Generalized Method of Moments with Latent Variables

Parameter Estimation in Spatial Generalized Linear Mixed Models with Skew Gaussian Random Effects using Laplace Approximation

 Spatial generalized linear mixed models are used commonly for modelling non-Gaussian discrete spatial responses. We present an algorithm for parameter estimation of the models using Laplace approximation of likelihood function. In these models, the spatial correlation structure of data is carried out by random effects or latent variables. In most spatial analysis, it is assumed that rando...

The Welfare Cost of Inflation: Theory with an Application of Generalized Method of Moments (GMM) to Ira

Fast moment estimation for generalized latent Dirichlet models

We develop a generalized method of moments (GMM) approach for fast parameter estimation in a new class of Dirichlet latent variable models with mixed data types. Parameter estimation via GMM has been demonstrated to have computational and statistical advantages over alternative methods, such as expectation maximization, variational inference, and Markov chain Monte Carlo. The key computational ...

Optimal Government Budget Allocation According to Aggregate Welfare using Generalized Method of Moments

How should the government budget be allocated to public education, higher education, health, transportation, IT, energy, or indirect public services including expenses on laws and regulations, business governance, and tax reforms. We examine data between 1989 and 2019 of public spending and their outcomes for each affair and title. The results show that despite that number of students declined ...

به‌کارگیری متغیرهای پنهان در مدل رگرسیون لجستیک برای حذف اثر هم‌خطی چندگانه در تحلیل برخی عوامل مرتبط با سرطان پستان

Background and Objectives: Logistic regression is one of the most widely used generalized linear models for analysis of the relationships between one or more explanatory variables and a categorical response. Strong correlations among explanatory variables (multicollinearity) reduce the efficiency of model to a considerable degree. In this study we used latent variables to reduce the effects of ...