The HiDimStat package provides statistical inference methods to solve the problem of variable importance evaluation in the context of predictive model using high ...

Multivariate statistical inference encompasses methods that evaluate multiple outcomes or parameters jointly, allowing researchers to understand complex interdependencies within data. Permutation ...

Statistical learning (SL) is a fundamental cognitive ability enabling individuals to detect and exploit regularities in environmental input. It plays a crucial role in language acquisition, perceptual ...

Howard Lutnick, the commerce secretary, suggested government spending should be excluded from data about U.S. economic output. By Ben Casselman and Colby Smith Comments from a member of President ...

ABSTRACT: Singh, Gewali, and Khatiwada proposed a skewness measure for probability distributions called Area Skewness (AS), which has desirable properties but has not been widely applied in practice.

ABSTRACT: This study investigates the application of the two-parameter Weibull distribution in modeling state holding times within HIV/AIDS progression dynamics. By comparing the performance of the ...

Machine learning is increasingly used as an efficient substitute for traditional data collection when the latter is challenging. For example, predictions of conditions such as poverty, deforestation, ...

This repository contains the R code accompanying the paper "Simultaneous Statistical Inference for Off-Policy Evaluation in Reinforcement Learning" ([https://neurips ...

Mitchell Grant is a self-taught investor with over 5 years of experience as a financial trader. He is a financial content strategist and creative content editor. Timothy Li is a consultant, accountant ...