Data science methods used in wind energy applications. 
              Current functionalities include creating a multi-dimensional power curve model, 
              performing power curve function comparison, covariate matching, and energy decomposition. 
              Relevant works for the developed functions are: 
              funGP() - Prakash et al. (2022) <doi:10.1080/00401706.2021.1905073>, 
              AMK() - Lee et al. (2015) <doi:10.1080/01621459.2014.977385>, 
              tempGP() - Prakash et al. (2022) <doi:10.1080/00401706.2022.2069158>, 
              ComparePCurve() - Ding et al. (2021) <doi:10.1016/j.renene.2021.02.136>,
              deltaEnergy() - Latiffianti et al. (2022) <doi:10.1002/we.2722>,
              syncSize() - Latiffianti et al. (2022) <doi:10.1002/we.2722>,
              imptPower() - Latiffianti et al. (2022) <doi:10.1002/we.2722>,
              All other functions - Ding (2019, ISBN:9780429956508).

Data objects in R can be rendered as HTML tables using the
    JavaScript library 'DataTables' (typically via R Markdown or Shiny).
    The 'DataTables' library has been included in this R package. The
    package name 'DT' is an abbreviation of 'DataTables'.

Offers statistical methods to compare diagnostic performance between two binary diagnostic tests on the same subject in clinical studies. Includes functions for generating formatted tables to display diagnostic outcomes, facilitating a clear and comprehensive comparison directly through the R console. Inspired by and extending the functionalities of the 'DTComPair', 'tableone', and 'gtsummary' packages.

Deconvolving cell types from high-throughput gene profiling data. For more information on dtangle see Hunt et al. (2019) <doi:10.1093/bioinformatics/bty926>.

Function to create forest plots. Functions to use posterior samples from Bayesian bivariate meta-analysis model, Bayesian hierarchical summary receiver operating characteristic (HSROC) meta-analysis model or Bayesian latent class (LC) meta-analysis model to create Summary Receiver Operating Characteristic (SROC) plots using methods described by Harbord et al (2007)<doi:10.1093/biostatistics/kxl004>.