JSTOR Daily

Controlling for overdispersion in grouped conditional logit models: A computationally simple application of Dirichlet-multinomial regression

In this article, we provide a random utility-based derivation of the Dirichlet-multinomial regression and propose it as a convenient alternative for dealing with overdispersed multinomial data. We ...
GitHub

GitHub - Laurenssei/Predictive-Modeling-of-Student-Mathematics-Performance-Multinomial-Logistic-Regression-Analysis

This project develops and evaluates a multinomial logistic regression model to predict mathematics achievement levels (Poor, Average, Good, Excellent) among 358 final-year Junior High School students ...
JSTOR Daily

Bayesian Variable Selection and Model Averaging in High-Dimensional Multinomial Nonparametric Regression

This article presents a Bayesian method for estimating nonparametrically a high-dimensional multinomial regression model. The regression functions are expressed as sums of main effects and ...
IEEE

Improving the Performance of Multinomial Logistic Regression in Vowel Recognition by Determining Best Regression Coefficients

Abstract: The performance of Multinomial Logistic Regression (MLR) is highly dependent on the estimated value of its parameters (Regression Coefficients - RCs). However, the usual maximum likelihood ...
IEEE

Hyperspectral image denoising using legendre Fenchel Transformation for improved Multinomial Logistic Regression based classification

Abstract: The abundant spectral and spatial information in the hyperspectral images (HSI) are largely used in the field of remote sensing. Though there are highly sophisticated sensors to capture the ...