搜索结果: 1-15 共查到“理论统计学 parameter estimation”相关记录18条 . 查询时间(0.11 秒)
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...
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...
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...
A parameter estimation method based on random slow manifolds
Parameter estimation Slow-fast system Random slow manifold Quantifying uncer-tainty Numerical optimization
2013/5/2
A parameter estimation method is devised for a slow-fast stochastic dynamical system, where often only the slow component is observable. By using the observations only on the slow component, the syste...
Parameter estimation in high dimensional Gaussian distributions
high dimensional Gaussian Parameter estimation massive memory
2011/6/20
In order to compute the log-likelihood for high dimensional spatial Gaussian models, it is
necessary to compute the determinant of the large, sparse, symmetric positive definite precision
matrix, Q....
Hidden Markov Mixture Autoregressive Models: Parameter Estimation
Hidden Markov Model Mixture Autoregressive Model Parameter Estimation
2011/6/17
This report introduces a parsimonious structure for mixture of au-
toregressive models, where the weighting coefficients are determined
through latent random variables as functions of all past obser...
Manifold-Based Signal Recovery and Parameter Estimation from Compressive Measurements
Manifolds dimensionality reduction random projections Compressive Sensing spar-sity signal recovery parameter estimation
2010/3/10
A field known as Compressive Sensing (CS) has recently emerged to help address the growing
challenges of capturing and processing high-dimensional signals and data sets. CS exploits the
surprising f...
Parameter Estimation in Continuous Time Markov Switching Models: A Semi-Continuous Markov Chain Monte Carlo Approach
Bayesian inference data augmentation hidden Markov model
2009/9/24
In this paper,we combine useful aspects of both approaches.On the one hand,we are inspired by the discretization, where filtering for the state process is possible,on the other hand,we
catch attracti...
Computational Methods for Parameter Estimation in Climate Models
Parametric Uncertainties InverseProblems SimulatedAnnealing Climate Models
2009/9/22
Intensive computational methods have been used by Earth scientists
in a wide range of problems in data inversion and uncertainty quantication such
as earthquake epicenter location and climate projec...
Filtering and parameter estimation for a jump stochastic process with discrete observations
Filtering parameter estimation discrete observations
2009/3/19
A compound Poisson process is considered. We estimate the current position of the stochastic process based on past discrete-time observations (non-linear discrete filtering problem) in Bayesian settin...
Parameter estimation for fractional Ornstein-Uhlenbeck processes
Parameter estimation fractional Ornstein-Uhlenbeck processes
2010/3/17
We study a least squares estimator bT for the Ornstein-Uhlenbeck
process, dXt = Xtdt+dBHt , driven by fractional Brownian motion BH
with Hurst parameter H 12 . We prove the strong consistence o...
Parameter estimation for computationally intensive nonlinear regression with an application to climate modeling
Equilibrium climate sensitivity observed and modeled climate space–time modeling statistical surrogate temperature data
2010/3/17
Nonlinear regression is a useful statistical tool, relating observed
data and a nonlinear function of unknown parameters. When the
parameter-dependent nonlinear function is computationally intensive...
Parameter Estimation in Manneville-Pomeau Processes
Manneville-Pomeau Maps Long and Not so Long Dependence Estimation Autocorrelation Decay
2010/4/30
In this work we study a class of stochastic processes {Xt}t2N, where Xt = (◦ T t
s )(X0) is obtained from the iterations of the transformation Ts, invariant for an ergodic probability μs on [0,...