Chinese numerals processing in R, such as conversion between 
    Chinese numerals and Arabic numerals as well as detection and extraction of
    Chinese numerals in character objects and string. This package supports 
    the casual scale naming system and the respective SI prefix systems used 
    in mainland China and Taiwan: 
    "The State Council's Order on the Unified Implementation of Legal Measurement Units in Our Country"
    The State Council of the People's Republic of China (1984)
    "Names, Definitions and Symbols of the Legal Units of Measurement and the Decimal Multiples and Submultiples" 
    Ministry of Economic Affairs (2019) <https://gazette.nat.gov.tw/egFront/detail.do?metaid=108965>.

Performs copy number variants association analysis with Lasso and Weighted Fusion penalized regression. 
  Creates a "CNV profile curve" to represent an individual’s CNV events across a genomic region so to capture variations 
  in CNV length and dosage. When evaluating association, the CNV profile curve is directly used as a predictor in the 
  regression model, avoiding the need to predefine CNV loci. CNV profile regression estimates CNV effects at each genome
  position, making the results comparable across different studies. The penalization encourages sparsity 
  in variable selection with a Lasso penalty and encourages effect smoothness between consecutive CNV events with a weighted
  fusion penalty, where the weight controls the level of smoothing between adjacent CNVs. 
  For more details, see Si (2024) <doi:10.1101/2024.11.23.624994>.

Implements Dirichlet multinomial modeling of relative abundance data using functionality provided by the 'Stan' software. The purpose of this package is to provide a user friendly way to interface with 'Stan' that is suitable for those new to modeling. For more regarding the modeling mathematics and computational techniques we use see our publication in Molecular Ecology Resources titled 'Dirichlet multinomial modeling outperforms alternatives for analysis of ecological count data' (Harrison et al. 2020 <doi:10.1111/1755-0998.13128>).