Statistics

A look into analyzing patient survival data in clinical research.

A look at how the Makeham model analyzes death rates and risks.

Introducing advanced models for classifying positive and unlabeled data across various fields.

New models improve the detection of sensor issues in river water quality monitoring.

This article discusses efforts to improve school diversity through informed outreach.

Explore a new method for analyzing treatment effects over time.

Examining biases in air quality monitoring and their implications for public health.

Analyzing trends in speedrunning and machine learning reveals insights into record improvements.

A new method to analyze time series data from a frequency perspective.

Introducing a method for better estimation of rare event probabilities.

Exploring Bayesian inverse problems and their impact across multiple fields.

Learn how the hset package simplifies data collection and management in R.

A new method improves selection of data columns for better analysis.

New methods enhance speed and accuracy in analyzing health-related datasets.

Explore how depth functions enhance statistical analysis and understanding of data distributions.

A new method enhances the accuracy of two-sample testing amidst hidden differences.

TiDE combines simplicity and effectiveness for long-term time-series forecasting.

This paper discusses the difficulties in defining learnability for different probability distributions.

New methods enhance probabilistic circuits for better predictions and causal inference.

Sharp-SSL improves classification by efficiently selecting important features in semi-supervised learning.

Learn how Bayes Hilbert spaces improve Bayesian statistics with large datasets.

The adaptive Lasso improves data analysis by managing outliers and providing reliable estimates.

A look into better ways to estimate cross-correlation.

A new method enhances joint probability density estimation with lower-dimensional data.

A new statistical method offers better insights into treatment effects with multiple covariates.

A new method improves experimental design for complex systems with mixed responses.

Learn how uniform-block structures simplify data analysis and enhance insights.

Neural networks offer faster and flexible malaria case predictions.

A look into analyzing patient survival data in clinical research.

A concise guide to Bayesian Networks and the capabilities of pgmpy.

A novel approach improves analysis of health treatment impacts using observational data.

Introducing advanced models for classifying positive and unlabeled data across various fields.

Explore a new method for analyzing treatment effects over time.

Researchers combine data and strategies for better NBA predictions.

Analyzing the accuracy of health data during the COVID-19 pandemic.

Lockdowns led to higher deaths and costs in breast cancer treatment.

A practical guide to the Saltbox-Roof Probability Distribution and its applications.

Research examines how local interactions can simplify complex systems using image data.

This article explores interventional probability distributions and their role in causality.

How too many measurements can mislead safety in projects.

Caliper matching improves comparisons in research, reducing bias in treatment effect estimates.

Introducing advanced models for classifying positive and unlabeled data across various fields.

Sharp-SSL improves classification by efficiently selecting important features in semi-supervised learning.

Learn how Bayes Hilbert spaces improve Bayesian statistics with large datasets.

Examining how organisms make decisions amid uncertainty and risk.

A deep dive into sample complexity and its implications for machine learning predictions.

A look at estimating data distributions affected by noise.

Explore the skew-normal distribution and its use in data analysis.