Imagen de Portada

A Heteroscedastic Bayesian Generalized Logistic Regression Model with Application to Scaling Problems

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Sutton, Jack, Shahtahmassebi, Golnaz, Hanley, Quentin S., Ribeiro, Haroldo V.
Formato:	Preprint
Publicado:	2023
Materias:	Methodology
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Nonlinear Rank Scaling and Hidden Structure in NHS Expenditure Transparency Data
por: Mohammed, Animotu, et al.
Publicado: (2025)

Comprehensive indicators and fine granularity refine density scaling laws in rural-urban systems
por: Sutton, Jack, et al.
Publicado: (2025)

Variational Bayesian Logistic Tensor Regression with Application to Image Recognition
por: Jin, Yunzhi, et al.
Publicado: (2025)

Bayesian Multinomial Logistic Regression for Numerous Categories
por: Fisher, Jared D., et al.
Publicado: (2022)

On the Choice of Model Space Priors and Multiplicity Control in Bayesian Variable Selection: An Application to Streaming Logistic Regression
por: Ghosh, Joyee
Publicado: (2025)

An Online Algorithm for Bayesian Variable Selection in Logistic Regression Models With Streaming Data
por: Ghosal, Payel, et al.
Publicado: (2025)

Heteroscedastic Double Bayesian Elastic Net
por: Kimura, Masanari
Publicado: (2025)

A Compound Logistic Regression Model for Binary Responses
por: Almudevar, Anthony, et al.
Publicado: (2026)

A Flexible Empirical Bayes Approach to Generalized Linear Models, with Applications to Sparse Logistic Regression
por: Xie, Dongyue, et al.
Publicado: (2026)

Data-Driven Logistic Regression Ensembles With Applications in Genomics
por: Christidis, Anthony-Alexander, et al.
Publicado: (2021)

Empirical Bayes Method for Large Scale Multiple Testing with Heteroscedastic Errors
por: Seo, Kwangok, et al.
Publicado: (2025)

Conformalized Method for Empirical Bayes Normal Mean Inference Problem with Heteroscedastic Variance
por: Seo, Kwangok, et al.
Publicado: (2026)

Accurate Inference for Penalized Logistic Regression
por: Zhang, Yuming, et al.
Publicado: (2024)

Fully Bayesian Sequential Design for Mean Response Surface Prediction of Heteroscedastic Stochastic Simulations
por: Huang, Yuying, et al.
Publicado: (2025)

Logistic Regression Model for Differentially-Private Matrix Masked Data
por: Nghiem, Linh H, et al.
Publicado: (2024)

Comparing Variable Selection and Model Averaging Methods for Logistic Regression
por: Sekulovski, Nikola, et al.
Publicado: (2025)

H-AddiVortes: Heteroscedastic (Bayesian) Additive Voronoi Tessellations
por: Stone, Adam J., et al.
Publicado: (2025)

Bayesian Penalized Transformation Models: Structured Additive Location-Scale Regression for Arbitrary Conditional Distributions
por: Brachem, Johannes, et al.
Publicado: (2024)

Partial Ordering Bayesian Logistic Regression Model for Phase I Combination Trials and Computationally Efficient Approach to Operational Prior Specification
por: Chen, Weishi, et al.
Publicado: (2024)

Gender shapes the relationship between productivity and journal prestige in science
por: Ribeiro, Vitor H., et al.
Publicado: (2026)

Heteroscedastic Growth Curve Modeling with Shape-Restricted Splines
por: Jiao, Jieying, et al.
Publicado: (2025)

F-measure Maximizing Logistic Regression
por: Okabe, Masaaki, et al.
Publicado: (2019)

Valid Bayesian Inference based on Variance Weighted Projection for High-Dimensional Logistic Regression with Binary Covariates
por: Ojha, Abhishek, et al.
Publicado: (2024)

A Goodness-of-Fit Test for Mixed-Effects Logistic Regression
por: Linden, Ariel
Publicado: (2026)

Robust Functional Logistic Regression
por: Akturk, Berkay, et al.
Publicado: (2025)

Heteroscedasticity-aware stratified sampling to improve uplift modeling
por: Bokelmann, Björn, et al.
Publicado: (2024)

Prevalence estimation in infectious diseases with imperfect tests: A comparison of Frequentist and Bayesian Logistic Regression methods with misclassification correction
por: Alvarez, Jorge Mario Estrada, et al.
Publicado: (2025)

Generalized Bayesian Multidimensional Scaling and Model Comparison
por: Zhang, Jiarui, et al.
Publicado: (2023)

Estimating Conditional Average Treatment Effects with Heteroscedasticity by Model Averaging and Matching
por: Shi, Pengfei, et al.
Publicado: (2023)

Enhancing reliability in prediction intervals using point forecasters: Heteroscedastic Quantile Regression and Width-Adaptive Conformal Inference
por: Sebastián, Carlos, et al.
Publicado: (2024)

Improved Conditional Logistic Regression using Information in Concordant Pairs with Software
por: Tennenbaum, Jacob, et al.
Publicado: (2026)

On the Stability of General Bayesian Inference
por: Jewson, Jack, et al.
Publicado: (2023)

Generalized Geographically Weighted Regression Model within a Modularized Bayesian Framework
por: Liu, Yang, et al.
Publicado: (2021)

A New Look at the Odds Ratio in Logistic Regression
por: Martínez, José Raúl
Publicado: (2025)

Robust Liu-Type Estimation for Multicollinearity in Fuzzy Logistic Regression
por: Shemail, Ayad Habib, et al.
Publicado: (2025)

Age-Specific Logistic Regression with Complex Event Time Data
por: Haoxuan, et al.
Publicado: (2026)

Variance-Aware Estimation and Inference for Michaelis--Menten Models with Heteroscedastic Errors and Clustered Measurements
por: Kim, Mijeong, et al.
Publicado: (2026)

An Accurate Standard Error Estimation for Quadratic Exponential Logistic Regressions by Applying Generalized Estimating Equations to Pseudo-Likelihoods
por: Yong, Ong Wei, et al.
Publicado: (2025)

High Dimensional Logistic Regression Under Network Dependence
por: Mukherjee, Somabha, et al.
Publicado: (2021)

Zero-Inflated Logistic Regression Models with Shared Design: Identifiability, Existence of Estimates, and a Relabeling Rule
por: Tomo, Yui, et al.
Publicado: (2026)