R: MCMC for Spike and Slab Regression

# MCMC for Spike and Slab Regression

## Documentation for package ‘BoomSpikeSlab’ version 1.2.7

- DESCRIPTION file

## Help Pages

BayesNnet | Bayesian Feed Forward Neural Networks
BsplineBasis | Spline Basis Expansions
CoefficientGroup | Shrinking Regression Coefficients
ConditionalZellnerPrior | Create a spike and slab prior for use with lm.spike.
GetPredictorMatrix | GetPredictorMatrix
HiddenLayer | Bayesian Feed Forward Neural Networks
IndependentSpikeSlabPrior | A spike and slab prior assuming a priori independence.
IsplineBasis | Spline Basis Expansions
knots | Spline Basis Expansions
knots.SplineBasis | Spline Basis Expansions
lm.spike | Spike and slab regression
logit.spike | Spike and slab logistic regression
LogitPrior | Zellner Prior for Logistic Regression
LogitZellnerPrior | Zellner Prior for Logistic Regression
mlm.spike | Spike and slab multinomial logistic regression
model.matrix.glm.spike | Construct Design Matrices
MsplineBasis | Spline Basis Expansions
MultinomialLogitSpikeSlabPrior | Create a spike and slab prior for use with mlm.spike.
NestedRegression | Nested Regression
OdaOptions | Spike and slab regression
PartialDependencePlot | Plot a Bayesian Neural Network
plot.BayesNnet | Plot a Bayesian Neural Network
plot.lm.spike | Plot the results of a spike and slab regression.
plot.logit.spike | Plot a 'logit.spike' object
plot.poisson.spike | Plot a 'poisson.spike' object
plot.probit.spike | Plot a 'logit.spike' object
plot.qreg.spike | Plot the results of a spike and slab regression.
PlotBayesNnetPredictions | Plot a Bayesian Neural Network
PlotBayesNnetResiduals | Plot a Bayesian Neural Network
PlotLmSpikeCoefficients | Plot Coefficients.
PlotLmSpikeFit | Predicted vs actual plot for lm.spike.
PlotLmSpikeResiduals | Residual plot for lm.spike
PlotLogitSpikeFitSummary | Plot Logit or Probit Fit Summary
PlotLogitSpikeResiduals | Residual plot for 'logit.spike' objects.
PlotMarginalInclusionProbabilities | Plot marginal inclusion probabilities.
PlotModelSize | Plot a distribution of model size
PlotNetworkStructure | Plot a Bayesian Neural Network
PlotProbitSpikeFitSummary | Plot Logit or Probit Fit Summary
PlotProbitSpikeResiduals | Residual plot for 'logit.spike' objects.
poisson.spike | Spike and slab Poisson regression
PoissonZellnerPrior | Zellner Prior for Poisson Regression
predict.BayesNnet | Predictions using spike-and-slab regression.
predict.lm.spike | Predictions using spike-and-slab regression.
predict.logit.spike | Predictions using spike-and-slab regression.
predict.poisson.spike | Predictions using spike-and-slab regression.
predict.probit.spike | Predictions using spike-and-slab regression.
predict.qreg.spike | Predictions using spike-and-slab regression.
print.summary.lm.spike | Print method for spikeslab objects.
print.summary.logit.spike | Print method for spikeslab objects.
probit.spike | Spike and slab probit regression
qreg.spike | Quantile Regression
residuals.lm.spike | Extract lm.spike Residuals
ShrinkageRegression | Shrinking Regression Coefficients
spikeslab | Spike and slab regression
SpikeSlabGlmPrior | Zellner Prior for Glm's.
SpikeSlabGlmPriorDirect | Zellner Prior for Glm's.
SpikeSlabPrior | Create a spike and slab prior for use with lm.spike.
SpikeSlabPriorBase | Base class for spike and slab priors
SpikeSlabPriorDirect | Create a spike and slab prior for use with lm.spike.
SsvsOptions | Spike and slab regression
StudentIndependentSpikeSlabPrior | Spike and Slab Prior for Regressions with Student T Errors
StudentSpikeSlabPrior | Spike and Slab Prior for Student-T Regression
SuggestBurn | Suggest Burn-in
SummarizeSpikeSlabCoefficients | Numerical summaries of coefficients from a spike and slab regression.
summary.lm.spike | Numerical summaries of the results from a spike and slab regression.
summary.logit.spike | Numerical summaries of the results from a spike and slab logistic regression.
summary.probit.spike | Numerical summaries of the results from a spike and slab logistic regression.