Copertina

A general, flexible and harmonious framework to construct interpretable functions in regression analysis

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Zhan, Tianyu, Kang, Jian
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Methodology
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Deep Neural Networks Guided Ensemble Learning for Point Estimation
di: Zhan, Tianyu, et al.
Pubblicazione: (2021)

Subgroup learning in functional regression models under the RKHS framework
di: Guan, Xin, et al.
Pubblicazione: (2025)

Predictive variational inference for flexible regression models
di: Kock, Lucas, et al.
Pubblicazione: (2026)

Quantile regression with generalized multiquadric loss function
di: Gao, Wenwu, et al.
Pubblicazione: (2025)

A Class of Computational Methods to Reduce Selection Bias when Designing Phase 3 Clinical Trials
di: Zhan, Tianyu
Pubblicazione: (2023)

Estimands and cumulative incidence function regression in clinical trials: some new results on interpretability and robustness
di: Bühler, Alexandra, et al.
Pubblicazione: (2024)

Ordinal regression for meta-analysis of test accuracy: a flexible approach for utilising all threshold data
di: Cerullo, Enzo, et al.
Pubblicazione: (2025)

A more interpretable regression model for count data with excess of zeros
di: Pereira, Gustavo H. A., et al.
Pubblicazione: (2025)

A flexible empirical Bayes approach to multiple linear regression and connections with penalized regression
di: Kim, Youngseok, et al.
Pubblicazione: (2022)

A flexible and interpretable spatial covariance model for data on graphs
di: Christensen, Michael F., et al.
Pubblicazione: (2022)

Change-plane analysis in functional response quantile regression
di: Guan, Xin, et al.
Pubblicazione: (2025)

Marginally interpretable spatial logistic regression with bridge processes
di: Lee, Changwoo J., et al.
Pubblicazione: (2024)

A Bayesian regression framework for circular models with INLA
di: Ye, Xiang, et al.
Pubblicazione: (2026)

A graphical framework for interpretable correlation matrix models
di: Sterrantino, Anna Freni, et al.
Pubblicazione: (2023)

A framework for interpretation and testing of sparse canonical correlations
di: Senar, Nuria, et al.
Pubblicazione: (2023)

Climate change analysis from LRD manifold functional regression
di: Ovalle-Muñoz, Diana P., et al.
Pubblicazione: (2024)

Bayesian compositional regression with flexible microbiome feature aggregation and selection
di: Saha, Satabdi, et al.
Pubblicazione: (2024)

Bayesian network-guided sparse regression with flexible varying effects
di: Ren, Yangfan, et al.
Pubblicazione: (2024)

Scalable regression calibration approaches to correcting measurement error in multi-level generalized functional linear regression models with heteroscedastic measurement errors
di: Luan, Yuanyuan, et al.
Pubblicazione: (2023)

Bayesian inference for group-level cortical surface image-on-scalar-regression with Gaussian process priors
di: Whiteman, Andrew S., et al.
Pubblicazione: (2023)

A general nonparametric framework for testing hypotheses about function-valued parameters
di: Osom, Albert, et al.
Pubblicazione: (2026)

Extremile scalar-on-function regression
di: Battagliola, Maria Laura, et al.
Pubblicazione: (2024)

Semiparametric Weighted Spline Regression (SWSR) in Confirmatory Clinical Trials with Time-Varying Placebo Effects
di: Zhan, Tianyu, et al.
Pubblicazione: (2025)

A regression framework for studying relationships among attributes under network interference
di: Fritz, Cornelius, et al.
Pubblicazione: (2024)

Shape-restricted transfer learning analysis for generalized linear regression model
di: Li, Pengfei, et al.
Pubblicazione: (2024)

A general approach to construct powerful tests for intersections of one-sided null-hypotheses based on influence functions
di: Pipper, Christian Bressen, et al.
Pubblicazione: (2025)

A novel generalized additive scalar-on-function regression model for partially observed multidimensional functional data: An application to air quality classification
di: Hernández-Amaro, Pavel, et al.
Pubblicazione: (2025)

The $α$--regression for compositional data: a unified framework for standard, temporal and spatial regression models including compositional predictors
di: Tsagris, Michail, et al.
Pubblicazione: (2025)

An extended generalized Pareto regression model for count data
di: Ahmad, Touqeer, et al.
Pubblicazione: (2022)

Multilevel network meta-regression for general likelihoods: synthesis of individual and aggregate data with applications to survival analysis
di: Phillippo, David M., et al.
Pubblicazione: (2024)

A unified generalization of inverse regression via adaptive column selection
di: Jin, Yin, et al.
Pubblicazione: (2024)

Estimating effect thresholds and beyond: A flexible framework for multivariate alert detection
di: Ameis, Lucia, et al.
Pubblicazione: (2026)

An interpretable neural network-based non-proportional odds model for ordinal regression
di: Okuno, Akifumi, et al.
Pubblicazione: (2023)

Effective and flexible depth-based inference for functional parameters
di: Yeon, Hyemin
Pubblicazione: (2026)

A new block covariance regression model and inferential framework for massively large neuroimaging data
di: Kim, Hyoshin, et al.
Pubblicazione: (2025)

A general framework for probabilistic model uncertainty
di: Shirvaikar, Vik, et al.
Pubblicazione: (2024)

Envelope-based partial least squares in functional regression
di: Wu, Minxuan, et al.
Pubblicazione: (2025)

BARTSIMP: flexible spatial covariate modeling and prediction using Bayesian additive regression trees
di: Jiang, Alex Ziyu, et al.
Pubblicazione: (2023)

Locally sparse estimation for simultaneous functional quantile regression
di: Hu, Boyi, et al.
Pubblicazione: (2026)

Identifiable and interpretable nonparametric factor analysis
di: Xu, Maoran, et al.
Pubblicazione: (2023)