In addition to surface soil moisture (SSM) data, root zone soil moisture (RZSM) is particularly
significant for irrigation decision-making and agricultural drought warnings since water …

Bayesian inference provides a methodology for parameter estimation and uncertainty
quantification in machine learning and deep learning methods. Variational inference and …

Bayesian inference provides a methodology for parameter estimation and uncertainty
quantification in machine learning and deep learning methods. Variational inference and …

Latent variable models are widely used to account for unobserved determinants of economic
behavior. Traditional nonparametric methods to estimate latent heterogeneity do not scale …

This paper presents a quasi-Bayes approach to estimating nonparametric demand systems
for differentiated products. We transform the GMM objective function developed by Compiani …

A substantial body of research focuses on the statistical analysis of economic models
featuring either endogenous regressors or latent unobservable variables. These models …

The process of inference in a parametric statistical model involves assessing the uncertainty
of the surrounding parameters based on an observed sample. Often, the lack of analytical …

The need to accurately determine risk-return trade-offs in financial markets is an important
question that has occupied minds of various players in capital markets for over five decades …

The need to accurately determine risk-return trade-offs in financial markets is an important
question that has occupied minds of various players in capital markets for over five decades …