TKRISK Distribution Fitter Module
✔ Comprehensive Distribution Library
Access a wide range of probability distributions, including normal, lognormal, Weibull, gamma, beta, and many more, to fit diverse types of data.
✔ Advanced Fitting Algorithms
Utilize state-of-the-art fitting methods such as Maximum Likelihood Estimation (MLE), Method of Moments, and Bayesian inference for accurate parameter estimation.
✔ Goodness-of-Fit Tests
Employ various statistical tests including Kolmogorov-Smirnov, Anderson-Darling, and Chi-squared to assess the quality of distribution fits.
✔ Automated Distribution Selection
Leverage intelligent algorithms to automatically identify the best-fitting distribution from a set of candidates, saving time and ensuring optimal fits.
- Mixture Models: Fit complex, multi-modal data using mixture distributions, capturing nuanced patterns in your risk factors.
- Copula Fitting: Model dependencies between variables using various copula functions, enabling accurate representation of multivariate risks.
- Truncated and Censored Distributions: Handle incomplete or constrained data with specialized fitting techniques for truncated and censored distributions.
- Non-parametric Fitting: Implement kernel density estimation and other non-parametric methods for fitting arbitrary data distributions.
- Bayesian Model Averaging: Account for model uncertainty by averaging over multiple fitted distributions, providing more robust risk estimates.
- Feed fitted distributions directly into the Graph Creation module for more accurate probabilistic models.
- Enhance the Sampling module with precisely fitted distributions for realistic Monte Carlo simulations.
- Improve the accuracy of the Inference module by providing well-fitted priors and likelihoods.
- Support the Scenario Analysis module with data-driven distribution choices for more realistic scenario generation.
- Finance: Model asset returns, volatility patterns, and credit default rates for improved risk management.
- Insurance: Fit claim severity and frequency distributions for accurate premium pricing and reserving.
- Manufacturing: Model equipment failure times and quality control metrics for reliability analysis.
- Environmental Science: Fit distributions to climate data, pollution levels, and natural disaster occurrences for risk assessment.
- Healthcare: Model patient outcomes, treatment efficacy, and disease progression for evidence-based decision making.
- Supports fitting of univariate and multivariate distributions to datasets with millions of data points.
- Implements efficient algorithms for fast convergence, even with complex distributions.
- Provides parallel processing capabilities for improved performance on large datasets.
- Offers a comprehensive API for seamless integration with external data sources and custom fitting workflows.
- Includes advanced visualization tools for comparing fitted distributions and assessing fit quality.
Get Started with Advanced Distribution Fitting
Enhance the accuracy and reliability of your risk models with TKRISK's powerful Distribution Fitter module.
Whether you're analyzing financial returns, modeling insurance claims, or assessing environmental risks, our advanced fitting capabilities provide the precision you need for confident decision-making in uncertain environments.
