Salīdzināt metodes

	Optimāls eksperimentu plānojums (D-optimāls, I-optimāls)	Pilna faktorālā eksperimenta dizains
Nozare	Eksperimentu plānošana	Eksperimentu plānošana
Saime	Hypothesis test	Hypothesis test
Izcelsmes gads	1972	1926
Autors	V. V. Fedorov	R. A. Fisher
Tips	Computer-aided optimal design	Parametric factorial experiment
Pirmavots	Fedorov, V.V. (1972). Theory of Optimal Experiments. Academic Press.	Box, G. E. P., Hunter, J. S., & Hunter, W. G. (2005). Statistics for Experimenters: Design, Innovation, and Discovery (2nd ed.). Wiley. ISBN: 978-0471718130
Citi nosaukumi	D-Optimal Design, I-Optimal Design, Computer-Generated Design, Optimal Deneme Deseni (D-Optimal, I-Optimal)	factorial experiment, 2^k factorial, full factorial, Faktöriyel Deneme Deseni (Full Factorial, 2^k)
Saistītās	5	5
Kopsavilkums	Optimal experimental design is a computer-aided approach to constructing experiments that maximises statistical efficiency for a given model and run budget. Formalised by V. V. Fedorov in 1972, it selects experimental points from a candidate set so that the information matrix M = X'X is optimised according to a chosen criterion — most commonly D-optimality (maximising the determinant) or I-optimality (minimising average prediction variance). It is the preferred strategy whenever classical designs such as central composite or Box-Behnken cannot be applied because the experimental region is constrained or factor ranges are irregular.	A full factorial design is a parametric experimental method in which every combination of factor levels is tested simultaneously, enabling the estimation of all main effects and all interaction effects in a single study. Rooted in R. A. Fisher's foundational work on designed experiments (1926) and systematically developed by Box, Hunter, and Hunter (2005) and Montgomery (2017), the 2^k form tests k two-level factors across 2^k experimental runs and is the benchmark against which all other factorial designs are measured.