Random scaling factors in Bayesian distributional regression models with an application to real estate data

A Bayesian Nominal Regression Model with Random Effects for Analysing Tehran Labor Force Survey Data

Large survey data are often accompanied by sampling weights that reflect the inequality probabilities for selecting samples in complex sampling. Sampling weights act as an expansion factor that, by scaling the subjects, turns the sample into a representative of the community. The quasi-maximum likelihood method is one of the approaches for considering sampling weights in the frequentist framewo...

on some bayesian statistical models in actuarial science with emphasis on claim count

چکیده ندارد.

Data Mining: An Empirical Application in Real Estate Valuation

This paper presents the insights gained from applying data mining techniques, in particular neural networks for the purposes of developing an intelligent model used to predict real estate property values based on variety of factors. A dataset of over one thousand transactions in real estate properties was used. The dataset included 15 variables obtained from the multiple listing system (MLS) da...

Bayesian random-effects threshold regression with application to survival data with nonproportional hazards.

In epidemiological and clinical studies, time-to-event data often violate the assumptions of Cox regression due to the presence of time-dependent covariate effects and unmeasured risk factors. An alternative approach, which does not require proportional hazards, is to use a first hitting time model which treats a subject's health status as a latent stochastic process that fails when it reaches ...

Bayesian Grouped Horseshoe Regression with Application to Additive Models