Results 11 to 20 of about 26,329 (108)

On subset least squares estimation and prediction in vector autoregressive models with exogenous variables

Canadian Journal of Statistics, EarlyView.
Abstract We establish the consistency and the asymptotic distribution of the least squares estimators of the coefficients of a subset vector autoregressive process with exogenous variables (VARX). Using a martingale central limit theorem, we derive the asymptotic normal distribution of the estimators. Diagnostic checking is discussed using kernel‐based
Pierre Duchesne, Thanh‐Liem Huynh, Mylène Oscar   +2 more
wiley   +1 more source

Machine Learning‐Assisted Design of BaTiO3‐Based Superparaelectric High‐Entropy Ceramics with Superior Energy Storage

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
This study employed an adaptive iterative strategy combining machine learning algorithms, domain knowledge, experimental design, and experimental feedback to aim to precisely and quickly discover high‐entropy ceramics with excellent energy storage performance.
Haowen Liu, Xiaoyan Zhang, Zhiyuan Ma, Kailong Ma, Xiwei Qi   +4 more
wiley   +1 more source

The importance of considering regimes in long‐term asset allocation to real estate

Real Estate Economics, EarlyView.
Abstract We investigate the long‐term, regime‐dependent asset allocation of an investor's wealth in a mixed‐asset portfolio that includes publicly traded real estate. We show that augmenting standard VAR models with Markov‐switching features not only improves predictive power for asset returns but also introduces economically meaningful horizon effects
Massimo Guidolin, Mingwei (Max) Liang, Milena Petrova   +2 more
wiley   +1 more source

Effective high-temperature estimates for intermittent maps

, 2017
Using quantitative perturbation theory for linear operators, we prove spectral gap for transfer operators of various families of intermittent maps with almost constant potentials ("high-temperature" regime).
Kloeckner, Benoît
core   +1 more source

Enhancing generalizability theory with mixed‐effects models for heteroscedasticity in psychological measurement: A theoretical introduction with an application from EEG data

British Journal of Mathematical and Statistical Psychology, EarlyView.
Abstract Generalizability theory (G‐theory) defines a statistical framework for assessing measurement reliability by decomposing observed variance into meaningful components attributable to persons, facets, and error. Classic G‐theory assumes homoscedastic residual variances across measurement conditions, an assumption that is often violated in ...
Philippe Rast, Peter E. Clayson
wiley   +1 more source

A Comparative Review of Specification Tests for Diffusion Models

International Statistical Review, EarlyView.
Summary Diffusion models play an essential role in modelling continuous‐time stochastic processes in the financial field. Therefore, several proposals have been developed in the last decades to test the specification of stochastic differential equations.
A. López‐Pérez, D. Diz‐Castro, M. Febrero‐Bande, W. González‐Manteiga   +3 more
wiley   +1 more source

A concise proof of the Multiplicative Ergodic Theorem on Banach spaces

, 2015
We give a streamlined proof of the multiplicative ergodic theorem for quasi-compact operators on Banach spaces with a separable dual.Comment: 18 ...
González-Tokman, Cecilia, Quas, Anthony
core   +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

Frequently hypercyclic operators with irregularly visiting orbits

, 2018
We prove that a bounded operator $T$ on a separable Banach space $X$ satisfying a strong form of the Frequent Hypercyclicity Criterion (which implies in particular that the operator is universal in the sense of Glasner and Weiss) admits frequently ...
Grivaux, Sophie
core   +2 more sources

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