搜索结果: 1-15 共查到“统计学 sensitivity”相关记录18条 . 查询时间(0.072 秒)
Best (but oft-forgotten) practices: sensitivity analyses in randomized controlled trials
analysis commentary sensitivity statistics tutorial
2018/11/23
Arandomized controlled clinical trial is the best way to minimize bias in ascertaining treatment effects, but the credibility of the results of a trial depends on the validity of the methods used to a...
HRF estimation improves sensitivity of fMRI encoding and decoding models
fMRI hemodynamic HRF GLM BOLD en-coding decoding
2013/6/14
Extracting activation patterns from functional Magnetic Resonance Images (fMRI) datasets remains challenging in rapid-event designs due to the inherent delay of blood oxygen level-dependent (BOLD) sig...
In a model of the form $Y=h(X_1,\ldots,X_d)$ where the goal is to estimate a parameter of the probability distribution of $Y$, we define new sensitivity indices which quantify the importance of each v...
Goal-oriented error estimation for reduced basis method, with application to certified sensitivity analysis
reduced basis method surrogate model reduced order modelling re-sponse surface method scientific computation sensitivity analysis Sobol index computation Monte-Carlo method
2013/5/2
The reduced basis method is a powerful model reduction technique designed to speed up the computation of multiple numerical solutions of parameterized partial differential equations (PDEs). We conside...
Generalized Sobol sensitivity indices for dependent variables: numerical methods
Dependent variables Extended basis Greedy algorithm LARS Sensitivity analysis Sobol decomposition
2013/4/28
The hierarchically orthogonal functional decomposition of any measurable function f of a random vector X=(X_1,...,X_p) consists in decomposing f(X) into a sum of increasing dimension functions dependi...
We define and study a generalization of Sobol sensitivity indices for the case of a vector output.
Global sensitivity analysis of a numerical code, more specifically estimation of Sobol indices associated with input variables, generally requires a large number of model runs.
Reproducing kernels for spaces of zero mean functions. Application to sensitivity analysis
Kernel Methods Global Sensitivity Analysis Sobol-Hoeffding Decomposition
2011/7/6
Given a Reproducing Kernel Hilbert Space (H, h., .i) of real-valued functions and a suitable measure \mu over the source space, we decompose H as sum of a subspace of centered functions for {\mu} and ...
Geometric sensitivity of random matrix results: consequences for shrinkage estimators of covariance and related statistical methods
random matrix related statistical shrinkage estimators
2011/6/16
Shrinkage estimators of covariance are an important tool in modern applied and theoretical statistics.
They play a key role in regularized estimation problems, such as ridge regression (aka Tykhonov
...
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...
Identification, Inference and Sensitivity Analysis for Causal Mediation Effects
Causal inference causal mediation analysis direct and indirect effects linear structural equation models
2010/11/9
Causal mediation analysis is routinely conducted by applied researchers in a variety of disciplines. The goal of such an analysis is to investigate alternative causal mechanisms by examining the roles...
The Sensitivity of Respondent-driven Sampling Method
directed network hidden population network respondent-driven sampling RDS sensitivity
2010/3/10
Researchers in many scientific fields make inferences from individuals to larger groups. For many groups however,there is no list of members from which to take a random sample. Respondent-driven sampl...
On the role of contamination level and the least favourable bahaviour of gross-error sensitivity
the role of contamination level the least favourable bahaviour gross-error sensitivity
2009/9/23
The notion of contamination level is introduced and its
characterization for any pair of distribution functions is given.
A possibility of reformulation of some basic problems of the robust
statist...
Sensitivity of principal Hessian direction analysis
dimension reduction influence function influential observations principal hessian directions
2009/9/16
We provide sensitivity comparisons for two competing versions of the dimension reduction method principal Hessian directions (pHd). These comparisons consider the effects of small perturbations on the...
A note on sensitivity of principal component subspaces and the efficient detection of influential observations in high dimensions
distance between subspaces influential observations perturbation principal component analysis
2009/9/16
In this paper we introduce an influence measure based on second order expansion of the RV and GCD measures for the comparison between unperturbed and perturbed eigenvectors of a symmetric matrix estim...