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See detailComputational study of the error distribution in right-censored and selection-biased regression models
Laurent, Géraldine ULg; Heuchenne, Cédric ULg

Conference (2010, May 18)

Consider the regression model Y = m(X) + σ(X) Ɛ where m(X) =E [Y|X] and σ²(X) = Var [Y|X] are unknown smooth functions and the error Ɛ, with unknown distribution, is independent of X. The pair (X,Y) is ... [more ▼]

Consider the regression model Y = m(X) + σ(X) Ɛ where m(X) =E [Y|X] and σ²(X) = Var [Y|X] are unknown smooth functions and the error Ɛ, with unknown distribution, is independent of X. The pair (X,Y) is subject to generalized selection bias and the response to right censoring. We construct a new estimator for the cumulative distribution function of the error Ɛ, and develop a bootstrap technique to select the smoothing parameter involved in the procedure. The estimator is studied via extended simulations and applied to real unemployment data. [less ▲]

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See detailThe Optimal Design of the VSI T2 Control Chart
Faraz, Alireza ULg; Kazemzadeh, R. B.; Heuchenne, Cédric ULg et al

in Journal of Iranian Statistical Society (2010), 9(1), 1-19

Recent studies have shown that the variable sampling interval (VSI) scheme helps practitioners detect process shifts more quickly than the classical scheme (FRS). In this paper, the economically and ... [more ▼]

Recent studies have shown that the variable sampling interval (VSI) scheme helps practitioners detect process shifts more quickly than the classical scheme (FRS). In this paper, the economically and statistically optimal design of the VSI T2 control chart for monitoring the process mean vector is investigated. The cost model proposed by Lorenzen and Vance (1986) is minimized through a genetic algorithm (GA) approach. Then the effects of the costs and operating parameters on the optimal design (OD) of the chart parameters and resulting operating loss through a fractional factorial design is systematically studied and finally, based on the ANOVA results, a Meta model to facilitate implementation in industry is proposed to determine the OD of the VSI T2 control chart parameters from the process and cost parameters [less ▲]

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See detailA Meta Model to Optimal Design the VSI T2 Chart
Faraz, Alireza ULg; Heuchenne, Cédric ULg; Saniga, E.

Report (2010)

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See detailEstimation in nonparametric location-scale regression models with censored data
Heuchenne, Cédric ULg; Van Keilegom, Ingrid

in Annals of the Institute of Statistical Mathematics (2010), 62

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See detailTesting for one-sided alternatives in nonparametric censored curve comparison
Heuchenne, Cédric ULg; Pardo Fernandez, Juan-Carlos

in Proceedings of the 28th European Meeting of Statisticians. (2010)

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See detailGoodness-of-fit tests for the error distribution in nonparametric regression
Heuchenne, Cédric ULg; Van Keilegom, Ingrid

in Computational Statistics & Data Analysis (2010), 54

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See detailCensparreg
Heuchenne, Cédric ULg; Van Keilegom, Ingrid

Software (2010)

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See detailComputational treatment of the error distribution in nonparametric regression with right-censored and selection-biased data
Heuchenne, Cédric ULg; Laurent, Géraldine ULg

in Proceedings of the 19th International Conference on Computational Statistics (2010)

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See detailEstimation of the error distribution in right censored and selection biased regression models
Laurent, Géraldine ULg; Heuchenne, Cédric ULg

Conference (2009, October 15)

Consider the location-scale regression model Y=m(X) + σ(X) Ɛ where the error Ɛ is independent of the covariate X and where m and σ are unknown smooth functions. The pair (X; Y ) is subject to generalized ... [more ▼]

Consider the location-scale regression model Y=m(X) + σ(X) Ɛ where the error Ɛ is independent of the covariate X and where m and σ are unknown smooth functions. The pair (X; Y ) is subject to generalized bias selection and the response to right censoring. We construct an estimator for the cumulative distribution function of the error Ɛ, and develop a bootstrap procedure to select the smoothing parameter involved in the procedure. This method is studied via extension simulations and applied to real unemployment data. [less ▲]

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See detailSemiparametric inference in general heteroscedastic regression models.
Heuchenne, Cédric ULg

Scientific conference (2009, June 09)

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See detailSemiparametric inference in general heteroscedastic regression models
Heuchenne, Cédric ULg; Van Keilegom, Ingrid

in Proceedings of the Sixth Petersburg Workshop on Simulations (2009)

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See detailNonparametric Mean Preservation in Censored Regression
Heuchenne, Cédric ULg

Book published by VDM Verlag (2009)

The aim of this book is to estimate the conditional mean of some functions depending on the response variable Y (moments, distributions...) in regression models where this response is possibly censored ... [more ▼]

The aim of this book is to estimate the conditional mean of some functions depending on the response variable Y (moments, distributions...) in regression models where this response is possibly censored. In parametric regression, polynomial and nonlinear conditional means are estimated in a new way while, in nonparametric regression, some new estimators are provided to approximate general L-functionals (conditional mean, trimmed mean, quantiles...). The ideas developed in those methods lead to establish more general results in nonparametric estimation of the conditional mean of functions depending on Y and other variables and where the response can follow other schemes of incomplete data (not only censored but also missing or length-biased data). For each procedure, asymptotic properties are established while finite sample behavior is studied via simulations. Examples from a variety of areas highlight the interest of using the proposed methodologies in practice. [less ▲]

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See detailStrong uniform consistency results of the weighted average of conditional artificial data points
Heuchenne, Cédric ULg

in Journal of Statistical Planning & Inference (2008), 138(5), 1496-1515

In this paper, we study strong uniform consistency of a weighted average of artificial data points. This is especially useful when information is incomplete (censored data, missing data ...). In this case ... [more ▼]

In this paper, we study strong uniform consistency of a weighted average of artificial data points. This is especially useful when information is incomplete (censored data, missing data ...). In this case, reconstruction of the information is often achieved nonparametrically by using a local preservation of mean criterion for which the corresponding mean is estimated by a weighted average of new data points. The present approach enlarges the possible scope for applications beyond just the incomplete data context and can also be useful to treat the estimation of the conditional mean of specific functions of complete data points. As a consequence, we establish the strong uniform consistency of the Nadaraya - Watson [Nadaraya, E.A., 1964. On estimating regression. Theory Probab. Appl. 9, 141 - 142; Watson, G.S., 1964. Smooth regression analysis. Sankhya Ser. A 26, 359 - 372] estimator for general transformations of the data points. This result generalizes the one of Hardle et al. [Strong uniform consistency rates for estimators of conditional functionals. Ann. Statist. 16, 1428 - 1449]. In addition, the strong uniform consistency of a modulus of continuity will be obtained for this estimator. Applications of those two results are detailed for some popular estimators. (c) 2007 Elsevier B.V. All rights reserved. [less ▲]

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See detailGoodness-of-fit tests for censored regression based on artificial data points
González Manteiga, Wenceslao; Heuchenne, Cédric ULg; Sánchez Sellero, Cesar

Report (2008)

Detailed reference viewed: 61 (3 ULg)
See detailThe determinants of CDS prices: an industry-based investigation
Sougné, Danielle ULg; Heuchenne, Cédric ULg; Hübner, Georges ULg

in Wagner, Niklas (Ed.) Credit Risk: Models, Derivatives and Management. Empirical Studies and Analysis. Financial Mathematics Series. (2008)

Detailed reference viewed: 145 (40 ULg)
See detailParametric conditional mean and variance testing with censored data
Heuchenne, Cédric ULg; González Manteiga, Wenceslao; Sánchez Sellero, Cesar

in H. Skiadas, Christos (Ed.) Recent Advances in Applied Stochastic Models and Data Analysis. (2007)

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See detailPolynomial regression with censored data based on preliminary nonparametric estimation
Heuchenne, Cédric ULg; Van Keilegom, Ingrid

in Annals of the Institute of Statistical Mathematics (2007), 59(2), 273-297

Consider the polynomial regression model Y = (beta)0 + beta(1) X + center dot center dot center dot beta X-p(p) + sigma (X)epsilon, where sigma(2)(X) = Var(Y vertical bar X) is unknown, and epsilon is ... [more ▼]

Consider the polynomial regression model Y = (beta)0 + beta(1) X + center dot center dot center dot beta X-p(p) + sigma (X)epsilon, where sigma(2)(X) = Var(Y vertical bar X) is unknown, and epsilon is independent of X and has zero mean. Suppose that Y is subject to random right censoring. A new estimation procedure for the parameters beta(0), center dot center dot center dot, beta (p) is proposed, which extends the classical least squares procedure to censored data. The proposed method is inspired by the method of Buckley and James (1979, Biometrika, 66, 429-436), but is, unlike the latter method, a noniterative procedure due to nonparametric preliminary estimation of the conditional regression function. The asymptotic normality of the estimators is established. Simulations are carried out for both methods and they show that the proposed estimators have usually smaller variance and smaller mean squared error than Buckley-James estimators. The two estimation procedures are also applied to a medical and a astronomical data set. [less ▲]

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See detailLocation estimation in nonparametric regression with censored data
Heuchenne, Cédric ULg; Van Keilegom, Ingrid

in Journal Of Multivariate Analysis (2007), 98(8), 1558-1582

Consider the heteroscedastic model Y =m (X) +sigma(X)epsilon, where epsilon and X are independent, Y is subject to right censoring, m (center dot) is an unknown but smooth location function (like e.g ... [more ▼]

Consider the heteroscedastic model Y =m (X) +sigma(X)epsilon, where epsilon and X are independent, Y is subject to right censoring, m (center dot) is an unknown but smooth location function (like e.g. conditional mean, median, trimmed mean...) and sigma(center dot) an unknown but smooth scale function. In this paper we consider the estimation of m(center dot) under this model. The estimator we propose is a Nadaraya-Watson type estimator, for which the censored observations are replaced by 'synthetic' data points estimated under the above model. The estimator offers an alternative for the completely nonparametric estimator of m (center dot), which cannot be estimated consistently in a completely nonparametric way, whenever high quantiles of the conditional distribution of Y given X = x are involved. We obtain the asymptotic properties of the proposed estimator of m (x) and study its finite samplebehaviour in a simulation study. The method is also applied to a study of quasars in astronomy. (c) 2007 Elsevier Inc. All rights reserved. [less ▲]

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