Linear Mixed-Effects Models Using R: A Step-by-Step Approach
Linear mixed-effects models (LMMs) are an important class of statistical models
that can be used to analyze correlated data. Such data include clustered
observations, repeated measurements, longitudinal measurements, multivariate
The aim of our book is to help readers in fitting LMMs using R...
Algorithms for Sparsity-Constrained Optimization (Springer Theses)
This thesis demonstrates techniques that provide faster and more accurate solutions to a variety of problems in machine learning and signal processing. The author proposes a "greedy" algorithm, deriving sparse solutions with guarantees of optimality. The use of this algorithm removes many of the inaccuracies that occurred with the use...
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