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Parameter Estimation and Model Testing for Markov Processes via Conditional Characteristic Functions
Conditional characteristic function Diffusion processes Empirical likelihood Kernel smoothing L′ evy driven processes
2016/1/19
Markov processes are used in a wide range of disciplines including finance.The transition densities of these processes are often unknown. However, the conditionalcharacteristic functions are more like...
Computation of the Maximum H_infinity-norm of Parameter-Dependent Linear Systems by a Branch and Bound Algorithm
Computation Maximum H_infinity-norm Parameter-Dependent Linear Systems Bound Algorithm
2015/7/13
For linear systems that contain unspecified parameters that lie in given intervals, we present a branch and bound algorithm for computing the maximum H_infinity-norm over the set of uncertain paramete...
Branch and Bound Algorithm for Computing the Minimum Stability Degree of Parameter-Dependent Linear Systems
Branch Bound Algorithm Computing Minimum Stability Degree Parameter-Dependent Linear Systems
2015/7/13
We consider linear systems with unspecified parameters that lie between given upper and lower bounds. Except for a few special cases, the computation of many quantities of interest for such systems ca...
Integer Parameter Estimation in Linear Models with Applications to GPS
GPS integer least-squares integer parameter estimation linear model
2015/7/10
We consider parameter estimation in linear models when some of the parameters are known to be integers. Such problems arise, for example, in positioning using phase measurements in the global position...
Simulation-based Parameter Estimation for Complex Models: A Breast Cancer Natural History Modelling Illustration
Simulation-based Parameter Estimation Complex Models Breast Cancer Natural History Modelling Illustration
2015/7/6
Simulation-based parameter estimation offers a powerful means of estimating parameters in complex stochastic models. We illustrate the application of these ideas in the setting of a natural history mo...
Specializations of one-parameter families of polynomials
K number field algebraic geometry polynomials generalized laguerre polynomials
2014/12/25
Let K be a number field, and suppose λ(x,t)∈K[x,t] is irreducible over K(t). Using algebraic geometry and group theory, we describe conditions under which the K-exceptional set of λ, i.e. the set of α...
Penalized importance sampling for parameter estimation in stochastic differential equations
Chronic wasting disease Euler-Maruyama scheme Maximum likelihood estimation Partially observed discrete sparse data Penalized importance sampling Stochastic di
2013/6/14
We consider the problem of estimating parameters of stochastic differential equations with discrete-time observations that are either completely or partially observed. The transition density between t...
An ANOVA Test for Parameter Estimability using Data Cloning with Application to Statistical Inference for Dynamic Systems
Maximum Likelihood Estimation Over -Parametrized Models Markov Chain Monte Carlo Parameter Identifiability Differential Equation Models
2013/6/14
Models for complex systems are often built with more parameters than can be uniquely identified by available data. Because of the variety of causes, identifying a lack of parameter identifiability typ...
The parameters of temporal models, such as dynamic Bayesian networks, may be modelled in a Bayesian context as static or atemporal variables that influence transition probabilities at every time step....
Species dynamics in the two-parameter Poisson-Dirichlet diffusion model
alpha diversity infinite-alleles model infinite dimensional dimensional diffusion mutation rate Poisson-Dirichlet distribution weak convergence
2013/6/14
The recently introduced two-parameter infinitely-many neutral alleles model extends the celebrated one-parameter version, related to Kingman's distribution, to diffusive two-parameter Poisson-Dirichle...
Parameter Tuning for a Multi-Fidelity Dynamical Model of the Magnetosphere
Computer Experiments Expected Improvement Geomagnetic Storm Inverse Problem Lorenz ‘96 Model Fidelity Sequential Design Uncertainty Quantification
2013/4/28
Geomagnetic storms play a critical role in space weather physics with the potential for far reaching economic impacts including power grid outages, air traffic re-routing, satellite damage and GPS dis...
On confidence intervals in regression that utilize uncertain prior information about a vector parameter
Frequentist confidence interval Prior information Linear regression
2013/4/28
Consider a linear regression model with n-dimensional response vector, p-dimensional regression parameter beta and independent normally distributed errors. Suppose that the parameter of interest is th...
Parameter estimation for fractional birth and fractional death processes
birth process Yule process Yule{Furry process death process Mittag{Leer
2013/4/28
The fractional birth and the fractional death processes are more desirable in practice than their classical counterparts as they naturally provide greater flexibility in modeling growing and decreasin...
On drift parameter estimation for reflected fractional Ornstein-Uhlenbeck processes
Reflected fractional Ornstein-Uhlenbeck processes fractional Brownian motion frac-tional calculus parameter estimation maximum likelihood estimator sequential maximum likeli-hood estimator
2013/4/28
We consider a reflected Ornstein-Uhlenbeck process driven by a fractional Brownian motion with Hurst parameter $H\in(0,1)$. Our goal is to estimate an unknown drift parameter $\alpha\in (-\infty,\inft...
Parameter estimation for pair-copula constructions
copulae efficiency empirical distribution functions hierarchical construction stepwise estimation vines
2013/4/28
We explore various estimators for the parameters of a pair-copula construction (PCC), among those the stepwise semiparametric (SSP) estimator, designed for this dependence structure. We present its as...