Synopsis
Preface.- List of contributors.- First- and Higher-Order Continuous Time Models for Arbitrary N Using SEM.- A Continuous Time Approach to Intensive Longitudinal Data: What, Why and How?.- On Fitting a Continuous Time Stochastic Process Model in the Bayesian Framework.- Understanding the Time Course of Interventions with Continuous Time Dynamic Models.- Continuous-Time Modeling of Panel Data with Network Structure.- Uses and Limitation of Continuous-Time Models to Examine Dyadic Interactions.- Makes Religion Happy - or Makes Happiness Religious? An Analysis of a Three-Wave Panel Using and Comparing Discrete and Continuous Time Techniques.- Mediation Modeling: Differing Perspectives on Time Alter Mediation Inferences.- Stochastic Differential Equation Models with Time-Varying Parameters.- Robustness of Time Delay Embedding to Sampling Interval Misspecification.- Recursive Partitioning in Continuous Time Analysis.- Continuous versus Discrete Time Modelling in Growth and Business Cycle Theory.- Continuous Time State Space Modeling with an Application to High-Frequency Road Traffic Data.- Continuous Time Modelling Based on an Exact Discrete Time Representation.- Implementation of Multivariate Continuous-Time ARMA Models.- Langevin and Kalman Importance Sampling for Nonlinear Continuous-Discrete State Space Models.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
