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The research on the local correlation structure of copula function is an attractive topic.This paper investigates bivariate copula function’s local correlation structure by defining its concentration ...
This is the first of a series of papers which is devoted to a comprehensive theory of maps between orbifolds. In this paper, we define the maps in the more general context of orbispaces, and establish...
In this paper we show how to use Fourier transform methods to analyze the asymptotic behavior of kernel distribution function estimators. Exact expressions for the mean integrated squared error in ter...
We develop the basic building blocks of a frequency domain framework for drawing statistical inferences on the second-order structure of a stationary sequence of functional data. The key element in su...
Bivariate extreme-value distributions have been used in modeling extremes in environmental sciences and risk management. An important issue is estimating the dependence function, such as the Pickands ...
Challenging research in various fields has driven a wide range of methodological advances in variable selection for regression models with high-dimensional predictors. In comparison, selection of nonl...
Challenging research in various fields has driven a wide range of methodological advances in variable selection for regression models with high-dimensional predictors. In comparison, selection of nonl...
The analysis of the joint cumulative distribution function (CDF) with bivariate event time data is a challenging problem both theoretically and numerically. This paper develops a tensor spline-based s...
In this paper we develop a randomized block-coordinate descent method for minimizing the sum of a smooth and a simple nonsmooth block-separable convex function and prove that it obtains an $\epsilon$-...
Our perspective in this paper follows the framework adopted by Lin et al. (2006), who intro- duced several loss functions for the identi cation of the elements of a parameter ensemble that represent...
It is shown that, if   1/2 then the generalized Marcum Q function Q(a, b) is log-concave in b 2 [0,1). This proves a conjecture of Sun, Baricz and Zhou (2010). We also point out relevant results...
The paper proposes Monte Carlo algorithms for the computation of the information rate of two-dimensional source / channel models. The focus of the paper is on binary-input channels with constraints...
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...
The LASSO is a variable subset selection procedure in statistical linear regression based on ℓ1 penalization of the least-squares operator. Its behavior crucially depends, both in practice and...
In this paper we prove central limit theorems for bias reduced estimators of the structure function of several multifractal processes, namely mutiplicative cascades, multifractal random measures, mult...

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