In this paper, we study an kernel estimator of the conditional hazard quantile function (CHQF) of a scalar response variable Y given a random variable (rv) X taking values in a semi-metric space and using the proposed estimator based of the kernel smoothing method. The almost complete consistency and the asymptotic normality of this estimate are obtained when the sample is an independante sequence
International audienceA kernel conditional quantile estimate of a real-valued non-stationary spatial...
The main objective of this paper is to non-parametrically estimate the quantiles of a conditional di...
Let X be the variable of interest with distribution function F, hazard function $\lambda$ and Y be a...
This paper deals with the conditional hazard estimator of a real response where the variable is give...
The main goal of this paper is to study the asymptotic normality of the estimate of the Conditional ...
This paper considers the problem of nonparametric estimation of the conditional hazard function for ...
Given a stationary multidimensional spatial process (i=(i,i)∈ℝ×ℝ,i∈ℤ), we investigate a kernel estim...
Let be a response variable that is subject to left-truncation by a variable . We consider the proble...
Let (X, Y) be a two dimensional random variable with a joint density function f(x, y) and a joint di...
This paper contains a complete procedure for calculating the value of a conditional quantile estimat...
We introduce a new kernel hazard estimator in a nonparametric model where the stochastic hazard depe...
In this thesis we study some asymptotic properties of the kernel conditional quantile estimator whe...
The main objective of this paper is to estimate the conditional cumulative distribution using the no...
International audienceNonparametric regression quantiles can be obtained by inverting a kernel estim...
The estimation of conditional quantiles has become an increasingly important issue in insurance and ...
International audienceA kernel conditional quantile estimate of a real-valued non-stationary spatial...
The main objective of this paper is to non-parametrically estimate the quantiles of a conditional di...
Let X be the variable of interest with distribution function F, hazard function $\lambda$ and Y be a...
This paper deals with the conditional hazard estimator of a real response where the variable is give...
The main goal of this paper is to study the asymptotic normality of the estimate of the Conditional ...
This paper considers the problem of nonparametric estimation of the conditional hazard function for ...
Given a stationary multidimensional spatial process (i=(i,i)∈ℝ×ℝ,i∈ℤ), we investigate a kernel estim...
Let be a response variable that is subject to left-truncation by a variable . We consider the proble...
Let (X, Y) be a two dimensional random variable with a joint density function f(x, y) and a joint di...
This paper contains a complete procedure for calculating the value of a conditional quantile estimat...
We introduce a new kernel hazard estimator in a nonparametric model where the stochastic hazard depe...
In this thesis we study some asymptotic properties of the kernel conditional quantile estimator whe...
The main objective of this paper is to estimate the conditional cumulative distribution using the no...
International audienceNonparametric regression quantiles can be obtained by inverting a kernel estim...
The estimation of conditional quantiles has become an increasingly important issue in insurance and ...
International audienceA kernel conditional quantile estimate of a real-valued non-stationary spatial...
The main objective of this paper is to non-parametrically estimate the quantiles of a conditional di...
Let X be the variable of interest with distribution function F, hazard function $\lambda$ and Y be a...