Estimation and inference in spatially varying coefficient models
نویسندگان
چکیده
منابع مشابه
Statistical Inference for Varying Coefficient Models
This dissertation contains two projects that are related to varying coefficient models. The traditional least squares based kernel estimates of the varying coefficient model will lose some efficiency when the error distribution is not normal. In the first project, we propose a novel adaptive estimation method that can adapt to different error distributions and provide an efficient EM algorithm ...
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Recently there has been considerable work on stochastic time-varying coefficient models as vehicles for modelling structural change in the macroeconomy with a focus on the estimation of the unobserved sample path of time series of coefficient processes. The dominant estimation methods, in this context, are various filters, such as the Kalman filter, that are applicable when the models are cast ...
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By allowing the regression coefficients to change with certain covariates, the class of varying coefficient models offers a flexible approach to modeling nonlinearity and interactions between covariates. This paper proposes a novel estimation procedure for the varying coefficient models based on local ranks. The new procedure provides a highly efficient and robust alternative to the local linea...
متن کاملEfficient Estimation in Heteroscedastic Varying Coefficient Models
This paper considers statistical inference for the heteroscedastic varying coefficient model. We propose an efficient estimator for coefficient functions that is more efficient than the conventional local-linear estimator. We establish asymptotic normality for the proposed estimator and conduct some simulation to illustrate the performance of the proposed method.
متن کاملBayesian Spatially Varying Coefficient Models in the Presence of Collinearity
The belief that relationships between explanatory variables and a response variable in a regression model may vary within a study area has lead to the development of Bayesian regression models that allow for spatially varying coefficients (Gelfand et al., 2003). In the typical application of these spatially varying coefficient process (SVCP) models, marginal inference on the spatial pattern of ...
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ژورنال
عنوان ژورنال: Environmetrics
سال: 2017
ISSN: 1180-4009,1099-095X
DOI: 10.1002/env.2485