marginalpp.models: Marginal PP for models sharing information between diseases

In jennasimit/MTFM: Multinomial fine-mapping

Description

Calculate marginal model posterior probabilities for each disease

Usage

marginalpp.models(M, ABF, pr, kappa, p0)

Arguments

M	list of model matrices for diseases 1, 2, ..., n
ABF	list of log(ABF) vectors for diseases 1, 2, ...
pr	list of prior probabilities for the models in M
kappa	single value or vector of values to consider for the sharing scale parameter
p0	prior probability of the null model

Details

Given a list of model matrices and log ABFs, this function calculates the marginal model posterior probabilities for each disease without ever calculating the joint Bayes Factors for all cross-disease model configurations, which would require large amounts of memory.

Value

list of:

• single.pp: list of pp for each model in M[[i]] for disease i

• shared.pp: list of pp for each model in M[[i]] for disease i, M (not quite as input, reordered so null model is first row

• ABF: not quite as input, repordered so null model is first

• M: reordered so null model is first row

• kappa: as supplied

Author(s)

Chris Wallace

jennasimit/MTFM documentation built on Aug. 15, 2019, 6:14 p.m.