GENERALIZED BAYES ESTIMATION OF SPATIAL AUTOREGRESSIVE MODELS

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Variational Bayes for generalized autoregressive models

We describe a variational Bayes (VB) learning algorithm for generalized autoregressive (GAR) models. The noise is modeled as a mixture of Gaussians rather than the usual single Gaussian. This allows different data points to be associated with different noise levels and effectively provides robust estimation of AR coefficients. The VB framework is used to prevent overfitting and provides model-o...

متن کامل

Generalized Maximum Entropy Estimation of Spatial Autoregressive Models

We formulate generalized maximum entropy estimators for the general linear model and the censored regression model when there is first order spatial autoregression in the dependent variable and residuals. Monte Carlo experiments are provided to compare the performance of spatial entropy estimators in small and medium sized samples relative to classical estimators. Finally, the estimators are ap...

متن کامل

Instrumental Variable Quantile Estimation of Spatial Autoregressive Models∗

We propose a spatial quantile autoregression (SQAR) model, which allows cross-sectional dependence among the responses, unknown heteroscedasticity in the disturbances, and heterogeneous impacts of covariates on different points (quantiles) of a response distribution. The instrumental variable quantile regression (IVQR) method of Chernozhukov and Hansen (2006) is generalized to allow the data to...

متن کامل

Estimation of spatial autoregressive panel data models with fixed effects

This paper establishes asymptotic properties of quasi-maximum likelihood estimators for SAR panel data models with fixed effects and SAR disturbances. A direct approach is to estimate all the parameters including the fixed effects. Because of the incidental parameter problem, some parameter estimatorsmay be inconsistent or their distributions are not properly centered. We propose an alternative...

متن کامل

Maximum Likelihood Estimation for Generalized Autoregressive Score Models

The strong consistency and asymptotic normality of the maximum likelihood estimator in observation-driven models usually requires the study of the model both as a filter for the time-varying parameter and as a data generating process (DGP) for observed data. The probabilistic properties of the filter can be substantially different from those of the DGP. This difference is particularly relevant ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Statistics in Transition New Series

سال: 2019

ISSN: 1234-7655,2450-0291

DOI: 10.21307/stattrans-2019-012