DPpackage: Bayesian semi- and nonparametric modeling in R

Mathematics

• Modeling 100%
• Function Space 91%
• Dirichlet Process Prior 71%
• Binary Regression 71%
• Generalized Additive Models 71%
• C++ 67%
• Interval-censored Data 67%
• Model Comparison 66%
• Clustered Data 64%
• Generalized Linear Mixed Model 64%
• Bayes Factor 63%
• Bayesian Nonparametrics 63%
• Receiver Operating Characteristic Curve 62%
• Conditional Density 62%
• Probability Model 59%
• Semiparametric Model 58%
• Sampling Methods 57%
• Bayesian Model 57%
• Nonparametric Model 57%
• Density Estimation 57%
• Longitudinal Data 54%
• Regression Function 53%
• Prior distribution 51%
• Posterior distribution 50%
• Maximise 48%
• Data analysis 46%
• Robustness 42%
• Probability Distribution 42%
• Regression 39%
• Model 33%
• Context 31%

Business & Economics

• Modeling 90%
• Sampling 79%
• Dirichlet Process Prior 65%
• Longitudinal Data 59%
• Generalized Linear Mixed Model 59%
• Generalized Additive Models 59%
• Censored Data 56%
• Density Estimation 56%
• Bayes Factor 54%
• Semiparametric Model 52%
• Nonparametric Model 50%
• Posterior Distribution 50%
• Model Comparison 48%
• Probability Model 48%
• Robustness 47%
• Sampling Methods 40%
• Placing 38%
• Probability Distribution 37%

Engineering & Materials Science

• Sampling 46%
• Probability distributions 20%
• Relaxation 20%