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We provide easy to verify sufficient conditions for the consistency and asymptotic normality of a class of semiparametric optimization estimators where the criterion function does not obey standard smoothness conditions and simultaneously depends on some preliminary nonparametric estimators. Our results extend existing theories like those of Pakes and… (More)

Copulas are used to depict dependence among several random variables. Both parametric and non-parametric estimation methods have been studied in the literature. Moreover, profile empirical likelihood methods based on either empirical copula estimation or smoothed copula estimation have been proposed to construct confidence intervals of a copula. In this… (More)

- Frédéric Ferraty, Ingrid Van Keilegom, Philippe Vieu
- J. Multivariate Analysis
- 2012

Several classical time series models can be written as a regression model of the form Yt = m(Xt) + σ(Xt)εt, where (Xt, Yt), t = 0,±1,±2, . . ., is a bivariate strictly stationary process. Some of those models, such as ARCH or GARCH models, share the property of proportionality of the regression function, m, and the scale function, σ. In this article, we… (More)

- Elisa Maŕıa, MOLANES LÓPEZ, Ingrid VAN KEILEGOM
- 2009

The study of differences among groups is an interesting statistical topic in many applied fields. It is very common in this context to have data that are subject to mechanisms of loss of information, such as censoring and truncation. In the setting of a two-sample problem with data subject to left truncation and right censoring, we develop an empirical… (More)

- CATHOLIQUE DE LOUVAIN, Ingrid Van Keilegom, Jacobo de Uña-Álvarez, Luis Meira-Machado
- 2008

Let (T1, T2) be gap times corresponding to two consecutive events, which are observed subject to random right-censoring, and suppose the vector (T1, T2) satisfies the nonparametric location-scale regression model T2 = m(T1) + σ(T1)ε, where the functions m and σ are ‘smooth’, and ε is independent of T1. The aim of this paper is twofold. First, we propose a… (More)

Let (X,Y ) be a random vector, where Y denotes the variable of interest possibly subject to random right censoring, and X is a covariate. We construct confidence intervals and bands for the conditional survival and quantile function of Y given X using a nonparametric likelihood ratio approach. This approach was introduced by Thomas and Grunkemeier (1975),… (More)

- Natalie Neumeyer, Ingrid Van Keilegom
- J. Multivariate Analysis
- 2010

In this paper we consider the estimation of the error distribution in a heteroscedastic nonparametric regression model with multivariate covariates. As estimator we consider the empirical distribution function of residuals, which are obtained from multivariate local polynomial fits of the regression and variance functions, respectively. Weak convergence of… (More)

A test of the null hypothesis that a hazard rate is monotone nondecreasing, versus the alternative that it is not, is proposed. Both the test statistic and the means of calibrating it are new. Unlike previous approaches, neither is based on the assumption that the null distribution is exponential. Instead, empirical information is used to effectively… (More)

- Cédric Heuchenne, Ingrid Van Keilegom
- Technometrics
- 2007

Suppose the random vector (X,Y ) satisfies the regression model Y = m(X) + σ(X)ε, where m(·) = E(Y |·) belongs to some parametric class {mθ(·) : θ ∈ Θ} of regression functions, σ2(·) = Var(Y |·) is unknown, and ε is independent of X. The response Y is subject to random right censoring, and the covariate X is completely observed. A new estimation procedure… (More)