Search Results - "Statistics & Probability"

eBook

Bayesian Analysis of Infectious Diseases: COVID-19 and Beyond

by Lyle D. Broemeling
05.02.2021

“...Bayesian Analysis of Infectious Diseases -COVID-19 and Beyond shows how the Bayesian approach can be used to analyze the evolutionary behavior of infectious...”

Journal Article

Smoothed time‐dependent receiver operating characteristic curve for right censored survival data

by Beyene, Kassu Mehari El Ghouch, Anouar Published in Statistics in Medicine (2020)

“...The prediction reliability is of primary concern in many clinical studies when the objective is to develop new predictive models or improve existing risk...”

Book

An introduction to nonparametric statistics
First edition

by Kolassa, John E
2021

“..."This book presents the theory and practice of non-parametric statistics, with an emphasis on motivating principals. The course is a combination of traditional...”

Holdings Uni Bonn

eBook

A First Course in Ordinary Differential Equations

by Suman Kumar Tumuluri
26.03.2021

“...A First course in Ordinary Differential Equations provides a detailed introduction to the subject focusing on analytical methods to solve ODEs and theoretical...”

Journal Article

A generalized asymmetric exclusion process with Uq(sl2) stochastic duality

by Carinci, Gioia Giardinà, Cristian Redig, Frank Sasamoto, Tomohiro
05.11.2015

“...We study a new process, which we call ASEP(q, j ), where particles move asymmetrically on a one-dimensional integer lattice with a bias determined by q ? (0,...”

Journal Article

Multifractal methodology

by Salat, Hadrien Murcio, Roberto Arcaute, Elsa Published in Physica A (01.05.2017)

“...Various methods have been developed independently to study the multifractality of measures in many different contexts. Although they all convey the same...”

Fulltext

Journal Article

R-squared for Bayesian Regression Models

by Gelman, Andrew Goodrich, Ben Gabry, Jonah Vehtari, Aki Published in The American statistician (03.07.2019)

“...The usual definition of R 2 (variance of the predicted values divided by the variance of the data) has a problem for Bayesian fits, as the numerator can be...”

Journal Article

mclust 5: Clustering, Classification and Density Estimation Using Gaussian Finite Mixture Models

by Scrucca, Luca Fop, Michael Murphy, T Brendan Raftery, Adrian E Published in The R journal (01.08.2016)

“...Finite mixture models are being used increasingly to model a wide variety of random phenomena for clustering, classification and density estimation. is a...”

Journal Article

Sambamba: fast processing of NGS alignment formats

by Tarasov, Artem Vilella, Albert J Cuppen, Edwin Nijman, Isaac J Prins, Pjotr Published in Bioinformatics (Oxford, England) (19.02.2015)

“...Sambamba is a high-performance robust tool and library for working with SAM, BAM and CRAM sequence alignment files; the most common file formats for aligned...”

Journal Article

Likelihood-free inference via classification

by Gutmann, Michael U Gutmann, Michael U Dutta, Ritabrata Dutta, Ritabrata Kaski, Samuel Kaski, Samuel Corander, Jukka Corander, Jukka Published in Statistics and computing (01.03.2018)

“...Increasingly complex generative models are being used across disciplines as they allow for realistic characterization of data, but a common difficulty with...”

Fulltext

Journal Article

Nested and Repeated Cross Validation for Classification Model With High-Dimensional Data

by Zhong, Yi He, Jianghua Chalise, Prabhakar Published in Revista Colombiana de estadística (01.01.2020)

“...With the advent of high throughput technologies, the high-dimensional datasets are increasingly available. This has not only opened up new insight into...”

Journal Article

Generalized Poisson Hidden Markov Model for Overdispersed or Underdispersed Count Data

by George, Sebastian Jose, Ambily Published in Revista Colombiana de estadística (01.01.2020)

“...The most suitable statistical method for explaining serial dependency in time series count data is that based on Hidden Markov Models (HMMs). These models...”

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