Results 221 to 230 of about 91,156 (303)

Econometrics at the Extreme: From Quantile Regression to QFAVAR1

open access: yesJournal of Economic Surveys, EarlyView.
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

Extremely Fast Maximum Likelihood Estimation of High‐Order Autoregressive Models

open access: yesJournal of Time Series Analysis, EarlyView.
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

Automated Bandwidth Selection for Inference in Linear Models With Time‐Varying Coefficients

open access: yesJournal of Time Series Analysis, EarlyView.
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

Detecting Relevant Deviations From the White Noise Assumption for Non‐Stationary Time Series

open access: yesJournal of Time Series Analysis, EarlyView.
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

open access: yesJournal of Time Series Analysis, EarlyView.
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

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