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Boekhandel Douwes Den Haag

Chapman & Hall/CRC The R Series

Simulation and Power Analysis Using R

Brandon LeBeau

Simulation and Power Analysis Using R

Chapman & Hall/CRC The R Series

Simulation and Power Analysis Using R

Chapman & Hall/CRC The R Series: Simulation and Power Analysis Using R

Verschijnt binnenkort

 

Primarily aimed at researchers and graduate students of statistics and data science who want to study simulation and/or power analysis. It could be particularly useful for any researcher needing to supply a power analysis for a grant funding proposal.

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€ 125,00

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Beschrijving Chapman & Hall/CRC The R Series: Simulation and Power Analysis Using R

Primarily aimed at researchers and graduate students of statistics and data science who want to study simulation and/or power analysis. It could be particularly useful for any researcher needing to supply a power analysis for a grant funding proposal. It could be used to teach a special topics course to postgraduate students.

ISBN
9781032012506
Pagina's
227
Verschijnt
Serie
Chapman & Hall/CRC The R Series
Rubriek
Wiskunde algemeen
Druk
1
Uitvoering
Hardback
Taal
Engels
Uitgever
Taylor & Francis Ltd

Computer-Aided Kinematics and Dynamics of Mechanical Systems

This open access book presents a new approach to kinematics and dynamics of a broad spectrum of mechanical systems that is based on modern analytical (differential geometry) and computational (differential equation) solution methods that enable treatment of challenging applications that conventional methods are unable to reliably simulate.

Convergence in Measure and in Category

Here, convergence in a category is *-convergence with respect to convergence except on a set of first category, just as convergence in measure is *-convergence with respect to convergence almost everywhere.

Nonparametric Inference

Provides a comprehensive and balanced treatment of both classical and modern methods in nonparametric inference. It begins with foundational topics such as order statistics, ranks, and confidence intervals for medians and percentiles, before progressing to distribution-free tests, robust estimators, regression quantiles, and U-statistics.

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