An efficient algorithm for sampling from sink (x) for generating random correlation matrices. Issue 5 (4th May 2022)

• Record Type: Journal Article
• Authors: Makalic, Enes; Schmidt, Daniel F.
• Is Part Of: Communications in statistics. Volume 51:Issue 5(2022)
• Page Start: 2731
• Page End: 2735
• Publication Date: 2022-05-04
• Subjects: Correlation matrix -- Inverse transform sampling -- Rejection sampling; 62D05 -- 62H20 -- 62-04; Mathematical statistics -- Periodicals; Mathematical statistics -- Data processing -- Periodicals; Digital computer simulation -- Periodicals; 519.5
• DOI: 10.1080/03610918.2019.1700277
• Languages: English
• ISSNs: 0361-0918

Abstract

Abstract: In this note, we develop a novel algorithm for generating random numbers from a distribution with a probability density function proportional to sin k ( x ), x ∈ ( 0, π ) and k ≥ 1 . Our algorithm is highly efficient and is based on rejection sampling where the envelope distribution is an appropriately chosen beta distribution. An example application illustrating how the new algorithm can be used to generate random correlation matrices is discussed.