Parameter estimation for sigmoid Emax models in exposure-response relationship
نویسندگان
چکیده
منابع مشابه
Parameter estimation for autoregressive Gaussian-mixture processes: the EMAX algorithm
The problem of estimating parameters of discrete-time non-Gaussian autoregressive (AR) processes is addressed. The subclass of such processes considered is restricted to those whose driving noise samples are statistically independent and identically distributed according to a Gaussian-mixture probability density function (pdf). Because the likelihood function for this problem is typically unbou...
متن کاملParameter Estimation of Sigmoid Superpositions
Superposition of sigmoid function over a finite time interval is shown to be equivalent to the linear combination of the solutions of a linearly parameterized system of logistic differential equations. Due to the linearity with respect to the parameters of the system, it is possible to design an effective procedure for parameter adjustment. Stability properties of this procedure are analyzed. S...
متن کاملAdaptive optimal designs for dose-finding studies based on sigmoid Emax models
The adaptive design strategy is a feasible approach for optimal designs in dose-finding studies, where the information matrices usually depend on the unknown parameters. Focusing on three pharmacodynamics sigmoid Emax models, we derive the corresponding simple formats of the adaptive optimal designs regardless of the optimality criteria or parameters of interest. An algorithm for deriving a spe...
متن کاملA general method for parameter estimation in light-response models
Selecting appropriate initial values is critical for parameter estimation in nonlinear photosynthetic light response models. Failed convergence often occurs due to wrongly selected initial values when using currently available methods, especially the kind of local optimization. There are no reliable methods that can resolve the conundrum of selecting appropriate initial values. After comparing ...
متن کاملParameter estimation for neuron models
Methods for estimating parameters of the Hindmarsh-Rose (HR) neuron model from a single time series are investigated. Two approaches, (1) synchronization based parameter estimation and (2) adaptive observer, are presented. Both methods are applied to membrane potential data recorded from a single lateral pyloric neuron synaptically isolated from other neurons.
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Translational and Clinical Pharmacology
سال: 2017
ISSN: 2289-0882,2383-5427
DOI: 10.12793/tcp.2017.25.2.74