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GRID for model structure discovering in high dimensional regression
(2014)
Given a nonparametric regression model, we assume that the number of
covariates d → ∞ but only some of these covariates are relevant for the model. Our goal
is to identify the relevant covariates and to obtain some ...
Bias-corrected inference for multivariate nonparametric regression: model selection and oracle property
(2014)
The local polynomial estimator is particularly affected by the curse of di-
mensionality. So, the potentialities of such a tool become ineffective for large dimensional
applications. Motivated by this, we propose a new ...
A locally adaptive bandwidth selector for kernel based regression
(2009)
The selection of the smoothing parameter represents a crucial step in the
local polynomial regression, because of the implications on the consistency
of the nonparametric regression estimator and because of the difficulties ...
Parameter estimation in continuous stochastic volatility models
(2009)
Continuous-time di usion processes are often used in literature to
model dynamics of nancial markets. In such kinds of models a rel-
evant role is played by the variance of the process. So assumptions
on the functional ...
Weak consistent moving block bootstrap estimator of sampling distribution of CLS estimators in a class of bilinear models
(2005)
Grahn, (1995) introduced the Conditional Least Squares estimators for the
class (I) of bilinear models. Such estimators have a variance which is difficulty
to derive analytically. The aim of the present paper is to ...
Weak consistent moving block bootstrap estimator for the variance of CLS estimators in a class of bilinear models
(2008)
Grahn (1995) introduced the Conditional Least Squares estimators for the
class (I) of bilinear models. These estimators have a variance which is difficulty
to derive analytically. In this paper we derive the conditions ...