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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 computationMon, 14 Dec 2009 03:36:30 -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/14/t1260787023alhof21121l9rxd.htm/, Retrieved Sun, 05 May 2024 09:12:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=67512, Retrieved Sun, 05 May 2024 09:12:27 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact127

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] [Ws 8 autocorrelat...] [2009-11-27 12:17:11] [12f02da0296cb21dc23d82ae014a8b71]
-   PD            [(Partial) Autocorrelation Function] [Paper Y3 D=d=1] [2009-12-14 10:36:30] [b653746fe14da1ddc21bd75262e8c46b] [Current]
- RMP               [Variance Reduction Matrix] [Paper Y3 variance...] [2009-12-17 09:42:04] [4637f404ac59dfaba4ecf14efa20abbd]
- RMP               [Standard Deviation-Mean Plot] [Paper SdMP Y3 ] [2009-12-17 10:18:03] [4637f404ac59dfaba4ecf14efa20abbd]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
98.2
96.92
99.06
99.65
99.82
99.99
100.33
99.31
101.1
101.1
100.93
100.85
100.93
99.6
101.88
101.81
102.38
102.74
102.82
101.72
103.47
102.98
102.68
102.9
103.03
101.29
103.69
103.68
104.2
104.08
104.16
103.05
104.66
104.46
104.95
105.85
106.23
104.86
107.44
108.23
108.45
109.39
110.15
109.13
110.28
110.17
109.99
109.26
109.11
107.06
109.53
108.92
109.24
109.12
109
107.23
109.49
109.04
109.02
109.23

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=67512&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=67512&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67512&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
10.2237441.53390.065878
20.2865081.96420.027718
30.2652321.81830.037694
40.3007892.06210.022375
5-0.162777-1.11590.13506
60.0313710.21510.415323
70.1533171.05110.149296
8-0.107704-0.73840.231977
9-0.215384-1.47660.073226
10-0.249279-1.7090.047026
11-0.084641-0.58030.282252
12-0.488814-3.35110.000798
13-0.282436-1.93630.029429
14-0.163294-1.11950.134311
15-0.04089-0.28030.390229
16-0.199606-1.36840.088842
170.0161540.11070.456146
180.0243060.16660.434186
19-0.042892-0.29410.385007
20-0.075643-0.51860.303244
21-0.01508-0.10340.459051
220.1354970.92890.178838
230.0238780.16370.435336
240.0018330.01260.495013
250.1408580.96570.169575
260.079610.54580.293901
27-0.071684-0.49140.3127
280.0118910.08150.467688
290.0531010.3640.35873
30-0.038726-0.26550.395896
31-0.071693-0.49150.312678
320.0707640.48510.314917
330.0510830.35020.363874
34-0.020824-0.14280.443544
35-0.048165-0.33020.371358
360.0807880.55390.291152

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.223744 & 1.5339 & 0.065878 \tabularnewline
2 & 0.286508 & 1.9642 & 0.027718 \tabularnewline
3 & 0.265232 & 1.8183 & 0.037694 \tabularnewline
4 & 0.300789 & 2.0621 & 0.022375 \tabularnewline
5 & -0.162777 & -1.1159 & 0.13506 \tabularnewline
6 & 0.031371 & 0.2151 & 0.415323 \tabularnewline
7 & 0.153317 & 1.0511 & 0.149296 \tabularnewline
8 & -0.107704 & -0.7384 & 0.231977 \tabularnewline
9 & -0.215384 & -1.4766 & 0.073226 \tabularnewline
10 & -0.249279 & -1.709 & 0.047026 \tabularnewline
11 & -0.084641 & -0.5803 & 0.282252 \tabularnewline
12 & -0.488814 & -3.3511 & 0.000798 \tabularnewline
13 & -0.282436 & -1.9363 & 0.029429 \tabularnewline
14 & -0.163294 & -1.1195 & 0.134311 \tabularnewline
15 & -0.04089 & -0.2803 & 0.390229 \tabularnewline
16 & -0.199606 & -1.3684 & 0.088842 \tabularnewline
17 & 0.016154 & 0.1107 & 0.456146 \tabularnewline
18 & 0.024306 & 0.1666 & 0.434186 \tabularnewline
19 & -0.042892 & -0.2941 & 0.385007 \tabularnewline
20 & -0.075643 & -0.5186 & 0.303244 \tabularnewline
21 & -0.01508 & -0.1034 & 0.459051 \tabularnewline
22 & 0.135497 & 0.9289 & 0.178838 \tabularnewline
23 & 0.023878 & 0.1637 & 0.435336 \tabularnewline
24 & 0.001833 & 0.0126 & 0.495013 \tabularnewline
25 & 0.140858 & 0.9657 & 0.169575 \tabularnewline
26 & 0.07961 & 0.5458 & 0.293901 \tabularnewline
27 & -0.071684 & -0.4914 & 0.3127 \tabularnewline
28 & 0.011891 & 0.0815 & 0.467688 \tabularnewline
29 & 0.053101 & 0.364 & 0.35873 \tabularnewline
30 & -0.038726 & -0.2655 & 0.395896 \tabularnewline
31 & -0.071693 & -0.4915 & 0.312678 \tabularnewline
32 & 0.070764 & 0.4851 & 0.314917 \tabularnewline
33 & 0.051083 & 0.3502 & 0.363874 \tabularnewline
34 & -0.020824 & -0.1428 & 0.443544 \tabularnewline
35 & -0.048165 & -0.3302 & 0.371358 \tabularnewline
36 & 0.080788 & 0.5539 & 0.291152 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67512&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]0.223744[/C][C]1.5339[/C][C]0.065878[/C][/ROW]
[ROW][C]2[/C][C]0.286508[/C][C]1.9642[/C][C]0.027718[/C][/ROW]
[ROW][C]3[/C][C]0.265232[/C][C]1.8183[/C][C]0.037694[/C][/ROW]
[ROW][C]4[/C][C]0.300789[/C][C]2.0621[/C][C]0.022375[/C][/ROW]
[ROW][C]5[/C][C]-0.162777[/C][C]-1.1159[/C][C]0.13506[/C][/ROW]
[ROW][C]6[/C][C]0.031371[/C][C]0.2151[/C][C]0.415323[/C][/ROW]
[ROW][C]7[/C][C]0.153317[/C][C]1.0511[/C][C]0.149296[/C][/ROW]
[ROW][C]8[/C][C]-0.107704[/C][C]-0.7384[/C][C]0.231977[/C][/ROW]
[ROW][C]9[/C][C]-0.215384[/C][C]-1.4766[/C][C]0.073226[/C][/ROW]
[ROW][C]10[/C][C]-0.249279[/C][C]-1.709[/C][C]0.047026[/C][/ROW]
[ROW][C]11[/C][C]-0.084641[/C][C]-0.5803[/C][C]0.282252[/C][/ROW]
[ROW][C]12[/C][C]-0.488814[/C][C]-3.3511[/C][C]0.000798[/C][/ROW]
[ROW][C]13[/C][C]-0.282436[/C][C]-1.9363[/C][C]0.029429[/C][/ROW]
[ROW][C]14[/C][C]-0.163294[/C][C]-1.1195[/C][C]0.134311[/C][/ROW]
[ROW][C]15[/C][C]-0.04089[/C][C]-0.2803[/C][C]0.390229[/C][/ROW]
[ROW][C]16[/C][C]-0.199606[/C][C]-1.3684[/C][C]0.088842[/C][/ROW]
[ROW][C]17[/C][C]0.016154[/C][C]0.1107[/C][C]0.456146[/C][/ROW]
[ROW][C]18[/C][C]0.024306[/C][C]0.1666[/C][C]0.434186[/C][/ROW]
[ROW][C]19[/C][C]-0.042892[/C][C]-0.2941[/C][C]0.385007[/C][/ROW]
[ROW][C]20[/C][C]-0.075643[/C][C]-0.5186[/C][C]0.303244[/C][/ROW]
[ROW][C]21[/C][C]-0.01508[/C][C]-0.1034[/C][C]0.459051[/C][/ROW]
[ROW][C]22[/C][C]0.135497[/C][C]0.9289[/C][C]0.178838[/C][/ROW]
[ROW][C]23[/C][C]0.023878[/C][C]0.1637[/C][C]0.435336[/C][/ROW]
[ROW][C]24[/C][C]0.001833[/C][C]0.0126[/C][C]0.495013[/C][/ROW]
[ROW][C]25[/C][C]0.140858[/C][C]0.9657[/C][C]0.169575[/C][/ROW]
[ROW][C]26[/C][C]0.07961[/C][C]0.5458[/C][C]0.293901[/C][/ROW]
[ROW][C]27[/C][C]-0.071684[/C][C]-0.4914[/C][C]0.3127[/C][/ROW]
[ROW][C]28[/C][C]0.011891[/C][C]0.0815[/C][C]0.467688[/C][/ROW]
[ROW][C]29[/C][C]0.053101[/C][C]0.364[/C][C]0.35873[/C][/ROW]
[ROW][C]30[/C][C]-0.038726[/C][C]-0.2655[/C][C]0.395896[/C][/ROW]
[ROW][C]31[/C][C]-0.071693[/C][C]-0.4915[/C][C]0.312678[/C][/ROW]
[ROW][C]32[/C][C]0.070764[/C][C]0.4851[/C][C]0.314917[/C][/ROW]
[ROW][C]33[/C][C]0.051083[/C][C]0.3502[/C][C]0.363874[/C][/ROW]
[ROW][C]34[/C][C]-0.020824[/C][C]-0.1428[/C][C]0.443544[/C][/ROW]
[ROW][C]35[/C][C]-0.048165[/C][C]-0.3302[/C][C]0.371358[/C][/ROW]
[ROW][C]36[/C][C]0.080788[/C][C]0.5539[/C][C]0.291152[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67512&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67512&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
10.2237441.53390.065878
20.2865081.96420.027718
30.2652321.81830.037694
40.3007892.06210.022375
5-0.162777-1.11590.13506
60.0313710.21510.415323
70.1533171.05110.149296
8-0.107704-0.73840.231977
9-0.215384-1.47660.073226
10-0.249279-1.7090.047026
11-0.084641-0.58030.282252
12-0.488814-3.35110.000798
13-0.282436-1.93630.029429
14-0.163294-1.11950.134311
15-0.04089-0.28030.390229
16-0.199606-1.36840.088842
170.0161540.11070.456146
180.0243060.16660.434186
19-0.042892-0.29410.385007
20-0.075643-0.51860.303244
21-0.01508-0.10340.459051
220.1354970.92890.178838
230.0238780.16370.435336
240.0018330.01260.495013
250.1408580.96570.169575
260.079610.54580.293901
27-0.071684-0.49140.3127
280.0118910.08150.467688
290.0531010.3640.35873
30-0.038726-0.26550.395896
31-0.071693-0.49150.312678
320.0707640.48510.314917
330.0510830.35020.363874
34-0.020824-0.14280.443544
35-0.048165-0.33020.371358
360.0807880.55390.291152






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.2237441.53390.065878
20.2489071.70640.047265
30.1811191.24170.110256
40.1915121.31290.097789
5-0.390456-2.67680.005101
6-0.072746-0.49870.31015
70.2538091.740.044199
8-0.115915-0.79470.2154
9-0.194982-1.33670.093873
10-0.430025-2.94810.002483
110.0690160.47310.319149
12-0.10455-0.71680.238536
13-0.079542-0.54530.294059
140.0453980.31120.378501
150.1096610.75180.22796
160.1802671.23580.111329
17-0.055253-0.37880.353273
18-0.212972-1.46010.075463
19-0.006522-0.04470.482263
20-0.025291-0.17340.431547
21-0.171991-1.17910.122144
22-0.08821-0.60470.27413
230.0423220.29010.386492
24-0.130144-0.89220.18841
250.0693460.47540.318347
26-0.051726-0.35460.362232
270.0758930.52030.302649
280.1448390.9930.162906
29-0.146223-1.00250.160629
30-0.106999-0.73350.233434
31-0.12963-0.88870.189346
320.085340.58510.280652
330.0184640.12660.449904
34-0.134327-0.92090.180903
35-0.023892-0.16380.435297
360.0249290.17090.432517

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.223744 & 1.5339 & 0.065878 \tabularnewline
2 & 0.248907 & 1.7064 & 0.047265 \tabularnewline
3 & 0.181119 & 1.2417 & 0.110256 \tabularnewline
4 & 0.191512 & 1.3129 & 0.097789 \tabularnewline
5 & -0.390456 & -2.6768 & 0.005101 \tabularnewline
6 & -0.072746 & -0.4987 & 0.31015 \tabularnewline
7 & 0.253809 & 1.74 & 0.044199 \tabularnewline
8 & -0.115915 & -0.7947 & 0.2154 \tabularnewline
9 & -0.194982 & -1.3367 & 0.093873 \tabularnewline
10 & -0.430025 & -2.9481 & 0.002483 \tabularnewline
11 & 0.069016 & 0.4731 & 0.319149 \tabularnewline
12 & -0.10455 & -0.7168 & 0.238536 \tabularnewline
13 & -0.079542 & -0.5453 & 0.294059 \tabularnewline
14 & 0.045398 & 0.3112 & 0.378501 \tabularnewline
15 & 0.109661 & 0.7518 & 0.22796 \tabularnewline
16 & 0.180267 & 1.2358 & 0.111329 \tabularnewline
17 & -0.055253 & -0.3788 & 0.353273 \tabularnewline
18 & -0.212972 & -1.4601 & 0.075463 \tabularnewline
19 & -0.006522 & -0.0447 & 0.482263 \tabularnewline
20 & -0.025291 & -0.1734 & 0.431547 \tabularnewline
21 & -0.171991 & -1.1791 & 0.122144 \tabularnewline
22 & -0.08821 & -0.6047 & 0.27413 \tabularnewline
23 & 0.042322 & 0.2901 & 0.386492 \tabularnewline
24 & -0.130144 & -0.8922 & 0.18841 \tabularnewline
25 & 0.069346 & 0.4754 & 0.318347 \tabularnewline
26 & -0.051726 & -0.3546 & 0.362232 \tabularnewline
27 & 0.075893 & 0.5203 & 0.302649 \tabularnewline
28 & 0.144839 & 0.993 & 0.162906 \tabularnewline
29 & -0.146223 & -1.0025 & 0.160629 \tabularnewline
30 & -0.106999 & -0.7335 & 0.233434 \tabularnewline
31 & -0.12963 & -0.8887 & 0.189346 \tabularnewline
32 & 0.08534 & 0.5851 & 0.280652 \tabularnewline
33 & 0.018464 & 0.1266 & 0.449904 \tabularnewline
34 & -0.134327 & -0.9209 & 0.180903 \tabularnewline
35 & -0.023892 & -0.1638 & 0.435297 \tabularnewline
36 & 0.024929 & 0.1709 & 0.432517 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67512&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]0.223744[/C][C]1.5339[/C][C]0.065878[/C][/ROW]
[ROW][C]2[/C][C]0.248907[/C][C]1.7064[/C][C]0.047265[/C][/ROW]
[ROW][C]3[/C][C]0.181119[/C][C]1.2417[/C][C]0.110256[/C][/ROW]
[ROW][C]4[/C][C]0.191512[/C][C]1.3129[/C][C]0.097789[/C][/ROW]
[ROW][C]5[/C][C]-0.390456[/C][C]-2.6768[/C][C]0.005101[/C][/ROW]
[ROW][C]6[/C][C]-0.072746[/C][C]-0.4987[/C][C]0.31015[/C][/ROW]
[ROW][C]7[/C][C]0.253809[/C][C]1.74[/C][C]0.044199[/C][/ROW]
[ROW][C]8[/C][C]-0.115915[/C][C]-0.7947[/C][C]0.2154[/C][/ROW]
[ROW][C]9[/C][C]-0.194982[/C][C]-1.3367[/C][C]0.093873[/C][/ROW]
[ROW][C]10[/C][C]-0.430025[/C][C]-2.9481[/C][C]0.002483[/C][/ROW]
[ROW][C]11[/C][C]0.069016[/C][C]0.4731[/C][C]0.319149[/C][/ROW]
[ROW][C]12[/C][C]-0.10455[/C][C]-0.7168[/C][C]0.238536[/C][/ROW]
[ROW][C]13[/C][C]-0.079542[/C][C]-0.5453[/C][C]0.294059[/C][/ROW]
[ROW][C]14[/C][C]0.045398[/C][C]0.3112[/C][C]0.378501[/C][/ROW]
[ROW][C]15[/C][C]0.109661[/C][C]0.7518[/C][C]0.22796[/C][/ROW]
[ROW][C]16[/C][C]0.180267[/C][C]1.2358[/C][C]0.111329[/C][/ROW]
[ROW][C]17[/C][C]-0.055253[/C][C]-0.3788[/C][C]0.353273[/C][/ROW]
[ROW][C]18[/C][C]-0.212972[/C][C]-1.4601[/C][C]0.075463[/C][/ROW]
[ROW][C]19[/C][C]-0.006522[/C][C]-0.0447[/C][C]0.482263[/C][/ROW]
[ROW][C]20[/C][C]-0.025291[/C][C]-0.1734[/C][C]0.431547[/C][/ROW]
[ROW][C]21[/C][C]-0.171991[/C][C]-1.1791[/C][C]0.122144[/C][/ROW]
[ROW][C]22[/C][C]-0.08821[/C][C]-0.6047[/C][C]0.27413[/C][/ROW]
[ROW][C]23[/C][C]0.042322[/C][C]0.2901[/C][C]0.386492[/C][/ROW]
[ROW][C]24[/C][C]-0.130144[/C][C]-0.8922[/C][C]0.18841[/C][/ROW]
[ROW][C]25[/C][C]0.069346[/C][C]0.4754[/C][C]0.318347[/C][/ROW]
[ROW][C]26[/C][C]-0.051726[/C][C]-0.3546[/C][C]0.362232[/C][/ROW]
[ROW][C]27[/C][C]0.075893[/C][C]0.5203[/C][C]0.302649[/C][/ROW]
[ROW][C]28[/C][C]0.144839[/C][C]0.993[/C][C]0.162906[/C][/ROW]
[ROW][C]29[/C][C]-0.146223[/C][C]-1.0025[/C][C]0.160629[/C][/ROW]
[ROW][C]30[/C][C]-0.106999[/C][C]-0.7335[/C][C]0.233434[/C][/ROW]
[ROW][C]31[/C][C]-0.12963[/C][C]-0.8887[/C][C]0.189346[/C][/ROW]
[ROW][C]32[/C][C]0.08534[/C][C]0.5851[/C][C]0.280652[/C][/ROW]
[ROW][C]33[/C][C]0.018464[/C][C]0.1266[/C][C]0.449904[/C][/ROW]
[ROW][C]34[/C][C]-0.134327[/C][C]-0.9209[/C][C]0.180903[/C][/ROW]
[ROW][C]35[/C][C]-0.023892[/C][C]-0.1638[/C][C]0.435297[/C][/ROW]
[ROW][C]36[/C][C]0.024929[/C][C]0.1709[/C][C]0.432517[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67512&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67512&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
10.2237441.53390.065878
20.2489071.70640.047265
30.1811191.24170.110256
40.1915121.31290.097789
5-0.390456-2.67680.005101
6-0.072746-0.49870.31015
70.2538091.740.044199
8-0.115915-0.79470.2154
9-0.194982-1.33670.093873
10-0.430025-2.94810.002483
110.0690160.47310.319149
12-0.10455-0.71680.238536
13-0.079542-0.54530.294059
140.0453980.31120.378501
150.1096610.75180.22796
160.1802671.23580.111329
17-0.055253-0.37880.353273
18-0.212972-1.46010.075463
19-0.006522-0.04470.482263
20-0.025291-0.17340.431547
21-0.171991-1.17910.122144
22-0.08821-0.60470.27413
230.0423220.29010.386492
24-0.130144-0.89220.18841
250.0693460.47540.318347
26-0.051726-0.35460.362232
270.0758930.52030.302649
280.1448390.9930.162906
29-0.146223-1.00250.160629
30-0.106999-0.73350.233434
31-0.12963-0.88870.189346
320.085340.58510.280652
330.0184640.12660.449904
34-0.134327-0.92090.180903
35-0.023892-0.16380.435297
360.0249290.17090.432517


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0 ; par2 = 36 ;
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')