Results 21 to 30 of about 2,878 (136)

Does any fish scale of a fish have the same number of marks? A case study for two Mugilidae species

Journal of Fish Biology, EarlyView.
Abstract This study evaluates the difference in growth marks in scales from nine body areas of two Mugilidae species from the Gulf of Mexico: Mugil curema and Mugil cephalus. It addresses whether the different body areas show more (or fewer) marks, and which area(s) would be more useful in fish biology studies relying on mark analysis.
Ebenecer Guerra, Arturo Bell Enríquez‐García, Víctor H. Cruz‐Escalona, Eloísa Pacheco‐Almanzar, Sergio Álvarez‐Hernández, Emigdio Marín‐Enríquez, Ana Laura Ibáñez   +6 more
wiley   +1 more source

Ergodic Interference Alignment [PDF]

IEEE Transactions on Information Theory, 2009
16 pages, 6 figure, To appear in IEEE Transactions on Information ...
Nazer, B., Gastpar, M. ; Jafar, S.A. ; Vishwanath, S.   +5 more
openaire   +2 more sources

Monetary and Macroprudential Policies under Dollar‐Denominated Foreign Debt

Journal of Money, Credit and Banking, EarlyView.
Abstract This paper studies monetary and macroprudential policies in a small open economy that borrows from abroad in foreign currency. The model features a novel mechanism in which exchange rate depreciation triggered by a borrowing constraint is amplified through balance of payments adjustments, increasing the real burden of foreign debt and causing ...
HIDEHIKO MATSUMOTO
wiley   +1 more source

Econometrics at the Extreme: From Quantile Regression to QFAVAR1

Journal 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, Konstantinos N. Konstantakis, Dimitris Konstantios, Panayotis G. Michaelides, Arsenios‐Georgios N. Prelorentzos   +4 more
wiley   +1 more source

Markov Determinantal Point Process for Dynamic Random Sets

Journal 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

Tests for Changes in Count Time Series Models With Exogenous Covariates

Journal of Time Series Analysis, EarlyView.
ABSTRACT We deal with a parametric change in models for count time series with exogenous covariates specified via the conditional distribution, i.e., with integer generalized autoregressive conditional heteroscedastic models with covariates (INGARCH‐X).
Šárka Hudecová, Marie Hušková
wiley   +1 more source

On Exponential‐Family INGARCH Models

Journal of Time Series Analysis, EarlyView.
ABSTRACT A range of integer‐valued generalised autoregressive conditional heteroscedastic (INGARCH) models have been proposed in the literature, including those based on conditional Poisson, negative binomial and Conway‐Maxwell‐Poisson distributions. This note considers a larger class of exponential‐family INGARCH models, showing that maximum empirical
Alan Huang, Thomas Fung, Kyle Macaskill, Rowan Aukes   +3 more
wiley   +1 more source

Time‐Varying Dispersion Integer‐Valued GARCH Models

Journal of Time Series Analysis, EarlyView.
ABSTRACT We introduce a general class of INteger‐valued Generalized AutoRegressive Conditionally Heteroscedastic (INGARCH) processes by allowing simultaneously time‐varying mean and dispersion parameters. We call such models time‐varying dispersion INGARCH (tv‐DINGARCH) models.
Wagner Barreto‐Souza, Luiza S. C. Piancastelli, Konstantinos Fokianos, Hernando Ombao   +3 more
wiley   +1 more source

Estimation of Change Points for Non‐Linear (Auto‐)Regressive Processes Using Neural Network Functions

Journal of Time Series Analysis, EarlyView.
ABSTRACT In this paper, we propose a new test for the detection of a change in a non‐linear (auto‐)regressive time series as well as a corresponding estimator for the unknown time point of the change. To this end, we consider an at‐most‐one‐change model and approximate the unknown (auto‐)regression function by a neural network with one hidden layer. It
Claudia Kirch, Stefanie Schwaar
wiley   +1 more source

Robust CDF‐Filtering of a Location Parameter

Journal of Time Series Analysis, EarlyView.
ABSTRACT This paper introduces a novel framework for designing robust filters associated with signal plus noise models having symmetric observation density. The filters are obtained by a recursion where the innovation term is a transform of the cumulative distribution function of the residuals.
Leopoldo Catania, Andrew C. Harvey, Alessandra Luati   +2 more
wiley   +1 more source