نتایج جستجو برای: hierarchical models

تعداد نتایج: 983582  

Journal: :Journal of Mathematical Psychology 2013

Journal: :Journal of Research in Personality 2019

Journal: :Journal of open source software 2022

2011
Tracy M. Sweet Andrew C. Thomas Brian W. Junker

Intervention studies in school systems are sometimes aimed not at changing curriculum or classroom technique, but rather at changing the way that teachers, teaching coaches and administrators in schools work with one another—in short, changing the professional social networks of educators. Current methods of social network analysis are ill-suited to modeling the multiple partially-exchangeable ...

Journal: :journal of ai and data mining 2016
y. vaghei a. farshidianfar

in recent years, underactuated nonlinear dynamic systems trajectory tracking, such as space robots and manipulators with structural flexibility, has become a major field of interest due to the complexity and high computational load of these systems. hierarchical sliding mode control has been investigated recently for these systems; however, the instability phenomena will possibly occur, especia...

In recent years, underactuated nonlinear dynamic systems trajectory tracking, such as space robots and manipulators with structural flexibility, has become a major field of interest due to the complexity and high computational load of these systems. Hierarchical sliding mode control has been investigated recently for these systems; however, the instability phenomena will possibly occur, especia...

2009
Shane T. Jensen Kenneth E. Shirley

The use of statistical modeling in baseball has received substantial attention recently in both the media and academic community. We focus on a relatively under-explored topic: the use of statistical models for the analysis of fielding based on high-resolution data consisting of on-field location of batted balls. We combine spatial modeling with a hierarchical Bayesian structure in order to eva...

ژورنال: اندیشه آماری 2021

In this paper, we first define longitudinal-dynamic heteroscedastic hierarchical  normal  models. These models can be used to fit longitudinal data in which the dependency structure is constructed through a dynamic model rather than observations. We discuss different methods for estimating the hyper-parameters. Then the corresponding estimates for the hyper-parameter that causes the association...

Journal: :Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2016

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