GitHub

multinomial-logistic-regression

This project explores the determinants of inflation prediction errors using data from the Survey of Consumer Expectations (SCE) from 2013 to 2023 and monthly National and yearly State-level PCE. The ...
JSTOR Daily

A Comparison of Regression Models for Small Counts

This is a preview. Log in through your library . Abstract Count data with means <2 are often assumed to follow a Poisson distribution. However, in many cases these kinds of data, such as number of ...
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 ...
JSTOR Daily

Patterns and Trends in Occupational Attainment of First Jobs in the Netherlands, 1930-1995: Ordinary Least Squares Regression versus Conditional Multinomial Logistic Regression

Journal of the Royal Statistical Society. Series A (Statistics in Society), Vol. 166, No. 1 (2003), pp. 63-84 (22 pages) This paper brings together the virtues of linear regression models for status ...
Australian Bureau of Statistics

1352.0.55.044 - Research Paper: Using the Multinomial Logistic Regression Model to Construct Design-based Estimates for the Input-Output Survey via an Estimating Equation ...

One strategy for managing small business provider load is to ask small businesses for a reduced set of data items and then use synthetic estimation techniques to estimate totals for those data items ...
IEEE

Unlocking Nutritional Insights: Exploring Meal Analysis for Enhanced Dietary Choices with Multinomial Logistic Regression

Abstract: This study explores the application of Multinomial Logistic Regression (MLR) in analyzing meal compositions to facilitate improved dietary choices. With the escalating prevalence of ...