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Distribution and Symmetric Distribution Regression Model for Histogram-Valued Variables
data with variability linear regression Symbolic Data Analysis quantile functions Mallows distance
2013/4/28
Histogram-valued variables are a particular kind of variables studied in Symbolic Data Analysis where to each entity under analysis corresponds a distribution that may be represented by a histogram or...
Adaptive confidence bands in the nonparametric fixed design regression model
Adaptive confidence bands nonparametric fixed design regression model
2012/9/19
In this note, we consider the problem of existence of adaptive confidence bands in the fixed design regression model, adapting ideas in Hoffmann and Nickl [10] to the present case. In the course of th...
Classical regression analysis relates the expectation of a response variable to a linear combination of explanatory variables. In this article, we propose a covariance regression model that parameteri...
Efficient robust nonparametric estimation in a semimartingale regression model
Non-asymptotic estimation Robust risk Model selection
2010/10/19
The paper considers the problem of robust estimating a periodic function in a continuous time regression model with dependent disturbances given by a general square integrable semimartingale with unk...
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。
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, ...
ADAPTIVE KERNEL ESTIMATION OF THE MODE IN A NONPARAMETRIC RANDOM DESIGN REGRESSION MODEL
Nonparametric regression random design mode kernel smoothing Nadaraya-Watson estimator
2009/9/21
In a nonparametric regession model with random design,
where the regression function m is given by rn (x). = E (Y I X = x),
estimation of the location 0 (mode) and size m(B) of a unique maximum
of ...
DATA-DRIVEN SCORE TESTS FOR HOMOSCEDASTIC LINEAR REGRESSION MODEL:ASYMPTOTIC RESULTS
Efficient score hypothesis testing data-driven test linear regression selection rule
2009/9/18
We describe and investigate new tests for testing the
validity of a semiparametric random-design linear regression model.
The tests were introduced in Inglot and Ledwina (2006a, b). We repeat
here ...
Bayesian Inference of a Linear Segmented Regression Model
Bayesian Inference a Linear Segmented Regression Model
2009/9/17
Bayesian Inference of a Linear Segmented Regression Model。
Sensitivity Analysis to Select the Most Influential Risk Factors in a Logistic Regression Model
Risk Factors Logistic Regression Model
2009/9/3
The traditional variable selection methods for survival data depend on iteration procedures, and control of this process assumes tuning parameters that are problematic and time consuming, especially i...
Higher Order Approximation of the Probability Distribution of the Ratio Estimator for a Regression Model
Cornish-Fisher expansion Edgeworth expansion higher order approximation ratio estimator regression model
2009/3/10
In the present paper, we consider the problem of estimating a ratio ρ = E(Y) / E(X) in a regression model Y = α + βX + U. We obtain the higher order approximation of the probability distribution of th...
Exact Distributions of R2 and Adjusted R2 in a Linear Regression Model with Multivariate t Error Terms
adjusted R2 exact distribution interval estimation multivariate t error terms R2
2009/3/9
In this paper we consider a linear regression model when error terms obey a multivariate t distribution, and examine the effects of departure from normality of error terms on the exact distributions o...
Minimum distance regression model checking with Berkson measurement errors
Kernel estimator L2 distance consistency local alternatives
2010/3/18
Lack-of-fit testing of a regression model with Berkson measurement
error has not been discussed in the literature to date. To fill
this void, we propose a class of tests based on minimized integrate...