BAYESDEF

 

Bayesian Analysis of DSD

ITAM - UV
BAYESDEF is a package with a graphical interface dedicated to perform Bayesian analysis of
Definitive Screening Designs with thirteen runs. These very economic experimental plans are
gaining popularity because, under certain conditions, they allow the estimation of main,
interaction and quadratic effects. Tinhe package also allows the user to fit custom models to
the data. It also includes the additional feature to analyze the data using the least absolute
shrinkage and selection operator "lasso".
Note: CONS is free software and comes with ABSOLUTELY NO WARRANTY  

 

WINDOWS / LINUX 

1
#Comand to install
install.packages("gWidgetstcltk")
install.packages("BAYESDEF")
2
#Call to library
library(BAYESDEF)
3
#View the description 
library(help=BAYESDEF)
4
#View the requirements 
?BAYESDEF

 

MAC OS X 

1
2
#Install XQuartz
The use of X11 (including tcltk) requires XQuartz
3
#Restart the computer
4
#Comand to install
install.packages("gWidgetstcltk")
install.packages("BAYESDEF")
5
#Call to library
library(BAYESDEF)
6
#View the description 
library(help=BAYESDEF)
7
#View the requirements 
?BAYESDEF

 

EXAMPLE

1
#Call to library
library(BAYESDEF)
2
#Call the interface
BAYESDEF()
3
#Choose a data set (csv, txt or xlsx file)
File - Open 

4
#Choose the method 

5
#Choose the parameters - Bayesian

6
#Use of sections 
Method - Lasso

 

DOCUMENTATION

- BAYESDEF Manual

- BAYESDEF.tar.gz

 

REFERENCES

- Aguirre VM. Bayesian analysis of definitive screening designs when the response is nonnormal. 
Applied Stochastic Models in Business and Industry 2016; 32(4):440–452. DOI: 10.1002/asmb.2160

- Aguirre VM, de la Vara R. A Bayesian analysis of very small unreplicated experiments. Quality and 
Reliability Engineering International 2014a; 30(3):413–426. DOI: 10.1002/qre.1578

- Friedman J, Hastie T, Tibshirani R. Regularization paths for generalized linear models via coordinate
 descent. Journal of Statistical Software 2010; 33:1–22. DOI: 10.18637/jss.v033.i01

- Jones B, Nachtsheim C. A class of three-level designs for definitive screening in the presence of
 second order effects. Journal of Quality Technology 2011; 43:1–15.

- Tibshirani R. Regression shrinkage and selection via the lasso. Journal of the Royal Statistical
 Society B 1996; 58:267–288. DOI:10.1111/j.1467-9868.2011.00771.x

 

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