Grant: Discovery Grants Program - Individual
University of Regina
$15,000.00
""Bootstrap, confidence sets, and asymptotic analysis for some procedures of statistical inference""
FY 2012-13
Summary
Although my research program concerns many different aspects of statistics and probability theory, it revolves around a single theme: asymptotics (expansion of a statistic and/or of a distribution). The research involves the following four main components:
1. A general statement of the interval estimation problem for the ratio of two binomial proportions arising from data coming from two independent samples will be considered. Each sample may be obtained in the framework of direct or inverse binomial sampling. Asymptotic confidence intervals are constructed in accordance with different types of sampling schemes and unbiased estimators of success probabilities and their logarithms will be obtained. The ratio of two binomial proportions arises in prospective studies, in biological experiments, and in the comparison of manufacturing processes for quality control in industry. Statistical procedures for the ratio of binomial proportions (often called the relative risk) are also quite common in clinical trials and epidemiological studies, or more generally in a pharmaceutical setting. Hence we expect that this part of my (mostly theoretical) research will have many significant applications.
2. Asymptotic probability for the deviations of some nonclassical bootstrap U-statistics from the sample U-statistic will be investigated. I am mostly interested in such limit theorems for dependent bootstrap random variables as the law of the single logarithm, the central limit theorem, and the law of large numbers.
3. The construction of a confidence region based on the shrinkage estimator with constant confidence level will be investigated. This will require rectification of formulae for coverage probabilities by confidence sets centered at both James-Stein estimators.
4. Construction of stochastic models for crack development (models related to the Birnbaum-Saunders and Inverse Gaussian distributions) will be investigated. Solutions to the statistical problems of parameter estimation and hypothesis testing for these new models will be provided.
Program
Discovery Grants Program - Individual
Recipient
Location
Saskatchewan, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
261347-2012
Name nom
Volodin, Andrei
Department département
Mathematics and Statistics
Organization id
17
Institution établissement
University of Regina
Province en
Saskatchewan
Province fr
Saskatchewan
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2012
Competition year année de concours
2012
Award amount
15000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
Discovery grants programs
Group fr
Programmes de subventions à la découverte
Committee code
1508
Committee name en
Mathematics and Statistics
Committee name fr
Mathématiques et statistique
Area of application code
1205
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Mathematical sciences
Area of application fr
Sciences mathématiques
Research subject code
3000
Research subject group en
Statistics and probability
Research subject group fr
Statistique et probabilité
Research subject en
Statistics and probability
Research subject fr
Statistique et probabilité
Partie
1
Nb partie
5
Application title
""Bootstrap, confidence sets, and asymptotic analysis for some procedures of statistical inference""
Keyword
NSERC
Application summary
Although my research program concerns many different aspects of statistics and probability theory, it revolves around a single theme: asymptotics (expansion of a statistic and/or of a distribution). The research involves the following four main components:
1. A general statement of the interval estimation problem for the ratio of two binomial proportions arising from data coming from two independent samples will be considered. Each sample may be obtained in the framework of direct or inverse binomial sampling. Asymptotic confidence intervals are constructed in accordance with different types of sampling schemes and unbiased estimators of success probabilities and their logarithms will be obtained. The ratio of two binomial proportions arises in prospective studies, in biological experiments, and in the comparison of manufacturing processes for quality control in industry. Statistical procedures for the ratio of binomial proportions (often called the relative risk) are also quite common in clinical trials and epidemiological studies, or more generally in a pharmaceutical setting. Hence we expect that this part of my (mostly theoretical) research will have many significant applications.
2. Asymptotic probability for the deviations of some nonclassical bootstrap U-statistics from the sample U-statistic will be investigated. I am mostly interested in such limit theorems for dependent bootstrap random variables as the law of the single logarithm, the central limit theorem, and the law of large numbers.
3. The construction of a confidence region based on the shrinkage estimator with constant confidence level will be investigated. This will require rectification of formulae for coverage probabilities by confidence sets centered at both James-Stein estimators.
4. Construction of stochastic models for crack development (models related to the Birnbaum-Saunders and Inverse Gaussian distributions) will be investigated. Solutions to the statistical problems of parameter estimation and hypothesis testing for these new models will be provided.