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Asymptotic distributions and subsampling in spectral analysis for almost periodically correlated time series
α-mixing properties almost periodically correlated time series consistency spectral analysis subsampling
2011/3/21
The aim of this article is to establish asymptotic distributions and consistency of subsampling for spectral density and for magnitude of coherence for non-stationary, almost periodically correlated t...
An asymptotic approximation of the marginal likelihood for general Markov models
Statistics Theory (math.ST)
2010/12/17
The standard Bayesian Information Criterion (BIC) is derived under regularity conditions which are not always satisfied by the graphical models with hidden variables.
Asymptotic minimax risk of predictive density estimation for non-parametric regression
asymptotic minimax risk convergence rate non-parametric regression
2010/10/19
We consider the problem of estimating the predictive density of future observations from a non-parametric regression model. The density estimators are evaluated under Kullback--Leibler divergence and ...
Asymptotic Normality of Support Vector Machines for Classification and Regression
Nonparametric regression support vector machines asymptotic normality
2010/10/14
In nonparametric classification and regression problems, support vector machines (SVMs) attract much attention in theoretical and in applied statistics. In an abstract sense, SVMs can be seen as regu...
Asymptotic distribution of conical-hull estimators of directional edges
Asymptotic distribution conical-hull estimators directional edges
2010/10/14
Nonparametric data envelopment analysis (DEA) estimators have been widely applied in analysis of productive efficiency. Typically they are defined in terms of convex-hulls of the observed combinations...
Reconsidering the asymptotic null distribution of likelihood ratio tests for genetic linkage in multivariate variance components models
asymptotic null distribution likelihood ratio test mixing probabilities multivariate linkage
2010/4/30
Accurate knowledge of the null distribution of hypothesis tests is important for valid application of the tests. In previous papers and software, the asymptotic null distribution of likelihood ratio t...
On the covariance of the asymptotic empirical copula process
Asymptotic variance copula dependence parameter empirical process independence left-tail decreasing rank-based inference
2010/3/18
Conditions are given under which the empirical copula process associated with
a random sample from a bivariate continuous distribution has a smaller asymptotic
covariance function than the standard ...
Asymptotic optimality of the cross-entropy method for Markov chain problems
Asymptotic optimality cross-entropy method Markov chain problems
2010/3/11
The correspondence between the cross-entropymethod and the zero-variance
approximation to simulate a rare event problem in Markov chains is shown. This
leads to a sufficient condition that the cross...
Asymptotic admissibility of priors and elliptic differential equations
Asymptotic admissibility priors elliptic differential equations
2010/3/11
We evaluate priors by the second order asymptotic behaviour of the
corresponding estimators. Under certain regularity conditions, the risk di erences
between ecient estimators of parameters taking ...
Asymptotic inference for high-dimensional data
Covariance matrix estimation c0 functional genomics highdimensionaldata infinite-dimensional central limit theorem
2010/3/10
In this paper, we study inference for high-dimensional data characterized
by small sample sizes relative to the dimension of the data.
In particular, we provide an infinite-dimensional framework to ...
Asymptotic results for sample autocovariance functions and extremes of integrated generalized Ornstein-Uhlenbeck processes
continuous-time GARCH process extreme value theory generalizedOrnstein–Uhlenbeck process integrated generalized Ornstein–Uhlenbeck process
2010/3/10
We consider a positive stationary generalized Ornstein–Uhlenbeck process
Vt = e−tZ t0es− ds + V0 for t 0,and the increments of the integrated generalized Ornstein–Uhlenbeck process...
The Bayes oracle and asymptotic optimality of multiple testing procedures under sparsity
Multiple testing FDR Bayes oracle asymptotic optimality
2010/3/10
We investigate the asymptotic optimality of a large class of multiple testing rules using the
framework of Bayesian Decision Theory. We consider a parametric setup, in which observations
come from a...
Sharp non-asymptotic oracle inequalities for nonparametric heteroscedastic regression models
Adaptive estimation Heteroscedastic regression Nonasymptoticestimation Nonparametric estimation Oracle inequality
2010/3/10
An adaptive nonparametric estimation procedure is constructed
for heteroscedastic regression when the noise variance depends on the
unknown regression. A non-asymptotic upper bound for a quadratic
...
Asymptotic equivalence and sufficiency for volatility estimation under microstructure noise
High-frequency data integrated volatility spot volatilityestimation Le Cam deficiency equivalence of experiments
2010/3/9
The basic model for high-frequency data in finance is considered,
where an efficient price process is observed under microstructure noise.
It is shown that this nonparametric model is in Le Cam’s se...
Asymptotic efficiency and finite-sample properties of the generalized profiling estimation of parameters in ordinary differential equations
Ordinary differential equations parameters estimation profiling procedure consistency asymptotic normality
2010/3/18
Ordinary differential equations (ODEs) are commonly used to
model dynamic behavior of a system. Because many parameters are
unknown and have to be estimated from the observed data, there
is growing...