搜索结果: 61-75 共查到“理学 regression”相关记录136条 . 查询时间(0.094 秒)
Moving Taylor Bayesian Regression for nonparametric multidimensional function estimation with possibly correlated errors
interpolation irregular sampling numerical differentiation rational function smoothing
2012/4/24
We present a nonparametric method for estimating the value and several derivatives of an unknown, sufficiently smooth real-valued function of real-valued arguments from a finite sample of points, wher...
Minimax lower bound for kink location estimators in a nonparametric regression model with long-range dependence
nonparametric regression long-range dependence kink minimax
2011/9/22
Abstract: In this paper, a lower bound is determined in the minimax sense for change point estimators of the first derivative of a regression function in the fractional white noise model. Similar mini...
Multi-task Regression using Minimal Penalties
multi-task oracle inequality learning theory
2011/9/19
Abstract: In this paper we study the kernel multiple ridge regression framework, which we refer to as multi-task regression, using penalization techniques. The theoretical analysis of this problem sho...
Local Polynomial Regression Based on Functional Data
Local polynomial smoothing derivative estimation functional data sampling density optimal bandwidth asymptotic normality
2011/9/15
Abstract: Suppose that $n$ statistical units are observed, each following the model $Y(x_j)=m(x_j)+ \epsilon(x_j),\, j=1,...,N,$ where $m$ is a regression function, $0 \leq x_1 <...re ob...
Extended BIC for linear regression models with diverging number of relevant features and high or ultra-high feature spaces
Diverging number of parameters Feature selection Extended Bayes information criterion High dimensional feature space
2011/9/5
Abstract: In many conventional scientific investigations with high or ultra-high dimensional feature spaces, the relevant features, though sparse, are large in number compared with classical statistic...
Nonparametric Regression using the Concept of Minimum Energy
Nonparametric Regression Concept Minimum Energy Nuclear Experiment
2011/8/4
Abstract: It has recently been shown that an unbinned distance-based statistic, the energy, can be used to construct an extremely powerful nonparametric multivariate two sample goodness-of-fit test. A...
A regression Monte-Carlo method for Backward Doubly Stochastic Differential Equations
regression Monte-Carlo method Stochastic Differential Equations Probability
2011/8/30
Abstract: This paper extends the idea of E.Gobet, J.P.Lemor and X.Warin from the setting of Backward Stochastic Differential Equations to that of Backward Doubly Stochastic Differential equations. We ...
Dimensionally Constrained Symbolic Regression
Symbolic Regression Dimensionally Constrained
2011/9/14
We describe dimensionally constrained symbolic regression which has been developed for mass measurement in certain classes of events in high-energy physics (HEP).With symbolic regression, we can deriv...
A test of significance in functional quadratic regression
Absorption spectra Asymptotics Functional data analysis Polynomial regression Prediction Principal component analysis
2011/6/15
We consider a quadratic functional regression model in which a scalar response depends on a functional predictor; the common functional linear model is a special case. We wish to test the significance...
Seasonal prediction of winter extreme precipitation over Canada by support vector regression
winter extreme precipitation Canada support vector regression
2011/1/7
For forecasting the maximum 5-day accumulated precipitation over the winter season at lead times of 3, 6, 9 and 12 months over Canada from 1950 to 2007, two nonlinear and two linear regression models ...
The Hannan-Quinn Proposition for Linear Regression
Hannan-Quinn linear regression the law of iterated logarithms strong consistency
2011/2/23
We consider the variable selection problem in linear regression. Suppose that we have a set
of random variables X1, · · · ,Xm, Y, ǫ such that Y = Pk2 αkXk +ǫ with π ⊆ {1, · · · ,m} a...
Alternative method for choosing ridge parameter for regression
Ridge regression Ridge parameter Multicollinearity
2010/9/20
The parameter estimation method based on minimum residual sum of squares is unsatisfactory in the presence of multicollinearity. Hoerl and Kennard [1] introduced alternative method called ridge regres...
An analytic comparison of permutation methods for tests of partial regression coefficients in the linear model
analytic comparison permutation methods linear model
2010/9/21
An analytic comparison of permutation methods for tests of partial regression coefficients in the linear model.
On estimating parameters of censored generalized Poisson regression model
Generalized Poisson regression Mixture model
2010/9/21
When the sampling variance of a count variable Y is significantly greater or less than that predicted by an expected probability distribution, Y is said to be over- or underdispersed, respectively. A ...
Regression, model misspecification and causation, with pedagogical demonstration
Regression variable omission model incomplete bias
2010/9/20
This paper shows, by a proposition and a numerical example, how a classic simple or multiple normal regression can achieve with 0.99 probability a near perfect fit to a random sample of any size but d...