Amanote Research

Amanote Research

    RegisterSign In

Efficient Experimental Designs for Sigmoidal Growth Models

Journal of Statistical Planning and Inference - Netherlands
doi 10.1016/j.jspi.2007.05.027
Full Text
Open PDF
Abstract

Available in full text

Categories
UncertaintyApplied MathematicsStatisticsProbability
Date

January 1, 2008

Authors
Holger DetteAndrey Pepelyshev
Publisher

Elsevier BV


Related search

Optimal Designs for Asymmetric Sigmoidal Response Curves in Bioassays and Immunoassays

Statistical Methods in Medical Research
Health Information ManagementEpidemiologyStatisticsProbability
2019English

Profile Construction in Experimental Choice Designs for Mixed Logit Models

Marketing Science
MarketingEconomicsInternational ManagementBusinessEconometrics
2002English

Experimental Designs

American Journal of Public Health and the Nations Health
1958English

On the Use of Structural Equation Models in Experimental Designs

Journal of Marketing Research
MarketingEconomicsInternational ManagementBusinessEconometrics
1989English

Sicegar: R Package for Sigmoidal and Double-Sigmoidal Curve Fitting

2017English

Optimal Designs for Linear Mixture Models

Statistica Neerlandica
UncertaintyStatisticsProbability
1975English

Highly Efficient Designs to Handle the Incorrect Specification of Linear Mixed Models

Communications in Statistics Part B: Simulation and Computation
ModelingStatisticsProbabilitySimulation
2008English

A New and Efficient Tool for Optical Designs

SPIE Newsroom
2014English

Two-Group Experimental Designs

Western Journal of Nursing Research
Nursing
2003English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2025 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy