Semiparametric estimation of multinomial discrete-choice models using a subset of choices

Source URL: fox.web.rice.edu

CLUSTERING MULTINOMIAL OBSERVATIONS VIA FINITE AND INFINITE MIXTURE MODELS AND MCMC ALGORITHMS Mario Medvedovic, University of Cincinnati Medical Center Mario Medvedovic, Department of Environmental Health, University of

Source URL: eh3.uc.edu

Nonparametric identification and estimation of random coefficients in multinomial choice models

Source URL: fox.web.rice.edu

KS_JU@DPIL-FIRE2016:Detecting Paraphrases in Indian Languages Using Multinomial Logistic Regression Model Kamal Sarkar Department of Computer Science and Engineering Jadavpur University, Kolkata, India

Source URL: ceur-ws.org

A Fast and Numerically Robust Method for Exact Multinomial Goodness-of-Fit Test Uri KEICH and Niranjan NAGARAJAN Evaluating the significance of goodness-of-fits tests for multinomial data in general, and estimating the p

Source URL: www.maths.usyd.edu.au

Maximum Likelihood Estimation of Dirichlet Distribution Parameters Jonathan Huang Abstract. Dirichlet distributions are commonly used as priors over proportional data. In this paper, I will introduce this distribution, d

Source URL: jonathan-huang.org

• Statistics
• Mathematical analysis
• Probability
• Probability distributions
• Gamma distribution
• Dirichlet distribution
• Exponential family
• Beta distribution
• Mixture model
• Multinomial distribution
• Likelihood function
• Maximum likelihood estimation

Correlated Community Estimation Models Over a Set of Names Suresh Veluru∗ , Yogachandran Rahulamathavan∗ , Suresh Manandhar† , and Muttukrishnan Rajarajan∗ ∗ Information Security Group, School of Engineering a

Source URL: www.uncertaintyofidentity.com

• Statistics
• Probability
• Probability distributions
• Statistical natural language processing
• Latent Dirichlet allocation
• Statistical models
• Mixture model
• Topic model
• Dirichlet distribution
• Multinomial distribution
• Gibbs sampling
• Perplexity

Some Issues in Using PROC LOGISTIC for Binary Logistic Regression by David C. Schlotzhauer Contents

Source URL: www.ats.ucla.edu

• Statistics
• Regression analysis
• Logistic regression
• Logit
• Odds ratio
• Probit model
• Statistical classification
• Dependent and independent variables
• Multinomial logistic regression
• Dummy variable

Let’s Put Garbage—Can Regressions and Garbage—Can Probits Where They Belong Christopher H. Achen Department of Politics Princeton University Princeton, NJ 08544

Source URL: www.columbia.edu

• Statistics
• Regression analysis
• Linear regression
• Probit
• Ordinary least squares
• Dependent and independent variables
• Errors and residuals
• General linear model
• Econometrics
• Dummy variable
• Multinomial logistic regression

FP7-ICT Strategic Targeted Research Project (STREP) TrendMiner (NoLarge-scale, Cross-lingual Trend Mining and Summarisation of Real-time Media Streams D3.3.1 Tools for mining non-stationary data - v2 Clustering

Source URL: www.trendminer-project.eu

• Statistical natural language processing
• Machine learning
• Statistics
• Artificial intelligence
• Topic model
• Latent Dirichlet allocation
• Gibbs sampling
• Multinomial logistic regression
• Dynamic topic model
• Dirichlet-multinomial distribution