Convergence and rates for fixed-interval multiple-track smoothing using $k$-means type optimization

Nonparametric fixed-interval smoothing with vector splines

Marginal means/rates models for multiple type recurrent event data.

Recurrent events are frequently observed in biomedical studies, and often more than one type of event is of interest. Follow-up time may be censored due to loss to follow-up or administrative censoring. We propose a class of semi-parametric marginal means/rates models, with a general relative risk form, for assessing the effect of covariates on the censored event processes of interest. We formu...

A hybrid DEA-based K-means and invasive weed optimization for facility location problem

In this paper, instead of the classical approach to the multi-criteria location selection problem, a new approach was presented based on selecting a portfolio of locations. First, the indices affecting the selection of maintenance stations were collected. The K-means model was used for clustering the maintenance stations. The optimal number of clusters was calculated through the Silhou...

Fixed Interval Smoothing for Nonlinear Continuous Time Systems

Here, dr~dr and dw/dt are independent, zero mean, ganssian white noise processes, with covariances I 3 ( t r ) and R ( t ) 8 ( t T), respectively. The matrix R(t) is positive definite for all t. An a priori distribution for the density of x 0 is assumed known, and it is assumed that f , G, h and R all have sufficient smoothness properties to guarantee the usual existence and uniqueness requirem...

The Fixed-Interval Smoothing Problem for Continuous Systems

The smoothing problem for continuous systems is treated in a state space representation by means of variational calculus techniques. The smoothing problem is introduced in an criterion by means of an artificial discontinuity that splits the problem in term of forward and backward filtering problems. Hence, the smoother design is realized in three steps. First, a forward filter is developed. Sec...