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    Longitudinal Data with Serial Correlation

    Longitudinal Data with Serial Correlation

    - A State-Space Approach

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    Bog E-bog
    • Format
    • Bog, paperback
    • Engelsk

    Beskrivelse

    This monograph is written for students at the graduate level in biostatistics, statistics or other disciplines that collect longitudinal data. It concentrates on the state space approach that provides a convenient way to compute likelihoods using the Kalman filter.

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    Detaljer
    • SprogEngelsk
    • Sidetal240
    • Udgivelsesdato02-12-2019
    • ISBN139780367450083
    • Forlag Chapman & Hall/CRC
    • FormatPaperback
    Størrelse og vægt
  • Vægt453 g
    • coffee cup img
    10 cm
    book img
    15,2 cm
    22,9 cm

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    Conditional expectation State Vector Kalman Filter EM algorithm Random input Covariance matrix ARMA Process Autoregression Coefficient ARMA Coefficient Continuous Time State Space Models Compound Symmetry Discrete Time State Space Representation Cholesky Factorization Laird Ware Model Ln Likelihood Kalman Recursion Observational Error Variance Nonparametric Wilcoxon Rank Sum Test Subject’s Random Effects Yule Walker Equation Multivariate Growth Curve Model Log Insulin Observation Error Standard Deviation Non-negative Real Part State Covariance Matrix
    Machine Name: SAXO081