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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 computationFri, 04 Dec 2009 04:49:54 -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/04/t12599274809i0dcvzzqxu188g.htm/, Retrieved Sun, 28 Apr 2024 00:47:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63317, Retrieved Sun, 28 Apr 2024 00:47:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact103

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]
-    D        [(Partial) Autocorrelation Function] [Methode 1 d,D=0 l...] [2009-11-25 19:21:34] [36becc366f59efff5c3495030cea7527]
-   P           [(Partial) Autocorrelation Function] [Methode 1 d=0, D=...] [2009-11-25 19:28:04] [36becc366f59efff5c3495030cea7527]
- R PD              [(Partial) Autocorrelation Function] [Methode 1 d=1, D=...] [2009-12-04 11:49:54] [d1818fb1d9a1b0f34f8553ada228d3d5] [Current]
-   P                 [(Partial) Autocorrelation Function] [D=0, d=1 en λ=1] [2009-12-04 11:55:41] [4f1a20f787b3465111b61213cdeef1a9]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
105.7
105.7
111.1
82.4
60
107.3
99.3
113.5
108.9
100.2
103.9
138.7
120.2
100.2
143.2
70.9
85.2
133
136.6
117.9
106.3
122.3
125.5
148.4
126.3
99.6
140.4
80.3
92.6
138.5
110.9
119.6
105
109
129.4
148.6
101.4
134.8
143.7
81.6
90.3
141.5
140.7
140.2
100.2
125.7
119.6
134.7
109
116.3
146.9
97.4
89.4
132.1
139.8
129
112.5
121.9
121.7
123.1

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=63317&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=63317&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63317&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
1-0.554309-3.80020.000208
20.03660.25090.401487
30.064690.44350.329722
4-0.118272-0.81080.210775
50.0659010.45180.326747
60.1648741.13030.132038
7-0.274076-1.8790.033229
80.2124881.45670.075918
9-0.16888-1.15780.126401
100.041380.28370.388948
110.2197181.50630.069339
12-0.365664-2.50690.007848
130.1632081.11890.134435
140.0596080.40870.342326
15-0.068924-0.47250.319372
160.021970.15060.440462
170.0983480.67420.25173
18-0.231959-1.59020.059244
190.1672251.14640.128709
20-0.07961-0.54580.293899
210.2033351.3940.084938
22-0.287199-1.96890.027436
230.167261.14670.128659
24-0.051696-0.35440.362308
250.0481030.32980.371516
26-0.059648-0.40890.342225
270.0505490.34650.36524
28-0.065408-0.44840.327957
290.0898710.61610.270392
30-0.073492-0.50380.308365
310.0344880.23640.40706
32-0.037028-0.25390.400359
33-0.03811-0.26130.397512
340.1373120.94140.175666
35-0.079147-0.54260.294984
360.0094910.06510.474198

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.554309 & -3.8002 & 0.000208 \tabularnewline
2 & 0.0366 & 0.2509 & 0.401487 \tabularnewline
3 & 0.06469 & 0.4435 & 0.329722 \tabularnewline
4 & -0.118272 & -0.8108 & 0.210775 \tabularnewline
5 & 0.065901 & 0.4518 & 0.326747 \tabularnewline
6 & 0.164874 & 1.1303 & 0.132038 \tabularnewline
7 & -0.274076 & -1.879 & 0.033229 \tabularnewline
8 & 0.212488 & 1.4567 & 0.075918 \tabularnewline
9 & -0.16888 & -1.1578 & 0.126401 \tabularnewline
10 & 0.04138 & 0.2837 & 0.388948 \tabularnewline
11 & 0.219718 & 1.5063 & 0.069339 \tabularnewline
12 & -0.365664 & -2.5069 & 0.007848 \tabularnewline
13 & 0.163208 & 1.1189 & 0.134435 \tabularnewline
14 & 0.059608 & 0.4087 & 0.342326 \tabularnewline
15 & -0.068924 & -0.4725 & 0.319372 \tabularnewline
16 & 0.02197 & 0.1506 & 0.440462 \tabularnewline
17 & 0.098348 & 0.6742 & 0.25173 \tabularnewline
18 & -0.231959 & -1.5902 & 0.059244 \tabularnewline
19 & 0.167225 & 1.1464 & 0.128709 \tabularnewline
20 & -0.07961 & -0.5458 & 0.293899 \tabularnewline
21 & 0.203335 & 1.394 & 0.084938 \tabularnewline
22 & -0.287199 & -1.9689 & 0.027436 \tabularnewline
23 & 0.16726 & 1.1467 & 0.128659 \tabularnewline
24 & -0.051696 & -0.3544 & 0.362308 \tabularnewline
25 & 0.048103 & 0.3298 & 0.371516 \tabularnewline
26 & -0.059648 & -0.4089 & 0.342225 \tabularnewline
27 & 0.050549 & 0.3465 & 0.36524 \tabularnewline
28 & -0.065408 & -0.4484 & 0.327957 \tabularnewline
29 & 0.089871 & 0.6161 & 0.270392 \tabularnewline
30 & -0.073492 & -0.5038 & 0.308365 \tabularnewline
31 & 0.034488 & 0.2364 & 0.40706 \tabularnewline
32 & -0.037028 & -0.2539 & 0.400359 \tabularnewline
33 & -0.03811 & -0.2613 & 0.397512 \tabularnewline
34 & 0.137312 & 0.9414 & 0.175666 \tabularnewline
35 & -0.079147 & -0.5426 & 0.294984 \tabularnewline
36 & 0.009491 & 0.0651 & 0.474198 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63317&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]-0.554309[/C][C]-3.8002[/C][C]0.000208[/C][/ROW]
[ROW][C]2[/C][C]0.0366[/C][C]0.2509[/C][C]0.401487[/C][/ROW]
[ROW][C]3[/C][C]0.06469[/C][C]0.4435[/C][C]0.329722[/C][/ROW]
[ROW][C]4[/C][C]-0.118272[/C][C]-0.8108[/C][C]0.210775[/C][/ROW]
[ROW][C]5[/C][C]0.065901[/C][C]0.4518[/C][C]0.326747[/C][/ROW]
[ROW][C]6[/C][C]0.164874[/C][C]1.1303[/C][C]0.132038[/C][/ROW]
[ROW][C]7[/C][C]-0.274076[/C][C]-1.879[/C][C]0.033229[/C][/ROW]
[ROW][C]8[/C][C]0.212488[/C][C]1.4567[/C][C]0.075918[/C][/ROW]
[ROW][C]9[/C][C]-0.16888[/C][C]-1.1578[/C][C]0.126401[/C][/ROW]
[ROW][C]10[/C][C]0.04138[/C][C]0.2837[/C][C]0.388948[/C][/ROW]
[ROW][C]11[/C][C]0.219718[/C][C]1.5063[/C][C]0.069339[/C][/ROW]
[ROW][C]12[/C][C]-0.365664[/C][C]-2.5069[/C][C]0.007848[/C][/ROW]
[ROW][C]13[/C][C]0.163208[/C][C]1.1189[/C][C]0.134435[/C][/ROW]
[ROW][C]14[/C][C]0.059608[/C][C]0.4087[/C][C]0.342326[/C][/ROW]
[ROW][C]15[/C][C]-0.068924[/C][C]-0.4725[/C][C]0.319372[/C][/ROW]
[ROW][C]16[/C][C]0.02197[/C][C]0.1506[/C][C]0.440462[/C][/ROW]
[ROW][C]17[/C][C]0.098348[/C][C]0.6742[/C][C]0.25173[/C][/ROW]
[ROW][C]18[/C][C]-0.231959[/C][C]-1.5902[/C][C]0.059244[/C][/ROW]
[ROW][C]19[/C][C]0.167225[/C][C]1.1464[/C][C]0.128709[/C][/ROW]
[ROW][C]20[/C][C]-0.07961[/C][C]-0.5458[/C][C]0.293899[/C][/ROW]
[ROW][C]21[/C][C]0.203335[/C][C]1.394[/C][C]0.084938[/C][/ROW]
[ROW][C]22[/C][C]-0.287199[/C][C]-1.9689[/C][C]0.027436[/C][/ROW]
[ROW][C]23[/C][C]0.16726[/C][C]1.1467[/C][C]0.128659[/C][/ROW]
[ROW][C]24[/C][C]-0.051696[/C][C]-0.3544[/C][C]0.362308[/C][/ROW]
[ROW][C]25[/C][C]0.048103[/C][C]0.3298[/C][C]0.371516[/C][/ROW]
[ROW][C]26[/C][C]-0.059648[/C][C]-0.4089[/C][C]0.342225[/C][/ROW]
[ROW][C]27[/C][C]0.050549[/C][C]0.3465[/C][C]0.36524[/C][/ROW]
[ROW][C]28[/C][C]-0.065408[/C][C]-0.4484[/C][C]0.327957[/C][/ROW]
[ROW][C]29[/C][C]0.089871[/C][C]0.6161[/C][C]0.270392[/C][/ROW]
[ROW][C]30[/C][C]-0.073492[/C][C]-0.5038[/C][C]0.308365[/C][/ROW]
[ROW][C]31[/C][C]0.034488[/C][C]0.2364[/C][C]0.40706[/C][/ROW]
[ROW][C]32[/C][C]-0.037028[/C][C]-0.2539[/C][C]0.400359[/C][/ROW]
[ROW][C]33[/C][C]-0.03811[/C][C]-0.2613[/C][C]0.397512[/C][/ROW]
[ROW][C]34[/C][C]0.137312[/C][C]0.9414[/C][C]0.175666[/C][/ROW]
[ROW][C]35[/C][C]-0.079147[/C][C]-0.5426[/C][C]0.294984[/C][/ROW]
[ROW][C]36[/C][C]0.009491[/C][C]0.0651[/C][C]0.474198[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63317&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63317&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
1-0.554309-3.80020.000208
20.03660.25090.401487
30.064690.44350.329722
4-0.118272-0.81080.210775
50.0659010.45180.326747
60.1648741.13030.132038
7-0.274076-1.8790.033229
80.2124881.45670.075918
9-0.16888-1.15780.126401
100.041380.28370.388948
110.2197181.50630.069339
12-0.365664-2.50690.007848
130.1632081.11890.134435
140.0596080.40870.342326
15-0.068924-0.47250.319372
160.021970.15060.440462
170.0983480.67420.25173
18-0.231959-1.59020.059244
190.1672251.14640.128709
20-0.07961-0.54580.293899
210.2033351.3940.084938
22-0.287199-1.96890.027436
230.167261.14670.128659
24-0.051696-0.35440.362308
250.0481030.32980.371516
26-0.059648-0.40890.342225
270.0505490.34650.36524
28-0.065408-0.44840.327957
290.0898710.61610.270392
30-0.073492-0.50380.308365
310.0344880.23640.40706
32-0.037028-0.25390.400359
33-0.03811-0.26130.397512
340.1373120.94140.175666
35-0.079147-0.54260.294984
360.0094910.06510.474198






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.554309-3.80020.000208
2-0.390707-2.67850.005078
3-0.210681-1.44440.077636
4-0.284553-1.95080.028529
5-0.266273-1.82550.037143
60.0939940.64440.261227
7-0.094747-0.64960.259571
80.0578150.39640.346818
9-0.10353-0.70980.240679
10-0.137866-0.94520.174704
110.1982011.35880.090348
12-0.202578-1.38880.085719
13-0.211166-1.44770.077172
14-0.154483-1.05910.147487
15-0.007302-0.05010.480143
16-0.139581-0.95690.171753
170.0726730.49820.310327
180.0196760.13490.446637
19-0.110909-0.76040.225419
20-0.128922-0.88380.19064
210.1985471.36120.089975
22-0.199829-1.370.088605
23-0.011751-0.08060.468065
24-0.020266-0.13890.445047
25-0.03154-0.21620.414873
26-0.047553-0.3260.372933
27-0.044258-0.30340.381455
28-0.043892-0.30090.382405
290.0794290.54450.294323
300.0440380.30190.382026
31-0.138349-0.94850.173869
32-0.170232-1.16710.124538
33-0.001225-0.00840.496669
34-0.155474-1.06590.145962
35-0.054667-0.37480.354756
360.0756020.51830.303339

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.554309 & -3.8002 & 0.000208 \tabularnewline
2 & -0.390707 & -2.6785 & 0.005078 \tabularnewline
3 & -0.210681 & -1.4444 & 0.077636 \tabularnewline
4 & -0.284553 & -1.9508 & 0.028529 \tabularnewline
5 & -0.266273 & -1.8255 & 0.037143 \tabularnewline
6 & 0.093994 & 0.6444 & 0.261227 \tabularnewline
7 & -0.094747 & -0.6496 & 0.259571 \tabularnewline
8 & 0.057815 & 0.3964 & 0.346818 \tabularnewline
9 & -0.10353 & -0.7098 & 0.240679 \tabularnewline
10 & -0.137866 & -0.9452 & 0.174704 \tabularnewline
11 & 0.198201 & 1.3588 & 0.090348 \tabularnewline
12 & -0.202578 & -1.3888 & 0.085719 \tabularnewline
13 & -0.211166 & -1.4477 & 0.077172 \tabularnewline
14 & -0.154483 & -1.0591 & 0.147487 \tabularnewline
15 & -0.007302 & -0.0501 & 0.480143 \tabularnewline
16 & -0.139581 & -0.9569 & 0.171753 \tabularnewline
17 & 0.072673 & 0.4982 & 0.310327 \tabularnewline
18 & 0.019676 & 0.1349 & 0.446637 \tabularnewline
19 & -0.110909 & -0.7604 & 0.225419 \tabularnewline
20 & -0.128922 & -0.8838 & 0.19064 \tabularnewline
21 & 0.198547 & 1.3612 & 0.089975 \tabularnewline
22 & -0.199829 & -1.37 & 0.088605 \tabularnewline
23 & -0.011751 & -0.0806 & 0.468065 \tabularnewline
24 & -0.020266 & -0.1389 & 0.445047 \tabularnewline
25 & -0.03154 & -0.2162 & 0.414873 \tabularnewline
26 & -0.047553 & -0.326 & 0.372933 \tabularnewline
27 & -0.044258 & -0.3034 & 0.381455 \tabularnewline
28 & -0.043892 & -0.3009 & 0.382405 \tabularnewline
29 & 0.079429 & 0.5445 & 0.294323 \tabularnewline
30 & 0.044038 & 0.3019 & 0.382026 \tabularnewline
31 & -0.138349 & -0.9485 & 0.173869 \tabularnewline
32 & -0.170232 & -1.1671 & 0.124538 \tabularnewline
33 & -0.001225 & -0.0084 & 0.496669 \tabularnewline
34 & -0.155474 & -1.0659 & 0.145962 \tabularnewline
35 & -0.054667 & -0.3748 & 0.354756 \tabularnewline
36 & 0.075602 & 0.5183 & 0.303339 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63317&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]-0.554309[/C][C]-3.8002[/C][C]0.000208[/C][/ROW]
[ROW][C]2[/C][C]-0.390707[/C][C]-2.6785[/C][C]0.005078[/C][/ROW]
[ROW][C]3[/C][C]-0.210681[/C][C]-1.4444[/C][C]0.077636[/C][/ROW]
[ROW][C]4[/C][C]-0.284553[/C][C]-1.9508[/C][C]0.028529[/C][/ROW]
[ROW][C]5[/C][C]-0.266273[/C][C]-1.8255[/C][C]0.037143[/C][/ROW]
[ROW][C]6[/C][C]0.093994[/C][C]0.6444[/C][C]0.261227[/C][/ROW]
[ROW][C]7[/C][C]-0.094747[/C][C]-0.6496[/C][C]0.259571[/C][/ROW]
[ROW][C]8[/C][C]0.057815[/C][C]0.3964[/C][C]0.346818[/C][/ROW]
[ROW][C]9[/C][C]-0.10353[/C][C]-0.7098[/C][C]0.240679[/C][/ROW]
[ROW][C]10[/C][C]-0.137866[/C][C]-0.9452[/C][C]0.174704[/C][/ROW]
[ROW][C]11[/C][C]0.198201[/C][C]1.3588[/C][C]0.090348[/C][/ROW]
[ROW][C]12[/C][C]-0.202578[/C][C]-1.3888[/C][C]0.085719[/C][/ROW]
[ROW][C]13[/C][C]-0.211166[/C][C]-1.4477[/C][C]0.077172[/C][/ROW]
[ROW][C]14[/C][C]-0.154483[/C][C]-1.0591[/C][C]0.147487[/C][/ROW]
[ROW][C]15[/C][C]-0.007302[/C][C]-0.0501[/C][C]0.480143[/C][/ROW]
[ROW][C]16[/C][C]-0.139581[/C][C]-0.9569[/C][C]0.171753[/C][/ROW]
[ROW][C]17[/C][C]0.072673[/C][C]0.4982[/C][C]0.310327[/C][/ROW]
[ROW][C]18[/C][C]0.019676[/C][C]0.1349[/C][C]0.446637[/C][/ROW]
[ROW][C]19[/C][C]-0.110909[/C][C]-0.7604[/C][C]0.225419[/C][/ROW]
[ROW][C]20[/C][C]-0.128922[/C][C]-0.8838[/C][C]0.19064[/C][/ROW]
[ROW][C]21[/C][C]0.198547[/C][C]1.3612[/C][C]0.089975[/C][/ROW]
[ROW][C]22[/C][C]-0.199829[/C][C]-1.37[/C][C]0.088605[/C][/ROW]
[ROW][C]23[/C][C]-0.011751[/C][C]-0.0806[/C][C]0.468065[/C][/ROW]
[ROW][C]24[/C][C]-0.020266[/C][C]-0.1389[/C][C]0.445047[/C][/ROW]
[ROW][C]25[/C][C]-0.03154[/C][C]-0.2162[/C][C]0.414873[/C][/ROW]
[ROW][C]26[/C][C]-0.047553[/C][C]-0.326[/C][C]0.372933[/C][/ROW]
[ROW][C]27[/C][C]-0.044258[/C][C]-0.3034[/C][C]0.381455[/C][/ROW]
[ROW][C]28[/C][C]-0.043892[/C][C]-0.3009[/C][C]0.382405[/C][/ROW]
[ROW][C]29[/C][C]0.079429[/C][C]0.5445[/C][C]0.294323[/C][/ROW]
[ROW][C]30[/C][C]0.044038[/C][C]0.3019[/C][C]0.382026[/C][/ROW]
[ROW][C]31[/C][C]-0.138349[/C][C]-0.9485[/C][C]0.173869[/C][/ROW]
[ROW][C]32[/C][C]-0.170232[/C][C]-1.1671[/C][C]0.124538[/C][/ROW]
[ROW][C]33[/C][C]-0.001225[/C][C]-0.0084[/C][C]0.496669[/C][/ROW]
[ROW][C]34[/C][C]-0.155474[/C][C]-1.0659[/C][C]0.145962[/C][/ROW]
[ROW][C]35[/C][C]-0.054667[/C][C]-0.3748[/C][C]0.354756[/C][/ROW]
[ROW][C]36[/C][C]0.075602[/C][C]0.5183[/C][C]0.303339[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63317&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63317&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
1-0.554309-3.80020.000208
2-0.390707-2.67850.005078
3-0.210681-1.44440.077636
4-0.284553-1.95080.028529
5-0.266273-1.82550.037143
60.0939940.64440.261227
7-0.094747-0.64960.259571
80.0578150.39640.346818
9-0.10353-0.70980.240679
10-0.137866-0.94520.174704
110.1982011.35880.090348
12-0.202578-1.38880.085719
13-0.211166-1.44770.077172
14-0.154483-1.05910.147487
15-0.007302-0.05010.480143
16-0.139581-0.95690.171753
170.0726730.49820.310327
180.0196760.13490.446637
19-0.110909-0.76040.225419
20-0.128922-0.88380.19064
210.1985471.36120.089975
22-0.199829-1.370.088605
23-0.011751-0.08060.468065
24-0.020266-0.13890.445047
25-0.03154-0.21620.414873
26-0.047553-0.3260.372933
27-0.044258-0.30340.381455
28-0.043892-0.30090.382405
290.0794290.54450.294323
300.0440380.30190.382026
31-0.138349-0.94850.173869
32-0.170232-1.16710.124538
33-0.001225-0.00840.496669
34-0.155474-1.06590.145962
35-0.054667-0.37480.354756
360.0756020.51830.303339


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 ;
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')