Imagen de Portada

npcure: An R Package for Nonparametric Inference in Mixture Cure Models

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	López-Cheda, Ana, Jácome, M. Amalia, López-de-Ullibarri, Ignacio
Formato:	Preprint
Publicado:	2024
Materias:	Methodology
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Nonparametric latency estimation for mixture cure models
por: López-Cheda, Ana, et al.
Publicado: (2024)

Nonparametric covariate hypothesis tests for the cure rate in mixture cure models
por: López-Cheda, Ana, et al.
Publicado: (2024)

Nonparametric incidence estimation and bootstrap bandwidth selection in mixture cure models
por: López-Cheda, Ana, et al.
Publicado: (2024)

A product-limit estimator of the conditional survival function when cure status is partially known
por: Safari, Wende C., et al.
Publicado: (2024)

Estimating lengths-of-stay of hospitalised COVID-19 patients using a non-parametric model: a case study in Galicia (Spain)
por: López-Cheda, Ana, et al.
Publicado: (2024)

Cure models to estimate time until hospitalization due to COVID-19
por: Pedrosa-Laza, Maria, et al.
Publicado: (2024)

Nonparametric Bayesian Multi-Treatment Mixture Cure Survival Model with Application in Pediatric Oncology
por: Chang, Peter, et al.
Publicado: (2025)

A Generalized Mixture Cure Model Incorporating Known Cured Individuals
por: Karakatsoulis, Georgios
Publicado: (2024)

Nonparametric Inference for Extreme CoVaR and CoES
por: Zhong, Qingzhao, et al.
Publicado: (2025)

Dynamic Prediction in Mixture Cure Models: A Model-Based Landmarking Approach
por: Cipriani, Marta, et al.
Publicado: (2025)

hdMTD: An R Package for High-Dimensional Mixture Transition Distribution Models
por: Gripp, Maiara, et al.
Publicado: (2025)

Fast Bootstrapping Nonparametric Maximum Likelihood for Latent Mixture Models
por: Wang, Shijie, et al.
Publicado: (2024)

bayesCureRateModel: Bayesian Cure Rate Modeling for Time to Event Data in R
por: Papastamoulis, Panagiotis, et al.
Publicado: (2024)

Nonparametric Inference Framework for Time-dependent Epidemic Models
por: Luu, Son, et al.
Publicado: (2024)

Variational Nonparametric Inference in Functional Stochastic Block Model
por: Shang, Zuofeng, et al.
Publicado: (2024)

ipd: An R Package for Conducting Inference on Predicted Data
por: Salerno, Stephen, et al.
Publicado: (2024)

A Finite-Horizon Mixture Cure Model with Application to Online Flea Market Data
por: Komiyama, Yuji, et al.
Publicado: (2026)

Bayesian Semiparametric Mixture Cure (Frailty) Models
por: Kızılaslan, Fatih, et al.
Publicado: (2025)

Nonparametric Inference for Balance in Signed Networks
por: Chen, Xuyang, et al.
Publicado: (2024)

mpower: An R Package for Power Analysis of Exposure Mixture Studies via Monte Carlo Simulations
por: Nguyen, Phuc H., et al.
Publicado: (2022)

Nonparametric Statistical Inference for Multivariate Niche Overlap
por: Beck, Jonas, et al.
Publicado: (2026)

Bootstrap Nonparametric Inference under Data Integration
por: Shang, Zuofeng, et al.
Publicado: (2025)

Nonparametric Inference on Unlabeled Histograms
por: Ma, Yun, et al.
Publicado: (2025)

A Nonparametric Mixed-Effects Mixture Model for Patterns of Clinical Measurements Associated with COVID-19
por: Ma, Xiaoran, et al.
Publicado: (2023)

EM Approaches to Nonparametric Estimation for Mixture of Linear Regressions
por: Welbaum, Andrew, et al.
Publicado: (2025)

A Nonparametric Maximum Likelihood Approach to Mixture of Regression
por: Jiang, Hansheng, et al.
Publicado: (2021)

SSLfmm: An R Package for Semi-Supervised Learning with a Mixed-Missingness Mechanism in Finite Mixture Models
por: McLachlan, Geoffrey J., et al.
Publicado: (2025)

dynamite: An R Package for Dynamic Multivariate Panel Models
por: Tikka, Santtu, et al.
Publicado: (2023)

Nonparametric Inference with an Instrumental Variable under a Separable Binary Treatment Choice Model
por: Park, Chan, et al.
Publicado: (2026)

Efficient Nonparametric Inference for Mediation Analysis with Nonignorable Missing Confounders
por: Shan, Jiawei, et al.
Publicado: (2024)

Statistical Models for Repeated Categorical Ratings: The R Package rater
por: Pullin, Jeffrey M., et al.
Publicado: (2020)

nlive: an R Package to facilitate the application of the sigmoidal and random changepoint mixed models
por: Capuano, Ana W, et al.
Publicado: (2023)

Bayesian Variational Inference for Mixed Data Mixture Models
por: Wang, Junyang, et al.
Publicado: (2025)

Deep Nonparametric Inference for Conditional Hazard Function
por: Su, Wen, et al.
Publicado: (2024)

Nonparametric Identification and Inference for Counterfactual Distributions with Confounding
por: Sun, Jianle, et al.
Publicado: (2026)

Flexible Nonparametric Inference for Causal Effects under the Front-Door Model
por: Guo, Anna, et al.
Publicado: (2023)

On Efficient and Scalable Computation of the Nonparametric Maximum Likelihood Estimator in Mixture Models
por: Zhang, Yangjing, et al.
Publicado: (2022)

Nonparametric FBST for Validating Linear Models
por: Lassance, Rodrigo F. L., et al.
Publicado: (2024)

Nonparametric modal regression with missing response observations
por: Pérez-González, Ana, et al.
Publicado: (2025)

Flexible Bayesian Nonparametric Product Mixtures for Multi-scale Functional Clustering
por: Yao, Tsung-Hung, et al.
Publicado: (2024)