Jonas Krampe

TL;DR: In this article, a model-based bootstrap procedure is proposed for estimating the sparsified version of the underlying vector autoregressive model, and the asymptotic distribution of such estimators in the time series context is derived.

TL;DR: This paper considers sparse vector autoregressive models and develops appropriate bootstrap methods to infer properties of such processes, like the construction of confidence intervals and of tests for individual or for groups of model parameters, and establishes asymptotic validity of the bootstrap procedure proposed for estimation and, appropriately modified, for testing purposes.

TL;DR: The risk of obtaining MAIS 2+ injuries is significantly higher in oblique crashes than in nonoblique crashes, and this measure of accident severity was termed objective equivalent speed (oEES) because it does not depend on the accident reconstruction and thus eliminates reconstruction biases like impact direction and vehicle model year.

TL;DR: In this article, a spectral density-driven bootstrap for time series is proposed, which uses the entire sequence of estimated moving average coefficients together with appropriately generated pseudoinnovations to obtain a bootstrap pseudo-time series.

TL;DR: The concept of mechanical specific energy (MSE) by Teale (1965) helps to increase the instantaneous rate of penetration (ROP) for well drilling and has been improved mathematically in recent years by several authors.