Kernel regression estimationRandom samplingLet Z = (X, Y)= {Z(t)} t鈭 be a stationary continuous-time process taking values in . By means of the corresponding discrete-time process { X(t i ), Y(t i )} i =1 n , sampled at random instants { t i }, a nonparametric kernel ...
Kernelestimationofregressionfunctions 系统标签: rosteringmosakernelregressionestimationnoncyclic AMulti-objectiveSimulatedAnnealing forBusDriverRostering KunkunPeng 1,2 ,YindongShen 1,2(B) ,andJingpengLi 3 1 SchoolofAutomation,HuazhongUniversityofScienceandTechnology, Wuhan430074,Hubei,China pengkunkun@126,yin...
For the nonparametric estimation of regression functions with a one-dimensional design parameter, a new kernel estimate is defined and shown to be superior to the one introduced by Priestley and Chao (1972). The results are not restricted to positive kernels, but extend to classes of kernels sat...
The problem of deciding how much to smooth is of greatimportance in nonparametric regression. Before embarking ontechnical solutions of the problem it is worth noting that aselection of the smoothing parameter is always related to acertain interpretation of the smooth. However, a goodautomatically se...
Kernel Estimation of the Derivative of the Regression Function Using Repeated-Measurements DataNonparametric statisticsRegression analysisCorrelationFunctions(Mathematics)EstimatesBandwidthOptimizationLimitationsGraphsGrowth(General)In fixed design kernel nonparametic regression, there has been a paucity of results for...
Gasser, T., & Müller, H. G. (1979). Kernel estimation of regression functions. InSmoothing techniques for curve estimation(pp. 23-68). Springer, Berlin, Heidelberg. Marron, J. S., & Wand, M. P. (1992). Exact mean integrated squared error.The Annals of Statistics,20(2), 712-736...
The authors derive laws of the iterated logarithm for kernel estimator of regression function based on directional data. The results are distribution free ... WANG,XIAOMING,ZHAO,... - 《Chinese Annals of Mathematics》 被引量: 0发表: 2000年 Large sample theory of the estimation of the error ...
Estimation of extreme regression risk measures The class of quantiles lies at the heart of extreme-value theory and is one of the basic tools in risk management. The alternative family of expectiles is based on squared rather than absolute error loss minimization. It has recently bee... S Gir...
Nonparametric estimation of regression functions with both categorical and continuous data J. Econometrics (2004) SuL. et al. Nonparametric dynamic panel data models: Kernel estimation and specification testing J. Econometrics (2013) AitkenC.G.G. Kernel methods for the estimation of discrete distribut...
In this paper, we investigate a modified kernel estimation of the regression function r(x)=E(Y|X=x). The main goal of this paper is to establish the consistency and the rate of convergence of such a modified kernel estimator for strong mixing functional data with only E|Y|<∞, which ...