Logistic regression for simulating damage occurrence on a fruit grading line

A NEW APPROACH FOR PARAMETER ESTIMATION IN FUZZY LOGISTIC REGRESSION

Logistic regression analysis is used to model categorical dependent variable. It is usually used in social sciences and clinical research. Human thoughts and disease diagnosis in clinical research contain vagueness. This situation leads researchers to combine fuzzy set and statistical theories. Fuzzy logistic regression analysis is one of the outcomes of this combination and it is used in situa...

Sample size determination for logistic regression

The problem of sample size estimation is important in medical applications, especially in cases of expensive measurements of immune biomarkers. This paper describes the problem of logistic regression analysis with the sample size determination algorithms, namely the methods of univariate statistics, logistics regression, cross-validation and Bayesian inference. The authors, treating the regr...

A logistic regression of risk factors for disease occurrence on Asian shrimp farms.

Serious shrimp-disease outbreaks have reduced shrimp production and slowed industry growth since 1991. This paper tests factors such as farm sitting and design, and farm-management practices for relationships with disease occurrence. Logistic regression is used to analyze farm-level data from 3951 shrimp farms in 13 Asian countries. Disease occurrence is modeled as a 0-1 variable where 1 = dise...

Predicting shrimp disease occurrence: artificial neural networks vs. logistic regression

Predicting the occurrence of disease outbreaks in aquacultural farms can be of considerable value to the long-term sustainable development of the industry. Prior research on disease prediction has essentially depended upon traditional statistical models with varying degrees of prediction accuracy. Furthermore, the application of these models in sustainable aquaculture development and in control...

Notes on Logistic Regression