Results 141 to 150 of about 768,227 (181)
Programmable Nanoscale Motion via Molecular Patterning on DNA Origami. [PDF]
Angew Chem Int Ed EnglPaffen L +6 more
europepmc +1 more source
Exploring Bayesian adaptive designs in multi-arm randomized controlled trials with a patient preference arm. [PDF]
J Biopharm StatBrown AR +5 more
europepmc +1 more source
A Practical Framework to Design Immunization Studies Based on the Beta Distribution. [PDF]
Stat MedEmbacher S +3 more
europepmc +1 more source
Genetic controllers for enhancing the evolutionary longevity of synthetic gene circuits in bacteria. [PDF]
Nat CommunByrom DP, Darlington APS.
europepmc +1 more source
A Study of D-optimal Designs Efficiency for Polynomial Regression [PDF]
Anna Weinberg, Gérard Antille
core
Some of the next articles are maybe not open access.
Related searches:
Related searches:
Chemometrics and Intelligent Laboratory Systems, 1995
Abstract Many classical symmetrical designs have desirable characteristics, one of which is called D-optimality. The D-optimality concept can also be applied to select a design when the classical symmetrical designs cannot be used, such as when the experimental region is not regular in shape, when the number of experiments chosen by a classical ...
P.F. de Aguiar +4 more
openaire +1 more source
Abstract Many classical symmetrical designs have desirable characteristics, one of which is called D-optimality. The D-optimality concept can also be applied to select a design when the classical symmetrical designs cannot be used, such as when the experimental region is not regular in shape, when the number of experiments chosen by a classical ...
P.F. de Aguiar +4 more
openaire +1 more source
D-optimal fractional factorial designs
Statistics & Probability Letters, 1998zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Chiu, Wan-Yi, John, Peter W. M.
openaire +2 more sources
Quantitative Structure-Activity Relationships, 1993
AbstractStatistical design in principal properties based on D‐optimality criteria are particularly appropriate for selecting the most informative molecules to be synthesized and tested in the framework of QSAR studies. Selection by D‐optimal designs are better than those based on fractional factorial designs since they allow one to reduce the number of
BARONI, Massimo +4 more
openaire +2 more sources
AbstractStatistical design in principal properties based on D‐optimality criteria are particularly appropriate for selecting the most informative molecules to be synthesized and tested in the framework of QSAR studies. Selection by D‐optimal designs are better than those based on fractional factorial designs since they allow one to reduce the number of
BARONI, Massimo +4 more
openaire +2 more sources