搜索结果: 1-15 共查到“理论统计学 Asymptotic”相关记录63条 . 查询时间(0.257 秒)
Asymptotic Hodge theory and quantum products
Convergence properties the dollar polarization hodge structure quantum potential
2014/12/29
Assuming suitable convergence properties for the Gromov-Witten potential of a Calabi-Yau manifold $X$ one may construct a polarized variation of Hodge structure over the complexified K\"ahler cone of ...
Asymptotic behaviour of small solutions for the discrete nonlinear Schrödinger and Klein–Gordon equations
Discrete schrodinger propagator klein Gordon equation form the analysis of decay estimate
2014/12/29
We show decay estimates for the propagator of the discrete Schrödinger and Klein–Gordon equations in the form {{\| {U(t)f} \|}_{{l^\infty}}} \leq C (1+|t|)^{-d/3}{{\| {f} \|}_{{l^1}}} . This impl...
Asymptotic calculation of discrete non-linear wave interactions
Discrete the dispersion equation klein Gordon
2014/12/25
We illustrate how to compute asymptotic interactions between discrete solitary waves of dispersive equations, using the approach proposed by Manton [N.S. Manton, Nucl. Phys. B 150 (1979) 397]. We also...
Asymptotic stability of small solitons in the discrete nonlinear Schr¨odinger equation in one dimension
Small solitary wave one dimensional discrete nonlinear septic nonlinear power law equation
2014/12/25
Asymptotic stability of small solitons in one dimension is proved in the framework of a discrete nonlinear Schr¨odinger equation with septic and higher power-law nonlinearities and an external potenti...
Asymptotic behavior of the magnetization near critical and tricritical points via Ginzburg-Landau polynomials
Asymptotic behavior of magnetization gold landau lattice model of the spin
2014/12/25
The purpose of this paper is to prove connections among the asymptotic behavior of the magnetization, the structure of the phase transitions, and a class of polynomials that we call the Ginzburg–Landa...
Asymptotic normality of a Sobol index estimator in Gaussian process regression framework
Sensitivity analysis Gaussian process regression asymptotic normality stochas-tic simulators Sobol index
2013/6/14
Stochastic simulators such as Monte-Carlo estimators are widely used in science and engineering to study physical systems through their probabilistic representation. Global sensitivity analysis aims t...
A general approach to the joint asymptotic analysis of statistics from sub-samples
Empirical processes sub-sampling,self-normalization change point weak con-vergence Time series compact differentiability
2013/6/14
In time series analysis, statistics based on collections of estimators computed from sub-samples play a crucial role in an increasing variety of important applications. Proving results about the joint...
Asymptotic normality and efficiency of two Sobol index estimators
sensitivity analysis Sobol indices asymptotic efficiency asymptotic normality confidence intervals metamodelling surface response methodology
2013/4/28
Many mathematical models involve input parameters, which are not precisely known. Global sensitivity analysis aims to identify the parameters whose uncertainty has the largest impact on the variabilit...
Asymptotic Normality of Estimates in Flexible Seasonal Time Series Model with Weak Dependent Error Terms
seasonal time series model local linear estimates consistency and asymptotic
2013/5/2
In this paper we considered a general seasonal time series model with K-dependent and \rambda-dependent errors, which are new concepts of dependence. In this model we derived consistency and asymptoti...
Variance estimation and asymptotic confidence bands for the mean estimator of sampled functional data with high entropy unequal probability sampling designs
covariance function finite population Hajek approximation Horvitz-Thompso estimator Kullback-Leibler divergence rejective sampling unequal probability sampling without replacement
2012/11/23
For fixed size sampling designs with high entropy it is well known that the variance of the Horvitz-Thompson estimator can be approximated by the H\'ajek formula. The interest of this asymptotic varia...
An estimator for the quadratic covariation of asynchronously observed Itô processes with noise: Asymptotic distribution theory
Density estimation Kullback–Leibler divergence
2011/7/6
The article is devoted to the nonparametric estimation of the quadratic covariation of non-synchronously observed It\^o processes in an additive microstructure noise model.
Asymptotic probability distribution of distances between local extrema of error terms of a moving average process
distance between local extremum maximum extrema probability density distribution function average random stochastic moving average
2011/6/20
Consider error terms i of a moving average process MA(q), where
i = Pq
j=0 "i−j and "i - independent identically distributed (i.i.d.) random
variables. We recognize a term i as a local max...
Asymptotic Behaviour of Approximate Bayesian Estimators
Parameter Estimation Hidden Markov Model Maximum Likelihood Approximate Bayesian Computation Sequential Monte Carlo
2011/6/20
Although approximate Bayesian computation (ABC) has become
a popular technique for performing parameter estimation when the
likelihood functions are analytically intractable there has not as yet
be...
Asymptotic Inference of Autocovariances of Stationary Processes
Autocovariance blocks of blocks bootstrapping Box-Pierce test extreme value distribution moderate deviation normal comparison physical dependence measure short range dependence stationary process summability of cumulants
2011/6/17
The paper presents a systematic theory for asymptotic inference of autocovariances of
stationary processes.We consider nonparametric tests for serial correlations based on the maximum (or
L1) and th...
Asymptotic properties of maximum likelihood estimators in models with multiple change points
change-point fraction common parameter consistency convergence rate Kullback–Leibler distance within-segment parameter
2011/3/24
Models with multiple change points are used in many fields; however, the theoretical properties of maximum likelihood estimators of such models have received relatively little attention. The goal of t...