[PDF] Top 20 Regression modeling for nonparametric estimation of distribution and quantile functions

... University and Georgia Institute of Technology Abstract: We propose a local linear estimator of a smooth distribution ...a regression model in which the value of the empirical ... See full document

... CHEN and Tzee-Ming HUANG Key words and phrases: boundary bias; copula models; dependence; kernel ...measures of dependence among components of random ...marginal and the joint ... See full document

... terms of percentage  are useful as indices for identifying ...class of symmetric quantiles for estimating unknown nonlinear regression conditional ...than regression quantiles ... See full document

... basis functions For body movements and novel views synthesis, the nonparametric regression model with kernel regression is trained for the prediction of deformed ... See full document

... images of optimized parameter- ization ...illumination and geometric features of a BTF, especially shadows, specular highlights, and uneven ...surfaces. For example, one can roughly ... See full document

... methods for modeling and identification of Hammerstein- type systems published in the open literature focused on the single- input-single-output (SISO) ...Verhaegen and Westwick; 1 Al- ... See full document

... Kamien and Tauman (1986), in an oligopoly, when the number of firms is small (or very large), the strategy of entering the market and simultaneously licensing the cost-reducing technology to ... See full document

... some quantile estimators and related bandwidth selection methods and give two new bandwidth selection ...exponential and log normal we simulated the methods and compared their ... See full document

... Methodology and data description ...levels of cash holdings, and explores the possible decision-making factors that can explain the cash ...General regression methods, such as OLS or the ... See full document

... determination of initial values The initial guesses are important for further optimization ...value of center and covariance, the correspondences with regard to feature alignment should be ... See full document

... In the computer experiments reported, the estimate of the Bayes risk is taken as the sample mean of the density estimate by making use of the leave-one-out method.. The probability densi[r] ... See full document

... domain and to provide an interface between problems and solvers in different ...designed for handling discrete decision variables can optimize transformed con- tinuous ...probability of search ... See full document

... Meeker & Escobar (91 presented many up-to-date statisti- cal methods for analyzing reliability data. In life sciences, Capra & Muller [l] proposed an acceler- ated time [r] ... See full document

... the quantile inference, in sharp contrast to the counterparts from the univariate unit root tests focusing on the average ...sign and size of the shock, in general, have marked impact on the speed ... See full document

... variable of interest can be observed only if its value satisfies certain selection ...methods for analyzing such data critically rely on the assumption that the truncation variable is quasi-independent ... See full document

... Previous local studies for eutrophication were mostly focused on the water quality and external loads only, and the internal load was rarely explored, especiallyfor an off-stream reservo[r] ... See full document

... degree of freedom that is available in the problem of surface ...technique for estimating gradients and curvatures of contour lines, without passing explicitly to derivatives of ... See full document

... Clustering and Symbolic Regres- sion (CSR) power estimation method for smartphone sub- ...accuracy of subsystem power estimation by investigating nonlinear and asynchronous power ... See full document

... The approximation considered in this paper will prove to be useful in practice for growth curve model prediction, for multivariate analysis of variance as well as for other occasio[r] ... See full document

... degree of smoothness used in the data smoothing step has a great impact on the result of the subsequent PCA ...power of the first few principal components demonstrated in this article is in fact ... See full document