print.OBsProb: Printing Objective Posterior Probabilities from Bayesian...
In OBsMD: Objective Bayesian Model Discrimination in Follow-Up Designs

print.OBsProb

R Documentation

Printing Objective Posterior Probabilities from Bayesian Design

Description

Printing method for lists of class OBsProb. It prints the posterior probabilities of factors and models from the Objective Bayesian procedure.

Usage

    ## S3 method for class 'OBsProb'
print(x, X = TRUE, resp = TRUE, factors = TRUE, models = TRUE,
            nTop, digits = 3, plt = FALSE, verbose = FALSE, Sh= TRUE, CV=TRUE,...)

Arguments

`x`	list. Object of `OBsProb` class, output from the `OBsProb` function.
`X`	logical. If `TRUE`, the design matrix is printed.
`resp`	logical. If `TRUE`, the response vector is printed.
`factors`	logical. If `TRUE`, marginal posterior probabilities are printed .
`models`	logical. If `TRUE`, models posterior probabilities are printed.
`nTop`	integer. Number of the top ranked models to print.
`digits`	integer. Significant digits to use for printing.
`plt`	logical. If `TRUE`, factor marginal probabilities are plotted.
`verbose`	logical. If `TRUE`, the `unclass`-ed list `x` is displayed.
`Sh`	logical. If `TRUE`, the Shannon index is printed.
`CV`	logical. If `TRUE`, the coefficient of variation is printed.
`...`	additional arguments passed to `print` function.

Value

The function prints out marginal factors and models posterior probabilities. Returns invisible list with the components:

`calc`	numeric vector with general calculation information.
`probabilities`	Data frame with the marginal posterior factor probabilities.
`models`	Data frame with model posterior probabilities.
`Sh`	Normalized Shannon heterogeneity index on the posterior probabilities of models
`CV`	Coefficient of variation of factor posterior probabilities.

Author(s)

Marta Nai Ruscone.

References

Box, G. E. P. and Meyer R. D. (1986) An Analysis of Unreplicated Fractional Factorials., Technometrics 28(1), 11–18. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1080/00401706.1986.10488093")}.

Box, G. E. P. and Meyer, R. D. (1993) Finding the Active Factors in Fractionated Screening Experiments., Journal of Quality Technology 25(2), 94–105. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1080/00224065.1993.11979432")}.

Examples

library(OBsMD)
data(OBsMD.es5, package="OBsMD")
X <- as.matrix(OBsMD.es5[,1:5])
y <- OBsMD.es5[,6]
# Using for model prior probability a Beta with parameters a=1 b=1
es5.OBsProb <- OBsProb(X=X,y=y, abeta=1, bbeta=1, blk=0,mFac=5,mInt=2,nTop=32)
print(es5.OBsProb)
summary(es5.OBsProb)
plot(es5.OBsProb)

OBsMD documentation built on Nov. 14, 2023, 5:10 p.m.