搜索结果: 61-75 共查到“知识库 卫生统计学”相关记录82条 . 查询时间(3.376 秒)
Robust nonparametric detection of objects in noisy images
Image analysis signal detection image recon-struction percolation noisy image nonparametric noise robust testing nite sample performance
2011/3/24
We propose a novel statistical hypothesis testing method for detection of objects in noisy images. The method uses results from percolation theory and random graph theory. We present an algorithm that...
Confidence intervals for sensitivity indices using reduced-basis metamodels
sensitivity analysis reduced basis method Sobol indices bootstrap method Monte Carlo method
2011/3/24
Global sensitivity analysis is often impracticable for complex and time demanding numerical models, as it requires a large number of runs. The reduced-basis approach provides a way to replace the orig...
Improved RIP Analysis of Orthogonal Matching Pursuit
compressive sensing sparse approximation orthogonal matching pursuit restricted isometry property greedy algorithms error bounds
2011/3/25
Orthogonal Matching Pursuit (OMP) has long been considered a powerful heuristic for attacking compressive sensing problems; however, its theoretical development is, unfortunately, somewhat lacking. Th...
Missing Data Imputation and Corrected Statistics for Large-Scale Behavioral Databases
missing data imputation statistics corrected for missing data item performance behavioral databases model goodness of fit
2011/3/23
This paper presents a new methodology to solve problems resulting from missing data in large-scale item performance behavioral databases. Useful statistics corrected for missing data are described, an...
Tight conditions for consistent variable selection in high dimensional nonparametric regression
Tight conditions for consistent variable selection high dimensional nonparametric regression
2011/3/23
We address the issue of variable selection in the regression model with very high ambient dimension, i.e., when the number of covariates is very large. The main focus is on the situation where the num...
Comment: Quantifying the Fraction of Missing Information for Hypothesis Testing in Statistical and Genetic Studies
Quantifying Statistical Genetic Studies
2011/3/21
Comment on "Quantifying the Fraction of Missing Information for Hypothesis Testing in Statistical and Genetic Studies" [arXiv:1102.2774]
Comment: Quantifying the Fraction of Missing Information for Hypothesis Testing in Statistical and Genetic Studies
Quantifying Statistical Genetic Studies
2011/3/21
Comment on "Quantifying the Fraction of Missing Information for Hypothesis Testing in Statistical and Genetic Studies" [arXiv:1102.2774]
Comment: Quantifying Information Loss in Survival Stud
Quantifying Information Survival Stud Comment
2011/3/21
Comment on "Quantifying the Fraction of Missing Information for Hypothesis Testing in Statistical and Genetic Studies"[arXiv:1102.2774]
Kernel density estimation (KDE) is a popular statistical technique for estimating the underlying density distribution with minimal assumptions. Although they can be shown to achieve asymptotic estima...
On the Levy density function
density function fractional calculus Mellin convolution operator
2011/3/21
In this paper, we introduce the Levy density function as the limit of a generalized Mittag-Leffler density function. The fractional integral equation for the generalized Mittag-Leffler density functio...
Limiting Laws of Coherence of Random Matrices with Applications to Testing Covariance Structure and Construction of Compressed Sensing Matrices
Chen-Stein method coherence compressed sensing matrix covariance struc-ture law of large numbers limiting distribution maxima moderate deviations mutual incoherence property random matrix sample correlation matrix
2011/3/23
Testing covariance structure is of significant interest in many areas of statistical analysis and construction of compressed sensing matrices is an important problem in signal processing. Motivated b...
Estimating and Understanding Exponential Random Graph Models
Random graph Erd-os-Renyi graph limit Exponential Random Graphs param-eter estimation
2011/3/25
We introduce a new method for estimating the parameters of exponential random graph models. The method is based on a large-deviations approximation to the normalizing constant shown to be consistent u...
Estimating conditional quantiles with the help of the pinball loss
nonparametric regression quantile estimation support vector machines
2011/3/21
The so-called pinball loss for estimating conditional quantiles is a well-known tool in both statistics and machine learning. So far, however, only little work has been done to quantify the efficiency...
Compressible Priors for High-dimensional Statistics
linear inverse problem LASSO sparsity sparse regression ridge regression com-pressible prior compressive sensing instance optimality maximum a posteriori high-dimensional statistics order statistics
2011/3/18
We develop a principled way of identifying probability distributions whose independent and identically distributed (iid) realizations are compressible, i.e., can be approximated as sparse. We focus on...
Chi-square Intervals for a Poisson Parameter - Bayes, Classical and Structural
Confidence interval coverage probability estimation interval Poisson
2011/3/18
The 'standard' confidence interval for a Poisson parameter is only one of a number of estimation intervals based on the chi-square distribution that may be used in the estimation of the mean or mean r...