R2GUESS-package |
Sparse Bayesian variable selection method for linear regression based analysis of possibly multivariate outcomes. |
Analysis.permutation |
Computing the FDR-controlled level for the significance of the MPPI |
as.ESS.object |
Compiles the main input and output files from a previous run of 'R2GUESS' and creates an ESS object. |
boxplotbeta |
Draws boxplots of the posterior distribution of regression coefficient(s) for a given predictor |
check.convergence |
Diagnostic plots for the evaluation of the convergence of the algorithm |
data.X |
Data set compiling genotype data for 29 rats. |
data.Y.Hopx |
Data set compiling gene expression levels (HOPX gene) for 29 rats. |
example.as.ESS.object |
Function creating an 'ESS' object from the example files contained in the package |
Extend.R2GUESS |
Extends an already finished 'R2GUESS' run for an extra user-defined number of iterations |
FDR.permutation |
Performs parallel permuted runs of 'R2GUESS' and returns the empirical FDR-controlled level for the significance of the MPPI |
get.g.sweep |
Internal function used to generate the regression coefficients. This function extracts the values of the shrinkage factor g for a given model specified by its ranked posterior probability |
get.sweep.best.model |
Internal function used to generate the regression coefficients. This function extracts the sweep(s) for which each selected models has been visited along the MCMC run. |
MAP.file |
MAP file describing genotypes from the rats experiment. |
pairwise.correlation |
Calculates and plots the pairwise correlation between outcomes |
plot.ESS |
Provides diagnostic plots to assess the convergence of the MCMC procedure along the run |
plotcim |
Clustered Image Maps (CIMs) (heat maps) |
plotcim.explore |
Plots a cluster image mapping of correlations between outcomes and all predictors |
plotmodel |
Visualisation of the proximity between best models |
plotMPPI |
Plots the marginal posterior probability of inclusion (MPPI) for each predictor |
plotvariable |
Visualisation of the best models |
Postprocess.R2GUESS |
Performs posterior inference from an interrupted 'R2GUESS' run. |
print.ESS |
Provides a 'print' method for class 'ESS' |
R2GUESS |
Wrapper function that reads the input files and parameter values required by GUESS, runs the C++ code from R and stores the main GUESS output in an 'ESS' object |
Resume.R2GUESS |
Function resuming an interrupted 'R2GUESS' run |
sample.beta |
Posterior distribution of the regression coefficients for a chosen model |
summary.ESS |
'summary' method for class 'ESS' |