搜索结果: 151-165 共查到“管理学 regression”相关记录247条 . 查询时间(0.092 秒)
An asymptotic fixed-precision confidence interval for the minimum of a quandratic regression function
An asymptotic fixed-precision confidence interval a quandratic regression function
2009/9/23
An asymptotic fixed-precision confidence interval for the minimum of a quandratic regression function。
An omnibus test of fit for Cox's proportional hazards
regression model is proposed for continuous data. The vrocedure is
extended to a random censorship model. Density estimation methods
are used.
A process based on stratification for Cox's regression model
A process based on stratification Cox's regression model
2009/9/23
A process based on stratification to check the proportional
hazards assumption in a general Cox's regression model is
considered. The stratification is based on a nonrandom choice of strata
for ind...
Test for differences between M-estimates of non-linear regression model
M-estimates non-linear regression model
2009/9/23
Test for differences between M-estimates of non-linear regression model。
P. Nonparametric binary regression with random covariates
P. Nonparametric binary regression random covariates
2009/9/22
The performance of Bayes' estimates is studied under an
assumption of conditional exchangeability. More exactly, for each
subject in a data set, let < be a vector of binary covariates and kt q be
a...
M-estimation for linear regression with infinite variance
M-estimation linear regression infinite variance
2009/9/22
The limiting behavior of M-estimates for a Iinear model
when the regressors and/or errors have heavy tailed distributions is
given. By hermy toil we mean that the distribution is in the domain of
a...
Bayesian Inference for Shape Mixtures of Skewed Distributions, with Application to Regression Analysis
Posterior analysis regression model shape parameter skewness symmetry
2009/9/22
We introduce a class of shape mixtures of skewed distributions and
study some of its main properties. We discuss a Bayesian interpretation and some
invariance results of the proposed class. We devel...
An asymptotic representation of Bahadur type of the
difference of M-estimators &l-fl$-lv'), i-e. of the difference of
mtimators of regression coefficients for the full data set and for the set
from...
Exact Bayesian Regression of Piecewise Constant Functions
Bayesian regression exact polynomial algorithm non-parametric inference piecewise constant function dynamic programming
2009/9/22
We derive an exact and efficient Bayesian regression algorithm for piece-
wise constant functions of unknown segment number, boundary locations, and lev-
els. The derivation works for any noise and ...
A Spatially-adjusted Bayesian Additive Regression Tree Model to Merge Two Datasets
BART CART Missing variables Spatial model Survey
2009/9/22
Scientic hypotheses of interest often involve variables that are not
available in a single survey. This is a common problem for researchers working
with survey data. We propose a model-based approac...
Bayesian inference for an extended simple regression measurement error model using skewed priors
Berkson model non-informative prior non-random sample pseudo-Bayes factor regression calibration structural error model Winbugs
2009/9/22
In this paper, we introduce a Bayesian extended regression model
with two-stage priors when the covariate is positive and measured with error.
Connections are made with some results in Arellano-Vall...
Geographically Assisted Elicitation of Expert Opinion for Regression Models
elicitation expert opinion regression
2009/9/22
One of the perceived strengths of Bayesian modelling is the ability to
include prior information. Although objective or noninformative priors might be
preferred in some situations, in many other app...
Selecting regression model
Weighted Hellinger distance diagnostics and choice of model diversity of (robust) estimates
2009/9/21
A new tool for the identiSicritian of wgrmsian made1 is
pro@ and its promes a r&~ & %AdT lre Irey impomce of the new
tool is &at it is abk to solve still not very weU-known problem ofditremity
es, ...
On the bootstrapping heteroscedastic regression models
Bootstrap heteroscedastic regression ordinary least squares estimates
2009/9/21
The distributjons of deviations of point estimators for
parameters of iterest are essential in the evvaluation of the eficiency of
point estimators. The bootstrap method suggested by B. Efron is on...
Almost sure properties of weighted vectorial martingales transforms with applications to prediction for linear regression models
least squares estimators cumulative prediction and estimation Linear regression models
2009/9/21
We establish new almost sure properties for powers of
weighted martingale transbrms. It allows us to deduce usefuI asymptotic
results for cumulative prediction and estimation errors associated
with...