SLSEdesign - Optimal Regression Design under the Second-Order Least Squares Estimator
With given inputs that include number of points, discrete design space, a measure of skewness, models and parameter value, this package calculates the objective value, optimal designs and plot the equivalence theory under A- and D-optimal criteria under the second-order Least squares estimator. This package is based on the paper "Properties of optimal regression designs under the second-order least squares estimator" by Chi-Kuang Yeh and Julie Zhou (2021) <doi:10.1007/s00362-018-01076-6>.
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convex-optimizationcvxdesign-of-experimentsleast-squaresoptimal-designs
4.59 score 3 scripts 2.0k downloadsrtForecastEval - Evaluate the Discrepancy between Two Real-Time Updated Probabilistic Forecasts
Methods from Yeh, Rice, and Dubin (2022, doi:10.1080/00031305.2021.1967781; arXiv:2010.00781) for comparing two continuously updated probabilistic forecasts under squared (Brier) loss: pointwise loss and variance, a global delta test (Monte Carlo p-values), simulation designs, and a naive pointwise band plot.
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forecastinggoodness-of-fit
4.00 score 1 stars 448 downloadsgtDesign - Convex Optimal Designs for Group Testing Experiments
Finite candidate-set approximate optimal designs for group testing and related experiments, using convex optimization and equivalence checks. Implements the information matrix and cost structure for the prevalence / sensitivity / specificity model used in Huang and colleagues (2020), as in Chi-Kuang Yeh, Weng Kee Wong, and Julie Zhou (<doi:10.48550/arXiv.2508.08445>).
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group-testingoptimal-design
3.30 score 5 scripts 516 downloads