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Review

2017

Review

2017

Abstract The mathematical/statistical software platform R has seen an immense increase in popularity within the last decade. Its… Expand

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Review

2017

Review

2017

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential… Expand

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Highly Cited

2017

Highly Cited

2017

The brms package implements Bayesian multilevel models in R using the probabilistic programming language Stan. A wide range of… Expand

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Review

2016

Review

2016

As any real-life data, data modeled by linear mixed-effects models often contain outliers or other contamination. Even little… Expand

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Highly Cited

2004

Highly Cited

2004

This paper discusses advantages and shortcomings of the S environment for multivariable geostatistics, in particular when… Expand

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Highly Cited

2004

Highly Cited

2004

kernlab is an extensible package for kernel-based machine learning methods in R. It takes advantage of R's new S4 ob ject model… Expand

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Highly Cited

2003

Highly Cited

2003

Clarify is a program that uses Monte Carlo simulation to convert the raw output of statistical procedures into results that are… Expand

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Highly Cited

2001

Highly Cited

2001

A comprehensive, but simple-to-use software package for executing a range of standard numerical analysis and operations used in… Expand

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Highly Cited

1990

Highly Cited

1990

Contents: Preface. Part I: Conceptual Bases of Experimental Design and Analysis. The Logic of Experimental Design. Introduction… Expand

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Highly Cited

1987

Highly Cited

1987

-Repeatability is a useful tool for the population geneticist or genetical ecologist, but several papers have carried errors in… Expand

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