Results 221 to 230 of about 436,673 (317)

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

Hidden Markov graphical models with state‐dependent generalized hyperbolic distributions

Canadian Journal of Statistics, EarlyView.
Abstract In this article, we develop a novel hidden Markov graphical model to investigate time‐varying interconnectedness between different financial markets. To identify conditional correlation structures under varying market conditions and accommodate shape features embedded in financial time series, we rely upon the generalized hyperbolic family of ...
Beatrice Foroni, Luca Merlo, Lea Petrella   +2 more
wiley   +1 more source

Preparing to act follows Bayesian inference rules. [PDF]

iScience
Tarasi L, Tabarelli de Fatis C, Covelli M, Ippolito G, Avenanti A, Romei V.   +5 more
europepmc   +1 more source

Approximate Bayesian inference for spatial flood frequency analysis

, 2019
Árni V. Jóhannesson, Birgir Hrafnkelsson, Raphaël Huser, Haakon Bakka, Stefan Siegert   +4 more
openalex   +1 more source

Macroevolutionary Rates of Species Interactions: Approximate Bayesian Inference from Cophylogenies

Yichao Zeng (11309451), Cristian Roman Palacios (21162284)   +1 more
openalex   +1 more source

MicroRNA target gene prediction of ischemic stroke by using variational Bayesian inference for Gauss mixture model

, 2019
Jun Wu, Bin Wang, Ju Zhou, Fa-jing Ji
openalex   +2 more sources

Partial identification with categorical data and nonignorable missing outcomes

Canadian Journal of Statistics, EarlyView.
Abstract Nonignorable missing outcomes are common in real‐world datasets and often require strong parametric assumptions to achieve identification. These assumptions can be implausible or untestable, and so we may wish to forgo them in favour of partially identified models that narrow the set of a priori possible values to an identification region.
Daniel Daly‐Grafstein, Paul Gustafson
wiley   +1 more source

Neural variability in the default mode network compresses with increasing belief precision during Bayesian inference. [PDF]

Cereb Cortex
Skowron A, Kosciessa JQ, Lorenz RC, Hertwig R, van den Bos W, Garrett DD.   +5 more
europepmc   +1 more source

FIGURE 2. Bayesian inference trees reconstructed using A in A review of geographic variation in the monocled cobra, Naja kaouthia Lesson, 1831 (Serpentes: Elapidae) with the designation of a neotype

Balchan, Neil R., Esquerré, Damien, Wogan, Guinevere O. U., Wüster, Wolfgang   +3 more
openalex   +1 more source

Bayesian clustering of multivariate extremes

Canadian Journal of Statistics, EarlyView.
Abstract The asymptotic dependence structure between multivariate extreme values is fully characterized by their projections on the unit simplex. Under mild conditions, the only constraint on the resulting distributions is that their marginal means must be equal, which results in a nonparametric model that can be difficult to use in applications ...
Sonia Alouini, Anthony C. Davison
wiley   +1 more source