Results 201 to 210 of about 128,734 (275)

Causal Models as a Scientific Framework for Next‐Generation Ecosystem and Climate‐Linked Stock Assessments

open access: yesFish and Fisheries, EarlyView.
ABSTRACT Rapid changes in marine ecosystems highlight the need to account for time‐varying productivity in stock assessments used to support fisheries management. Common approaches incorporate annual variation or regressing processes such as recruitment, natural mortality, or growth on environmental variables.
J. Champagnat   +6 more
wiley   +1 more source

Estimating Velocities of Infectious Disease Spread Through Spatio‐Temporal Log‐Gaussian Cox Point Processes

open access: yesInternational Statistical Review, EarlyView.
Summary Understanding the spread of infectious diseases such as COVID‐19 is crucial for informed decision‐making and resource allocation. A critical component of disease behaviour is the velocity with which disease spreads, defined as the rate of change between time and space.
Fernando Rodriguez Avellaneda   +2 more
wiley   +1 more source

A Non‐Parametric Framework for Correlation Functions on Product Metric Spaces

open access: yesInternational Statistical Review, EarlyView.
Summary We propose a non‐parametric framework for analysing data defined over products of metric spaces, a versatile class encountered in various fields. This framework accommodates non‐stationarity and seasonality and is applicable to both local and global domains, such as the Earth's surface, as well as domains evolving over linear time or time ...
Pier Giovanni Bissiri   +3 more
wiley   +1 more source

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

Markov Determinantal Point Process for Dynamic Random Sets

open access: yesJournal of Time Series Analysis, EarlyView.
ABSTRACT The Law of Determinantal Point Process (LDPP) is a flexible parametric family of distributions over random sets defined on a finite state space, or equivalently over multivariate binary variables. The aim of this paper is to introduce Markov processes of random sets within the LDPP framework. We show that, when the pairwise distribution of two
Christian Gouriéroux, Yang Lu
wiley   +1 more source

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