Latest Articles for Statistical Modeling

Learn how to manage workforce stability through advanced modeling techniques.

Learn how regularization shapes predictions in machine learning through Empirical Risk Minimization.

GLMMcosinor offers flexible modeling for studying complex biological rhythms.

Research on clustering methods improves understanding of extreme climate interactions.

This article discusses a model for analyzing extreme weather and angular components.

Exploring methods for solving inverse problems in 3D printing.

Research compares NLME model approaches for drug effect estimation.

This study reveals how SGD can enhance Gaussian Processes for better predictions.

Researchers use mobile data and advanced models to analyze human movement patterns over time.

A guide to estimating Gaussian mixture densities effectively.

New technique improves inference for latent Gaussian models with complex data.

A new method enhances classification of body fluids for criminal investigations.

New insights improve predictive performance in statistical modeling.

Exploring the role of measurement error models in biological data interpretation.

A look at Bayesian structure learning and its role across various fields.

This article examines tumor-immune interactions using mathematical models and Allee effects.

This framework aids users in applying Gaussian Processes effectively for predictive modeling.

This study introduces a new method to analyze sparse economic networks.

This article examines overfitting issues in shallow ReLU networks with noisy data.

This study analyzes how the pandemic affected various causes of death in Italy.

This study evaluates how statFEM handles errors in complex models.

New methods for learning GMMs enhance accuracy and stability using Cramer type distances.

Learn about improved methods for uncertainty estimates in Gaussian process regression.

Methods to improve estimation accuracy in large data sets.

A look at how Variational Prediction simplifies Bayesian methods.

Learn how NSBM helps analyze unlabeled networks and detect communities effectively.

A new method enhances hyperparameter optimization efficiency in machine learning.

Utilizing transformers enhances Bayesian optimization across diverse datasets.

A new approach to analyze count time series and forecast future trends.

A look into the random walk Metropolis-Hastings algorithm for statistical sampling.

A new method improves prediction accuracy for insurance claims and costs.

New methods enhance accuracy in predicting financial price movements and option pricing.

EDICT enhances predictions for data collected at uneven intervals, improving decision-making.

Exploring the potential of Natural Evolution Strategies in variational inference models.

Identifiability and falsifiability are crucial in Bayesian model growth.

New algorithms improve accuracy in detecting overlapping communities in networks.

A study using dynamic models to analyze flood probabilities in the Taquari River.

A guide to analyzing complex data using Bayesian dependent mixture models.

This study examines how changes in cycles affect information mixing speed.

A study on estimating R(t) and r(t) from ONS data during the pandemic.