Minimax Robustness of Bayesian Forecasting under Functional Distortions of Probability Densities

The problems of robustness in Bayesian forecasting are considered under distortions of the hypothetical probability densities. The expressions for the guaranteed upper risk functional are obtained and the robust prediction statistics under certain types of distortions are constructed

On Robustifying of the Sequential Probability Ratio Test for a Discrete Model under “Contaminations”

The problem of robustifying of the sequential probability ratio test is considered for a discrete hypothetical model. Exact values for error probabilities and for conditional expected sample sizes are obtained. Asymptotic robustness analysis for these characteristics is performed under “contaminations”. A two-parametric family of modified sequential probability ratio tests is proposed and analyzed to get the robust test by the minimax risk criterion. Numerical experiments illustrate the theoretical results

Robustness Evaluation in Sequential Testing of Composite Hypotheses

The problem of sequential testing of composite hypotheses is considered. Asymptotic expansions are constructed for the conditional error probabilities and expected sample sizes under “contamination” of the probability distribution of observations. To obtain these results a new approach based on approximation of the generalized likelihood ratio statistic by a specially constructed Markov chain is proposed. The approach is illustrated numerically

Robust Sequential Testing of Hypotheses on Discrete Probability Distributions

The paper is devoted to analysis of approximations of the models in sequential hypotheses testing and to construction of new robust sequential test under the distortions presented by mixtures of probability distributions. The previous results of the authors are extended to the case of arbitrary discrete probability distributions. The theory is illustrated by computer modelling

On Robustifying of the Sequential Probability Ratio Test for a Discrete Model under “Contaminations”

The problem of robustifying of the sequential probability ratio test is considered for a discrete hypothetical model. Exact values for error probabilities and for conditional expected sample sizes are obtained. Asymptotic robustness analysis for these characteristics is performed under “contaminations”. A two-parametric family of modified sequential probability ratio tests is proposed and analyzed to get the robust test by the minimax risk criterion. Numerical experiments illustrate the theoretical results

Robustness Evaluation in Sequential Testing of Composite Hypotheses

The problem of sequential testing of composite hypotheses is considered. Asymptotic expansions are constructed for the conditional error probabilities and expected sample sizes under “contamination” of the probability distribution of observations. To obtain these results a new approach based on approximation of the generalized likelihood ratio statistic by a specially constructed Markov chain is proposed. The approach is illustrated numerically

Minimax Robustness of Bayesian Forecasting under Functional Distortions of Probability Densities

The problems of robustness in Bayesian forecasting are considered under distortions of the hypothetical probability densities. The expressions for the guaranteed upper risk functional are obtained and the robust prediction statistics under certain types of distortions are constructed

An Approach to Robustness Evaluation for Sequential Testing under Functional Distortions in L1-metric

The problem of sensitivity analysis for the sequential probability ratio test under func- tional distortions of the observation probability distribution is considered. For the situa- tion where distorted densities of the log likelihood ratio statistic belong to ?-neighborhoods of hypothetical centers in the L1-metric the least favorable distributions that maximize the conditional error probabilities are constructed. The instability coefficient is obtained to enable robustness evaluation for the sequential probability ratio test and its modification – trimmed sequential probability ratio test

Robust Sequential Testing of Hypotheses on Discrete Probability Distributions

The paper is devoted to analysis of approximations of the models in sequential hypotheses testing and to construction of new robust sequential test under the distortions presented by mixtures of probability distributions. The previous results of the authors are extended to the case of arbitrary discrete probability distributions. The theory is illustrated by computer modelling

Nanodiamonds in Biotechnology: Application for Purification of Proteins and Test-Systems of Indication

Обсуждаются перспективы применения наноалмазов в биотехнологии. На примере очистки рекомбинантной бактериальной люциферазы из экстрактов клеток-продуцентов E. coli показана возможность эффективного выделения белков из сложных белковых смесей с помощью наноалмазов: процесс проводится при минимуме оборудования и затрат времени; позволяет за один технологический цикл получать целевой продукт в препаративных количествах, высокого качества (по данным SDS-электрофореза) и выходом до 40-45 %. Демонстрируется возможность использования наноалмазов в создании систем индикации на примере конструирования биолюминесцентной тест-системы на основе комплекса наноалмаз- люцифераза и инертной полимерной матрицы.This paper discusses the perspectives of applications of the detonation nanodiamonds in biotechnology. An effective separation of proteins from complex protein mixtures by using of nanodiamonds is shown on the example of purification of recombinant luciferase from the extracts of E. coli bacterial cells: the process requires minimum equipment and time; one technological cycle yields 40-45 % of desired product with high-quality (according to the SDS-PAGE). The application of nanodiamonds for design of indicating systems is demonstrated on the example of a biosensor system based on the nanodiamondluciferase complex and inert polymeric matrix