A Weighted Survival Regression Framework for Incorporating External Prediction Information. [PDF]
Ghosh D.
europepmc +1 more source
Econometrics at the Extreme: From Quantile Regression to QFAVAR1
ABSTRACT This paper surveys quantile modelling from its theoretical origins to current advances. We organize the literature and present core econometric formulations and estimation methods for: (i) cross‐sectional quantile regression; (ii) quantile time series models and their time series properties; (iii) quantile vector autoregressions for ...
Stéphane Goutte +4 more
wiley +1 more source
Unlocking the power of time-since-infection models: data augmentation for improved instantaneous reproduction number estimation. [PDF]
Shi J, Zhou Y, Huang J.
europepmc +1 more source
Extremely Fast Maximum Likelihood Estimation of High‐Order Autoregressive Models
ABSTRACT We consider the problem of exact maximum likelihood estimation of potentially high‐order (p>50$$ p>50 $$) autoregressive models. We propose an extremely fast coordinate‐wise algorithm for fitting autoregressive models. This fast algorithm exploits several properties of the negative log‐likelihood when parameterised in terms of partial ...
Daniel F. Schmidt, Enes Makalic
wiley +1 more source
Modeling growth performance of heterogeneous rabbits in a pastured system using nonlinear, spline and random regression models. [PDF]
Bashiru HA, Oseni SO.
europepmc +1 more source
Automated Bandwidth Selection for Inference in Linear Models With Time‐Varying Coefficients
ABSTRACT The problem of selecting the smoothing parameter, or bandwidth, for kernel‐based estimators of time‐varying coefficients in linear models with possibly endogenous explanatory variables is considered. We examine automated bandwidth selection by means of cross‐validation, a nonparametric variant of Akaike's information criterion, and bootstrap ...
Charisios Grivas, Zacharias Psaradakis
wiley +1 more source
Spatiotemporal Heterogeneity Learning: Generalized SpatioTemporal Semi-Varying Coefficient Models With Structure Identification. [PDF]
Gu Z, Li X, Wang G, Wang L.
europepmc +1 more source
Detecting Relevant Deviations From the White Noise Assumption for Non‐Stationary Time Series
ABSTRACT We consider the problem of detecting deviations from a white noise assumption in time series. Our approach differs from the numerous methods proposed for this purpose with respect to two aspects. First, we allow for non‐stationary time series. Second, we address the problem that a white noise test is usually not performed because one believes ...
Patrick Bastian
wiley +1 more source
Adaptive Estimation for Weakly Dependent Functional Times Series
ABSTRACT We propose adaptive mean and autocovariance function estimators for stationary functional time series under 𝕃p−m‐approximability assumptions. These estimators are designed to adapt to the regularity of the curves and to accommodate both sparse and dense data designs.
Hassan Maissoro +2 more
wiley +1 more source
A Robust Association Test Leveraging Unknown Genetic Interactions: Application to Cystic Fibrosis Lung Disease. [PDF]
Kim S, Lin YC, Strug LJ.
europepmc +1 more source

