Results 161 to 170 of about 776,491 (337)
Variance Matrix Priors for Dirichlet Process Mixture Models With Gaussian Kernels
International Statistical Review, EarlyView.Summary Bayesian mixture modelling is widely used for density estimation and clustering. The Dirichlet process mixture model (DPMM) is the most popular Bayesian non‐parametric mixture modelling approach. In this manuscript, we study the choice of prior for the variance or precision matrix when Gaussian kernels are adopted.
Wei Jing +2 more
wiley +1 more source
Disease gene identification by using graph kernels and Markov random fields [PDF]
, 2014 BoLin Chen +3 more
openalex +1 more source
Handling Out‐of‐Sample Areas to Estimate the Unemployment Rate at Local Labour Market Areas in Italy
International Statistical Review, EarlyView.Summary Unemployment rate estimates for small areas are used to efficiently support the distribution of services and the allocation of resources, grants and funding. A Fay–Herriot type model is the most used tool to obtain these estimates. Under this approach out‐of‐sample areas require some synthetic estimates. As the geographical context is extremely
Roberto Benedetti +4 more
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 +3 more
wiley +1 more source
Income, Mortality, and Literacy Distribution Dynamics Across States in Mexico: 1940-2000 [PDF]
This paper analyzes the dynamics of the distributions of per capita Gross Domestic Product (GDP), the infant mortality rate, and the adult literacy rate across states in Mexico between 1994 and 2000.
Rodrigo García Verdú
core
Medical Knowledge Integration Into Reinforcement Learning Algorithms for Dynamic Treatment Regimes
International Statistical Review, EarlyView.Summary The goal of precision medicine is to provide individualised treatment at each stage of chronic diseases, a concept formalised by dynamic treatment regimes (DTR). These regimes adapt treatment strategies based on decision rules learned from clinical data to enhance therapeutic effectiveness.
Sophia Yazzourh +3 more
wiley +1 more source
A Non‐Parametric Framework for Correlation Functions on Product Metric Spaces
International 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
Central Limit Theorem for Kernel Estimator of Invariant Density in Bifurcating Markov Chains Models [PDF]
, 2022 S. Valère Bitseki Penda +1 more
openalex +1 more source
Journal of Animal Breeding and Genetics, EarlyView.ABSTRACT This study aimed to estimate the variance components, heritabilities and genetic correlations between four new different categories of stayability (STAY48‐2, STAY48‐3, STAY54‐2, STAY54‐3) with weight at 240 days of age (W240), weight at 450 days of age (W450), scrotal circumference at 365 days of age (SC365), age at puberty in males (APM ...
Letícia Silva Pereira +5 more
wiley +1 more source
Nonparametric Bayesian modeling for non-normal data through a transformation
AIMS MathematicsIn many applications, modeling based on a normal kernel is preferred because not only does the normal kernel belong to the family of stable distributions, but also it is easy to satisfy the stationary condition in the stochastic process.
Sangwan Kim, Yongku Kim , Jung-In Seo
doaj +1 more source