6 citations · 12 across the 6 of their papers we have counts for
6 papers
BFI: An R Package for Bayesian Federated Inference
Hassan Pazira, Marianne A. Jonker
Bayesian Federated Inference (BFI) estimates statistical models from multicenter data when individual-level observations cannot be combined across centers. We present \pkg{BFI}, an…
An Accurate and Single-Communication Federated Inference Algorithm
Laura Montagnani, Anthony CC Coolen, Marianne A Jonker
Joint analyses across multiple institutions are increasingly important in biomedical and epidemiological research, particularly for rare diseases where datasets are typical small.…
Bayesian Federated Inference for Survival Models
Hassan Pazira, Emanuele Massa, Jetty AM Weijers +2
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, m…
Bayesian Federated Inference for regression models based on non-shared multicenter data sets from heterogeneous populations
Marianne A Jonker, Hassan Pazira, Anthony CC Coolen
To estimate accurately the parameters of a regression model, the sample size must be large enough relative to the number of possible predictors for the model. In practice, sufficie…
Penalization-induced shrinking without rotation in high dimensional GLM regression: a cavity analysis
Emanuele Massa, Marianne Jonker, Anthony Coolen
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. Unfo…
Correction of overfitting bias in regression models
Emanuele Massa, Marianne Jonker, Kit Roes +1
Regression analysis based on many covariates is becoming increasingly common. However, when the number of covariates is of the same order as the number of observations , max…