Kernel estimation and display of a five-dimensional conditional intensity function

Kernel and Nearest Neighbor Estimation of a Conditional Quantile

Let (Xl'Z1)' (X2,Z2),· .. ,(Xn,Zn) be LLd. as (X,Z), Z taking values in Rl, and for o < p < 1, let ep(x) denote the conditional p-quantile of Z given X=x, i.e., P(Z ~ ep(x) IX=x) = p. In this paper, kernel and nearest neighbor estimators of ep(x) are proposed. As a first step in studying the asymptotics of these estimates, Bahadur type ~ representations of the sample conditional quantile functi...

Recursive Kernel Estimation of the Conditional Intensity of Nonstationary Point Processes

This paper develops adaptive nonparametric methods for analyzing seismic data. Kernel smoothing techniques are suitable for space-time point processes; however, they must be adapted to deal with the nonstationarity of earthquakes. By this we mean changes in the spatial and temporal pattern of point occurrences. A class of recursive kernel density and regression estimators are proposed to study ...

Adaptive pointwise estimation of conditional density function

Kernel estimation of multivariate cumulative distribution function

A smooth kernel estimator is proposed for multivariate cumulative distribution functions (cdf), extending the work of Yamato [H. Yamato, Uniform convergence of an estimator of a distribution function, Bull. Math. Statist. 15 (1973), pp. 69–78.] on univariate distribution function estimation. Under assumptions of strict stationarity and geometrically strong mixing, we establish that the proposed...

Using Conditional Kernel Density Estimation for Wind Power Density Forecasting

Of the various renewable energy resources, wind power is widely recognized as one of the most promising. The management of wind farms and electricity systems can benefit greatly from the availability of estimates of the probability distribution of wind power generation. However, most research has focused on point forecasting of wind power. In this paper, we develop an approach to producing dens...