Over 10 mio. titler Fri fragt ved køb over 499,- Hurtig levering 30 dages retur

Nonparametric Models for Longitudinal Data

- With Implementation in R

Normalpris

kr. 544,95

Medlemspris

kr. 509,95
  • Du sparer kr. 35,00
  • Fri fragt
Som medlem af Saxo Premium 20 timer køber du til medlemspris, får fri fragt og 20 timers streaming/md. i Saxo-appen. De første 7 dage er gratis for nye medlemmer, derefter koster det 99,-/md. og kan altid opsiges. Løbende medlemskab, der forudsætter betaling med kreditkort. Fortrydelsesret i medfør af Forbrugeraftaleloven. Mindstepris 0 kr. Læs mere

Beskrivelse

Nonparametric Models for Longitudinal Data with Implementations in R presents a comprehensive summary of major advances in nonparametric models and smoothing methods with longitudinal data. It covers methods, theories, and applications that are particularly useful for biomedical studies in the era of big data and precision medicine. It also provides flexible tools to describe the temporal trends, covariate effects and correlation structures of repeated measurements in longitudinal data.

This book is intended for graduate students in statistics, data scientists and statisticians in biomedical sciences and public health. As experts in this area, the authors present extensive materials that are balanced between theoretical and practical topics. The statistical applications in real-life examples lead into meaningful interpretations and inferences.

Features:





Provides an overview of parametric and semiparametric methods





Shows smoothing methods for unstructured nonparametric models





Covers structured nonparametric models with time-varying coefficients





Discusses nonparametric shared-parameter and mixed-effects models





Presents nonparametric models for conditional distributions and functionals





Illustrates implementations using R software packages





Includes datasets and code in the authors’ website





Contains asymptotic results and theoretical derivations



Both authors are mathematical statisticians at the National Institutes of Health (NIH) and have published extensively in statistical and biomedical journals. Colin O. Wu earned his Ph.D. in statistics from the University of California, Berkeley (1990), and is also Adjunct Professor at the Georgetown University School of Medicine. He served as Associate Editor for Biometrics and Statistics in Medicine, and reviewer for National Science Foundation, NIH, and the U.S. Department of Veterans Affairs. Xin Tian earned her Ph.D. in statistics from Rutgers, the State University of New Jersey (2003). She has served on various NIH committees and collaborated extensively with clinical researchers.

Læs hele beskrivelsen
Detaljer
  • SprogEngelsk
  • Sidetal552
  • Udgivelsesdato30-06-2020
  • ISBN139780367571665
  • Forlag Chapman & Hall/CRC
  • FormatPaperback
Størrelse og vægt
  • Vægt453 g
  • coffee cup img
    10 cm
    book img
    15,6 cm
    23,4 cm

    Anmeldelser

    Vær den første!

    Log ind for at skrive en anmeldelse.

    Findes i disse kategorier...