On conditional independence and the relationship between sufficiency and invariance under the Bayesian point of view.
On domination and sufficiency in sequential analysis
On the bilateral truncated exponential distribution.
On the equivalence of invariance and almost-invariance from a Bayesian point of view.
On the factorization criterion for quantum statistics
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.
Optimal estimation of high quantiles in a large nonparametric model
"A high quantile is a quantile of order q with q close to one." A precise constructive definition of high quantiles is given and optimal estimates are presented.