292 citations · 310 across the 6 of their papers we have counts for
6 papers
36Cl Concentrations from Polar Ice Cores Set New Constraints on the Carrington Event
F. Mekhaldi, C. I. Paleari, A. M. Smith +12
The Carrington event of 1859 CE is considered as one of the largest geomagnetic storms of the observational era, and often used as a benchmark for a worst-case scenario. Yet, there…
emcee v3: A Python ensemble sampling toolkit for affine-invariant MCMC
Daniel Foreman-Mackey, Will M. Farr, Manodeep Sinha +10
emcee is a Python library implementing a class of affine-invariant ensemble samplers for Markov chain Monte Carlo (MCMC). This package has been widely applied to probabilistic mode…
Heavy tailed spatial autocorrelation models
A. Kreuzer, T. Erhardt, T. Nagler +1
Appropriate models for spatially autocorrelated data account for the fact that observations are not independent. A popular model in this context is the simultaneous autoregressive…
Standardized drought indices: A novel uni- and multivariate approach
Tobias M. Erhardt, Claudia Czado
As drought is among the natural hazards which affects people and economies worldwide and often results in huge monetary losses sophisticated methods for drought monitoring and deci…
Spatial composite likelihood inference using local C-vines
Tobias Michael Erhardt, Claudia Czado, Ulf Schepsmeier
We present a vine copula based composite likelihood approach to model spatial dependencies, which allows to perform prediction at arbitrary locations. This approach combines establ…
R-vine Models for Spatial Time Series with an Application to Daily Mean Temperature
Tobias Michael Erhardt, Claudia Czado, Ulf Schepsmeier
We introduce an extension of R-vine copula models for the purpose of spatial dependency modeling and model based prediction at unobserved locations. The newly derived spatial R-vin…