evidence (version 0.8.10)

BnNsir: Bayesian analysis of n >= 2 Normal means with standard improper reference priors.

Description

Several exploratory plots are produced, after which this function calculates and plots the posterior densities of the treatment means and their differences. Pooled or separate variances can be specified. Note that this function uses Standard Improper Reference (SIR) priors.

Usage

BnNsir(formula, data, var.equal = TRUE, alpha = 0.05, plotit = TRUE,
 r = 10000)

Arguments

formula

the usual formula interface: response ~ factor

data

a data.frame containing the response and the factor variables

var.equal

should a pooled variance be used? Specify var.equal = FALSE if you want separate variances to be fitted

alpha

1 - level of credibility, so that for alpha = 0.05 (the default) credible intervals will have 95% credibility

plotit

are plots desired?

r

the number of samples of the posterior that should be taken

Value

none returned: the function is used for the plots and the printed information it produces

References

van Hulst, R. 2018. Evaluating Scientific Evidence. ms.

See Also

B2Nsir

Examples

# NOT RUN {
data(PlantGrowth)
BnNsir(weight ~ group, PlantGrowth)
# }