FIML Estimation of an Endogenous Switching Model for Count Data

Properties of estimators of count data model with endogenous switching

We examine properties of estimators of count data model with endogenous switching. The estimation of the count data model that accommodates endogenous switching can be accomplished by Full Information Maximum Likelihood (FIML). However, FIML estimation requires fully and correctly specified model and is computationally burdensome. Alternative estimation methods do not require fully specified mo...

A Bayesian Analysis of Endogenous Switching Models for Count Data

an application of equilibrium model for crude oil tanker ships insurance futures in iran

با توجه به تحریم های بین المملی علیه صنعت بیمه ایران امکان استفاده از بازارهای بین المملی بیمه ای برای نفتکش های ایرانی وجود ندارد. از طرفی از آنجایی که یکی از نوآوری های اخیر استفاده از بازارهای مالی به منظور ریسک های فاجعه آمیز می باشد. از اینرو در این پایان نامه سعی شده است با استفاده از این نوآوری ها با طراحی اوراق اختیارات راهی نو جهت بیمه گردن نفت کش های ایرانی ارائه نمود. از آنجایی که بر...

Development of an Analytic Model for Flux Switching Motors

This paper presents developing an analytical model for flux switching motors. The motor is a class of variable reluctance motors that has two windings on stator; a field winding and an armature winding. Due to saliency of both stator and rotor poles, accurate modeling is difficult which arises from the nonlinear behavior of the machine. This paper presents a simple model which is able to predic...

Estimation of Count Data using Bivariate Negative Binomial Regression Models

Abstract Negative binomial regression model (NBR) is a popular approach for modeling overdispersed count data with covariates. Several parameterizations have been performed for NBR, and the two well-known models, negative binomial-1 regression model (NBR-1) and negative binomial-2 regression model (NBR-2), have been applied. Another parameterization of NBR is negative binomial-P regression mode...