Results 111 to 120 of about 70,468 (320)
Restricted Tweedie stochastic block models
Canadian Journal of Statistics, EarlyView.Abstract The stochastic block model (SBM) is a widely used framework for community detection in networks, where the network structure is typically represented by an adjacency matrix. However, conventional SBMs are not directly applicable to an adjacency matrix that consists of nonnegative zero‐inflated continuous edge weights.
Jie Jian, Mu Zhu, Peijun Sang
wiley +1 more source
Asymptotic properties of cross‐classified sampling designs
Canadian Journal of Statistics, EarlyView.Abstract We investigate the family of cross‐classified sampling designs across an arbitrary number of dimensions. We introduce a variance decomposition that enables the derivation of general asymptotic properties for these designs and the development of straightforward and asymptotically unbiased variance estimators.
Jean Rubin, Guillaume Chauvet
wiley +1 more source
A Markov approach to credit rating migration conditional on economic states
Canadian Journal of Statistics, EarlyView.Abstract We develop a model for credit rating migration that accounts for the impact of economic state fluctuations on default probabilities. The joint process for the economic state and the rating is modelled as a time‐homogeneous Markov chain. While the rating process itself possesses the Markov property only under restrictive conditions, methods ...
Michael Kalkbrener, Natalie Packham
wiley +1 more source
Limit vector variational inequality problems via scalarization [PDF]
, 2018 Monica Bianchi, I. V. Konnov, R. Pini
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
Random vector variational inequalities and random noncooperative vector equilibrium [PDF]
, 1996 Gue Myung Lee +2 more
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Korpelevich Method for Solving Bilevel Variational Inequalities on Riemannian Manifolds
AxiomsThe bilevel variational inequality on Riemannian manifolds refers to a mathematical problem involving the interaction between two levels of optimization, where one level is constrained by the other level.
Jiagen Liao, Zhongping Wan
doaj +1 more source
Causal analysis of extreme risk in a network of industry portfolios
Canadian Journal of Statistics, EarlyView.Abstract We provide a detailed review of causal dependence within the framework of max‐linear structural models. Such models express each node variable as a max‐linear function of its parental node variables in a directed acyclic graph (DAG) and some exogenous innovation.
Claudia Klüppelberg, Mario Krali
wiley +1 more source
Bayesian leave-one-out cross-validation for large data
, 2019 Model inference, such as model comparison, model checking, and model selection, is an important part of model development. Leave-one-out cross-validation (LOO) is a general approach for assessing the generalizability of a model, but unfortunately, LOO ...
Andersen, Michael Riis +3 more
core
Generalized Vector Variational-Like Inequalities
Journal of Mathematical Extension, 2010 In this paper, we consider different types of generalized vector variational-like inequalities and study the relationships between their solutions. We study the general forms of Stampacchia and Minty type vector variational inequalities for bifunctions and establish the existence of their solutions in the setting of topological vector spaces. We extend
M. Rezaei, H. Gazor
openaire +1 more source