ANALYSIS OF PROTEIN ACTIVITY DATA BY GAUSSIAN STOCHASTIC PROCESS MODELS

DOI10.1081/BIP-100101005zbMath0944.92011OpenAlexW2015542188WikidataQ30560275 ScholiaQ30560275MaRDI QIDQ4244523

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Publication date: 20 July 1999

Published in: Journal of Biopharmaceutical Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1081/bip-100101005

zbMATH Keywords

semiparametric regressioncross-validationdata-adaptiveoptimal storage conditionsprotein constructs

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Applications of statistics to biology and medical sciences; meta analysis (62P10) Biochemistry, molecular biology (92C40)

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Spatial sampling design for parameter estimation of the covariance function ⋮ Analysis methods for computer experiments: how to assess and what counts? ⋮ High-Low Level Support Vector Regression Prediction Approach (HL-SVR) for Data Modeling with Input Parameters of Unequal Sample Sizes ⋮ EzGP: Easy-to-Interpret Gaussian Process Models for Computer Experiments with Both Quantitative and Qualitative Factors

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