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On Approximation of the Backward Stochastic Differential Equation
Backward SDE approximation of the solution small noise asymptotics
2013/6/14
We consider the problem of approximation of the solution of the backward stochastic differential equation in the Markovian case. We suppose that the trend coefficient of the diffusion process depends ...
False Discovery Rate Control under Archimedean Copula
Clayton copula exchangeability Gumbel cop-ula linear step-up test multiple hypotheses testing,p-values
2013/6/14
We prove that the linear step-up procedure $\vp^{LSU}$ considered by Benjamini and Hochberg (1995) controls the false discovery rate (FDR) in the case of dependent $p$-values whose dependency structur...
Random Latin squares and Sudoku designs generation
Random Latin squares and Sudoku designs generation
2013/6/14
Uniform random generation of Latin squares is a classical problem. In this paper we prove that both Latin squares and Sudoku designs are maximum cliques of properly defined graphs. We have developed a...
Computing the posterior expectation of phylogenetic trees
Bayesian statistics BHV tree space Frechet mean geometric median phylogenetic trees posterior expectation
2013/6/14
Inferring phylogenetic trees from multiple sequence alignments often relies upon Markov chain Monte Carlo (MCMC) methods to generate tree samples from a posterior distribution. To give a rigorous appr...
Bayesian Functional Generalized Additive Models with Sparsely Observed Covariates
auction data functional data analysis functional regression linear mixed models measurement error MCMC penalized splines variational inference
2013/6/14
The functional generalized additive model (FGAM) was recently proposed in McLean et al. (2012) as a more flexible alternative to the common functional linear model (FLM) for regressing a scalar on fun...
Hierarchically-coupled hidden Markov models for learning kinetic rates from single-molecule data
Hierarchically-coupled hidden Markov models learning kinetic rates single-molecule data
2013/6/14
We address the problem of analyzing sets of noisy time-varying signals that all report on the same process but confound straightforward analyses due to complex inter-signal heterogeneities and measure...
Light tails: Gibbs conditional principle under extreme deviation
Light tails Gibbs conditional principle extreme deviation
2013/6/14
Let $X_{1},..,X_{n}$ denote an i.i.d. sample with light tail distribution and $S_{1}^{n}$ denote the sum of its terms; let $a_{n}$ be a real sequence\ going to infinity with $n.$\ In a previous paper ...
Ensemble Copula Coupling as a Multivariate Discrete Copula Approach
multivariate discrete copula stochastic array Sklar’s theorem statistical ensemble postprocessing ensemble copula coupling
2013/6/14
In probability and statistics, copulas play important roles theoretically as well as to address a wide range of problems in various application areas. In this paper, we introduce the concept of multiv...
Calibration diagnostics for point process models via the probability integral transform
Calibration diagnostics point process models probability integral transform
2013/6/14
We propose the use of the probability integral transform (PIT) for model validation in point process models. The simple PIT diagnostics assess the calibration of the model and can detect inconsistenci...
Efficient Density Estimation via Piecewise Polynomial Approximation
Efficient Density Estimation Piecewise Polynomial Approximation
2013/6/14
We give a highly efficient "semi-agnostic" algorithm for learning univariate probability distributions that are well approximated by piecewise polynomial density functions. Let $p$ be an arbitrary dis...
An ANOVA Test for Parameter Estimability using Data Cloning with Application to Statistical Inference for Dynamic Systems
Maximum Likelihood Estimation Over -Parametrized Models Markov Chain Monte Carlo Parameter Identifiability Differential Equation Models
2013/6/14
Models for complex systems are often built with more parameters than can be uniquely identified by available data. Because of the variety of causes, identifying a lack of parameter identifiability typ...
Stable Estimation of a Covariance Matrix Guided by Nuclear Norm Penalties
Covariance estimation Regularization Condition number Canonical correlation analysis Discriminant analysis Clustering
2013/6/14
Estimation of covariance matrices or their inverses plays a central role in many statistical methods. For these methods to work reliably, estimated matrices must not only be invertible but also well-c...
Optimization with First-Order Surrogate Functions
Optimization First-Order Surrogate Functions
2013/6/14
In this paper, we study optimization methods consisting of iteratively minimizing surrogates of an objective function. By proposing several algorithmic variants and simple convergence analyses, we mak...
Informative Bayesian inference for the skew-normal distribution
Bayesian inference Gibbs sampling Markov Chain Monte Carlo Multivariate skew-normal distribution Stochastic representation of the skew-normal Uni
2013/6/14
Motivated by the analysis of the distribution of university grades, which is usually asymmetric, we discuss two informative priors for the shape parameter of the skew-normal distribution, showing that...
Estimating the quadratic covariation of an asynchronously observed semimartingale with jumps
asynchronous observations co-jumps statistics of semimartingales quadratic covariation
2013/6/14
We consider estimation of the quadratic (co)variation of a semimartingale from discrete observations which are irregularly spaced under high-frequency asymptotics. In the univariate setting, results b...