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Nonparametric Methods: A Selected Overview

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Statistical Learning in Genetics

Part of the book series: Statistics for Biology and Health ((SBH))

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Abstract

Throughout this book a phrase like “assume the data have been generated by the following probability model” has been abundantly used. Indeed, the standard parametric assumption is that observed data represent one realisation from some given probability model and the goal can be to infer the parameters of the model. Alternatively and from a classical frequentist setting, conditionally on estimated parameters, the goal may be to predict future observations.

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Authors and Affiliations

  1. Aarhus University, Aarhus, Denmark

    Daniel Sorensen

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  1. Daniel Sorensen
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Sorensen, D. (2023). Nonparametric Methods: A Selected Overview. In: Statistical Learning in Genetics. Statistics for Biology and Health. Springer, Cham. https://doi.org/10.1007/978-3-031-35851-7_11

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