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20182024
most citedAnalytic solutions for locally optimal designs for gamma models having linear predictor without intercept

2 citations · 3 across the 9 of their papers we have counts for

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8 papers · 1 filter

stat.ME2024

Optimal Design in Repeated Testing for Count Data

Parisa Parsamaram, Heinz Holling, Rainer Schwabe

In this paper, we develop optimal designs for growth curve models with count data based on the Rasch Poisson-Gamma counts (RPGCM) model. This model is often used in educational and…

stat.ME2023

D-optimal Subsampling Design for Massive Data Linear Regression

Torsten Glemser, Rainer Schwabe

Data reduction is a fundamental challenge of modern technology, where classical statistical methods are not applicable because of computational limitations. We consider multiple li…

stat.ME2023

-Optimal and Nearly -Optimal Exact Designs for Binary Response on the Ball

Martin Radloff, Rainer Schwabe

In this paper the results of Radloff and Schwabe (2019a) will be extended for a special class of symmetrical intensity functions. This includes binary response models with logit an…

stat.ME2020

Optimal Design for Probit Choice Models with Dependent Utilities

Ulrike Graßhoff, Heiko Großmann, Heinz Holling +1

In this paper we derive locally D-optimal designs for discrete choice experiments based on multinomial probit models. These models include several discrete explanatory variables as…

stat.ME2018

Optimal Designs for Second-Order Interactions in Paired Comparison Experiments with Binary Attributes

Eric Nyarko, Rainer Schwabe

In paired comparison experiments respondents usually evaluate pairs of competing options. For this situation we introduce an appropriate model and derive optimal designs in the pre…

stat.ME2018

D-Optimal Design for the Rasch Counts Model with Multiple Binary Predictors

Ulrike Graßhoff, Heinz Holling, Rainer Schwabe

In this paper, we derive optimal designs for the Rasch Poisson counts model and the Rasch Poisson-Gamma counts model incorporating several binary predictors for the difficulty para…