搜索结果: 1-15 共查到“理论统计学 bias”相关记录16条 . 查询时间(0.109 秒)
Iterative bias reduction multivariate smoothing in R: The ibr package
multivariate smoothing L2 boosting thin-plate splines kernel regression R
2011/6/20
In multivariate nonparametric analysis, sparseness of the co-
variates also called curse of dimensionality, forces one to use large smoothing
parameters. This leads to a biased smoother. Instead of ...
Recursive bias estimation for multivariate regression smoothers
nonparametric regression；smoother；kernel；thin-plate splines；stopping rules
2011/6/17
This paper presents a practical and simple fully nonparametric multivariate smooth-
ing procedure that adapts to the underlying smoothness of the true regression function. Our
estimator is easily co...
The Importance of Scale for Spatial-Confounding Bias and Precision of Spatial Regression Estimators
Epidemiology, identifiability, mixed model,penalized likelihood random effects spatial correlation splines
2010/11/9
Residuals in regression models are often spatially correlated.Prominent examples include studies in environmental epidemiology to understand the chronic health effects of pollutants.
A Generalized Publication Bias Model
publication bias meta-analysis file-drawer hypothesis fail-safe number
2010/4/30
Scargle (2000) has discussed Rosenthal&Rubin's (1978) "fail-safe number" (FSN)
method for estimating the number of unpublished studies in meta-analysis. He concluded
that this FSN cannot possibly be...
Does adjustment for measurement error induce positive bias if there is no true association?
adjustment measurement error positive bias true association
2010/3/18
This article is a response to an off-the-record discussion that I had at an international meeting of epidemiologists. It centered on a concern, perhaps widely spread, that measurement error
adjustmen...
Relative Age Effect in Elite Sports:Methodological Bias or Real Discrimination?
Relative Age Effect Soccer Discrimination Bias
2010/3/9
Sport sciences researchers talk about a relative age effect when they observe a biased
distribution of elite athletes’ birthdates, with an over-representation of those born at the
beginning of the c...
Relaxation Penalties and Priors for Plausible Modeling of Nonidentified Bias Sources
Bias biostatistics causality epidemiology measurement error misclassification observational studies odds ratio relative risk
2010/3/9
In designed experiments and surveys, known laws or de-
sign feat ures provide checks on the most relevant aspects of a model
and identify the target parameters. In contrast, in most observational
s...
On minimum bias and variance estimation for parametric models with shrinking contamination
minimum bias and variance estimation parametric models shrinking contamination
2009/9/24
A close relationship is derived between optimal Mestimation
and optimal robust testing for shrinking contaminations.
Explicit formulas are given for solutions when the loss is defined as
convex com...
The papex deals with the concept of robustness given
by Zielidski (see [17J and [18]). The uniformly most bias-robust
estimates of the scale parameter, based on order statistics and
spacings, for s...
A Method for Avoiding Bias from Feature Selection with Application to Naive Bayes Classification Models
feature selection optimistic bias naive Bayes models gene expression data
2009/9/22
For many classication and regression problems, a large number of
features are available for possible use this is typical of DNA microarray data
on gene expression, for example. Often, for computatio...
BOUNDS ON THE BIAS OF APPROXIMATION OF FRACTIONAL RECORD VALUES
Fractional record values projection method Moriguti's inequality variation diminishing property
2009/9/18
We present sharp bounds for an approximation of f r a ~
tiond kth record values by convex combinations of ordinary kth
record values. The bounds are expressed in different scale units measured
in p...
Bias Corrected Maximum Likelihood Estimators in Nonlinear Overdispersed Models
Maximum Likelihood Estimators Nonlinear Overdispersed Models
2009/9/17
Bias Corrected Maximum Likelihood Estimators in Nonlinear Overdispersed Models。
A Unified Approach for Predicting Long- and Short-Term Capability Indices with Dependence on Manufacturing Target Bias
Manufacturing statistics
2009/9/3
It is shown that the exact solution for the capability index (CPI) for Gaussian-distributed process with target bias can be expressed in terms of an unbiased CPI and a normalized target bias. The prin...
Analytic Bias Reduction for k-Sample Functionals
Bias reduction k–samples Nonparametric U–statistics Unbiased estimate Von Misesderivatives
2010/3/18
We give analytic methods for nonparametric bias reduction that remove the need for
computationally intensive methods like the bootstrap and the jackknife.
We call an estimate pth order if its bias h...
The sparsity and bias of the Lasso selection in high-dimensional linear regression
Penalized regression high-dimensional data variable selection bias rate consistency spectral analysis random matrices
2010/4/30
Meinshausen and Buhlmann [Ann. Statist. 34 (2006) 1436–1462]
showed that, for neighborhood selection in Gaussian graphical models,
under a neighborhood stability condition, the LASSO is consistent,
...