搜索结果: 1-15 共查到“统计学 Parameter Estimation”相关记录25条 . 查询时间(0.1 秒)
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...
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 the stochastic Morris-Lecar neuronal model with particle filter methods
Parameter estimatio stochastic Morris-Lecar neuronal mode particle filter methods
2012/9/19
In this paper, we consider the classic measurement error regression scenario in which our independent,or design, variables are observed with several sources of additive noise. We will show that our mo...
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...
Parameter estimation in a spatial unit root autoregressive model
Spatial autoregressive processes unit root models
2011/3/23
Spatial autoregressive model $X_{k,\ell}=\alpha X_{k-1,\ell}+\beta X_{k,\ell-1}+\gamma X_{k-1,\ell-1}+\epsilon_{k,\ell}$ is investigated in the unit root case, that is when the parameters are on the b...
Parameter estimation in a spatial unit root autoregressive model
Spatial autoregressive processes unit root models
2011/3/22
Spatial autoregressive model $X_{k,\ell}=\alpha X_{k-1,\ell}+\beta X_{k,\ell-1}+\gamma X_{k-1,\ell-1}+\epsilon_{k,\ell}$ is investigated in the unit root case, that is when the parameters are on the b...
Asymptotically optimal parameter estimation under quantization constraints
Asymptotically quantization constraints parameter estimation
2011/3/18
The problem of decentralized parameter estimation is considered for diffusion-type processes whose drift coefficients are linear with respect to the unknown parameter. This problem is motivated by app...
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...