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Showing 1 to 9 of 9 for “"D-Optimal Design"”.

  1. Bayesian D-Optimal Design for Generalized Linear Models

    Bayesian optimal designs have received increasing attention in recent years, especially in biomedical and clinical trials. Bayesian design procedures can utilize the available prior information of the unknown parameters so that a better design can be achieved. However, a difficulty in dealing with …

    vt Repository record for Bayesian D-Optimal Design for Generalized Linear Models (opens in a new tab)

  2. One-Stage and Bayesian Two-Stage Optimal Designs for Mixture Models

    In this research, Bayesian two-stage D-D optimal designs for mixture experiments with or without process variables under model uncertainty are developed. A Bayesian optimality criterion is used in the first stage to minimize the determinant of the posterior variances of the parameters. The second …

    vt Repository record for One-Stage and Bayesian Two-Stage Optimal Designs for Mixture Models (opens in a new tab)

  3. New Theory and Algorithms for Convex Optimization with Non-Standard Structures

    … solution, where 𝛿0 denotes the initial optimality gap and 𝑅ℎ is the variation of ℎ on its domain. This result establishes certain intrinsic connections between 𝜃-logarithmically homogeneous barriers and the Frank-Wolfe method. When specialized to the 𝐷-optimal design problem, we …

    mit Repository record for New Theory and Algorithms for Convex Optimization with Non-Standard Structures (opens in a new tab)

  4. Measurement Error in Designed Experiments for Second Order Models

    Measurement error (ME) in the factor levels of designed experiments is often overlooked in the planning and analysis of experimental designs. A familiar model for this type of ME, called the Berkson error model, is discussed at length. Previous research has examined the effect of Berkson error on …

    vt Repository record for Measurement Error in Designed Experiments for Second Order Models (opens in a new tab)

  5. Consumer Choice of Hotel Experiences: The Effects of Cognitive, Affective, and Sensory Attributes

    … two purposes, this dissertation includes the design of a choice experiment to examine how cognitive, affective, and sensory attributes predict consumer hotel choice using multinomial logit (MNL) and random parameter (or mixed) logit (RPL) models. For choice experiments, the main objectives are …

    vt Repository record for Consumer Choice of Hotel Experiences: The Effects of Cognitive, Affective, and Sensory Attributes (opens in a new tab)

  6. Improvement of Release Criteria for Immediate Release Solid Oral Dosage Forms

    … the safety of the supply chain. A study was designed to test the hypothesis that existing compendial tests for content uniformity and dissolution would protect the supply chain against substandard and counterfeit drugs if basic field tests failed.</p><p> Compendial tests for content …

    duquesne Repository record for Improvement of Release Criteria for Immediate Release Solid Oral Dosage Forms (opens in a new tab)

  7. A Predictor Analysis Framework for Surface Radiation Budget Reprocessing Using Design of Experiments

    … affect the output data. This research utilized designed experiments that systematically and simultaneously varied all of the input parameters of the shortwave algorithm. A D-Optimal design of experiments (DOE) was chosen to accommodate the 14 types of atmospheric properties computed by the …

    odu Repository record for A Predictor Analysis Framework for Surface Radiation Budget Reprocessing Using Design of Experiments (opens in a new tab)

  8. DESIGNS FOR TESTING LACK OF FIT FOR A CLASS OF SIGMOID CURVE MODELS

    … the last decades. A well planned experiment design is essential to accurately estimate the parameters of the model. In contrast to a large literature and extensive results on optimal designs for linear models, research on the design for nonlinear, including sigmoid curve, models has not kept …

    temple Repository record for DESIGNS FOR TESTING LACK OF FIT FOR A CLASS OF SIGMOID CURVE MODELS (opens in a new tab)