Performance assessment of the anticipatory approach to optimal experimental design for model discrimination

[Lecture Notes in Statistics] Functional

[Lecture Notes in Statistics] Functional Approach to Optimal Experimental Design Volume 184 || Fundamentals of the Optimal Experimental Design

✍ , 📂 Article 📅 2006 🏛 Springer-Verlag 🌐 English ⚖ 187 KB

The Book Presents A Novel Approach For Studying Optimal Experimental Designs. The Functional Approach Consists Of Representing Support Points Of The Designs By Taylor Series. It Is Thoroughly Explained For Many Linear And Nonlinear Regression Models Popular In Practice Including Polynomial, Trigonom

Experimental design for the identificati

Experimental design for the identification of macrokinetic models and model discrimination

✍ R. Takors; W. Wiechert; D. Weuster-Botz 📂 Article 📅 1997 🏛 John Wiley and Sons 🌐 English ⚖ 310 KB 👁 2 views

An experimental design method for the identification of macrokinetic models was developed applying an extended D-optimal design criterion. The D-optimal design criterion was modified to consider variable measurement variances as well as multivariate macrokinetic models. The macrokinetics of formate

Optimal design: A computer program to st

Optimal design: A computer program to study the best possible spacing of design points for model discrimination

✍ W.G. Bardsley; R.M.W. Wood; E.M. Melikhova 📂 Article 📅 1996 🏛 Elsevier Science 🌐 English ⚖ 964 KB

A Bayesian experimental design approach

A Bayesian experimental design approach for assessing new product performance: An application to disinfectant formulation

✍ Navid Omidbakhsh; Thomas A. Duever; Ali Elkamel; Park M. Reilly 📂 Article 📅 2010 🏛 John Wiley and Sons 🌐 English ⚖ 194 KB

[Lecture Notes in Statistics] Functional

[Lecture Notes in Statistics] Functional Approach to Optimal Experimental Design Volume 184 || The Monod Model

✍ , 📂 Article 📅 2006 🏛 Springer-Verlag 🌐 English ⚖ 447 KB

The Book Presents A Novel Approach For Studying Optimal Experimental Designs. The Functional Approach Consists Of Representing Support Points Of The Designs By Taylor Series. It Is Thoroughly Explained For Many Linear And Nonlinear Regression Models Popular In Practice Including Polynomial, Trigonom

Sequential experimental design for model

Sequential experimental design for model discrimination in the case of multiple responses

✍ G. Buzzi Ferraris; P. Forzatti; G. Emig; H. Hofmann 📂 Article 📅 1984 🏛 Elsevier Science 🌐 English ⚖ 366 KB