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Ordinary least squares (OLS) is the default method for fitting linear models, but is not applicable for problems with dimensionality larger than the sample size. For these problems, we advocate the use of a generalized version of OLS…

Methodology · Statistics 2016-06-17 Xiangyu Wang , David Dunson , Chenlei Leng

Cross validation residuals are well known for the ordinary least squares model. Here leave-M-out cross validation is extended to generalised least squares. The relationship between cross validation residuals and Cook's distance is…

Methodology · Statistics 2018-09-06 Ingrid Annette Baade

The dramatic growth of big datasets presents a new challenge to data storage and analysis. Data reduction, or subsampling, that extracts useful information from datasets is a crucial step in big data analysis. We propose an orthogonal…

Methodology · Statistics 2021-06-01 Lin Wang , Jake Elmstedt , Weng Kee Wong , Hongquan Xu

The number of the non-shared edges of two phylogenies is a basic measure of the dissimilarity between the phylogenies. The non-shared edges are also the building block for approximating a more sophisticated metric called the nearest…

Data Structures and Algorithms · Computer Science 2007-05-23 Wing-Kai Hon , Ming-Yang Kao , Tak-Wah Lam , Wing-Kin Sung , Siu-Ming Yiu

Accurate estimation of evolutionary distances between taxa is important for many phylogenetic reconstruction methods. In the case of bacteria, distances can be estimated using a range of different evolutionary models, from single nucleotide…

Populations and Evolution · Quantitative Biology 2017-04-17 Stuart Serdoz , Attila Egri-Nagy , Jeremy Sumner , Barbara R. Holland , Peter D. Jarvis , Mark M. Tanaka , Andrew R. Francis

In statistics, series of ordinary least squares problems (OLS) are used to study the linear correlation among sets of variables of interest; in many studies, the number of such variables is at least in the millions, and the corresponding…

Computational Engineering, Finance, and Science · Computer Science 2015-04-30 Alvaro Frank , Diego Fabregat-Traver , Paolo Bientinesi

A recurring theme in the least squares approach to phylogenetics has been the discovery of elegant combinatorial formulas for the least squares estimates of edge lengths. These formulas have proved useful for the development of efficient…

Combinatorics · Mathematics 2009-11-13 Radu Mihaescu , Lior Pachter

Classification of gene trees is an important task both in the analysis of multi-locus phylogenetic data, and assessment of the convergence of Markov Chain Monte Carlo (MCMC) analyses used in Bayesian phylogenetic tree reconstruction. The…

Combinatorics · Mathematics 2024-06-10 Georgios Aliatimis , Ruriko Yoshida , Burak Boyaci , James A. Grant

Likelihood-based methods are widely considered the best approaches for reconstructing ancestral states. Although much effort has been made to study properties of these methods, previous works often assume that both the tree topology and…

Methodology · Statistics 2021-04-02 Lam Si Tung Ho , Edward Susko

When performing an analysis on a collection of molecular sequences, it can be convenient to reduce the number of sequences under consideration while maintaining some characteristic of a larger collection of sequences. For example, one may…

Populations and Evolution · Quantitative Biology 2012-09-03 Frederick A. Matsen , Aaron Gallagher , Connor McCoy

Ancestral maximum likelihood (AML) is a method that simultaneously reconstructs a phylogenetic tree and ancestral sequences from extant data (sequences at the leaves). The tree and ancestral sequences maximize the probability of observing…

Populations and Evolution · Quantitative Biology 2017-07-24 Elchanan Mossel , Sebastien Roch , Mike Steel

We analyse a maximum-likelihood approach for combining phylogenetic trees into a larger `supertree'. This is based on a simple exponential model of phylogenetic error, which ensures that ML supertrees have a simple combinatorial description…

Populations and Evolution · Quantitative Biology 2007-08-17 Mike Steel , Allen Rodrigo

A set of general allometric scaling laws is derived for different systems represented by tree networks. The formulation postulates self-similar networks with an arbitrary number of branches developed in each generation, and with an…

Physics and Society · Physics 2017-10-06 L. Zavala Sansón , A. González-Villanueva

Orthogonal least square (OLS) is an important sparse signal recovery algorithm for compressive sensing, which enjoys superior probability of success over other well-known recovery algorithms under conditions of correlated measurement…

Information Theory · Computer Science 2018-08-02 Samrat Mukhopadhyay , Siddhartha Satpathi , Mrityunjoy Chakraborty

Phylogenetic networks are a type of leaf-labelled, acyclic, directed graph used by biologists to represent the evolutionary history of species whose past includes reticulation events. A phylogenetic network is tree-child if each non-leaf…

Combinatorics · Mathematics 2017-11-27 Magnus Bordewich , Katharina T Huber , Vincent Moulton , Charles Semple

Ordinary least-squares (OLS) estimators for a linear model are very sensitive to unusual values in the design space or outliers among y values. Even one single atypical value may have a large effect on the parameter estimates. This article…

Methodology · Statistics 2014-04-28 Chun Yu , Weixin Yao , Xue Bai

We study the problem of inferring a sparse vector from random linear combinations of its components. We propose the Accelerated Orthogonal Least-Squares (AOLS) algorithm that improves performance of the well-known Orthogonal Least-Squares…

Machine Learning · Statistics 2018-04-17 Abolfazl Hashemi , Haris Vikalo

It has recently been discovered that the conclusions of many highly influential econometrics studies can be overturned by removing a very small fraction of their samples (often less than $0.5\%$). These conclusions are typically based on…

Machine Learning · Computer Science 2024-10-11 Ittai Rubinstein , Samuel B. Hopkins

Terrestrial laser scanning (TLS) is the standard technique used to create accurate point clouds for digital forest inventories. However, the measurement process is demanding, requiring up to two days per hectare for data collection,…

An Orthogonal Least Squares (OLS) based feature selection method is proposed for both binomial and multinomial classification. The novel Squared Orthogonal Correlation Coefficient (SOCC) is defined based on Error Reduction Ratio (ERR) in…

Machine Learning · Computer Science 2021-11-09 Sikai Zhang , Zi-Qiang Lang