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pro vyhledávání: '"Massa, Emanuele"'
Autor:
Massa, Emanuele
We investigate analytically the behaviour of the penalized maximum partial likelihood estimator (PMPLE). Our results are derived for a generic separable regularization, but we focus on the elastic net. This penalization is routinely adopted for survi
Externí odkaz:
http://arxiv.org/abs/2405.13690
In cancer research, overall survival and progression free survival are often analyzed with the Cox model. To estimate accurately the parameters in the model, sufficient data and, more importantly, sufficient events need to be observed. In practice, t
Externí odkaz:
http://arxiv.org/abs/2404.17464
Replica analysis of overfitting in regression models for time to event data: the impact of censoring
We use statistical mechanics techniques, viz. the replica method, to model the effect of censoring on overfitting in Cox's proportional hazards model, the dominant regression method for time-to-event data. In the overfitting regime, Maximum Likelihoo
Externí odkaz:
http://arxiv.org/abs/2312.02870
In high dimensional regression, where the number of covariates is of the order of the number of observations, ridge penalization is often used as a remedy against overfitting. Unfortunately, for correlated covariates such regularisation typically ind
Externí odkaz:
http://arxiv.org/abs/2209.04270
Regression analysis based on many covariates is becoming increasingly common. However, when the number of covariates $p$ is of the same order as the number of observations $n$, maximum likelihood regression becomes unreliable due to overfitting. This
Externí odkaz:
http://arxiv.org/abs/2204.05827