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.

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

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

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

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 ...

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 ...

This course cannot be taken with ST102 Elementary Statistical Theory, ST107 Quantitative Methods (Statistics) or ST108 Statistical Methods for the Social Sciences. The course provides a precise and ...

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), ...