On the translated exponential model with censoring.
On the two-sided multiparameter control
On the two-sided quality control
Let the random variable have the normal distribution . Explicit formulas for maximum likelihood estimator of are derived under the hypotheses , where are arbitrary fixed numbers. Asymptotic distribution of the likelihood ratio statistic for testing this hypothesis is derived and some of its quantiles are presented.
On the uniqueness of the M. L. estimates in curved exponential families
On the Variance of the Ratio Estimator.
On unbiased Lehmann-estimators of a variance of an exponential distribution with quadratic loss function.
Lehmann in [4] has generalised the notion of the unbiased estimator with respect to the assumed loss function. In [5] Singh considered admissible estimators of function λ-r of unknown parameter λ of gamma distribution with density f(x|λ, b) = λb-1 e-λx xb-1 / Γ(b), x>0, where b is a known parameter, for loss function L(λ-r, λ-r) = (λ-r - λ-r)2 / λ-2r.Goodman in [1] choosing three loss functions of different shape found unbiased Lehmann-estimators, of the variance σ2 of the normal distribution....
On Uniformly Minimum Variance Unbiased Estimation when no Complete Sufficient Statistics Exist.
On variance of the two-stage estimator in variance-covariance components model
The paper deals with a linear model with linear variance-covariance structure, where the linear function of the parameter of expectation is to be estimated. The two-stage estimator is based on the observation of the vector and on the invariant quadratic estimator of the variance-covariance components. Under the assumption of symmetry of the distribution and existence of finite moments up to the tenth order, an approach to determining the upper bound for the difference in variances of the estimators...
On variance-covariance components estimation in linear models with AR(1) disturbances.
On Weak Convergence of Parameter Estimators of General Statistical Parametric Models
One of the calibration problems
One sample tests for the location of modes of nonnormal data.
One-sided approximation of Bayes rule and its application to regression model with Cauchy noise
Optimal alternative robustness in Bayesian Decision Theory.
In Martin et al (2003), we suggested an approach to general robustness studies in Bayesian Decision Theory and Inference, based on ε-contamination neighborhoods. In this note, we generalise the results considering neighborhoods based on norms, specifically, the supremum norm for utilities and the total variation norm for probability distributions. We provide tools to detect changes in preferences between alternatives under perturbations of the prior and/or the utility and the most sensitive direction....
Optimal elimination of nuisance parameters in mixed linear models
Optimal estimators for threshold-based quality measures.
Optimal L_p approximation techniques and data analysis
Optimal mean-variance robust hedging under asset price model misspecification.
Optimal sequential multiple hypothesis tests
This work deals with a general problem of testing multiple hypotheses about the distribution of a discrete-time stochastic process. Both the Bayesian and the conditional settings are considered. The structure of optimal sequential tests is characterized.
Optimal Tests and Estimators for Truncated Exponential Families.