The following pages link to Stefanie Biedermann (Q188341):
Displaying 24 items.
- (Q588052) (redirect page) (← links)
- Constrained optimal discrimination designs for Fourier regression models (Q734416) (← links)
- Optimal designs for full and partial likelihood information -- with application to survival models (Q894783) (← links)
- Optimal discrimination designs for exponential regression models (Q997267) (← links)
- Model robust designs for survival trials (Q1658159) (← links)
- A functional-algebraic determination of \(D\)-optimal designs for trigonometric regression models on a partial circle. (Q1871242) (← links)
- Compound optimal designs for percentile estimation in dose-response models with restricted design intervals (Q2455406) (← links)
- Designs for selected nonlinear models (Q2799897) (← links)
- Optimal design for additive partially nonlinear models (Q3011164) (← links)
- Optimal designs for indirect regression (Q3097930) (← links)
- (Q3376018) (← links)
- (Q3562492) (← links)
- Robust and Efficient Designs for the Michaelis–Menten Model (Q4468480) (← links)
- Optimal design when outcome values are not missing at random (Q4558444) (← links)
- Optimal design for experiments with possibly incomplete observations (Q4571225) (← links)
- Simultaneous confidence sets for several effective doses (Q4584963) (← links)
- Some robust design strategies for percentile estimation in binary response models (Q5295955) (← links)
- On Optimal Designs for Nonlinear Models: A General and Efficient Algorithm (Q5406368) (← links)
- (Q5413264) (← links)
- Tests in a Case–control Design Including Relatives (Q5430611) (← links)
- Optimal Designs for Dose–Response Models With Restricted Design Spaces (Q5754981) (← links)
- Testing linearity of regression models with dependent errors by kernel based methods (Q5936980) (← links)
- Optimal designs for testing the functional form of a regression via nonparametric estimation techniques (Q5937068) (← links)
- \(D\)-optimal designs for multiarm trials with dropouts (Q6627166) (← links)
