A general class of non-stationary time series is considered in this paper. We estimate the time-varying coefficients by using local linear M-estimation. For these estimators, weak Bahadur representations are obtained and used to construct simultaneous confidence bands. practical implementation, we propose a bootstrap based method circumvent slow logarithmic convergence theoretical Our results s...

The ability to estimate how a tumor might evolve in the future could have tremendous clinical benefits, from improved treatment decisions better dose distribution radiation therapy. Recent work has approached glioma growth modeling problem via deep learning and variational inference, thus dynamics entirely real patient data distribution. So far, this approach was constrained predefined image ac...

In recent years, interest has grown in modeling spatio-temporal data generated from monitoring networks, satellite imaging, and climate models. Under Gaussianity, the covariance function is core to modeling, inference, prediction. this article, we review various space-time structures which simplified assumptions, such as separability full symmetry, are made facilitate computation, associated te...