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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 05:10:15 -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/t1259928701ef10osma50j770l.htm/, Retrieved Sun, 28 Apr 2024 01:29:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63360, Retrieved Sun, 28 Apr 2024 01:29:07 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact129

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 12:10:15] [e31f2fa83f4a5291b9a51009566cf69b] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
95.1
97
112.7
102.9
97.4
111.4
87.4
96.8
114.1
110.3
103.9
101.6
94.6
95.9
104.7
102.8
98.1
113.9
80.9
95.7
113.2
105.9
108.8
102.3
99
100.7
115.5
100.7
109.9
114.6
85.4
100.5
114.8
116.5
112.9
102
106
105.3
118.8
106.1
109.3
117.2
92.5
104.2
112.5
122.4
113.3
100
110.7
112.8
109.8
117.3
109.1
115.9
96
99.8
116.8
115.7
99.4
94.3

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=63360&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=63360&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63360&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
1-0.629054-4.31264.1e-05
20.070250.48160.31616
30.2096571.43730.078624
4-0.212046-1.45370.076336
50.0734880.50380.308376
60.089210.61160.271877
7-0.15083-1.0340.153205
80.0606910.41610.339623
90.0853190.58490.280701
10-0.157947-1.08280.142205
110.1262730.86570.19553
12-0.052317-0.35870.360726
130.0095990.06580.473905
14-0.034079-0.23360.408141
150.0997820.68410.248645
16-0.137553-0.9430.175248
170.0707060.48470.315058
180.0681980.46750.321136
19-0.140071-0.96030.170914
200.0789110.5410.295536
210.0860080.58960.279127
22-0.290406-1.99090.02616
230.3875872.65720.005366
24-0.263946-1.80950.038384
250.0042340.0290.488483
260.1519791.04190.151391
27-0.117538-0.80580.212208
280.0179260.12290.451358
290.0456320.31280.377893
30-0.040397-0.27690.391517
31-0.027592-0.18920.42539
320.0926830.63540.264124
33-0.123369-0.84580.200982
340.0887030.60810.273018
35-0.075613-0.51840.303314
360.0435620.29860.383263

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.629054 & -4.3126 & 4.1e-05 \tabularnewline
2 & 0.07025 & 0.4816 & 0.31616 \tabularnewline
3 & 0.209657 & 1.4373 & 0.078624 \tabularnewline
4 & -0.212046 & -1.4537 & 0.076336 \tabularnewline
5 & 0.073488 & 0.5038 & 0.308376 \tabularnewline
6 & 0.08921 & 0.6116 & 0.271877 \tabularnewline
7 & -0.15083 & -1.034 & 0.153205 \tabularnewline
8 & 0.060691 & 0.4161 & 0.339623 \tabularnewline
9 & 0.085319 & 0.5849 & 0.280701 \tabularnewline
10 & -0.157947 & -1.0828 & 0.142205 \tabularnewline
11 & 0.126273 & 0.8657 & 0.19553 \tabularnewline
12 & -0.052317 & -0.3587 & 0.360726 \tabularnewline
13 & 0.009599 & 0.0658 & 0.473905 \tabularnewline
14 & -0.034079 & -0.2336 & 0.408141 \tabularnewline
15 & 0.099782 & 0.6841 & 0.248645 \tabularnewline
16 & -0.137553 & -0.943 & 0.175248 \tabularnewline
17 & 0.070706 & 0.4847 & 0.315058 \tabularnewline
18 & 0.068198 & 0.4675 & 0.321136 \tabularnewline
19 & -0.140071 & -0.9603 & 0.170914 \tabularnewline
20 & 0.078911 & 0.541 & 0.295536 \tabularnewline
21 & 0.086008 & 0.5896 & 0.279127 \tabularnewline
22 & -0.290406 & -1.9909 & 0.02616 \tabularnewline
23 & 0.387587 & 2.6572 & 0.005366 \tabularnewline
24 & -0.263946 & -1.8095 & 0.038384 \tabularnewline
25 & 0.004234 & 0.029 & 0.488483 \tabularnewline
26 & 0.151979 & 1.0419 & 0.151391 \tabularnewline
27 & -0.117538 & -0.8058 & 0.212208 \tabularnewline
28 & 0.017926 & 0.1229 & 0.451358 \tabularnewline
29 & 0.045632 & 0.3128 & 0.377893 \tabularnewline
30 & -0.040397 & -0.2769 & 0.391517 \tabularnewline
31 & -0.027592 & -0.1892 & 0.42539 \tabularnewline
32 & 0.092683 & 0.6354 & 0.264124 \tabularnewline
33 & -0.123369 & -0.8458 & 0.200982 \tabularnewline
34 & 0.088703 & 0.6081 & 0.273018 \tabularnewline
35 & -0.075613 & -0.5184 & 0.303314 \tabularnewline
36 & 0.043562 & 0.2986 & 0.383263 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63360&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]-0.629054[/C][C]-4.3126[/C][C]4.1e-05[/C][/ROW]
[ROW][C]2[/C][C]0.07025[/C][C]0.4816[/C][C]0.31616[/C][/ROW]
[ROW][C]3[/C][C]0.209657[/C][C]1.4373[/C][C]0.078624[/C][/ROW]
[ROW][C]4[/C][C]-0.212046[/C][C]-1.4537[/C][C]0.076336[/C][/ROW]
[ROW][C]5[/C][C]0.073488[/C][C]0.5038[/C][C]0.308376[/C][/ROW]
[ROW][C]6[/C][C]0.08921[/C][C]0.6116[/C][C]0.271877[/C][/ROW]
[ROW][C]7[/C][C]-0.15083[/C][C]-1.034[/C][C]0.153205[/C][/ROW]
[ROW][C]8[/C][C]0.060691[/C][C]0.4161[/C][C]0.339623[/C][/ROW]
[ROW][C]9[/C][C]0.085319[/C][C]0.5849[/C][C]0.280701[/C][/ROW]
[ROW][C]10[/C][C]-0.157947[/C][C]-1.0828[/C][C]0.142205[/C][/ROW]
[ROW][C]11[/C][C]0.126273[/C][C]0.8657[/C][C]0.19553[/C][/ROW]
[ROW][C]12[/C][C]-0.052317[/C][C]-0.3587[/C][C]0.360726[/C][/ROW]
[ROW][C]13[/C][C]0.009599[/C][C]0.0658[/C][C]0.473905[/C][/ROW]
[ROW][C]14[/C][C]-0.034079[/C][C]-0.2336[/C][C]0.408141[/C][/ROW]
[ROW][C]15[/C][C]0.099782[/C][C]0.6841[/C][C]0.248645[/C][/ROW]
[ROW][C]16[/C][C]-0.137553[/C][C]-0.943[/C][C]0.175248[/C][/ROW]
[ROW][C]17[/C][C]0.070706[/C][C]0.4847[/C][C]0.315058[/C][/ROW]
[ROW][C]18[/C][C]0.068198[/C][C]0.4675[/C][C]0.321136[/C][/ROW]
[ROW][C]19[/C][C]-0.140071[/C][C]-0.9603[/C][C]0.170914[/C][/ROW]
[ROW][C]20[/C][C]0.078911[/C][C]0.541[/C][C]0.295536[/C][/ROW]
[ROW][C]21[/C][C]0.086008[/C][C]0.5896[/C][C]0.279127[/C][/ROW]
[ROW][C]22[/C][C]-0.290406[/C][C]-1.9909[/C][C]0.02616[/C][/ROW]
[ROW][C]23[/C][C]0.387587[/C][C]2.6572[/C][C]0.005366[/C][/ROW]
[ROW][C]24[/C][C]-0.263946[/C][C]-1.8095[/C][C]0.038384[/C][/ROW]
[ROW][C]25[/C][C]0.004234[/C][C]0.029[/C][C]0.488483[/C][/ROW]
[ROW][C]26[/C][C]0.151979[/C][C]1.0419[/C][C]0.151391[/C][/ROW]
[ROW][C]27[/C][C]-0.117538[/C][C]-0.8058[/C][C]0.212208[/C][/ROW]
[ROW][C]28[/C][C]0.017926[/C][C]0.1229[/C][C]0.451358[/C][/ROW]
[ROW][C]29[/C][C]0.045632[/C][C]0.3128[/C][C]0.377893[/C][/ROW]
[ROW][C]30[/C][C]-0.040397[/C][C]-0.2769[/C][C]0.391517[/C][/ROW]
[ROW][C]31[/C][C]-0.027592[/C][C]-0.1892[/C][C]0.42539[/C][/ROW]
[ROW][C]32[/C][C]0.092683[/C][C]0.6354[/C][C]0.264124[/C][/ROW]
[ROW][C]33[/C][C]-0.123369[/C][C]-0.8458[/C][C]0.200982[/C][/ROW]
[ROW][C]34[/C][C]0.088703[/C][C]0.6081[/C][C]0.273018[/C][/ROW]
[ROW][C]35[/C][C]-0.075613[/C][C]-0.5184[/C][C]0.303314[/C][/ROW]
[ROW][C]36[/C][C]0.043562[/C][C]0.2986[/C][C]0.383263[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63360&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63360&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
1-0.629054-4.31264.1e-05
20.070250.48160.31616
30.2096571.43730.078624
4-0.212046-1.45370.076336
50.0734880.50380.308376
60.089210.61160.271877
7-0.15083-1.0340.153205
80.0606910.41610.339623
90.0853190.58490.280701
10-0.157947-1.08280.142205
110.1262730.86570.19553
12-0.052317-0.35870.360726
130.0095990.06580.473905
14-0.034079-0.23360.408141
150.0997820.68410.248645
16-0.137553-0.9430.175248
170.0707060.48470.315058
180.0681980.46750.321136
19-0.140071-0.96030.170914
200.0789110.5410.295536
210.0860080.58960.279127
22-0.290406-1.99090.02616
230.3875872.65720.005366
24-0.263946-1.80950.038384
250.0042340.0290.488483
260.1519791.04190.151391
27-0.117538-0.80580.212208
280.0179260.12290.451358
290.0456320.31280.377893
30-0.040397-0.27690.391517
31-0.027592-0.18920.42539
320.0926830.63540.264124
33-0.123369-0.84580.200982
340.0887030.60810.273018
35-0.075613-0.51840.303314
360.0435620.29860.383263






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.629054-4.31264.1e-05
2-0.538581-3.69230.000289
3-0.142536-0.97720.166742
4-0.083683-0.57370.284453
5-0.079852-0.54740.293335
60.0724620.49680.310832
70.0259150.17770.429875
8-0.073858-0.50630.307491
90.0440750.30220.38193
10-0.019031-0.13050.448375
110.0163570.11210.455595
12-0.03227-0.22120.412935
130.0500210.34290.36659
14-0.074077-0.50780.306969
150.0624140.42790.335344
16-0.028927-0.19830.421826
17-0.075997-0.5210.302404
180.0541190.3710.356145
190.0297120.20370.419736
20-0.045243-0.31020.378902
210.1407320.96480.169789
22-0.223321-1.5310.066235
230.1117740.76630.223669
24-0.011142-0.07640.469717
25-0.022243-0.15250.439727
26-0.083762-0.57420.284271
270.0329580.22590.411112
280.04470.30640.38031
29-0.004529-0.03110.48768
300.0266830.18290.42782
31-0.004545-0.03120.487638
32-0.04606-0.31580.376787
33-0.045462-0.31170.378335
34-0.057185-0.3920.348401
35-0.131638-0.90250.185705
36-0.177329-1.21570.115084

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.629054 & -4.3126 & 4.1e-05 \tabularnewline
2 & -0.538581 & -3.6923 & 0.000289 \tabularnewline
3 & -0.142536 & -0.9772 & 0.166742 \tabularnewline
4 & -0.083683 & -0.5737 & 0.284453 \tabularnewline
5 & -0.079852 & -0.5474 & 0.293335 \tabularnewline
6 & 0.072462 & 0.4968 & 0.310832 \tabularnewline
7 & 0.025915 & 0.1777 & 0.429875 \tabularnewline
8 & -0.073858 & -0.5063 & 0.307491 \tabularnewline
9 & 0.044075 & 0.3022 & 0.38193 \tabularnewline
10 & -0.019031 & -0.1305 & 0.448375 \tabularnewline
11 & 0.016357 & 0.1121 & 0.455595 \tabularnewline
12 & -0.03227 & -0.2212 & 0.412935 \tabularnewline
13 & 0.050021 & 0.3429 & 0.36659 \tabularnewline
14 & -0.074077 & -0.5078 & 0.306969 \tabularnewline
15 & 0.062414 & 0.4279 & 0.335344 \tabularnewline
16 & -0.028927 & -0.1983 & 0.421826 \tabularnewline
17 & -0.075997 & -0.521 & 0.302404 \tabularnewline
18 & 0.054119 & 0.371 & 0.356145 \tabularnewline
19 & 0.029712 & 0.2037 & 0.419736 \tabularnewline
20 & -0.045243 & -0.3102 & 0.378902 \tabularnewline
21 & 0.140732 & 0.9648 & 0.169789 \tabularnewline
22 & -0.223321 & -1.531 & 0.066235 \tabularnewline
23 & 0.111774 & 0.7663 & 0.223669 \tabularnewline
24 & -0.011142 & -0.0764 & 0.469717 \tabularnewline
25 & -0.022243 & -0.1525 & 0.439727 \tabularnewline
26 & -0.083762 & -0.5742 & 0.284271 \tabularnewline
27 & 0.032958 & 0.2259 & 0.411112 \tabularnewline
28 & 0.0447 & 0.3064 & 0.38031 \tabularnewline
29 & -0.004529 & -0.0311 & 0.48768 \tabularnewline
30 & 0.026683 & 0.1829 & 0.42782 \tabularnewline
31 & -0.004545 & -0.0312 & 0.487638 \tabularnewline
32 & -0.04606 & -0.3158 & 0.376787 \tabularnewline
33 & -0.045462 & -0.3117 & 0.378335 \tabularnewline
34 & -0.057185 & -0.392 & 0.348401 \tabularnewline
35 & -0.131638 & -0.9025 & 0.185705 \tabularnewline
36 & -0.177329 & -1.2157 & 0.115084 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63360&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]-0.629054[/C][C]-4.3126[/C][C]4.1e-05[/C][/ROW]
[ROW][C]2[/C][C]-0.538581[/C][C]-3.6923[/C][C]0.000289[/C][/ROW]
[ROW][C]3[/C][C]-0.142536[/C][C]-0.9772[/C][C]0.166742[/C][/ROW]
[ROW][C]4[/C][C]-0.083683[/C][C]-0.5737[/C][C]0.284453[/C][/ROW]
[ROW][C]5[/C][C]-0.079852[/C][C]-0.5474[/C][C]0.293335[/C][/ROW]
[ROW][C]6[/C][C]0.072462[/C][C]0.4968[/C][C]0.310832[/C][/ROW]
[ROW][C]7[/C][C]0.025915[/C][C]0.1777[/C][C]0.429875[/C][/ROW]
[ROW][C]8[/C][C]-0.073858[/C][C]-0.5063[/C][C]0.307491[/C][/ROW]
[ROW][C]9[/C][C]0.044075[/C][C]0.3022[/C][C]0.38193[/C][/ROW]
[ROW][C]10[/C][C]-0.019031[/C][C]-0.1305[/C][C]0.448375[/C][/ROW]
[ROW][C]11[/C][C]0.016357[/C][C]0.1121[/C][C]0.455595[/C][/ROW]
[ROW][C]12[/C][C]-0.03227[/C][C]-0.2212[/C][C]0.412935[/C][/ROW]
[ROW][C]13[/C][C]0.050021[/C][C]0.3429[/C][C]0.36659[/C][/ROW]
[ROW][C]14[/C][C]-0.074077[/C][C]-0.5078[/C][C]0.306969[/C][/ROW]
[ROW][C]15[/C][C]0.062414[/C][C]0.4279[/C][C]0.335344[/C][/ROW]
[ROW][C]16[/C][C]-0.028927[/C][C]-0.1983[/C][C]0.421826[/C][/ROW]
[ROW][C]17[/C][C]-0.075997[/C][C]-0.521[/C][C]0.302404[/C][/ROW]
[ROW][C]18[/C][C]0.054119[/C][C]0.371[/C][C]0.356145[/C][/ROW]
[ROW][C]19[/C][C]0.029712[/C][C]0.2037[/C][C]0.419736[/C][/ROW]
[ROW][C]20[/C][C]-0.045243[/C][C]-0.3102[/C][C]0.378902[/C][/ROW]
[ROW][C]21[/C][C]0.140732[/C][C]0.9648[/C][C]0.169789[/C][/ROW]
[ROW][C]22[/C][C]-0.223321[/C][C]-1.531[/C][C]0.066235[/C][/ROW]
[ROW][C]23[/C][C]0.111774[/C][C]0.7663[/C][C]0.223669[/C][/ROW]
[ROW][C]24[/C][C]-0.011142[/C][C]-0.0764[/C][C]0.469717[/C][/ROW]
[ROW][C]25[/C][C]-0.022243[/C][C]-0.1525[/C][C]0.439727[/C][/ROW]
[ROW][C]26[/C][C]-0.083762[/C][C]-0.5742[/C][C]0.284271[/C][/ROW]
[ROW][C]27[/C][C]0.032958[/C][C]0.2259[/C][C]0.411112[/C][/ROW]
[ROW][C]28[/C][C]0.0447[/C][C]0.3064[/C][C]0.38031[/C][/ROW]
[ROW][C]29[/C][C]-0.004529[/C][C]-0.0311[/C][C]0.48768[/C][/ROW]
[ROW][C]30[/C][C]0.026683[/C][C]0.1829[/C][C]0.42782[/C][/ROW]
[ROW][C]31[/C][C]-0.004545[/C][C]-0.0312[/C][C]0.487638[/C][/ROW]
[ROW][C]32[/C][C]-0.04606[/C][C]-0.3158[/C][C]0.376787[/C][/ROW]
[ROW][C]33[/C][C]-0.045462[/C][C]-0.3117[/C][C]0.378335[/C][/ROW]
[ROW][C]34[/C][C]-0.057185[/C][C]-0.392[/C][C]0.348401[/C][/ROW]
[ROW][C]35[/C][C]-0.131638[/C][C]-0.9025[/C][C]0.185705[/C][/ROW]
[ROW][C]36[/C][C]-0.177329[/C][C]-1.2157[/C][C]0.115084[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63360&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63360&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
1-0.629054-4.31264.1e-05
2-0.538581-3.69230.000289
3-0.142536-0.97720.166742
4-0.083683-0.57370.284453
5-0.079852-0.54740.293335
60.0724620.49680.310832
70.0259150.17770.429875
8-0.073858-0.50630.307491
90.0440750.30220.38193
10-0.019031-0.13050.448375
110.0163570.11210.455595
12-0.03227-0.22120.412935
130.0500210.34290.36659
14-0.074077-0.50780.306969
150.0624140.42790.335344
16-0.028927-0.19830.421826
17-0.075997-0.5210.302404
180.0541190.3710.356145
190.0297120.20370.419736
20-0.045243-0.31020.378902
210.1407320.96480.169789
22-0.223321-1.5310.066235
230.1117740.76630.223669
24-0.011142-0.07640.469717
25-0.022243-0.15250.439727
26-0.083762-0.57420.284271
270.0329580.22590.411112
280.04470.30640.38031
29-0.004529-0.03110.48768
300.0266830.18290.42782
31-0.004545-0.03120.487638
32-0.04606-0.31580.376787
33-0.045462-0.31170.378335
34-0.057185-0.3920.348401
35-0.131638-0.90250.185705
36-0.177329-1.21570.115084


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')