Estimation of sparse directed acyclic graphs for multivariate counts data
نویسندگان
چکیده
منابع مشابه
Sparse Directed Acyclic Word Graphs
The suffix tree of string w is a text indexing structure that represents all suffixes ofw. A sparse suffix tree ofw represents only a subset of suffixes of w. An application to sparse suffix trees is composite pattern discovery from biological sequences. In this paper, we introduce a new data structure named sparse directed acyclic word graphs (SDAWGs), which are a sparse text indexing version ...
متن کاملSparse compact directed acyclic word graphs
The suffix tree of string w represents all suffixes of w, and thus it supports full indexing of w for exact pattern matching. On the other hand, a sparse suffix tree of w represents only a subset of the suffixes of w, and therefore it supports sparse indexing of w. There has been a wide range of applications of sparse suffix trees, e.g., natural language processing and biological sequence analy...
متن کاملPenalized Estimation of Directed Acyclic Graphs From Discrete Data
The Bayesian network, with structure given by a directed acyclic graph (DAG), is a popular class of graphical models. However, learning Bayesian networks from discrete or categorical data is particularly challenging, due to the large parameter space and the difficulty in searching for a sparse structure. In this article, we develop a maximum penalized likelihood method to tackle this problem. I...
متن کاملExact estimation of multiple directed acyclic graphs
Abstract. This paper considers the problem of estimating the structure of multiple related directed acyclic graph (DAG) models. Building on recent developments in exact estimation of DAGs using integer linear programming (ILP), we present an ILP approach for joint estimation over multiple DAGs, that does not require that the vertices in each DAG share a common ordering. Furthermore, we allow al...
متن کاملPenalized likelihood methods for estimation of sparse high-dimensional directed acyclic graphs.
Directed acyclic graphs are commonly used to represent causal relationships among random variables in graphical models. Applications of these models arise in the study of physical and biological systems where directed edges between nodes represent the influence of components of the system on each other. Estimation of directed graphs from observational data is computationally NP-hard. In additio...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Biometrics
سال: 2016
ISSN: 0006-341X
DOI: 10.1111/biom.12467