搜索结果: 1-15 共查到“统计学 Inverse”相关记录40条 . 查询时间(0.135 秒)
The Inverse Weibull Survival Distribution and its Proper Application
Mean residual life Model selection UBT shaped hazard rate
2013/6/14
The peculiar properties of the Inverse Weibull (IW) distribution are shown. It is proven that the IW distribution is one of the few models having upside- down bathtub (UBT) shaped hazard function. Thr...
Estimating Network Degree Distributions Under Sampling: An Inverse Problem, with Applications to Monitoring Social Media Networks
Estimating Network Degree Distributions Sampling An Inverse Problem Applications Monitoring Social Media Networks
2013/6/14
Networks are a popular tool for representing elements in a system and their interconnectedness. Many observed networks can be viewed as only samples of some true underlying network. Such is frequently...
A New Global Stochastic Search Approach for Inverse Problems: Application to Ultrasound Modulated Optical Tomography
inverse problems global stochastic search discretized Kushner-Stratonovich equation gain-based update ultrasound modulated optical tomography
2013/6/14
A global stochastic search method, which is strictly derivative-free yet directed through a gain-based additive update term, is proposed and applied to the inverse problem of ultrasound modulated opti...
Practical Tikhonov Regularized Estimators in Reproducing Kernel Hilbert Spaces for Statistical Inverse Problems
Tikhonov Regularized Estimators Reproducing Kernel Hilbert Spaces Statistical Inverse Problems
2013/6/13
Regularized kernel methods such as support vector machines (SVM) and support vector regression (SVR) constitute a broad and flexible class of methods which are theoretically well investigated and comm...
Additive inverse regression models with convolution-type operators
Inverse regression Additive models Convolution-type operators Mathematical subject codes: primary 62G08 secondary 62G15 62G20
2013/4/27
In a recent paper Birke and Bissantz (2008) considered the problem of nonparametric estimation in inverse regression models with convolution-type operators. For multivariate predictors nonparametric m...
Inverse Signal Classification for Financial Instruments
time-series classification signal analysis decision tree learning
2013/4/28
The paper presents new machine learning methods: signal composition, which classifies time-series regardless of length, type, and quantity; and self-labeling, a supervised-learning enhancement. The pa...
On characteristics of an ordinary differential equation and a related inverse problem in epidemiology
Chronic disease Compartment model Incidence Mortality Prevalence Population
2012/9/18
In this work we examine the properties of a recently described ordinary differential equation that relates the age-specific prevalence of achronic dis-ease with the incidence and mortalities of the di...
Inverse Modeling of Dynamical Systems: Multi-Dimensional Extensions of a Stochastic Switching Problem
Inverse Modeling of Dynamical Systems Multi-Dimensional Extensions Stochastic Switching Problem
2012/9/18
The Buridan's ass paradox is characterized by perpetual indecision between two states, which are never attained. When this problem is formulated as a dynamical
system, indecision is modeled by a disc...
Efficient Estimators for Sequential and Resolution-Limited Inverse Problems
deconvolution ill-posed image processing sig-nal recovery
2012/9/18
A common problem in the sciences is that a signal of interest is observed only indirectly, through smooth functionals of the signal whose values are then obscured by noise. In suchinverse problems, th...
An Interpretation of the Moore-Penrose Generalized Inverse of a Singular Fisher Information Matrix
Fisher Information Matrix Moore-Penrose
2011/7/19
An interpretation of the Moore-Penrose generalized inverse of a singular Fisher information matrix (FIM) is presented in this paper, from the perspective of Cramer-Rao bound (CRB). CRB is a lower boun...
Sparse Inverse Covariance Estimation via an Adaptive Gradient-Based Method
Sparse Covariance Estimation Adaptive Gradient-Based Method
2011/7/6
We study the problem of estimating from data, a sparse approximation to the inverse covariance matrix. Estimating a sparsity constrained inverse covariance matrix is a key component in Gaussian graphi...
Bayesian multitask inverse reinforcement learning
Bayesian inference multitask learning inverse reinforce-ment learning
2011/7/6
We generalise the problem of inverse reinforcement learning to multiple tasks, from a set of demonstrations. Each demonstration may represent one expert trying to solve a different task.
Estimation of covariance matrices based on hierarchical inverse-Wishart priors
Bayesian covariance estimation Skrinkage Hierarchical Inverse-Wishart prior
2011/7/5
This paper focuses on Bayesian shrinkage for covariance matrix estimation. We examine posterior properties and frequentist risks of Bayesian estimators based on new hierarchical inverse-Wishart priors...
A two-stage hybrid procedure for estimating an inverse regression function
Two-stage estimator bootstrap adaptive design asymptotic properties
2011/6/17
We consider a two-stage procedure (TSP) for estimating an inverse
regression function at a given point, where isotonic regression
is used at stage one to obtain an initial estimate and a local linea...
Besov priors for Bayesian inverse problems
Bayesian inverse problems Fernique-like theorem
2011/6/16
We consider the inverse problem of estimating a function u from
noisy, possibly nonlinear, observations. We adopt a Bayesian approach to the
problem and widen the existing theory, which is developed...