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Lopuhaä, H.P. (author)A unified approach is provided for a method of estimation of the regression parameter in balanced linear models with a structured covariance matrix that combines a high breakdown point with high asymptotic efficiency at models with multivariate normal errors. Of main interest are linear mixed effects models, but our approach also includes...journal article 2023
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Lopuhaä, H.P. (author), Gares, Valerie (author), RuizGazen, Anne (author)We provide a unified approach to Sestimation in balanced linear models with structured covariance matrices. Of main interest are Sestimators for linear mixed effects models, but our approach also includes Sestimators in several other standard multivariate models, such as multiple regression, multivariate regression and multivariate...journal article 2023
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Lopuhaä, H.P. (author), Musta, E. (author)We investigate the asymptotic behavior of the Lpdistance between<br/>a monotone function on a compact interval and a smooth estimator<br/>of this function. Our main result is a central limit theorem for the Lperror<br/>of smooth isotonic estimators obtained by smoothing a Grenandertype<br/>estimator or isotonizing the ordinary kernel...journal article 2019
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Lopuhaä, H.P. (author), Musta, E. (author)We consider Grenandertype estimators for a monotone function (Formula presented.), obtained as the slope of a concave (convex) estimate of the primitive of λ. Our main result is a central limit theorem for the Hellinger loss, which applies to estimation of a probability density, a regression function or a failure rate. In the case of density...journal article 2018
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Lopuhaä, H.P. (author), Musta, E. (author)We consider the smoothed maximum likelihood estimator and the smoothed Grenandertype estimator for a monotone baseline hazard rate 0 in the Cox model. We analyze their asymptotic behaviour and show that they are asymptotically normal at rate nm=.2mC1/, when 0 is m 2 times continuously differentiable, and that both estimators are...journal article 2018
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Boistard, H. (author), Lopuhää, H.P. (author), RuizGazen, A. (author)This paper is devoted to rejective sampling. We provide an expansion of joint inclusion probabilities of any order in terms of the inclusion probabilities of order one, extending previous results by Hájek (1964) and Hájek (1981) and making the remainder term more precise. Following Hájek (1981), the proof is based on Edgeworth expansions. The...journal article 2012
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 Durot, C. (author), Kulikov, V.N. (author), Lopuhaä, H.P. (author) journal article 2012
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Ruchjana, B.N. (author), Borovkova, S.A. (author), Lopuhaa, H.P. (author)In this paper we studied a least squares estimation parameters of the Generalized Space Time AutoRegressive (GSTAR) model and its properties, especially in consistency and asymptotic normality. We use R software to estimate the GSTAR parameter and apply the model toward real phenomena of data, such as an oil production data at volcanic layer.conference paper 2011
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Kulikov, V.N. (author), Lopuhaä, H.P. (author)We investigate the distribution of some global measures of deviation between the empirical distribution function and its least concave majorant. In the case that the underlying distribution has a strictly decreasing density, we prove asymptotic normality for several L k type distances. In the case of a uniform distribution, we also establish...journal article 2007
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 Cator, E.A. (author), Jongbloed, G. (author), Kraaikamp, C. (author), Wellner, J.A. (author), Lopuhaä, H.P. (author) book 2007
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 Kulikov, V.N. (author), Lopuhaa, H.P. (author) journal article 2006
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Kulikov, V.N. (author), Lopuhaa, H.P. (author)We investigate the limit behavior of the Lkdistance between a decreasing density f and its nonparametric maximum likelihood estimator fn for k ? 1. Due to the inconsistency of fn at zero, the case k = 2.5 turns out to be a kind of transition point.We extend asymptotic normality of the L1distance to the Lkdistance for 1 ? k < 2.5, and...journal article 2005
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De Wolf, P.P. (author), Lopuhaa, H.P. (author), Groeneboom, P. (author)A large part of the theory of extreme value index estimation is developed for positive extreme value indices. The bestknown estimator of a positive extreme value index is probably the Hill estimator. This estimator belongs to the category of moment estimators, but can also be interpreted as a quasimaximum likelihood estimator. It has been...journal article 2003
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Goverde, R.M.P. (author), Hansen, I.A. (author), Hooghiemstra, G. (author), Lopuhaa, H.P. (author)The estimation of the precise arrival and departure times of trains at stations is done by means of a software tool that extracts the occupation and clearance times of each train per track section of the Dutch Railways‘ network. The software tool was applied to the whole automatically collected set of signal data of the area of Eindhoven during...conference paper 2001
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Lopuhaa, H.P. (author)We investigate the asymptotic behavior ofa weighted sample mean and covariance, where the weights are determined by the Mahalanobis distances with respect to initial robust estimators. We derive an explicit expansion for the weighted estimators. From this expansion it can be seen that reweighting does not improve the rate ofconvergence ofthe...journal article 1999
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Lopuhaa, H.P. (author)We propose an affine equivariant estimator of multivariate location that combines a high breakdown point and a bounded influence function with high asymptotic efficiency. This proposal is basically a location $M$estimator based on the observations obtained after scaling with an affine equivariant high breakdown covariance estimator. The...journal article 1991
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 Lopuhaä, H.P. (author) doctoral thesis 1990
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Lopuhaa, H.P. (author), Rousseeuw, P.J. (author)Finitesample replacement breakdown points are derived for different types of estimators of multivariate location and covariance matrices. The role of various equivariance properties is illustrated. The breakdown point is related to a measure of performance based on large deviations probabilities. Finally, we show that onestep reweighting...journal article 1989
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Lopuhaa, H.P. (author)We discuss the relation between Sestimators and Mestimators of multivariate location and covariance. As in the case of the estimation of a multiple regression parameter, Sestimators are shown to satisfy firstorder conditions of Mestimators. We show that the influence function IF (x;S F) of Sfunctionals exists and is the same as that of...journal article 1989