In the Big Data era, many scientific and engineering domains are producing massive data streams, with petabyte and exabyte scales becoming increasingly common. Besides the explosive growth in volume, ...

Approaches for statistical inference -- The Bayes approach -- Bayesian computation -- Model criticism and selection -- The empirical Bayes approach -- Bayesian design -- Special methods and models -- ...

Articulate the primary interpretations of probability theory and the role these interpretations play in Bayesian inference Use Bayesian inference to solve real-world statistics and data science ...

Longitudinal data analysis is an essential statistical approach for studying phenomena observed repeatedly over time, allowing researchers to explore both within-subject and between-subject variations ...

Scientists have developed a method to identify symmetries in multi-dimensional data using Bayesian statistical techniques. Bayesian statistics has been in the spotlight in recent years due to ...

Journal of the Royal Statistical Society. Series B (Statistical Methodology), Vol. 67, No. 2 (2005), pp. 219-234 (16 pages) Precise classification of tumours is critical for the diagnosis and ...

A frequently used experimental design is one in which the experimental units are measured twice (e. g., under different test conditions). When the response variable is dichotomous, the equality of the ...

We review Bayesian and Bayesian decision theoretic approaches to subgroup analysis and applications to subgroup-based adaptive clinical trial designs. Subgroup analysis refers to inference about ...

Cobimetinib Plus Vemurafenib in Patients With Colorectal Cancer With BRAF Mutations: Results From the Targeted Agent and Profiling Utilization Registry (TAPUR) Study We divided the borrowing ...

Symmetries in nature make things beautiful; symmetries in data make data handling efficient. However, the complexity of identifying such patterns in data has always bedeviled researchers. Scientists ...