Conditional density function for surrogate scalar response

Adaptive pointwise estimation of conditional density function

A General Scalar-Valued Gap Function for Nonsmooth Multiobjective Semi-Infinite Programming

For a nonsmooth multiobjective mathematical programming problem governed by infinitely many constraints‎, ‎we define a new gap function that generalizes the definitions of this concept in other articles‎. ‎Then‎, ‎we characterize the efficient‎, ‎weakly efficient‎, ‎and properly efficient solutions of the problem utilizing this new gap function‎. ‎Our results are based on $(Phi,rho)-$invexity‎,...

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...

A geometric framework for density estimation and conditional density estimation

We introduce a geometrically intuitive procedure to obtain an estimator for a probability density function in the absence or presence of predictors. The estimation procedure is based on starting with an initial estimate of the density shape and then transforming it via a warping function to obtain the final estimate. The idea is to design the initial estimate to be computationally fast, albeit ...

Interpolating Conditional Density Trees

Joint distributions over many variables are frequently modeled by decomposing them into products of simpler, lower-dimensional conditional distributions, such as in sparsely connected Bayesian networks. However, au­ tomatically learning such models can be very computationally expensive when there are many datapoints and many continuous vari­ ables with complex nonlinear relationships, particula...