Nature

Empirical Likelihood Methods in Statistical Inference

Empirical likelihood methods have emerged as a robust, non‐parametric framework for statistical inference that skilfully bypasses the need for strong parametric assumptions. By constructing likelihood ...
JSTOR Daily

Inference From Stratified Samples: Properties of the Linearization, Jackknife and Balanced Repeated Replication Methods

The asymptotic normality of both linear and nonlinear statistics and the consistency of the variance estimators obtained using the linearization, jackknife and balanced repeated replication (BRR) ...
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Mastering the Basics: The Fundamentals of Statistics and Inference

Statistics is a branch of math that involves the collection, description, analysis, and inference of conclusions from quantitative data. But what is a statistic? Let’s find out. The word statistic is ...
JSTOR Daily

Bayesian Inference in Hidden Markov Models through the Reversible Jump Markov Chain Monte Carlo Method

Journal of the Royal Statistical Society. Series B (Statistical Methodology), Vol. 62, No. 1 (2000), pp. 57-75 (19 pages) Hidden Markov models form an extension of mixture models which provides a ...
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HKU Ecologist applied a novel statistical method to analysing causal inference and revealed importance of climate change in controlling deep-sea biodiversity

Which of temperature or food is more important for the richness of deep-sea animals? Dr Moriaki YASUHARA from the School of Biological Sciences, the Research Division for Ecology & Biodiversity, and ...