prob.creator creates a matrix of probabilities of encountering factor levels to support
construction of input for gibbs.sampler, which uses the Bayesian Mission Mean approach to analysis.
prob.creator(
num.factors,
num.factor.levels,
likelihood.encountering,
print.result = FALSE
)Returns a matrix with two columns, one with the factor number and the other with the likelihoods of encountering.
Number of factors in the model (e.g., factor \(\alpha_i\) with
levels i=1,2 is 1 factor). Input for num.factors should be a single number.
Number of levels for each factor (e.g., factor \(\alpha_i\)
with i=1,2 has 2 levels). Input for num.factor.levels may be a vector, a matrix, or a dataframe.
The probability of seeing each level of each factor (e.g., if the factor levels for
\(\alpha_i\) are equally likely, then the probabilities would be c(1/2, 1/2)).
The probabilities for each factor should sum to one. Input for likelihood.encountering may be a vector, a matrix,
or a dataframe.
Displays final probability matrix.
The ANOVA model includes main effects and two-way interactions. Priors on model parameters are assumed to be independent of each other; beta is then defined as the set of model parameters, which is multivariate normal.