Results 21 to 30 of about 269 (169)
A new simulation estimator of system reliability
A basic identity is proven and applied to obtain new simulation estimators concerning (a) system reliability, (b) a multi‐valued system. We show that the variance of this new estimator is often of the order α2 when the usual raw estimator has variance of the order α and α is small.
Sheldon M. Ross
wiley +1 more source
Nonparametric C- and D-vine-based quantile regression
Quantile regression is a field with steadily growing importance in statistical modeling. It is a complementary method to linear regression, since computing a range of conditional quantile functions provides more accurate modeling of the stochastic ...
Tepegjozova Marija +3 more
doaj +1 more source
Local linear approach: Conditional density estimate for functional and censored data
Let YY be a random real response, which is subject to right censoring by another random variable CC. In this paper, we study the nonparametric local linear estimation of the conditional density of a scalar response variable and when the covariable takes ...
Benkhaled Abdelkader, Madani Fethi
doaj +1 more source
Strong consistency of regression function estimator with martingale difference errors
In this paper, we consider the regression model with fixed design: Yi=g(xi)+εi{Y}_{i}=g\left({x}_{i})+{\varepsilon }_{i}, 1≤i≤n1\le i\le n, where {xi}\left\{{x}_{i}\right\} are the nonrandom design points, and {εi}\left\{{\varepsilon }_{i}\right\} is a ...
Chen Yingxia
doaj +1 more source
On the asymptotic covariance of the multivariate empirical copula process
Genest and Segers (2010) gave conditions under which the empirical copula process associated with a random sample from a bivariate continuous distribution has a smaller asymptotic covariance than the standard empirical process based on a random sample ...
Genest Christian +2 more
doaj +1 more source
Return level bounds for discrete and continuous random variables
Discrete extremes, Empirical processes, Generalized Pareto distribution, Return level, 62G05, 62G20, 62G30,
P. Naveau +7 more
core +1 more source
We study nonparametric estimators of conditional Kendall’s tau, a measure of concordance between two random variables given some covariates. We prove non-asymptotic pointwise and uniform bounds, that hold with high probabilities.
Derumigny Alexis, Fermanian Jean-David
doaj +1 more source
Pharmacokinetics and Pharmacodynamics Models of Tumor Growth and Anticancer Effects in Discrete Time
We study the h-discrete and h-discrete fractional representation of a pharmacokinetics-pharmacodynamics (PK-PD) model describing tumor growth and anticancer effects in continuous time considering a time scale h0, where h > 0.
Atıcı Ferhan M. +4 more
doaj +1 more source
Conditional Density Kernel Estimation Under Random Censorship for Functional Weak Dependence Data
The primary objective of this research is to investigate the asymptotic properties of the conditional density nonparametric estimator. The main areas of focus are the estimator’s consistency (with rates), including those involving censored data and quasi‐associated dependent variables, as well as its performance when the covariate is functional in ...
Hamza Daoudi +4 more
wiley +1 more source
Bias-reduced estimators of the Weibull tail-coefficient [PDF]
Weibull tail-coefficient, Bias-reduction, Least-squares approach, Asymptotic normality, 62G05, 62G20, 62G30,
Gardes, Laurent +7 more
core +1 more source

