Ordinal regression and classification ... thereby improving performance in applications like medical diagnosis and age prediction while maintaining model clarity [3,4]. Additionally, distance ...

For binary logistic regression, dependent variables must be binary, while ordinal logistic ... a range of applications in healthcare, finance, and marketing. Using logistic models with independent ...

Many economically important characteristics of agricultural crops are measured as ordinal ... model Under the multivariate model, we have formulated the thresholds as a subset of the regression ...

These sources of information are modeled as response variables in a multivariate ordinal regression model estimated by a composite likelihood procedure. The proposed framework provides probabilities ...

The data for this example are from Ezzet and Whitehead (1991), who describe a crossover experiment on two groups of patients using two different inhaler devices (A and B). Patients from group 1 used ...

The least absolute shrinkage and selection operator-logistic regression (Lasso-LR) model is optimal for predicting ...