The skew-Laplace distribution has been used for modelling particle size with point observations. In reality, the observations are truncated and grouped (rounded). This must be formally taken into account for accurate modelling, and it is shown how this leads to convenient closed-form expressions for the likelihood in this model. In a Bayesian framework, “noninformative” benchmark priors, which ...

AMS 2000 subject classifications: primary 62G07 secondary 62G20 a b s t r a c t In this paper we derive rates of uniform strong convergence for the kernel estimator of the regression function in a left-truncation model. It is assumed that the lifetime observations with multivariate covariates form a stationary α-mixing sequence. The estimation of the covariate's density is considered as well. U...

Ben T. Hirsch*, Marco D. Visser, Roland Kays and Patrick A. Jansen New York State Museum, 3140 CEC, Albany, NY 12230, USA; Smithsonian Tropical Research Institute, Unit 9100, Box 0948, DPO AA 34002-9898, USA; Department of Experimental Plant Ecology, Radboud University Nijmegen, Heyendaalseweg 135, 6525 AJ Nijmegen, The Netherlands; Centre for Ecosystem Studies, Wageningen University and Resear...

We obtain maximum likelihood estimates of the parameters when the observations on the response variable in a repeated measures design are truncated above a cutpoint. The maximum likelihood equations are solved iteratively using an EM-like procedure. It is observed that these estimates have smaller mean squared error than recently proposed iterative weighted least-squares estimates. The results ...

This thesis centers on nonparametric inferences of the cumulative hazard function of a right truncated variable. We present three variance estimators for the Nelson-Aalen estimator of the cumulative hazard function and conduct a simulation study to investigate their performances. A close match between the sampling standard deviation and the estimated standard error is observed when an estimated...

This work develops an estimator for the bivariate density given a sample of data truncated to a non-rectangular region. Such inference problems occur in various fields; the motivating application here was a problem in astronomy. The approach is semiparametric, combining a nonparametric local likelihood density estimator with a simple parametric form to account for the dependence of the two rand...

Sample selection bias has long been recognized in many fields including clinical trials, epidemiology studies, genome-wide association studies, and wildlife management. This paper investigates the maximum likelihood estimation for censored survival data with selection bias under the Cox regression models where the selection process is modeled parametrically. A novel expectation-maximization alg...

Tensor–product B–spline surfaces are commonly used as standard modeling tool in Computer Aided Geometric Design and for numerical simulation in Isogeometric Analysis. However, when considering tensor–product grids, there is no possibility of a localized mesh refinement without propagation of the refinement outside the region of interest. The recently introduced truncated hierarchical B–splines ...

A truncated sample consists of realizations of a pair of random variables (L, T) subject to the constraint that L ≤T. The major study interest with a truncated sample is to find the marginal distributions of L and T. Many studies have been done with the assumption that L and T are independent. We introduce a new way to specify a Cox model for a truncated sample, assuming that the truncation tim...