Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered considerable interest among researchers. The debate around the use of machine ...
It sounds like a procurement decision: pick a frontier LLM, standardize, negotiate pricing, and scale rollout. But in 2026, that mindset quietly breaks—because the enterprise problem is no longer ...
Coursework, Stata code, and notes for PBHS 32700: Biostatistical Methods (Spring 2024, University of Chicago). Topics include contingency tables, logistic regression, Poisson and negative binomial ...
The recent release of the rcssci R package represents a significant advancement in the way researchers visualize and analyze complex relationships between continuous variables and their outcomes. The ...
Based on the compounding mechanism, a unique discrete probability distribution is investigated in this paper. The Poisson distribution is mixed with a lifetime model called as the Fav-Jerry model. The ...
This is the seventh in a series of lecture notes which, if tied together into a textbook, might be entitled “Practical Regression.” The purpose of the notes is to supplement the theoretical content of ...
Objective: To estimate the association between exposure to particulate matter with less than 10u of aerodynamic diameter (PM 10) and hospital admissions due to acute respiratory diseases in children.
Abstract: This article examines the use of count data models to predict the number of tourists visiting Thailand’s national parks. The dataset, encompassing observations from 2016 to 2022 across 146 ...
Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demo of Poisson regression, where the goal is to predict a count of things arriving, such as the number of telephone calls ...
The Poisson distribution is widely used in artificial intelligence (AI) and machine learning. In Bayesian inference, probability distributions often help solve problems that would otherwise be ...
Abstract: Assumptions play a pivotal role in the selection and efficacy of statistical models, as unmet assumptions can lead to flawed conclusions and impact decision-making. In both traditional ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results