MGraph: graphical models for microarray data analysis

MGraph: graphical models for microarray data analysis

UNLABELLED This paper introduces a MATLAB toolbox, MGraph, which applies graphical models as a natural environment to formulate and solve problems in microarray data analysis. MGraph with its graphical interface allows the user to predict genetic regulatory networks by a graphical gaussian model (GGM), and to quantify the effects of different experimental treatment conditions on gene expression...

a new approach to credibility premium for zero-inflated poisson models for panel data

هدف اصلی از این تحقیق به دست آوردن و مقایسه حق بیمه باورمندی در مدل های شمارشی گزارش نشده برای داده های طولی می باشد. در این تحقیق حق بیمه های پبش گویی بر اساس توابع ضرر مربع خطا و نمایی محاسبه شده و با هم مقایسه می شود. تمایل به گرفتن پاداش و جایزه یکی از دلایل مهم برای گزارش ندادن تصادفات می باشد و افراد برای استفاده از تخفیف اغلب از گزارش تصادفات با هزینه پائین خودداری می کنند، در این تحقیق ...

Software for data analysis with graphical models

Wray L. Buntine RIACS at NASA Ames Research Center Mail Stop 269{2, Mo ett Field, CA 94035{1000, USA [email protected] H. Scott Roy Heuristicrats Research, Inc. 1678 Shattuck Avenue, Suite 310, Berkeley, CA 94709-1631, USA [email protected] Abstract Probabilistic graphical models are being used widely in arti cial intelligence and statistics, for instance, in diagnosis and expert syst...

Data Models for Exploratory Analysis of Heterogeneous Microarray Data

Ordinal Data Analysis via Graphical Models

Background. Undirected graphical models or Markov random fields (MRFs) are very popular for modeling multivariate probability distributions. A considerable amount of work on MRFs has focused on modeling continuous variables and unordered categorical variables also called as nominal variables. However, data from many real world applications involve ordered categorical variables also called as or...