Author: Marie G. GantzPublisher:
ISBN:
Category :
Languages : en
Pages : 208
Book Description
Applying Dirichlet Process Mixture Models to Compositional Data, with Application to Train Waybill Data
Author: Marie G. GantzDissertation Abstracts International
Author: Publisher:
ISBN:
Category : Dissertations, Academic
Languages : en
Pages : 860
Book Description
Analysis of the Dirichlet Process Mixture Model with Application to Dialogue Act Classification
Author: Alireza Bakhtiari KoohsorkhiPublisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
Analysis of Compositional Data Using Dirichlet Covariate Models
Author: Rafiq Hamed HijaziPublisher:
ISBN:
Category : Distribution (Probability theory)
Languages : en
Pages : 302
Book Description
Dirichlet Process Mixture Modeling
Author: Yuting QiPublisher:
ISBN:
Category : Mixture distributions (Probability theory)
Languages : en
Pages : 258
Book Description
In this dissertation, we develop two novel statistical models utilizing the Dirichlet process (DP) prior: (i) a DP-based hidden Markov mixture model, and (ii) multi-task compressive sensing.
Extensions of Dirichlet Process Mixture Models
Author: Natalie BurnsPublisher:
ISBN:
Category :
Languages : en
Pages : 0
Book Description
bottom level to ensure that the random partitions of subjects within each GWG trajectory class rely sufficiently on the neonatal outcomes and are not dominated by the maternal characteristics. The second extension, the EDP-HDP, is a model which combines the advantages of the EDP with characteristics of the hierarchical Dirichlet process (HDP). In this model, we place a DP prior on the base measure in the bottom level of the EDP. We include the GWG trajectories in the bottom level of clustering and child cardiometabolic outcomes in the top level of clustering to predict the child outcomes using the GWG measurements. Incorporating the HDP in the bottom level of the EDP allows the GWG trajectory classes to be shared across outcome clusters.
A Survey of Statistical Network Models
Author: Anna GoldenbergPublisher: Now Publishers Inc
ISBN: 1601983204
Category : Computers
Languages : en
Pages : 118
Book Description
Networks are ubiquitous in science and have become a focal point for discussion in everyday life. Formal statistical models for the analysis of network data have emerged as a major topic of interest in diverse areas of study, and most of these involve a form of graphical representation. Probability models on graphs date back to 1959. Along with empirical studies in social psychology and sociology from the 1960s, these early works generated an active network community and a substantial literature in the 1970s. This effort moved into the statistical literature in the late 1970s and 1980s, and the past decade has seen a burgeoning network literature in statistical physics and computer science. The growth of the World Wide Web and the emergence of online networking communities such as Facebook, MySpace, and LinkedIn, and a host of more specialized professional network communities has intensified interest in the study of networks and network data. Our goal in this review is to provide the reader with an entry point to this burgeoning literature. We begin with an overview of the historical development of statistical network modeling and then we introduce a number of examples that have been studied in the network literature. Our subsequent discussion focuses on a number of prominent static and dynamic network models and their interconnections. We emphasize formal model descriptions, and pay special attention to the interpretation of parameters and their estimation. We end with a description of some open problems and challenges for machine learning and statistics.
Mathematician for All Seasons
Author: Hugo SteinhausPublisher: Birkhäuser
ISBN: 3319231022
Category : Mathematics
Languages : en
Pages : 411
Book Description
This book presents, in his own words, the life of Hugo Steinhaus (1887–1972), noted Polish mathematician of Jewish background, educator, and mathematical popularizer. A student of Hilbert, a pioneer of the foundations of probability and game theory, and a contributor to the development of functional analysis, he was one of those instrumental to the extraordinary flowering of Polish mathematics before and after World War I. In particular, it was he who “discovered” the great Stefan Banach. Exhibiting his great integrity and wit, Steinhaus’s personal story of the turbulent times he survived – including two world wars and life postwar under the Soviet heel – cannot but be of consuming interest. His recounting of the fearful years spent evading Nazi terror is especially moving. The steadfast honesty and natural dignity he maintained while pursuing a life of demanding scientific and intellectual enquiry in the face of encroaching calamity and chaos show him to be truly a mathematician for all seasons. The present work will be of great interest not only to mathematicians wanting to learn some of the details of the mathematical blossoming that occurred in Poland in the first half of the 20th century, but also to anyone wishing to read a first-hand account of the history of those unquiet times in Europe – and indeed world-wide – by someone of uncommon intelligence and forthrightness situated near an eye of the storm.
Sisters, Super-Creeps and Slushy, Gushy Love Songs
Author: Karen McCombiePublisher:
ISBN: 9781407117867
Category : Ally (Fictitious character : McCombie)
Languages : en
Pages : 208
Book Description
Ally knows her super-efficient big sis Linn finds their chaotic family a bit ... exasperating. But when Linn falls for Q, the tearaway lead singer in a local band, all her sensible ways go out of the window. Everyone else can see that Q's a creep, but does Ally have the courage to burst Linn's heart-shaped bubble?
Author: Euripides