BeSS: An R Package for Best Subset Selection in Linear, Logistic and Cox Proportional Hazards Models
نویسندگان
چکیده
منابع مشابه
Bayesian variable selection for proportional hazards models
The authors consider the problem of Bayesian variable selection for proportional hazards regression models with right censored data. They propose a semi-parametric approach in which a nonparametric prior is specified for the baseline hazard rate and a fully parametric prior is specified for the regression coefficients. For the baseline hazard, they use a discrete gamma process prior, and for th...
متن کاملGradient lasso for Cox proportional hazards model
MOTIVATION There has been an increasing interest in expressing a survival phenotype (e.g. time to cancer recurrence or death) or its distribution in terms of a subset of the expression data of a subset of genes. Due to high dimensionality of gene expression data, however, there is a serious problem of collinearity in fitting a prediction model, e.g. Cox's proportional hazards model. To avoid th...
متن کاملGenerating Survival Times to Simulate Cox Proportional Hazards Models
Number of words: 2795 (excluding summary, references and tables) 2 SUMMARY This paper discusses techniques to generate survival times for simulation studies regarding Cox proportional hazards models. In linear regression models, the response variable is directly connected with the considered covariates, the regression coefficients and the simulated random errors. Thus, the response variable can...
متن کاملAttenuation in risk estimates in logistic and Cox proportional-hazards models due to group-based exposure assessment strategy.
In occupational epidemiology, it is often possible to obtain repeated measurements of exposure from a sample of subjects (workers) who belong to exposure groups associated with different levels of exposure. Average exposures from a sample of workers can be assigned to all members of that group including those who are not sampled, leading to a group-based exposure assessment. We discuss how this...
متن کاملFWDselect: An R Package for Variable Selection in Regression Models
In multiple regression models, when there are a large number (p) of explanatory variables which may or may not be relevant for predicting the response, it is useful to be able to reduce the model. To this end, it is necessary to determine the best subset of q (q ≤ p) predictors which will establish the model with the best prediction capacity. FWDselect package introduces a new forward stepwiseb...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Statistical Software
سال: 2020
ISSN: 1548-7660
DOI: 10.18637/jss.v094.i04