Fixed precision estimation of the parameters of a linear regression model with unknown covariance structure
Fixed-width confidence interval for a lognormal mean.
Further Developments in Estimation of the Largest Mean of K Normal Populations.
Information inequalities for the minimax risk of sequential estimators (with applications)
Information inequalities for the minimax risk of sequential estimators are derived in the case where the loss is measured by the squared error of estimation plus a linear functional of the number of observations. The results are applied to construct minimax sequential estimators of: the failure rate in an exponential model with censored data, the expected proportion of uncensored observations in the proportional hazards model, the odds ratio in a binomial distribution and the expectation of exponential...
Minimax and Bayes estimation when the loss function is unknown
Minimax sequential estimation for the multinomial and gamma processes
Minimax sequential estimation of parameters of random fields
Minimum variance importance sampling via Population Monte Carlo
Variance reduction has always been a central issue in Monte Carlo experiments. Population Monte Carlo can be used to this effect, in that a mixture of importance functions, called a D-kernel, can be iteratively optimized to achieve the minimum asymptotic variance for a function of interest among all possible mixtures. The implementation of this iterative scheme is illustrated for the computation of the price of a European option in the Cox-Ingersoll-Ross model. A Central Limit theorem as well...
Multi-Stage Point and Interval Estimation of the Largest Mean of K Normal Populations and the Associated Second-Order Properties.
Notes on dependence with complete connections
On calculating the Laplace transform of a special quadratic functional of the Ornstein-Uhlenbeck velocity process
On Estimating the Reliability After Sequentially Estimating the Mean: The Exponential Case.
On minimax sequential estimation of the mean value of a stationary Gaussian Markov process
On minimax sequential procedures for exponential families of stochastic processes
The problem of finding minimax sequential estimation procedures for stochastic processes is considered. It is assumed that in addition to the loss associated with the error of estimation a cost of observing the process is incurred. A class of minimax sequential procedures is derived explicitly for a one-parameter exponential family of stochastic processes. The minimax sequential procedures are presented in some special models, in particular, for estimating a parameter of exponential families of...
On sequential and fixed designs for estimation with comparisons and applications.
A fully sequential approach to the estimation of the difference of two population means for distributions belonging to the exponential family of distributions is adopted and compared with the best fixed design. Results on the lower bound for the Bayes risk due to estimation and expected costs are presented and shown to be of first order efficiency. Applications involving the Poisson and exponential distributions with gamma priors as well as the Bernouilli distribution with beta priors are given....
On Sequential Comparisons of Means of First-Order Autoregressive Models.
On sequential minimax estimation for the exponential class of processes
On the approximation of some optimal sequential plan
On the Asymptotic Behaviour of Linear Learning Processes with Partial Forgetting.
On the inequality of Cramér-Rao type in sequential estimation theory