Propagation of uncertainty using higher-order Taylor expansion and Monte Carlo simulation. Calculations are based on matrix calculus including covariance structure, referencing established methodologies from Arras 1998 (first order), Wang & Iyer 2005 (second order), and BIPM Supplement 1 (Monte Carlo). The dataset was authored by Andrej-Nikolai Spiess.
Use Cases
- Calculate first-order uncertainty propagation based on covariance matrices.
- Perform second-order uncertainty analysis using Taylor expansion methods.
- Estimate propagated uncertainties via Monte Carlo simulation techniques.
- Benchmark uncertainty propagation algorithms against established reference methods.
Strengths
- Methodology is explicitly based on three established, cited scientific references.
- Implements both analytical (Taylor expansion) and numerical (Monte Carlo) approaches for uncertainty propagation.
Limitations
- Row count, column definitions, and sample data are unavailable, limiting suitability assessment.
- Description metadata is limited; actual data quality and structure require manual inspection after download.
- Last update date and license are unknown.
Provenance
- Source
- Andrej-Nikolai Spiess
- Collection Method
- Likely contains computational implementations or results based on the cited uncertainty propagation methods.
- Time Range
- null
- Freshness
- Last updated date is unknown; freshness unverified.
- Geography
- null