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Empirical likelihood for spatial dynamic panel data models
Spatial dynamic panel data (SDPD) models have received great attention in economics in recent 10 years. Existing approaches for the estimation and...
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A Dynamic Occupancy Model for Interacting Species with Two Spatial Scales
Occupancy models have been extended to account for either multiple spatial scales or species interactions in a dynamic setting. However, as...
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A Generalization of the Spatial Binary Model to the Longitudinal Spatial Setup
When spatial data are repeatedly collected over a short period of time, they exhibit two-way correlations. More specifically at a given point of time...
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Estimation of fixed effects semiparametric single-index panel model with spatio-temporal correlated errors
Spatial error parametric panel model is one of the most popularly used analytical tools in spatial econometrics. Although this model takes into...
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Profile quasi-maximum likelihood estimation for semiparametric varying-coefficient spatial autoregressive panel models with fixed effects
This paper aims to propose a profile quasi-maximum likelihood estimation method for semiparametric varying-coefficient spatial autoregressive(SVCSAR)...
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GPS data on tourists: a spatial analysis on road networks
This paper proposes a spatial point process model on a linear network to analyse cruise passengers’ stop activities. It identifies and models...
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GMM estimation and variable selection of partially linear additive spatial autoregressive model
The generalized method of moments (GMM) has been recognized as a particularly popular estimation procedure in terms of computational simplicity and...
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Forecasting the housing vacancy rate in Japan using dynamic spatiotemporal effects models
This study attempts to predict and forecast the future heterogeneous increase in the vacant house ratio among prefectures in Japan using spatial...
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Detection of multiple change-points in high-dimensional panel data with cross-sectional and temporal dependence
We consider the detection of multiple change-points in a high-dimensional time series exhibiting both cross-sectional and temporal dependence....
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Evaluating the spatial heterogeneity of innovation drivers: a comparison between GWR and GWPR
In studies focusing on innovation activities, the potential spatial heterogeneity in the relationships between innovation and its triggering factors...
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An alternative semiparametric model for spatial panel data
We propose a semiparametric P-Spline model to deal with spatial panel data. This model includes a non-parametric spatio-temporal trend, a spatial lag...
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An Overview on Econometric Models for Linear Spatial Panel Data
When spatial data are repeatedly collected from the same spatial locations over a short period of time, a spatial panel/longitudinal data set is...
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Minimum contrast for the first-order intensity estimation of spatial and spatio-temporal point processes
In this paper, we harness a result in point process theory, specifically the expectation of the weighted K -function, where the weighting is done by...
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Integrating Different Data Sources Using a Bayesian Hierarchical Model to Unveil Glacial Refugia
Rapid anthropogenic climate change has elevated the interest in studying the biotic responses of species during the Last Glacial Maximum. During this...
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Robust estimation and inference of spatial panel data models with fixed effects
It is well established that the quasi maximum likelihood (QML) estimation of the spatial regression models is generally inconsistent under unknown...
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Non-Independent Data
Many infectious disease experiments result in non-independent data because of spatial autocorrelationAutocorrelation across fields (such as...
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Joint Spatial Modeling Bridges the Gap Between Disparate Disease Surveillance and Population Monitoring Efforts Informing Conservation of At-risk Bat Species
White-Nose Syndrome (WNS) is a wildlife disease that has decimated hibernating bats since its introduction in North America in 2006. As the disease...
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The Evolution of Dynamic Gaussian Process Model with Applications to Malaria Vaccine Coverage Prediction
Gaussian process (GP)-based statistical surrogates are popular, inexpensive substitutes for emulating the outputs of expensive computer models that...
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Rank-based instrumental variable estimation for semiparametric varying coefficient spatial autoregressive models
In this paper, it is aim to propose an instrumental variable rank estimation method for varying coefficient spatial autoregressive models. The newly...
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Tail and Quantile Estimation for Real-Valued \(\boldsymbol{\beta}\)-Mixing Spatial Data
AbstractThis paper deals with extreme-value index estimation of a heavy-tailed distribution of a spatial dependent process. We are particularly...
