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ESTIMATION AND FORECASTING IN SUINAR（1） MODEL
Forecasts Gibbs sampling INAR model panel data.
2009/2/25
This work considers a generalization of the INAR(1) model to the panel data first
order Seemingly Unrelated INteger AutoRegressive Poisson model, SUINAR(1).
It presents Bayesian and classical method...
A mixture model for unsupervised tail estimation
Mixing functions Heavy and Light Tailed Distributions Maximum Likelihood Mixture Mod
2010/3/18
This paper proposes a new method to combine several densities
such that each density dominates a separate part of a joint distribution. The
method is fully unsupervised, i.e. the parameters in the d...
Asymptotic normality of the integrated square error of a density estimator in the convolution model
convolution density estimation nonparametric density estimation central limit theorem integrated squared error noisy observations
2009/2/23
In this paper we consider a kernel estimator of a density in a convolution model and give a central limit theorem for its integrated square error (ISE). The kernel estimator is rather classical in min...
Weighted least squares methods for prediction in the functional data linear model
Cross-validation eigenfunction eigenvector functional data analysis functional linear regression mean squared error orthogonal series
2010/3/18
The problem of prediction in functional linear regression is conventionally addressed
by reducing dimension via the standard principal component basis. In this paper we
show that an alternative basi...
Detecting a conditional extrme value model
Regular variation domain of attraction heavy tails asymptotic independence conditional extremevalue model
2010/3/18
In classical extreme value theory probabilities of extreme events are estimated assuming all
the components of a random vector to be in a domain of attraction of an extreme value distribution. In con...
Adaptive estimation of linear functionals in the convolution model and applications
adaptive density estimation ARCH models deconvolution linear functionals model selection penalized contrast
2010/3/18
We consider the model Zi = Xi + εi, for i.i.d. Xi’s and εi’s and independent sequences (Xi)i2Nand (εi)i2N. The density f" of ε1 is assumed to be known, whereas the one of X1, denoted by
g, is unknown...
On rate optimal local estimation in functional linear model
Linear functional Orthogonal series estimation Thresholding Linear Galerkin projection Minimax-theory Sobolev space
2010/3/18
We consider the problem of estimating for a given representer h the value ℓh(β)
of a linear functional of the slope parameter β in functional linear regression, where
scalar responses Y1, . . ...
Bayesian projection approaches to variable selection and exploring model uncertainty
Bayesian variable selection Kullback-Leibler projection lasso non-negative garotte preconditioning
2010/3/17
A Bayesian approach to variable selection which is based on the expected Kullback-
Leibler divergence between the full model and its projection onto a submodel has
recently been suggested in the lit...
A structural model on a hypercube represented by optimal transport
determinant maximization Fourier series graphical model lasso optimal transport structural gradient model
2010/3/17
We propose a flexible statistical model for high-dimensional quantitative
data on a hypercube. Our model, called the structural gradient model (SGM),
is based on a one-to-one map on the hypercube th...
A mixture of experts model for rank data with applications in election studies
Rank data mixture models generalized linear models EMalgorithm MM algorithm
2010/3/17
A voting bloc is defined to be a group of voters who have similar
voting preferences. The cleavage of the Irish electorate into voting
blocs is of interest. Irish elections employ a “single transfer...
State-space based mass event-history model I：many decision-making agents with one target
Extremists Heterogeneity Interval censoring Logistic regression Maximum likelihood estimation Nematode
2010/3/17
A dynamic decision-making system that includes a mass of indistinguishable
agents could manifest impressive heterogeneity. This
kind of nonhomogeneity is postulated to result from macroscopic behavi...
Practical Robust Estimators for the Imprecise Dirichlet Model
Imprecise Dirichlet Model exact conservative approximate robust credibleinterval estimates entropy
2010/3/17
Walley’s Imprecise Dirichlet Model (IDM) for categorical i.i.d. data extends
the classical Dirichlet model to a set of priors. It overcomes several fundamental
problems which other approaches to unc...
Practical Robust Estimators for the Imprecise Dirichlet Model
Imprecise Dirichlet Model exact conservative approximate robust credibleinterval estimates entropy mutual information
2010/3/17
Walley’s Imprecise Dirichlet Model (IDM) for categorical i.i.d. data extends
the classical Dirichlet model to a set of priors. It overcomes several fundamental
problems which other approaches to unc...
Interpolating fields of carbon monoxide data using a hybrid statistical-physical model
Carbon monoxide satellite data Bayesian hierarchical models interpolation data assimilation
2010/3/17
Atmospheric Carbon Monoxide (CO) provides a window on the
chemistry of the atmosphere since it is one of few chemical constituents
that can be remotely sensed, and it can be used to determine
budge...
Probabilistic quantitative precipitation field forecasting using a two-stage spatial model
Discrete-continuous distribution ensemble forecast Gammadistribution latent Gaussian process numerical weather prediction
2010/3/17
Short-range forecasts of precipitation fields are needed in a wealth
of agricultural, hydrological, ecological and other applications. Forecasts
from numerical weather prediction models are often bi...