In the presence of covariate measurement error, there has been extensive interest in developing estimation methods for parameters associated with various survival ...

We introduce novel regression extrapolation based methods to correct the often large bias in subsampling variance estimation as well as hypothesis testing for spatial point and marked point processes.

Description: Introductory statistical methods, with emphasis on applications in biology. Topics include descriptive statistics, binomial and normal distributions, confidence interval estimation, ...

This comprehensive course bridges the gap between foundational statistical reasoning and practical applications related to business and engineering decision-making. Throughout the course, we’ll ...

Introduces exploratory data analysis, probability theory, statistical inference, and data modeling. Topics include discrete and continuous probability distributions, expectation, laws of large numbers ...

Generally, the use of ordinary missing data estimation, the UNTIE transformation, and the UNTIE= a-option should be avoided, particularly with hypothesis tests. With these options, parameters are ...

The purpose of this paper is to examine whether the efficiency structure hypothesis holds true for major Japanese commercial banks. The efficiency structure hypothesis, developed by Demesetz (1973), ...

This course is available to General Course ‘Spring Semester’ students conditional on having studied Michaelmas term content remotely. Note ST102 is part-examined in January. The course provides a ...