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Spatial Panel Data Models. Oxford Handbook of Panel Data
Spatial Panel Data Model Oxford Handbook Panel Data
2016/1/26
The consideration of interactions among regions or agents has become increasingly important in various fields of economics. In public economics, a state government’s cigarettes tax rate will be influe...
Testing Additive Separability of Error Term in Nonparametric Structural Models
Additive Separability Hypotheses Testing Nonparametric Structural Equation Non- separable Models
2016/1/25
This paper considers testing additive error structure in nonparametric structural models, against the alternative hypothesis that the random error term enters the nonparametric model non-additively.We...
Estimation of Spatial Panel Data Models with Time Varying Spatial Weights Matrices
Spatial autoregression Panel data Time varying spatial weights matrices Fixed e¤ects Maximum likelihood Impact analysis
2016/1/20
This paper investigates the quasi-maximum likelihood (QML) estimation of spatial panel data models where spatial weights matrices can be time varying. We show that QML estimate is consistent and asymp...
Tests for High Dimensional Generalized Linear Models
Generalized Linear Model Gene-Sets High Dimensional Covariate Nuisance Parameter U-statistics
2016/1/20
We consider testing regression coefficients in high dimensional generalized linear mod-els. By modifying a test statistic proposed by Goeman et al. (2011) for large but fixed dimensional settings, we ...
Learning the Structure of Mixed Graphical Models
Learning the Structure Mixed Graphical Models
2015/8/21
We consider the problem of learning the structure of a pairwise graphical model over continuous and discrete variables. We present a new pairwise model for graphical models with both continuous and di...
Integer Parameter Estimation in Linear Models with Applications to GPS
GPS integer least-squares integer parameter estimation linear model
2015/7/10
We consider parameter estimation in linear models when some of the parameters are known to be integers. Such problems arise, for example, in positioning using phase measurements in the global position...
Discrete Klein–Gordon models with static kinks free of the Peierls–Nabarro potential
Gordon type model nonlinear klein discretization static kink lattice the discrete model
2014/12/25
For the nonlinear Klein–Gordon type models, we describe a general method of discretization in which the static kink can be placed anywhere with respect to the lattice. These discrete models are, there...
Standard nearest-neighbour discretizations of Klein–Gordon models cannot preserve both energy and linear momentum
Discrete nonlinear klein GeDengBo equation the standard discrete linear momentum
2014/12/25
We consider nonlinear Klein–Gordon wave equations and illustrate that standard discretizations thereof (involving nearest neighbours) may preserve either standardly defined linear momentum or standard...
Exact static solutions for discrete ϕ4 models free of the Peierls-Nabarro barrier: Discretized first-integral approach
Discrete klein Gordon model the complete solution static static klein Gordon
2014/12/25
We propose a generalization of the discrete Klein-Gordon models free of the Peierls-Nabarro barrier derived in Spreight [Nonlinearity 12, 1373 (1999)] and Barashenkov et al. [Phys. Rev. E 72, 035602(R...
Two-component nonlinear Schrodinger models with a double-well potential
Model of condensate hyperfine status the mixture
2014/12/25
We introduce a model motivated by studies of Bose–Einstein condensates (BECs) trapped in double-well potentials. We assume that a mixture of two hyperfine states of the same atomic species is loaded i...
Generalized neighbor-interaction models induced by nonlinear lattices
Nonlinear schrodinger equation the space nonlinear coefficient complex nonlinear lattice
2014/12/24
It is shown that the tight-binding approximation of the nonlinear Schrödinger equation with a periodic linear potential and periodic in space nonlinearity coefficient gives rise to a number of no...
Approximation of epidemic models by diffusion processes and their statistical inference
Approximation epidemic models diffusion processes their statistical inference
2013/6/14
Among various mathematical frameworks, multidimensional continuous-time Markov jump processes $(Z_t)$ on $\N^d$ form a natural set-up for modeling $SIR$-like epidemics. In this study we extend the res...
Characterizing A Database of Sequential Behaviors with Latent Dirichlet Hidden Markov Models
LDHMMs sequential data variational inference variational EM behavior modeling sequence classification
2013/6/14
This paper proposes a generative model, the latent Dirichlet hidden Markov models (LDHMM), for characterizing a database of sequential behaviors (sequences). LDHMMs posit that each sequence is generat...
Fast inference in generalized linear models via expected log-likelihoods
Fast inference generalized linear models expected log-likelihoods
2013/6/14
Generalized linear models play an essential role in a wide variety of statistical applications. This paper discusses an approximation of the likelihood in these models that can greatly facilitate comp...
In this note the relation between the range-renewal speed and entropy for i.i.d. models is discussed.