eiwild (version 0.6.7)

prioriPlot: plots $\beta^{rc}$ given hyperpriori parameters

Description

prioriPlot simulates the $beta_i^rc$ values at first level given specific parameters at hyperpriori level

Usage

prioriPlot(pars, which, cols, alphaSample = 10000, betaSample = 300, plot = TRUE, ...)

Arguments

pars

list of parameters for hyperpriori. if which="gamma" then parameter has to be a list with shape and rate as parameters if which="expo" then parameter has to be a list with only lam

which

specified priori. "gamma" or "expo"

cols

integer specifying how many columns the RxC-Table should have

alphaSample

integer specifying the number of times new alpha-values are drawn

betaSample

integer specifying the number of times betas will be drawn for each alpha-value

plot

logical TRUE/FALSE if histogram should be plotted

...

additional arguments for "hist" function

Value

nested list with each element containing another list. First level are rows and second level are columns per row.

Details

Calculation is made via the marginal beta distribution

function structure:

• "gamma" choose one parameter for every alpha_rc-parameter or a two matrices of parameters specifying lambda's for every alpha_rc-parameter
• "expo" choose one parameter for every alpha_rc-parameter or a one matrix of parameters specifying lambda's for every alpha_rc-parameter

Examples

## Not run: 
# test1 <- prioriPlot(list(shape=4,rate=2), "gamma",cols=4)
# str(test1)
# 
# pars <- list(shape=matrix(1:9,3,3),rate=matrix(9:1,3,3))
# test2 <- prioriPlot(pars, "gamma",breaks=100)
# test3 <- prioriPlot(list(shape=8,rate=2),"gamma",breaks=100,cols=3)
# 
# pars4 <- list(shape=matrix(c(6,6,6),1,3), rate=matrix(c(4,4,4),1,3))
# test4 <- prioriPlot(pars4, "gamma",breaks=100)
# 
# pars5 <- list(lam=2)
# test5 <- prioriPlot(pars5, "expo",cols=4, breaks=100)
# 
# pars6 <- list(lam=matrix(1:9,3,3)/100)
# test6 <- prioriPlot(pars6, "expo", breaks=25, col=grey(0.8))
# 
# # example for 3x4-table
# set.seed(568)
# pars7 <- list(shape=matrix(sample(1:20,12), 3,4), rate=matrix(sample(1:20,12),3,4))
# test7 <- prioriPlot(pars7, "gamma",breaks=50)
# ## End(Not run)