In particular it is noted that at a centre of symmetry or near a mode of the distribution the kernei method breaks down. Point- wise estimation of a distribution function is motivated as a more useful technique than a reference range for preliminary medical diagnosis. 展开 ...
Strong uniform consistency and the weak convergence of the normalized process are also proved.doi:10.1007/BF02613509J.K. GhoraiV. SusarlaPhysica-VerlagMetrikaGhorai, JK, Susarla, V (1990) Kernel estimation of a smooth distribution function based on censored data. Metrika 37: pp. 71-86...
(1999). On kernel estimation of a multivariate distribution function. Statist. Probab. Lett. 2 163-168. MR1665267Jin, Zhezhen and Yongzhao Shao (1999): "On kernel estimation of a multivariate distribution func- tion," Statistics and Probability Letters, 41, 163-168....
Computation of the Generalized F Distribution Exact expressions for the cumulative distribution function of a random variable of the form ( α 1 X 1+ α 2 X 2)/ Y are given where X 1, X 2 and Y are ind... CF Dunkl,DE Ramirez - 《Australian & New Zealand Journal of Statistics》 被...
Kernel estimation of distribution functions and quantiles with missing data A distribution-free imputation procedure based on nonparametric kernel regression is proposed to estimate the distribution function and quantiles of a random variable that is incompletely observed. Assuming the baseline missing-at-ran...
Instatistics,kernel density estimation(KDE) is anon-parametricway toestimatetheprobability density functionof arandom variable. Definition Let (x1, x2, …, xn) be a univariateindependent and identically distributedsample drawn from some distribution with an unknowndensityƒ. We are interested in esti...
A.,Antoniadis,G.,... - 《Journal of the Royal Statistical Society》 被引量: 154发表: 1999年 Hazard rate estimation under dependence conditions Let X 1,…, X n be identically distributed R p-valued ( p≥1) random variables with distribution function F and probability density function with ...
Estimation of Probability Densities In Stochastic Processes, 2004 2.6.4. Kernel Estimators Kernel estimators were first proposed by Nadaraya [56] and Watson [82]. The methods related to the estimation of densities are closely related to this estimator. Nadaraya and Watson propose an interpolation pro...
The kernel distribution is a nonparametric estimation of the probability density function (pdf) of a random variable. The kernel distribution uses the following options. OptionDescriptionPossible Values KernelKernel function typenormal,box,triangle,epanechnikov ...
Recursive estimation of the univariate probability density functionf(x)for stationary processes\\{X_{j}\\}is considered. Quadratic-mean convergence and asy... E Masry - 《IEEE Transactions on Information Theory》 被引量: 172发表: 1986年 Kernel estimation of distribution functions and quantiles wi...