CatchAll

CatchAll estimates ecological and taxonomic diversity from observed count data using parametric and non-parametric statistical models.

Key Features:

• Estimation target: Calculates the number of classes or taxa from observed count data.
• Parametric models: Implements a suite of parametric estimators grounded in contemporary statistical research.
• Non-parametric procedures: Includes established non-parametric estimators for diversity and richness.
• Computational optimization: Optimized to handle large datasets for applications such as microbial ecology.
• Dual modeling approach: Combines parametric and non-parametric methods to enhance flexibility and accuracy in diversity estimation.

Scientific Applications:

• Species diversity estimation: Estimating species richness within ecosystems from count data.
• Microbial ecology: Estimating microbial species richness and distribution from microbial count datasets.
• Public health: Tracking and estimating the number of disease variants or classes from epidemiological count data.
• Criminal justice: Analyzing the number of crime-pattern classes from count data.
• Software engineering: Estimating the number of bug or defect classes from observed counts.

Methodology:

Computes parametric and non-parametric statistical estimators based on observed count data using advanced statistical models.