URL: http://linkinghub.elsevier.com/retrieve/pii/S1364815217302219 Authors: Manubens, Nicolau / Caron, Louis-Philippe / Hunter, Alasdair / Bellprat, Omar / Exarchou, Eleftheria / Fu?kar, Neven / García-Serrano, Javier / Massonnet, François / Ménégoz, Martin / Sicardi, Valentina / Batté, Lauriane / Prodhomme, Chloé / Torralba, Verónica / Cortesi, Nicola / Mula-Valls, Oriol / Serradell, Kim / Gue...

Inverse estimation is a classical and well-known problem in regression. In simple terms, it involves the use of an observed value of the response to make inference on the corresponding unknown value of the explanatory variable. To our knowledge, however, statistical software is somewhat lacking the capabilities for analyzing these types of problems. In this paper, we introduce investr (which st...

The R package sns implements Stochastic Newton Sampler (SNS), a Metropolis-Hastings Monte Carlo Markov Chain algorithm where the proposal density function is a multivariate Gaussian based on a local, second-order Taylor-series expansion of log-density. The mean of the proposal function is the full Newton step in Newton-Raphson optimization algorithm. Taking advantage of the local, multivariate ...

BACKGROUND The kinship2 package is restructured from the previous kinship package. Existing features are now enhanced and new features added for handling pedigree objects. METHODS Pedigree plotting features have been updated to display features on complex pedigrees while adhering to pedigree plotting standards. Kinship matrices can now be calculated for the X chromosome. Other methods have be...

This document is a user manual for the R package fastseg. It is only meant as a gentle introduction into how to use the basic functions implemented in this package. Not all features of the R package are described in full detail. Such details can be obtained from the documentation enclosed in the R package. Further note the following: (1) this is neither an introduction to segmentation algorithm...

Boosting is an iterative algorithm that combines simple classification rules with ‘mediocre’ performance in terms of misclassification error rate to produce a highly accurate classification rule. Stochastic gradient boosting provides an enhancement which incorporates a random mechanism at each boosting step showing an improvement in performance and speed in generating the ensemble. ada is an R ...

SparseM provides some basic R functionality for linear algebra with sparse matrices. Use of the package is illustrated by a family of linear model fitting functions that implement least squares methods for problems with sparse design matrices. Significant performance improvements in memory utilization and computational speed are possible for applications involving large sparse matrices.

This introduction to the R package sampleSelection is a slightly modified version of Toomet and Henningsen (2008b), published in the Journal of Statistical Software. This paper describes the implementation of Heckman-type sample selection models in R. We discuss the sample selection problem as well as the Heckman solution to it, and argue that although modern econometrics has nonand semiparamet...

This article introduces yaImpute, an R package for nearest neighbor search and imputation. Although nearest neighbor imputation is used in a host of disciplines, the methods implemented in the yaImpute package are tailored to imputation-based forest attribute estimation and mapping. The impetus to writing the yaImpute is a growing interest in nearest neighbor imputation methods for spatially ex...

Here we illustrate several uses of the package gaga, including simulation, differential expression analysis, class prediction and sample size calculations. In Section 1 we review the GaGa and MiGaGa models. In Section 2 we simulate gene expression data, which we use to fit the GaGa model in Section 3. Diagnostics for model goodness-of-fit are presented in Section 4. Section 5 shows how to find ...