References of "Heuchenne, Cédric"
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See detailScale checks in censored regression
Heuchenne, Cédric ULg; Dette, Holger

in Scandinavian Journal of Statistics (2012), 39

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See detailEstimation of a general parametric location in censored regression
Heuchenne, Cédric ULg; Van Keilegom, Ingrid

in Exploring research frontiers in contemporary statistics and econometrics - A Festschrift for Léopold Simar (2012)

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See detailThe Economic and Statistical Designs of Control charts for Censored and Non-Normal Data
Faraz, Alireza ULg; Heuchenne, Cédric ULg; Davis, Darwin, Edward et al

Scientific conference (2011, December)

In this research, we are dealing with constructing the statistical design (SD) and economic statistical design (ESD) of Shewhart and CUSUM control charts for reliability data which are right censored ... [more ▼]

In this research, we are dealing with constructing the statistical design (SD) and economic statistical design (ESD) of Shewhart and CUSUM control charts for reliability data which are right censored. This is the case which happens more frequently in the field. [less ▲]

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Peer Reviewed
See detailTesting for one-sided alternatives in nonparametric censored regression
Heuchenne, Cédric ULg; Pardo Fernandez, Juan Carlos

Conference (2011, December)

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

Conference (2011, December)

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See detailEstimation of the Error Distribution in a Semiparametric Transformation Model
Heuchenne, Cédric ULg; Samb, Rawane; Van Keilegom, Ingrid

Scientific conference (2011, November 15)

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

Scientific conference (2011, November 09)

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See detailA modified economic-statistical design of the T2 control chart with variable sample sizes and control limits
Seif, A.; Faraz, Alireza ULg; Heuchenne, Cédric ULg et al

in Journal of Applied Statistics (2011), 38(11), 2459-2469

Recent studies have shown that using variable sampling size and control limits (VSSC) schemes result in charts with more statistical power than variable sampling size (VSS) when detecting small to ... [more ▼]

Recent studies have shown that using variable sampling size and control limits (VSSC) schemes result in charts with more statistical power than variable sampling size (VSS) when detecting small to moderate shifts in the process mean vector. This paper presents an economic-statistical design (ESD) of the VSSC T2 control chart using the general model of Lorenzen and Vance [22]. The genetic algorithm approach is then employed to search for the optimal values of the six test parameters of the chart. We then compare the expected cost per unit of time of the optimally designed VSSC chart with optimally designed VSS and FRS (fixed ratio sampling) T2 charts as well as MEWMA charts. [less ▲]

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See detailStatistical Merits and Economic Evaluation of T2 Control Charts with the VSSC Scheme
Seif, Asghar; Moghadam, M.B.; Faraz, Alireza ULg et al

in Arabian Journal for Science and Engineering (2011), 36(7), 1461-1470

T2 control charts are used to monitor a process when more than one quality variable associated with the process is being observed. Recent studies have shown that using variable sampling size (VSS) schemes ... [more ▼]

T2 control charts are used to monitor a process when more than one quality variable associated with the process is being observed. Recent studies have shown that using variable sampling size (VSS) schemes results in charts with more statistical power for detecting small to moderate shifts in the process mean vector. This paper presents an economic-statistical design of T2 control charts with variable sample size and control limits (VSSC). We build a cost model of a VSSC T2 control chart for the purpose of economic-statistical design using the model of Costa and Rahim (J. Appl. Stat. 28:875–885, 2001). This cost model constructed involves the cost of false alarms, the cost of finding and eliminating an assignable cause, the cost associated with production in an out-of-control state, and the cost of sampling and testing. We optimize this model using a genetic algorithm approach. Furthermore, VSSC and VSS T2 charts are compared with respect to the expected cost per unit time. [less ▲]

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See detailMULTIOBJECTIVE DESIGN OF CONTROL CHARTS
Faraz, Alireza ULg; Heuchenne, Cédric ULg

in International Conference on Applied Statistics 2011 : Ljubljana 24-29 September 2011 (2011, September 24)

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See detailMonitoring delivery chains in a supply chain using multivariate control charts
Faraz, Alireza ULg; Heuchenne, Cédric ULg; Saniga, Erwin et al

Conference (2011, July 13)

The theory of the delivery chain considers the delivery of goods and services to customers within a specific time interval. Nowadays, organizations are focusing to satisfy their customers’ demands not ... [more ▼]

The theory of the delivery chain considers the delivery of goods and services to customers within a specific time interval. Nowadays, organizations are focusing to satisfy their customers’ demands not only to meet the expectations for products quality but also in delivery times through managing delivery chains. Obviously it is desirable that a company has minimum delivery time of goods and services to its customers. Therefore, establishing economic and reliable control charts for monitoring the key characteristics of delivery chain is of great importance especially for managers to improve the whole delivery chains performance. On the other hand, as we shall see in the present paper, the performance of a delivery chain is multivariate in nature because customers do not evaluate a delivery performance with a univariate mindset and also there are usually several production and delivery sites, and variety of different methods of transportation of goods and services. In this paper, we propose a relatively new application of the economic statistical design of the multivariate T2 control chart to monitor the delivery chain performance and it is illustrated through a case study in the TNT express mail in Iran. [less ▲]

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See detailError distribution estimation in right censored and selection biased location-scale models
Laurent, Géraldine ULg; Heuchenne, Cédric ULg

Poster (2011, June 23)

Suppose the random vector (X;Y) satis es the regression model Y = m(X)+sigma(X)*epsilon where m(X) = E[Y|X] and sigma²(X) = Var[Y|X] are unknown smooth functions and the error epsilon, with unknown ... [more ▼]

Suppose the random vector (X;Y) satis es the regression model Y = m(X)+sigma(X)*epsilon where m(X) = E[Y|X] and sigma²(X) = Var[Y|X] are unknown smooth functions and the error epsilon, with unknown distribution, is independent of the covariate X. The pair (X;Y) is subject to generalized selection biased and the response to right censoring. We construct a new estimator for the cumulative distribution function of the error epsilon, where the estimators of m(.) and sigma²(.) are obtained by extending the conditional estimation methods introduced in de Uña-Alvarez and Iglesias-Perez (2010). The asymptotic properties of the proposed estimator are established. A bootstrap technique is proposed to select the smoothing parameter involved in the procedure. This method is studied via extended simulations and applied to real unemployment data. Reference de UNA-ALVAREZ, J., IGLESIAS-PEREZ, M.C. (2010): Nonparametric estimation of a conditional distribution from length-biased data. Annals of the Institute of Statistical Mathematics, Vol. 62, 323-341. [less ▲]

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See detailNonparametric regression with parametric selection bias
Heuchenne, Cédric ULg; Laurent, Géraldine ULg

in Proceedings of the 14th Conference of the ASMDA International Society (ASMDA2011) (2011, June)

Detailed reference viewed: 30 (9 ULg)
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See detailTesting for one-sided alternatives in nonparametric censored regression
Heuchenne, Cédric ULg; Pardo Fernandez, J. C.

Scientific conference (2011, February 08)

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See detailLikelihood based inference for semi-competing risks
Heuchenne, Cédric ULg; Legrand, Catherine; Laurent, Stéphane ULg et al

E-print/Working paper (2011)

Detailed reference viewed: 31 (4 ULg)
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See detailEstimating the residual distribution in a semiparametric transformation model.
Heuchenne, Cédric ULg; Samb, Rawane; Van Keilegom, Ingrid

E-print/Working paper (2011)

Detailed reference viewed: 16 (3 ULg)
See detailEstimation of the error density in a semi-parametric transformation model.
Samb, Rawane; Heuchenne, Cédric ULg; Van Keilegom, Ingrid

E-print/Working paper (2011)

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

Poster (2010, October)

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 the covariate X. The pair ... [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 the covariate X. The pair (X;Y) is subject to generalized bias selection and the response to right censoring. We construct a new estimator for the cumulative distribution function of the error Ɛ , where the estimators of m(.) and σ²(.) are obtained by extending the conditional estimation methods introduced in de Uña-Alvarez and Iglesias-Perez (2008). The asymptotic properties of the functions m(.) and σ(.) are obtained. A bootstrap technique is proposed to select the smoothing parameter involved in the procedure. This method is studied via extended simulations and applied to real unemployment data. [less ▲]

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

Conference (2010, August 24)

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 ▲]

Detailed reference viewed: 10 (3 ULg)
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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 ▲]

Detailed reference viewed: 18 (5 ULg)