A review on estimation of stochastic differential equations for pharmacokinetic/pharmacodynamic models
This paper is a survey of existing estimation methods for pharmacokinetic/pharmacodynamic
(PK/PD) models based on stochastic differential equations (SDEs). Most parametric …
(PK/PD) models based on stochastic differential equations (SDEs). Most parametric …
[BOOK][B] Mixed effects models for the population approach: models, tasks, methods and tools
M Lavielle - 2014 - books.google.com
Wide-Ranging Coverage of Parametric Modeling in Linear and Nonlinear Mixed Effects
Models Mixed Effects Models for the Population Approach: Models, Tasks, Methods and …
Models Mixed Effects Models for the Population Approach: Models, Tasks, Methods and …
Singularity, misspecification and the convergence rate of EM
A line of recent work has analyzed the behavior of the Expectation-Maximization (EM)
algorithm in the well-specified setting, in which the population likelihood is locally strongly …
algorithm in the well-specified setting, in which the population likelihood is locally strongly …
On collocation-Galerkin method and fractional B-spline functions for a class of stochastic fractional integro-differential equations
I Masti, K Sayevand - Mathematics and Computers in Simulation, 2024 - Elsevier
In recent years, as detailed in several monographs, derivations of the fractional differential
equations and fractional integral equations are based on random functional or stochastic …
equations and fractional integral equations are based on random functional or stochastic …
[BOOK][B] Dynamical biostatistical models
D Commenges, H Jacqmin-Gadda - 2015 - books.google.com
This book presents statistical models and methods for the analysis of longitudinal data. It
focuses on models for analyzing repeated measures of quantitative and qualitative variables …
focuses on models for analyzing repeated measures of quantitative and qualitative variables …
Nadaraya–Watson estimator for IID paths of diffusion processes
This paper deals with a nonparametric Nadaraya–Watson (NW) estimator of the drift function
computed from independent continuous observations of a diffusion process. Risk bounds on …
computed from independent continuous observations of a diffusion process. Risk bounds on …
Nonparametric drift estimation for iid paths of stochastic differential equations
F Comte, V Genon-Catalot - The Annals of Statistics, 2020 - JSTOR
We consider N independent stochastic processes (** (t), t∈[0, T]), i= 1,..., N, defined by a
one-dimensional stochastic differential equation, which are continuously observed …
one-dimensional stochastic differential equation, which are continuously observed …
Practical estimation of high dimensional stochastic differential mixed-effects models
Stochastic differential equations (SDEs) are established tools for modeling physical
phenomena whose dynamics are affected by random noise. By estimating parameters of an …
phenomena whose dynamics are affected by random noise. By estimating parameters of an …
Particle methods for stochastic differential equation mixed effects models
Particle Methods for Stochastic Differential Equation Mixed Effects Models Page 1 Bayesian
Analysis (2021) 16, Number 2, pp. 575–609 Particle Methods for Stochastic Differential …
Analysis (2021) 16, Number 2, pp. 575–609 Particle Methods for Stochastic Differential …
Maximum likelihood estimation for stochastic differential equations with random effects
M Delattre, V GENON‐CATALOT… - … Journal of Statistics, 2013 - Wiley Online Library
We consider N independent stochastic processes (** (t), t∈[0, Ti]), i= 1,…, N, defined by a
stochastic differential equation with drift term depending on a random variable φi. The …
stochastic differential equation with drift term depending on a random variable φi. The …