LaplacesDemon16.1.6 package

The Bayesian Bootstrap

Bayes' Theorem

Big Data

Blocks

BMK Convergence Diagnostic

Approximate Bayesian Bootstrap

Acceptance Rate

Proposal Covariance

Initial Values

Parameter Names

As Posterior Predictive Check

Bayes Factor

Burn-in

Caterpillar Plot

Centering and Scaling

Combine Demonoid Objects

Conditional Plots

Consort with Laplace's Demon

Cumulative Sample Function

Demon Choice Data Set

Demon FX Data Set

Demon Sessions Data Set

Demon Snacks Data Set

Demon Space-Time Data Set

de Finetti's Game

De-Burn

Asymmetric Laplace Distribution: Univariate

Asymmetric Log-Laplace Distribution

Asymmetric Multivariate Laplace Distribution

Bernoulli Distribution

Categorical Distribution

Continuous Relaxation of a Markov Random Field Distribution

Dirichlet Distribution

Generalized Pareto Distribution

Generalized Poisson Distribution

Half-Cauchy Distribution

Half-Normal Distribution

Half-t Distribution

Horseshoe Distribution

Huang-Wand Distribution

Inverse Beta Distribution

(Scaled) Inverse Chi-Squared Distribution

Inverse Gamma Distribution

Inverse Gaussian Distribution

Inverse Matrix Gamma Distribution

Inverse Wishart Distribution: Cholesky Parameterization

Inverse Wishart Distribution

Mixture of Laplace Distributions

Laplace Distribution: Precision Parameterization

Laplace Distribution: Univariate Symmetric

LASSO Distribution

Log-Laplace Distribution: Univariate Symmetric

Log-Normal Distribution: Precision Parameterization

Matrix Gamma Distribution

Matrix Normal Distribution

Multivariate Cauchy Distribution: Cholesky Parameterization

Multivariate Cauchy Distribution: Precision-Cholesky Parameterization

Multivariate Cauchy Distribution: Precision Parameterization

Multivariate Cauchy Distribution

Multivariate Laplace Distribution: Cholesky Parameterization

Multivariate Laplace Distribution

Multivariate Normal Distribution: Cholesky Parameterization

Multivariate Normal Distribution: Precision-Cholesky Parameterization

Multivariate Normal Distribution: Precision Parameterization

Multivariate Normal Distribution

Multivariate Polya Distribution

Multivariate Power Exponential Distribution: Cholesky Parameterization

Multivariate Power Exponential Distribution

Multivariate t Distribution: Cholesky Parameterization

Multivariate t Distribution: Precision-Cholesky Parameterization

Multivariate t Distribution: Precision Parameterization

Multivariate t Distribution

Normal-Inverse-Wishart Distribution

Normal-Laplace Distribution: Univariate Asymmetric

Mixture of Normal Distributions

Normal Distribution: Precision Parameterization

Normal Distribution: Variance Parameterization

Normal-Wishart Distribution

Pareto Distribution

Power Exponential Distribution: Univariate Symmetric

Scaled Inverse Wishart Distribution

Skew Discrete Laplace Distribution: Univariate

Skew-Laplace Distribution: Univariate

Truncated Stick-Breaking Prior Distribution

Student t Distribution: Precision Parameterization

Student t Distribution: Univariate

Truncated Distributions

Wishart Distribution: Cholesky Parameterization

Wishart Distribution

Yang-Berger Distribution

Hyperprior-g Prior and Zellner's g-Prior

Prior Elicitation

Effective Sample Size due to Autocorrelation

Gelfand's Convergence Diagnostic

Gelman and Rubin's MCMC Convergence Diagnostic

Geweke's Convergence Diagnostic

Generate Initial Values

Hangartner's Convergence Diagnostic

Heidelberger and Welch's MCMC Convergence Diagnostic

Server Listening

Integrated Autocorrelation Time

Variable Importance

Constrain to Interval

Appeased

Logical Check of a Bayesian Model

Logical Check of Classes

Logical Check of a Constant

Logical Check of Constraints

Logical Check of Data

Logical Check of a Model

Logical Check of Propriety

Logical Check of Stationarity

Iterative Quadrature

Joint Density Plot

Joint Probability Region Plot

Juxtapose MCMC Algorithm Inefficiency

Kullback-Leibler Divergence (KLD)

Kolmogorov-Smirnov Convergence Diagnostic

Laplace Approximation

tools:::Rd_package_title("LaplacesDemon")

LaplacesDemon RAM Estimate

Laplace's Demon

Levene's Test

Logarithm of the Marginal Likelihood

The log-log and complementary log-log functions

The logit and inverse-logit functions

Loss Matrix

Lowest Posterior Loss Interval

Math Utility Functions

Matrix Utility Functions

Monte Carlo Standard Error

Minnesota Prior

Multiple Imputation Sequential Sampling

The Mode(s) of a Vector

Model Specification Time

Probability Interval

Plot Hellinger Distances

Plots of Posterior Predictive Checks

Plot samples from the output of Laplace's Demon

Plot Variable Importance

Plots of Posterior Predictive Checks

Plot the output of IterativeQuadrature

Plot MCMC Juxtaposition

Plots of Posterior Predictive Checks

Plot the output of LaplaceApproximation

Plot samples from the output of MISS

Plots of Posterior Predictive Checks

Plot samples from the output of PMC

Plots of Posterior Predictive Checks

Plot the output of VariationalBayes

Plot a Numerical Matrix

Plot Samples

PMC RAM Estimate

Population Monte Carlo

Posterior Checks

Precision

Posterior Predictive Checks

Posterior Predictive Checks

Posterior Predictive Checks

Posterior Predictive Checks

Posterior Predictive Checks

Print an object of class demonoid to the screen.

Print an object of class heidelberger to the screen.

Print an object of class iterquad to the screen.

Print an object of class laplace to the screen.

Print an object of class miss to the screen.

Print an object of class pmc to the screen.

Print an object of class raftery to the screen.

Print an object of class vb to the screen.

Raftery and Lewis's diagnostic

Rejection Sampling

Sensitivity Analysis

Sampling Importance Resampling

Truncated Stick-Breaking

Posterior Predictive Check Summary

Posterior Predictive Check Summary

Posterior Predictive Check Summary

MISS Summary

Posterior Predictive Check Summary

Posterior Predictive Check Summary

Thin

Holdout Validation

Variational Bayes

Widely Applicable Information Criterion