23 февр. 2021 г. · This publication is a tutorial on using survival models in brms to model animal behavioral sequences, so it may be relevant. The paper is open ...

1 окт. 2021 г. · I'm working on a project that aims to assess the survival of oak seedlings under different conditions. We planted a few hundred acorns under different types of ...

1 сент. 2022 г. · The Weibull, Log-normal, and Exponential, these survival models have been used for fitting of AES data with the help of brms packages of R and ...

As we'll see, brms supports parametric and nonparametric continuous-time survival models. In the sections and chapters to come, we will make extensive use of ...

Brms survival analysis. The brms package provides a user-friendly interface for Bayesian modeling, allowing users to fit various types of generalized linear ...

A wide range of distributions and link functions are supported, allowing users to fit – among others – linear, robust linear, binomial, Pois- son, survival, ...

26 июн. 2017 г. · They are widely used for survival analysis in medical research and would be a nice addition to the package. ... brms package can do bayesian ...

20 авг. 2021 г. · To sum up, we have seen some of the flexibility in the parametric approach to survival analysis as can be implemented with the pack- age brms.

9 авг. 2019 г. · Fitting the exponential model using BRMS. In general, parametric survival models can be fitted using sampling based methods such as MCMC. The ...

Three ways to do parametric survival analysis: survival::survreg : maximum likelihood; brms::brm : Baysian, with Stan; MC Stan. Maximum likelihood: survreg.