Loss Distribution Estimation, External Data and Model Averaging

modeling loss data by phase-type distribution

بیمه گران همیشه بابت خسارات بیمه نامه های تحت پوشش خود نگران بوده و روش هایی را جستجو می کنند که بتوانند داده های خسارات گذشته را با هدف اتخاذ یک تصمیم بهینه مدل بندی نمایند. در این پژوهش توزیع های فیزتایپ در مدل بندی داده های خسارات معرفی شده که شامل استنباط آماری مربوطه و استفاده از الگوریتم em در برآورد پارامترهای توزیع است. در پایان امکان استفاده از این توزیع در مدل بندی داده های گروه بندی ...

Model Averaging With Holdout Estimation of the Posterior Distribution

The holdout estimation of the expected loss of a model is biased and noisy. Yet, practicians often rely on it to select the model to be used for further predictions. Repeating the learning phase with small variations of the training set, reveals a variation on the selected model which then induces an important variation of the final test performances. Thus, we propose a small modification to th...

Model Averaging Estimation for Sparse High-dimensional Data

Bayesian model comparison and model averaging for small-area estimation

This paper considers small-area estimation with proportion data, and discusses the choice of upper-level model for the variation over areas. Inference about the random effects for the areas may depend strongly on the choice of this model, but this choice is not a straightforward matter. We show that posterior distributions of the deviances for the competing models provide a valuable tool for th...

Bayesian curve estimation by model averaging

A Bayesian approach is used to estimate a nonparametric regression model. The main features of the procedure are, first, the functional form of the curve is approximated by a mixture of local polynomials by Bayesian Model Averaging (BMA); second, the model weights are approximated by the BIC criterion, and third, a robust estimation procedure is incorporated to improve the smoothness of the est...