[BOOK][B] Computational Statistics in Data Science
WW Piegorsch, RA Levine, HH Zhang, TCM Lee - 2022 - books.google.com
… into how computational statistics may progress in this age of big data and transdisciplinary
data science. It … computational infrastructure for data analysis through R software; for making …
data science. It … computational infrastructure for data analysis through R software; for making …
Design and analysis of optimization algorithms using computational statistics
T Bartz–Beielstein, KE Parsopoulos… - … & Computational …, 2004 - Wiley Online Library
… analysis of optimization algorithms. The proposed technique employs computational statistic
… combines methods from computational statistics and exploratory data analysis to improve (…
… combines methods from computational statistics and exploratory data analysis to improve (…
[BOOK][B] Symbolic data analysis: Conceptual statistics and data mining
L Billard, E Diday - 2012 - books.google.com
… Computational Statistics is comprised of practical guides and cutting edge research books on
new developments in computational statistics… as realizations in the interval [73, 167]; or the …
new developments in computational statistics… as realizations in the interval [73, 167]; or the …
[BOOK][B] Density estimation for statistics and data analysis
BW Silverman - 2018 - taylorfrancis.com
… data set and to explore how density estimates can be used, both in their own right and as
an ingredient of other statistical … A projection pursuit algorithm for exploratory data analysis. …
an ingredient of other statistical … A projection pursuit algorithm for exploratory data analysis. …
[BOOK][B] Assignment methods in combinational data analysis
L Hubert - 1986 - books.google.com
… This book carries the same logic over to a variety of different data analysis situations. In
all cases, the concern is with evaluating some observed index in relation to a specific …
all cases, the concern is with evaluating some observed index in relation to a specific …
Robust statistics in data analysis—A review: Basic concepts
M Daszykowski, K Kaczmarek… - … and intelligent laboratory …, 2007 - Elsevier
… described by such statistics as data mean, standard … of the data, multivariate chemometric
data analysis techniques ought to be applied. Steps of data analysis usually lead through data …
data analysis techniques ought to be applied. Steps of data analysis usually lead through data …
[BOOK][B] Computational statistical mechanics
WG Hoover - 2012 - books.google.com
… This book aims to use the tools of computation and simulation and the useful … of statistical
mechanics established by Maxwell, Boltzmann, and Gibbs to the concepts and computational …
mechanics established by Maxwell, Boltzmann, and Gibbs to the concepts and computational …
Principal component analysis of interval data: a symbolic data analysis approach
Summary The present paper deals with the study of continuous interval data by means of
suitable Principal Component Analyses (PCA). Statistical units described by interval data can …
suitable Principal Component Analyses (PCA). Statistical units described by interval data can …
A non-parametric method to estimate the number of clusters
… statistic, a non-parametric and data-driven method for determining the number of clusters in
a dataset. The slope statistic … and does not require intensive computations. Furthermore, it …
a dataset. The slope statistic … and does not require intensive computations. Furthermore, it …
Theoretical and practical aspects of the quadratic error in the local linear estimation of the conditional density for functional data
M Rachdi, A Laksaci, J Demongeot, A Abdali… - Computational Statistics …, 2014 - Elsevier
… The usefulness of the estimator is highlighted through the exact expression involved in the
leading terms of the quadratic error, and by conducting a computational investigation to show …
leading terms of the quadratic error, and by conducting a computational investigation to show …