J
James Theiler
Researcher at Los Alamos National Laboratory
Publications - 259
Citations - 24106
James Theiler is an academic researcher from Los Alamos National Laboratory. The author has contributed to research in topics: Hyperspectral imaging & Pixel. The author has an hindex of 52, co-authored 243 publications receiving 21241 citations. Previous affiliations of James Theiler include University of California, San Diego & California Institute of Technology.
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Testing for nonlinearity in time series: the method of surrogate data
TL;DR: In this article, a statistical approach for identifying nonlinearity in time series is described, which first specifies some linear process as a null hypothesis, then generates surrogate data sets which are consistent with this null hypothesis and finally computes a discriminating statistic for the original and for each of the surrogate sets.
Journal ArticleDOI
Tracking Changes in SARS-CoV-2 Spike: Evidence that D614G Increases Infectivity of the COVID-19 Virus.
Bette T. Korber,Will Fischer,Sandrasegaram Gnanakaran,Hyejin Yoon,James Theiler,Werner Abfalterer,Nick Hengartner,Elena E. Giorgi,Tanmoy Bhattacharya,Brian T. Foley,Kathryn M. Hastie,Matthew Parker,David G Partridge,Cariad Evans,Timothy M. Freeman,Thushan I de Silva,Adrienne Angyal,Rebecca Brown,Laura Carrilero,Luke R. Green,Luke R. Green,Luke R. Green,Danielle C. Groves,Katie Johnson,Alexander J Keeley,Benjamin B Lindsey,Paul J. Parsons,Mohammad Raza,Sarah Rowland-Jones,Nikki Smith,Rachel Tucker,Dennis Wang,Matthew Wyles,Charlene McDanal,Lautaro G. Perez,Haili Tang,Alex Moon-Walker,Alex Moon-Walker,Alex Moon-Walker,Sean P. J. Whelan,Celia C. LaBranche,Erica Ollmann Saphire,David C. Montefiori +42 more
TL;DR: A SARS-CoV-2 variant carrying the Spike protein amino acid change D614G has become the most prevalent form in the global pandemic, and it is found that the G614 variant grows to higher titer as pseudotyped virions.
Testing for nonlinearity in time series: The method of surrogate data
TL;DR: A statistical approach for identifying nonlinearity in time series which is demonstrated for numerical data generated by known chaotic systems, and applied to a number of experimental time series, which arise in the measurement of superfluids, brain waves, and sunspots.
Journal ArticleDOI
Timing the ancestor of the HIV-1 pandemic strains.
Bette T. Korber,Mark Muldoon,Mark Muldoon,James Theiler,Feng Gao,Rajan Gupta,Alan Lapedes,Alan Lapedes,Beatrice H. Hahn,Steven M. Wolinsky,Tanmoy Bhattacharya +10 more
TL;DR: Using a comprehensive full-length envelope sequence alignment, the date of the last common ancestor of the main group of HIV-1 is estimated to be 1931 (1915-41).
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Spurious dimension from correlation algorithms applied to limited time-series data
TL;DR: In this paper, an algorithm for measuring the dimension of a strange attractor from a time series is applied both to autocorrelated Gaussian noise and to a dynamical system.