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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, 11 Dec 2009 04:43:59 -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/11/t1260532039d974evwe0gadfdo.htm/, Retrieved Sun, 28 Apr 2024 19:25:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=66025, Retrieved Sun, 28 Apr 2024 19:25:16 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact131

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] [WS 8, ACF model 1] [2009-11-27 23:37:27] [96e597a9107bfe8c07649cce3d4f6fec]
-               [(Partial) Autocorrelation Function] [WS 9, ACF model (...] [2009-12-04 11:59:07] [96e597a9107bfe8c07649cce3d4f6fec]
-   PD            [(Partial) Autocorrelation Function] [WS 9, ACF model (...] [2009-12-04 12:03:38] [96e597a9107bfe8c07649cce3d4f6fec]
-                   [(Partial) Autocorrelation Function] [WS 10, ACF model ...] [2009-12-11 10:41:25] [96e597a9107bfe8c07649cce3d4f6fec]
-   PD                  [(Partial) Autocorrelation Function] [WS 10, ACF model ...] [2009-12-11 11:43:59] [e31f2fa83f4a5291b9a51009566cf69b] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
93.8
93.8
107.6
101
95.4
96.5
89.2
87.1
110.5
110.8
104.2
88.9
89.8
90
93.9
91.3
87.8
99.7
73.5
79.2
96.9
95.2
95.6
89.7
92.8
88
101.1
92.7
95.8
103.8
81.8
87.1
105.9
108.1
102.6
93.7
103.5
100.6
113.3
102.4
102.1
106.9
87.3
93.1
109.1
120.3
104.9
92.6
109.8
111.4
117.9
121.6
117.8
124.2
106.8
102.7
116.8
113.6
96.1
85

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 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 & 5 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=66025&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]5 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=66025&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=66025&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 time5 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.4797583.71620.000223
20.1710231.32470.09514
30.2188261.6950.047628
40.285082.20820.015531
50.3579522.77270.003698
60.2897042.2440.014266
70.292372.26470.013578
80.0851090.65920.25613
9-0.016455-0.12750.449501
10-0.099406-0.770.222163
110.1447371.12110.133351
120.4803113.72050.00022
130.0971040.75220.227445
14-0.115001-0.89080.188298
15-0.045091-0.34930.364055
160.0444880.34460.365798
170.0985210.76310.224185
180.0378650.29330.385152
190.0198650.15390.439113
20-0.133382-1.03320.152834
21-0.198656-1.53880.064558
22-0.224169-1.73640.043812
23-0.077878-0.60320.274311
240.1269160.98310.164757
25-0.131925-1.02190.155468
26-0.291624-2.25890.013768
27-0.230905-1.78860.039365
28-0.086607-0.67090.252443
29-0.066527-0.51530.304112
30-0.13432-1.04040.151155
31-0.138502-1.07280.143821
32-0.248519-1.9250.029486
33-0.29285-2.26840.013458
34-0.250706-1.9420.028421
35-0.149071-1.15470.126396
36-0.027783-0.21520.415169

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.479758 & 3.7162 & 0.000223 \tabularnewline
2 & 0.171023 & 1.3247 & 0.09514 \tabularnewline
3 & 0.218826 & 1.695 & 0.047628 \tabularnewline
4 & 0.28508 & 2.2082 & 0.015531 \tabularnewline
5 & 0.357952 & 2.7727 & 0.003698 \tabularnewline
6 & 0.289704 & 2.244 & 0.014266 \tabularnewline
7 & 0.29237 & 2.2647 & 0.013578 \tabularnewline
8 & 0.085109 & 0.6592 & 0.25613 \tabularnewline
9 & -0.016455 & -0.1275 & 0.449501 \tabularnewline
10 & -0.099406 & -0.77 & 0.222163 \tabularnewline
11 & 0.144737 & 1.1211 & 0.133351 \tabularnewline
12 & 0.480311 & 3.7205 & 0.00022 \tabularnewline
13 & 0.097104 & 0.7522 & 0.227445 \tabularnewline
14 & -0.115001 & -0.8908 & 0.188298 \tabularnewline
15 & -0.045091 & -0.3493 & 0.364055 \tabularnewline
16 & 0.044488 & 0.3446 & 0.365798 \tabularnewline
17 & 0.098521 & 0.7631 & 0.224185 \tabularnewline
18 & 0.037865 & 0.2933 & 0.385152 \tabularnewline
19 & 0.019865 & 0.1539 & 0.439113 \tabularnewline
20 & -0.133382 & -1.0332 & 0.152834 \tabularnewline
21 & -0.198656 & -1.5388 & 0.064558 \tabularnewline
22 & -0.224169 & -1.7364 & 0.043812 \tabularnewline
23 & -0.077878 & -0.6032 & 0.274311 \tabularnewline
24 & 0.126916 & 0.9831 & 0.164757 \tabularnewline
25 & -0.131925 & -1.0219 & 0.155468 \tabularnewline
26 & -0.291624 & -2.2589 & 0.013768 \tabularnewline
27 & -0.230905 & -1.7886 & 0.039365 \tabularnewline
28 & -0.086607 & -0.6709 & 0.252443 \tabularnewline
29 & -0.066527 & -0.5153 & 0.304112 \tabularnewline
30 & -0.13432 & -1.0404 & 0.151155 \tabularnewline
31 & -0.138502 & -1.0728 & 0.143821 \tabularnewline
32 & -0.248519 & -1.925 & 0.029486 \tabularnewline
33 & -0.29285 & -2.2684 & 0.013458 \tabularnewline
34 & -0.250706 & -1.942 & 0.028421 \tabularnewline
35 & -0.149071 & -1.1547 & 0.126396 \tabularnewline
36 & -0.027783 & -0.2152 & 0.415169 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=66025&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]0.479758[/C][C]3.7162[/C][C]0.000223[/C][/ROW]
[ROW][C]2[/C][C]0.171023[/C][C]1.3247[/C][C]0.09514[/C][/ROW]
[ROW][C]3[/C][C]0.218826[/C][C]1.695[/C][C]0.047628[/C][/ROW]
[ROW][C]4[/C][C]0.28508[/C][C]2.2082[/C][C]0.015531[/C][/ROW]
[ROW][C]5[/C][C]0.357952[/C][C]2.7727[/C][C]0.003698[/C][/ROW]
[ROW][C]6[/C][C]0.289704[/C][C]2.244[/C][C]0.014266[/C][/ROW]
[ROW][C]7[/C][C]0.29237[/C][C]2.2647[/C][C]0.013578[/C][/ROW]
[ROW][C]8[/C][C]0.085109[/C][C]0.6592[/C][C]0.25613[/C][/ROW]
[ROW][C]9[/C][C]-0.016455[/C][C]-0.1275[/C][C]0.449501[/C][/ROW]
[ROW][C]10[/C][C]-0.099406[/C][C]-0.77[/C][C]0.222163[/C][/ROW]
[ROW][C]11[/C][C]0.144737[/C][C]1.1211[/C][C]0.133351[/C][/ROW]
[ROW][C]12[/C][C]0.480311[/C][C]3.7205[/C][C]0.00022[/C][/ROW]
[ROW][C]13[/C][C]0.097104[/C][C]0.7522[/C][C]0.227445[/C][/ROW]
[ROW][C]14[/C][C]-0.115001[/C][C]-0.8908[/C][C]0.188298[/C][/ROW]
[ROW][C]15[/C][C]-0.045091[/C][C]-0.3493[/C][C]0.364055[/C][/ROW]
[ROW][C]16[/C][C]0.044488[/C][C]0.3446[/C][C]0.365798[/C][/ROW]
[ROW][C]17[/C][C]0.098521[/C][C]0.7631[/C][C]0.224185[/C][/ROW]
[ROW][C]18[/C][C]0.037865[/C][C]0.2933[/C][C]0.385152[/C][/ROW]
[ROW][C]19[/C][C]0.019865[/C][C]0.1539[/C][C]0.439113[/C][/ROW]
[ROW][C]20[/C][C]-0.133382[/C][C]-1.0332[/C][C]0.152834[/C][/ROW]
[ROW][C]21[/C][C]-0.198656[/C][C]-1.5388[/C][C]0.064558[/C][/ROW]
[ROW][C]22[/C][C]-0.224169[/C][C]-1.7364[/C][C]0.043812[/C][/ROW]
[ROW][C]23[/C][C]-0.077878[/C][C]-0.6032[/C][C]0.274311[/C][/ROW]
[ROW][C]24[/C][C]0.126916[/C][C]0.9831[/C][C]0.164757[/C][/ROW]
[ROW][C]25[/C][C]-0.131925[/C][C]-1.0219[/C][C]0.155468[/C][/ROW]
[ROW][C]26[/C][C]-0.291624[/C][C]-2.2589[/C][C]0.013768[/C][/ROW]
[ROW][C]27[/C][C]-0.230905[/C][C]-1.7886[/C][C]0.039365[/C][/ROW]
[ROW][C]28[/C][C]-0.086607[/C][C]-0.6709[/C][C]0.252443[/C][/ROW]
[ROW][C]29[/C][C]-0.066527[/C][C]-0.5153[/C][C]0.304112[/C][/ROW]
[ROW][C]30[/C][C]-0.13432[/C][C]-1.0404[/C][C]0.151155[/C][/ROW]
[ROW][C]31[/C][C]-0.138502[/C][C]-1.0728[/C][C]0.143821[/C][/ROW]
[ROW][C]32[/C][C]-0.248519[/C][C]-1.925[/C][C]0.029486[/C][/ROW]
[ROW][C]33[/C][C]-0.29285[/C][C]-2.2684[/C][C]0.013458[/C][/ROW]
[ROW][C]34[/C][C]-0.250706[/C][C]-1.942[/C][C]0.028421[/C][/ROW]
[ROW][C]35[/C][C]-0.149071[/C][C]-1.1547[/C][C]0.126396[/C][/ROW]
[ROW][C]36[/C][C]-0.027783[/C][C]-0.2152[/C][C]0.415169[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=66025&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=66025&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
10.4797583.71620.000223
20.1710231.32470.09514
30.2188261.6950.047628
40.285082.20820.015531
50.3579522.77270.003698
60.2897042.2440.014266
70.292372.26470.013578
80.0851090.65920.25613
9-0.016455-0.12750.449501
10-0.099406-0.770.222163
110.1447371.12110.133351
120.4803113.72050.00022
130.0971040.75220.227445
14-0.115001-0.89080.188298
15-0.045091-0.34930.364055
160.0444880.34460.365798
170.0985210.76310.224185
180.0378650.29330.385152
190.0198650.15390.439113
20-0.133382-1.03320.152834
21-0.198656-1.53880.064558
22-0.224169-1.73640.043812
23-0.077878-0.60320.274311
240.1269160.98310.164757
25-0.131925-1.02190.155468
26-0.291624-2.25890.013768
27-0.230905-1.78860.039365
28-0.086607-0.67090.252443
29-0.066527-0.51530.304112
30-0.13432-1.04040.151155
31-0.138502-1.07280.143821
32-0.248519-1.9250.029486
33-0.29285-2.26840.013458
34-0.250706-1.9420.028421
35-0.149071-1.15470.126396
36-0.027783-0.21520.415169






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.4797583.71620.000223
2-0.076827-0.59510.277007
30.2186521.69370.047757
40.1316211.01950.156022
50.2257041.74830.042764
60.0357570.2770.391378
70.1753591.35830.089723
8-0.260708-2.01940.023958
9-0.061232-0.47430.318504
10-0.346625-2.68490.004683
110.3666442.840.003075
120.3836572.97180.002128
13-0.282837-2.19080.016179
14-0.043735-0.33880.367983
15-0.005057-0.03920.484443
16-0.090446-0.70060.243134
170.0151120.11710.453603
18-0.189696-1.46940.073477
19-0.092151-0.71380.239059
200.0150890.11690.453675
21-0.00129-0.010.496032
220.0892980.69170.245898
23-0.12372-0.95830.170871
24-0.018693-0.14480.442679
250.050030.38750.349868
26-0.094702-0.73360.233038
27-0.063983-0.49560.310991
280.0696490.53950.295769
29-0.188871-1.4630.074345
300.0479160.37120.355916
31-0.076028-0.58890.279066
32-0.066336-0.51380.304628
33-0.07239-0.56070.288535
340.0735530.56970.285492
35-0.078408-0.60730.272955
360.1015840.78690.21723

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.479758 & 3.7162 & 0.000223 \tabularnewline
2 & -0.076827 & -0.5951 & 0.277007 \tabularnewline
3 & 0.218652 & 1.6937 & 0.047757 \tabularnewline
4 & 0.131621 & 1.0195 & 0.156022 \tabularnewline
5 & 0.225704 & 1.7483 & 0.042764 \tabularnewline
6 & 0.035757 & 0.277 & 0.391378 \tabularnewline
7 & 0.175359 & 1.3583 & 0.089723 \tabularnewline
8 & -0.260708 & -2.0194 & 0.023958 \tabularnewline
9 & -0.061232 & -0.4743 & 0.318504 \tabularnewline
10 & -0.346625 & -2.6849 & 0.004683 \tabularnewline
11 & 0.366644 & 2.84 & 0.003075 \tabularnewline
12 & 0.383657 & 2.9718 & 0.002128 \tabularnewline
13 & -0.282837 & -2.1908 & 0.016179 \tabularnewline
14 & -0.043735 & -0.3388 & 0.367983 \tabularnewline
15 & -0.005057 & -0.0392 & 0.484443 \tabularnewline
16 & -0.090446 & -0.7006 & 0.243134 \tabularnewline
17 & 0.015112 & 0.1171 & 0.453603 \tabularnewline
18 & -0.189696 & -1.4694 & 0.073477 \tabularnewline
19 & -0.092151 & -0.7138 & 0.239059 \tabularnewline
20 & 0.015089 & 0.1169 & 0.453675 \tabularnewline
21 & -0.00129 & -0.01 & 0.496032 \tabularnewline
22 & 0.089298 & 0.6917 & 0.245898 \tabularnewline
23 & -0.12372 & -0.9583 & 0.170871 \tabularnewline
24 & -0.018693 & -0.1448 & 0.442679 \tabularnewline
25 & 0.05003 & 0.3875 & 0.349868 \tabularnewline
26 & -0.094702 & -0.7336 & 0.233038 \tabularnewline
27 & -0.063983 & -0.4956 & 0.310991 \tabularnewline
28 & 0.069649 & 0.5395 & 0.295769 \tabularnewline
29 & -0.188871 & -1.463 & 0.074345 \tabularnewline
30 & 0.047916 & 0.3712 & 0.355916 \tabularnewline
31 & -0.076028 & -0.5889 & 0.279066 \tabularnewline
32 & -0.066336 & -0.5138 & 0.304628 \tabularnewline
33 & -0.07239 & -0.5607 & 0.288535 \tabularnewline
34 & 0.073553 & 0.5697 & 0.285492 \tabularnewline
35 & -0.078408 & -0.6073 & 0.272955 \tabularnewline
36 & 0.101584 & 0.7869 & 0.21723 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=66025&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]0.479758[/C][C]3.7162[/C][C]0.000223[/C][/ROW]
[ROW][C]2[/C][C]-0.076827[/C][C]-0.5951[/C][C]0.277007[/C][/ROW]
[ROW][C]3[/C][C]0.218652[/C][C]1.6937[/C][C]0.047757[/C][/ROW]
[ROW][C]4[/C][C]0.131621[/C][C]1.0195[/C][C]0.156022[/C][/ROW]
[ROW][C]5[/C][C]0.225704[/C][C]1.7483[/C][C]0.042764[/C][/ROW]
[ROW][C]6[/C][C]0.035757[/C][C]0.277[/C][C]0.391378[/C][/ROW]
[ROW][C]7[/C][C]0.175359[/C][C]1.3583[/C][C]0.089723[/C][/ROW]
[ROW][C]8[/C][C]-0.260708[/C][C]-2.0194[/C][C]0.023958[/C][/ROW]
[ROW][C]9[/C][C]-0.061232[/C][C]-0.4743[/C][C]0.318504[/C][/ROW]
[ROW][C]10[/C][C]-0.346625[/C][C]-2.6849[/C][C]0.004683[/C][/ROW]
[ROW][C]11[/C][C]0.366644[/C][C]2.84[/C][C]0.003075[/C][/ROW]
[ROW][C]12[/C][C]0.383657[/C][C]2.9718[/C][C]0.002128[/C][/ROW]
[ROW][C]13[/C][C]-0.282837[/C][C]-2.1908[/C][C]0.016179[/C][/ROW]
[ROW][C]14[/C][C]-0.043735[/C][C]-0.3388[/C][C]0.367983[/C][/ROW]
[ROW][C]15[/C][C]-0.005057[/C][C]-0.0392[/C][C]0.484443[/C][/ROW]
[ROW][C]16[/C][C]-0.090446[/C][C]-0.7006[/C][C]0.243134[/C][/ROW]
[ROW][C]17[/C][C]0.015112[/C][C]0.1171[/C][C]0.453603[/C][/ROW]
[ROW][C]18[/C][C]-0.189696[/C][C]-1.4694[/C][C]0.073477[/C][/ROW]
[ROW][C]19[/C][C]-0.092151[/C][C]-0.7138[/C][C]0.239059[/C][/ROW]
[ROW][C]20[/C][C]0.015089[/C][C]0.1169[/C][C]0.453675[/C][/ROW]
[ROW][C]21[/C][C]-0.00129[/C][C]-0.01[/C][C]0.496032[/C][/ROW]
[ROW][C]22[/C][C]0.089298[/C][C]0.6917[/C][C]0.245898[/C][/ROW]
[ROW][C]23[/C][C]-0.12372[/C][C]-0.9583[/C][C]0.170871[/C][/ROW]
[ROW][C]24[/C][C]-0.018693[/C][C]-0.1448[/C][C]0.442679[/C][/ROW]
[ROW][C]25[/C][C]0.05003[/C][C]0.3875[/C][C]0.349868[/C][/ROW]
[ROW][C]26[/C][C]-0.094702[/C][C]-0.7336[/C][C]0.233038[/C][/ROW]
[ROW][C]27[/C][C]-0.063983[/C][C]-0.4956[/C][C]0.310991[/C][/ROW]
[ROW][C]28[/C][C]0.069649[/C][C]0.5395[/C][C]0.295769[/C][/ROW]
[ROW][C]29[/C][C]-0.188871[/C][C]-1.463[/C][C]0.074345[/C][/ROW]
[ROW][C]30[/C][C]0.047916[/C][C]0.3712[/C][C]0.355916[/C][/ROW]
[ROW][C]31[/C][C]-0.076028[/C][C]-0.5889[/C][C]0.279066[/C][/ROW]
[ROW][C]32[/C][C]-0.066336[/C][C]-0.5138[/C][C]0.304628[/C][/ROW]
[ROW][C]33[/C][C]-0.07239[/C][C]-0.5607[/C][C]0.288535[/C][/ROW]
[ROW][C]34[/C][C]0.073553[/C][C]0.5697[/C][C]0.285492[/C][/ROW]
[ROW][C]35[/C][C]-0.078408[/C][C]-0.6073[/C][C]0.272955[/C][/ROW]
[ROW][C]36[/C][C]0.101584[/C][C]0.7869[/C][C]0.21723[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=66025&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=66025&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
10.4797583.71620.000223
2-0.076827-0.59510.277007
30.2186521.69370.047757
40.1316211.01950.156022
50.2257041.74830.042764
60.0357570.2770.391378
70.1753591.35830.089723
8-0.260708-2.01940.023958
9-0.061232-0.47430.318504
10-0.346625-2.68490.004683
110.3666442.840.003075
120.3836572.97180.002128
13-0.282837-2.19080.016179
14-0.043735-0.33880.367983
15-0.005057-0.03920.484443
16-0.090446-0.70060.243134
170.0151120.11710.453603
18-0.189696-1.46940.073477
19-0.092151-0.71380.239059
200.0150890.11690.453675
21-0.00129-0.010.496032
220.0892980.69170.245898
23-0.12372-0.95830.170871
24-0.018693-0.14480.442679
250.050030.38750.349868
26-0.094702-0.73360.233038
27-0.063983-0.49560.310991
280.0696490.53950.295769
29-0.188871-1.4630.074345
300.0479160.37120.355916
31-0.076028-0.58890.279066
32-0.066336-0.51380.304628
33-0.07239-0.56070.288535
340.0735530.56970.285492
35-0.078408-0.60730.272955
360.1015840.78690.21723


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 36 ; par2 = -1.0 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 36 ; par2 = -1.0 ; 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')