JSTOR Daily

Smooth Empirical Bayes Estimation for One-Parameter Discrete Distributions

A study is made of the simple empirical Bayes estimators proposed by Robbins (1956). These estimators are compared with `best' conventional estimators in terms of ...
Risk

Bayesian nonparametric covariance estimation with noisy and nonsynchronous asset prices

The covariance matrix of asset returns is the key input for many problems in finance and economics. This paper introduces a Bayesian nonparametric method to estimate the ex post covariance matrix from ...
Nature

Bayesian Predictive Density Estimation

Bayesian predictive density estimation represents a cornerstone of modern statistical inference by integrating prior knowledge with observed data to produce a predictive distribution for future ...
Opinion

How To Speed Up the Search for Cures Through a Change in Probability Theory

The post How To Speed Up the Search for Cures Through a Change in Probability Theory appeared first on Reason.com.
Risk

Robust calibration of financial models using Bayesian estimators

The authors consider a general calibration problem for derivative pricing models, which they reformulate into a Bayesian framework to attain posterior distributions for model parameters. They then ...
JSTOR Daily

NETWORK AUTOCORRELATION MODELING: BAYESIAN TECHNIQUES FOR ESTIMATING AND TESTING MULTIPLE NETWORK AUTOCORRELATIONS

The network autocorrelation model has been the workhorse for estimating and testing the strength of theories of social influence in a network. In many network studies, different types of social ...
lse

Bayesian Machine Learning

This course is available on the MSc in Applied Social Data Science, MSc in Data Science, MSc in Econometrics and Mathematical Economics, MSc in Health Data Science, MSc in Operations Research & ...