Results 121 to 130 of about 23,712,988 (293)
Clustering Survival Outcomes using Dirichlet Process Mixture [PDF]
, 2014 Motivated by the national evaluation of mortality rates at kidney transplant centers in the United States, we sought to assess transplant center long- term survival outcomes by applying a methodology developed in Bayesian non-parametrics literature.
Shi, Jingchunzi +3 more
core +1 more source
Antiferroelectric Phase Transitions Under Electric Fields: A Review of Physics and Applications
Interdisciplinary Materials, EarlyView.Field‐induced phase transitions in antiferroelectric materials, driven by electric field, temperature, or stress, enable diverse applications including energy storage, electrocaloric cooling, and negative capacitance. These transitions are regulated through compositional design, strain engineering, heterostructure, and size effect, providing a unified ...
Dingxin Wang +7 more
wiley +1 more source
Bayesian Nonparametric Model for Estimating Multistate Travel Time Distribution
Journal of Advanced Transportation, 2017 Multistate models, that is, models with more than two distributions, are preferred over single-state probability models in modeling the distribution of travel time.
Emmanuel Kidando +3 more
doaj +1 more source
Time-Sensitive Dirichlet Process Mixture Models
, 2005 We introduce Time-Sensitive Dirichlet Process Mixture models for clustering. The models allow infinite mixture components just like standard Dirichlet process mixture models.
John Lafferty +2 more
core
Irrigation and Drainage, EarlyView.ABSTRACT Crop modelling is essential for agricultural water management but often relies on simplified water balance routines that limit representation of soil moisture dynamics. To address this limitation, we developed a coupled model that integrates the 1‐D Richards equation, solved using a finite difference method into the FAO AquaCrop.
Krishna Panthi +2 more
wiley +1 more source
Mapping the Influence of Ansoff's Corporate Strategy
Strategic Change, EarlyView.ABSTRACT This paper conducts a systematic, data‐driven analysis of H. Igor Ansoff's enduring impact on strategic management scholarship. Despite Ansoff's recognition as the “father of strategic management” and the continued relevance of his frameworks—including the Ansoff matrix, weak signals analysis, and strategic thrust—a comprehensive understanding
Ivan Zupic +3 more
wiley +1 more source
Consensus Clustering for Multi-Source Data Integration via Dirichlet Process Mixture Models
IEEE AccessThe integration of multiple heterogeneous data sources for consensus clustering presents substantial methodological challenges, particularly when the true number of clusters is unknown and data sources provide conflicting information.
Nurul Afiqah Burhanuddin
doaj +1 more source
Journal of Statistical Software, 2017 msBP is an R package that implements a new method to perform Bayesian multiscale nonparametric inference introduced by Canale and Dunson (2016). The method, based on mixtures of multiscale beta dictionary densities, overcomes the drawbacks of Pólya trees
Antonio Canale
doaj +1 more source
A Dirichlet Mixture Model of Hawkes Processes for Event Sequence Clustering
CoRR, 2017 We propose an effective method to solve the event sequence clustering problems based on a novel Dirichlet mixture model of a special but significant type of point processes --- Hawkes process. In this model, each event sequence belonging to a cluster is generated via the same Hawkes process with specific parameters, and different clusters correspond to
Hongteng Xu, Hongyuan Zha
openaire +3 more sources
Strategic Change, EarlyView.ABSTRACT This systematic review examines how H. Igor Ansoff's theoretical contributions have evolved in contemporary strategic management through cluster analysis of 116 publications (1968–2024). Four distinct research clusters were identified, revealing that Ansoff's legacy has shifted from theoretical foundations to pedagogical applications and ...
Adiemir Hortega +4 more
wiley +1 more source