We consider the problem of estimating the conditional quantile of a time series at time t given observations of the same and perhaps other time series available at time t - 1. We discuss sieve estimates which are a nonparametric versions of the Koenker-Bassett regression quantiles and do not...

We consider a generalized mixture of nonlinear AR models, a hidden Markov model for which the autoregressive functions are single layer feedforward neural networks. The nontrivial problem of identifiability, which is usually postulated for hidden Markov models, is addressed here.

In this article we consider a CHARME model, a class of generalized mixture of nonlinear nonparametric AR-ARCH time series. To provide sets of conditions under which such processes are geometrically ergodic and, therefore, satisfy some mixing conditions, we apply the theory of Markov chains to...

type="main" xml:id="rssb12047-abs-0001" <title type="main">Summary</title> <p>We introduce a new estimator, the simultaneous multiscale change point estimator SMUCE, for the change point problem in exponential family regression. An unknown step function is estimated by minimizing the number of change points over the...</p>

It is shown how to choose the smoothing parameter in image denoising by a statistical multiresolution criterion, both globally and locally. Using inhomogeneous diffusion and total variation regularization as examples for localized regularization schemes, an efficient method for locally adaptive...