.253 & 0.107538 \tabularnewline
24 & 0.045961 & 0.356 & 0.36154 \tabularnewline
25 & -0.077796 & -0.6026 & 0.274521 \tabularnewline
26 & 0.041962 & 0.325 & 0.373142 \tabularnewline
27 & -0.098132 & -0.7601 & 0.225077 \tabularnewline
28 & -0.057354 & -0.4443 & 0.329224 \tabularnewline
29 & -0.001646 & -0.0127 & 0.494935 \tabularnewline
30 & 0.01471 & 0.1139 & 0.454833 \tabularnewline
31 & -0.068722 & -0.5323 & 0.298236 \tabularnewline
32 & 0.004866 & 0.0377 & 0.485029 \tabularnewline
33 & -0.091099 & -0.7056 & 0.241568 \tabularnewline
34 & 0.020147 & 0.1561 & 0.438254 \tabularnewline
35 & -0.000435 & -0.0034 & 0.498661 \tabularnewline
36 & 0.084931 & 0.6579 & 0.256569 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69794&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]-0.311205[/C][C]-2.4106[/C][C]0.009504[/C][/ROW]
[ROW][C]2[/C][C]-0.351979[/C][C]-2.7264[/C][C]0.004191[/C][/ROW]
[ROW][C]3[/C][C]0.109295[/C][C]0.8466[/C][C]0.200293[/C][/ROW]
[ROW][C]4[/C][C]-0.135287[/C][C]-1.0479[/C][C]0.149438[/C][/ROW]
[ROW][C]5[/C][C]0.02697[/C][C]0.2089[/C][C]0.417614[/C][/ROW]
[ROW][C]6[/C][C]0.175341[/C][C]1.3582[/C][C]0.089746[/C][/ROW]
[ROW][C]7[/C][C]0.005255[/C][C]0.0407[/C][C]0.483834[/C][/ROW]
[ROW][C]8[/C][C]0.17896[/C][C]1.3862[/C][C]0.085406[/C][/ROW]
[ROW][C]9[/C][C]0.138428[/C][C]1.0723[/C][C]0.143948[/C][/ROW]
[ROW][C]10[/C][C]-0.116393[/C][C]-0.9016[/C][C]0.185443[/C][/ROW]
[ROW][C]11[/C][C]-0.067495[/C][C]-0.5228[/C][C]0.301515[/C][/ROW]
[ROW][C]12[/C][C]-0.016835[/C][C]-0.1304[/C][C]0.448342[/C][/ROW]
[ROW][C]13[/C][C]-0.1688[/C][C]-1.3075[/C][C]0.098012[/C][/ROW]
[ROW][C]14[/C][C]-0.138314[/C][C]-1.0714[/C][C]0.144145[/C][/ROW]
[ROW][C]15[/C][C]-0.223753[/C][C]-1.7332[/C][C]0.0441[/C][/ROW]
[ROW][C]16[/C][C]0.010008[/C][C]0.0775[/C][C]0.469232[/C][/ROW]
[ROW][C]17[/C][C]0.116267[/C][C]0.9006[/C][C]0.185701[/C][/ROW]
[ROW][C]18[/C][C]-0.022559[/C][C]-0.1747[/C][C]0.430935[/C][/ROW]
[ROW][C]19[/C][C]0.101014[/C][C]0.7825[/C][C]0.218514[/C][/ROW]
[ROW][C]20[/C][C]-0.198932[/C][C]-1.5409[/C][C]0.064297[/C][/ROW]
[ROW][C]21[/C][C]0.096623[/C][C]0.7484[/C][C]0.22856[/C][/ROW]
[ROW][C]22[/C][C]0.02626[/C][C]0.2034[/C][C]0.419751[/C][/ROW]
[ROW][C]23[/C][C]-0.161758[/C][C]-1.253[/C][C]0.107538[/C][/ROW]
[ROW][C]24[/C][C]0.045961[/C][C]0.356[/C][C]0.36154[/C][/ROW]
[ROW][C]25[/C][C]-0.077796[/C][C]-0.6026[/C][C]0.274521[/C][/ROW]
[ROW][C]26[/C][C]0.041962[/C][C]0.325[/C][C]0.373142[/C][/ROW]
[ROW][C]27[/C][C]-0.098132[/C][C]-0.7601[/C][C]0.225077[/C][/ROW]
[ROW][C]28[/C][C]-0.057354[/C][C]-0.4443[/C][C]0.329224[/C][/ROW]
[ROW][C]29[/C][C]-0.001646[/C][C]-0.0127[/C][C]0.494935[/C][/ROW]
[ROW][C]30[/C][C]0.01471[/C][C]0.1139[/C][C]0.454833[/C][/ROW]
[ROW][C]31[/C][C]-0.068722[/C][C]-0.5323[/C][C]0.298236[/C][/ROW]
[ROW][C]32[/C][C]0.004866[/C][C]0.0377[/C][C]0.485029[/C][/ROW]
[ROW][C]33[/C][C]-0.091099[/C][C]-0.7056[/C][C]0.241568[/C][/ROW]
[ROW][C]34[/C][C]0.020147[/C][C]0.1561[/C][C]0.438254[/C][/ROW]
[ROW][C]35[/C][C]-0.000435[/C][C]-0.0034[/C][C]0.498661[/C][/ROW]
[ROW][C]36[/C][C]0.084931[/C][C]0.6579[/C][C]0.256569[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69794&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69794&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
1-0.311205-2.41060.009504
2-0.351979-2.72640.004191
30.1092950.84660.200293
4-0.135287-1.04790.149438
50.026970.20890.417614
60.1753411.35820.089746
70.0052550.04070.483834
80.178961.38620.085406
90.1384281.07230.143948
10-0.116393-0.90160.185443
11-0.067495-0.52280.301515
12-0.016835-0.13040.448342
13-0.1688-1.30750.098012
14-0.138314-1.07140.144145
15-0.223753-1.73320.0441
160.0100080.07750.469232
170.1162670.90060.185701
18-0.022559-0.17470.430935
190.1010140.78250.218514
20-0.198932-1.54090.064297
210.0966230.74840.22856
220.026260.20340.419751
23-0.161758-1.2530.107538
240.0459610.3560.36154
25-0.077796-0.60260.274521
260.0419620.3250.373142
27-0.098132-0.76010.225077
28-0.057354-0.44430.329224
29-0.001646-0.01270.494935
300.014710.11390.454833
31-0.068722-0.53230.298236
320.0048660.03770.485029
33-0.091099-0.70560.241568
340.0201470.15610.438254
35-0.000435-0.00340.498661
360.0849310.65790.256569


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 = 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')