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20182021
most citedAnalytic solutions for locally optimal designs for gamma models having linear predictor without intercept

2 citations · 3 across the 4 of their papers we have counts for

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math.ST2020

In- and Equivariance for Optimal Designs in Generalized Linear Models: The Gamma Model

Osama Idais, Rainer Schwabe

We give an overview over the usefulness of the concept of equivariance and invariance in the design of experiments for generalized linear models. In contrast to linear models here…

math.ST2019

The adaptive Wynn-algorithm in generalized linear models with univariate response

Fritjof Freise, Norbert Gaffke, Rainer Schwabe

For a nonlinear regression model the information matrices of designs depend on the parameter of the model. The adaptive Wynn-algorithm for D-optimal design estimates the parameter…

math.ST20192 cited

Analytic solutions for locally optimal designs for gamma models having linear predictor without intercept

Osama Idais, Rainer Schwabe

The gamma model is a generalized linear model for gamma-distributed outcomes. The model is widely applied in psychology, ecology or medicine. In this paper we focus on gamma models…

math.ST20181 cited

Optimal designs for -factor two-level models with first-order interactions on a symmetrically restricted design region

Fritjof Freise, Rainer Schwabe

We develop -optimal designs for linear models with first-order interactions on a subset of the full factorial design region, when both the number of factors set to the hig…

math.ST2018

Optimal Designs for Poisson Count Data with Gamma Block Effects

Marius Schmidt, Rainer Schwabe

The Poisson-Gamma model is a generalization of the Poisson model, which can be used for modelling count data. We show that the -optimality criterion for the Poisson-Gamma model…

math.ST2018

Optimal designs for two-level main effects models on a restricted design region

Fritjof Freise, Heinz Holling, Rainer Schwabe

We develop -optimal designs for linear main effects models on a subset of the full factorial design region, when the number of factors set to the higher level is bounded.…