Numerical experiments with least squares spline estimators in a parametric regression model.
Objective Bayesian point and region estimation in location-scale models.
Point and region estimation may both be described as specific decision problems. In point estimation, the action space is the set of possible values of the quantity on interest; in region estimation, the action space is the set of its possible credible regions. Foundations dictate that the solution to these decision problems must depend on both the utility function and the prior distribution. Estimators intended for general use should surely be invariant under one-to-one transformations, and this...
On a bivariate Poisson-geometric distribution
On a family of bayesian estimators and predictors for a Gumbel model based on the kth lower records
Bayesian estimation for the two parameters of a Gumbel distribution are obtained based on kth lower record values. Prediction, either point or interval, for future kth lower record values is also presented from a Bayesian view point. Some of the results of [4] can be obtained as special cases of our results (k=1).
On a generalization of the orthogonal regression
On a trivariate Poisson distribution
A four parameter trivariate Poisson distribution is considered. Recurrences for the probabilities and the partial derivatives of the probabilities with respect to the parameters are derived. Solutions of the maximum likelihood equations are obtaired and the determinant of their asymptotic covariance matrix is given. Applications of the maximum likelihood estimation technique to simulated data sets are also examined.
On admissibility of linear estimators in models with finitely generated parameter space
The paper refers to the research on the characterization of admissible estimators initiated by Cohen [2]. In our paper it is proved that for linear models with finitely generated parameter space the limit of a sequence of the unique locally best linear estimators is admissible. This result is used to give a characterization of admissible linear estimators of fixed and random effects in a random linear model for spatially located sensors measuring intensity of a source of signals in discrete instants...
On an accuracy of change points
On an estimation problem for type I censored spatial Poisson processes
In this paper we consider the problem of estimating the intensity of a spatial homogeneous Poisson process if a part of the observations (quadrat counts) is censored. The actual problem has occurred during a court case when one of the authors was a referee for the defense.
On asymptotics of the maximum likelihood scale invariant estimator of the shape parameter of the gamma distribution
The maximum likelihood scale invariant estimator of the shape parameter of the gamma distribution, proposed by the authors [Statist. Probab. Lett. 78 (2008)], is considered. The asymptotics of the mean square error of this estimator, with respect to that of the usual maximum likelihood estimator, is established.
On Bayesian estimation in an exponential distribution under random censorship
The paper gives some basic ideas of both the construction and investigation of the properties of the Bayesian estimates of certain parametric functions of the parent exponential distribution under the model of random censorship assuming the Koziol–Green model. Various prior distributions are investigated and the corresponding estimates are derived. The stress is put on the asymptotic properties of the estimates with the particular stress on the Bayesian risk. Small sample properties are studied...
On consistency of the MLE
On consistent -estimators: Tuning constants, unimodality and breakdown
On estimable and locally-estimable functions in the non-linear regression model
On estimating error concentration parameter for circular functional model.
On estimating the diffusion coefficient : parametric versus nonparametric
On Estimating the Variance of a Generalized Laplace.
On estimation of parameters in linear models
On estimation of reliability in the exponential case
On -estimators viewed as -estimators