搜索结果: 1-14 共查到“STATISTICAL ESTIMATION”相关记录14条 . 查询时间(0.093 秒)
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Weak values as statistical estimation
统计估计 弱值 量子可观测值 最小方差
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2023/11/15
Given a quantum observable and a state, one can construct a classical observable, such that it is the optimal estimate of the quantum observable, in the sense of minimum variance. We demonstrate how t...
DISCUSSION:THE DANTZIG SELECTOR:STATISTICAL ESTIMATION WHEN p IS MUCH LARGER THAN n
DANTZIG SELECTOR STATISTICAL ESTIMATION p IS MUCH LARGER THAN n
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2015/8/21
This is a fascinating paper on an important topic: the choice of predictor variables in large-scale linear models. A previous paper in these pages attacked the same problem using the “LARS” algorithm ...
The Dantzig selector:statistical estimation when p is much larger than n
Statistical linear model model selection ideal estimation oracle inequalities sparse solutions to underdetermined systems `1-minimization linear programming restricted orthonormality geometry in high dimensions random matrices
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2015/6/17
In many important statistical applications, the number of variables or parameters p is much larger than the number of observations n. Suppose then that we have observations y = Xβ + z, where β ∈ Rp is...
Modern statistical estimation via oracle inequalities
Modern statistical estimation oracle inequalities
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2015/6/17
A number of fundamental results in modern statistical theory involve thresholding estimators. This survey paper aims at reconstructing the history of how thresholding rules came to be popular in stati...
REJOINDER: THE DANTZIG SELECTOR:STATISTICAL ESTIMATION WHEN P IS MUCH LARGER THAN N
DANTZIG SELECTOR STATISTICAL ESTIMATION MUCH LARGER THAN N
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2015/6/17
First of all, we would like to thank all the discussants for their interest and comments, as well as for their thorough investigation. The comments all underlie the importance and timeliness of the to...
Supplementary materials for Statistical Estimation and Testing via the Sorted 1 Norm
Supplementary materials Statistical Estimation Sorted 1 Norm
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2015/6/17
In this note we give a proof showing that even though the number of false discoveries and the total number of discoveries are not continuous functions of the parameters, the formulas we obtain for the...
Statistical Estimation and Testing via the Sorted 1 Norm
Sparse regression variable selection false discovery rate lasso sorted 1 penalized estimation (SLOPE) prox operator
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2015/6/17
We introduce a novel method for sparse regression and variable selection, which is inspired by modern ideas in multiple testing. Imagine we have observations from the linear model y = Xβ + z, then we ...
UPDATING AND SPECIFICATION CHANGES - STATISTICAL ESTIMATION OF WORKLOAD
UPDATING AND SPECIFICATION STATISTICAL ESTIMATION WORKLOAD
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2015/3/16
UPDATING AND SPECIFICATION CHANGES - STATISTICAL ESTIMATION OF WORKLOAD.
Statistical estimation of quadratic Rényi entropy for a stationary m-dependent sequence
Entropy estimation quadratic R′enyi entropy stationarym-dependent sequence inter-point distances U-statistics
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2013/4/27
The R\'enyi entropy is a generalization of the Shannon entropy and is widely used in mathematical statistics and applied sciences for quantifying the uncertainty in a probability distribution. We cons...
Certain Relations between Mutual Information and Fidelity of Statistical Estimation
Certain Relations Mutual Information Fidelity of Statistical Estimation
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2010/10/19
I present several new relations between mutual information (MI) and statistical estimation error for a system that can be regarded simultaneously as a communication channel and as an estimator of an ...
Thresholded Lasso for high dimensional variable selection and statistical estimation
Linear regression Lasso Gauss-Dantzig Selector 1 regularization 0 penalty multiple-stepprocedure ideal model selection
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2010/3/10
Given n noisy samples with p dimensions, where n p, we show that the multi-step thresholding procedure based on the Lasso – we call it the Thresholded Lasso, can accurately estimate a sparse vector ...
About one problem of Bernoulli and Euler from the theory of statistical estimation
Asymptotic normality sample mean Bernoulli’s estimator Euler’s estimator maximum likelihood unbiased estimator
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2009/2/23
We consider some results by D. Bernoulli and L. Euler on the method of maximum likelihood in
parametric estimation. The statistical analysis is made by considering a parametric family with a shift pa...
What does intrinsic mean in statistical estimation？
Intrinsic bias mean square Rao distance information metric
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2009/2/23
In this paper we review different meanings of the word intrinsic in statistical estimation, focusing our attention on the use of this word in the analysis of the properties of an estimator.We review t...
Statistical estimation of stratospheric particle size distribution by combining optical modelling and lidar scattering measurements
stratospheric particle optical modelling lidar scattering
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2008/11/19
A method for estimating the stratospheric particle size distribution from multiwavelength lidar measurements is presented. It is based on matching measured and model-simulated backscatter coefficients...