We extend existing gene enrichment tests to perform adverse
    event enrichment analysis. Unlike the continuous gene expression data,
    adverse event data are counts. Therefore, adverse event data has many zeros
    and ties. We propose two enrichment tests. One is a modified Fisher's exact
    test based on pre-selected significant adverse events, while the other is
    based on a modified Kolmogorov-Smirnov statistic. We add Covariate
    adjustment to improve the analysis."Adverse event enrichment tests using
    VAERS" Shuoran Li, Lili Zhao (2020) <doi:10.48550/arXiv.2007.02266>.

Facilitate the analysis of data related to aquatic ecology, specifically the establishment of carbon budget. 
  Currently, the package allows the below analysis.
  (i) the calculation of greenhouse gas flux based on data obtained from trace gas analyzer using the method described in Lin et al. (2024).
  (ii) the calculation of Dissolved Oxygen (DO) metabolism based on data obtained from dissolved oxygen data logger using the method described in Staehr et al. (2010). 
  Yong et al. (2024) <doi:10.5194/bg-21-5247-2024>.
  Staehr et al. (2010) <doi:10.4319/lom.2010.8.0628>.

Fetch Australian Energy Market Operator (AEMO)
    public data from 'NEMweb' <http://nemweb.com.au> and the
    Market Management System Data Model (MMSDM) historical
    archive. Provides tidy access to 5-minute and 30-minute
    wholesale electricity prices, regional demand, dispatch-unit
    output, interconnector flows, rooftop photovoltaic generation,
    generator bids, predispatch forecasts, frequency control
    ancillary services markets, and gas market data across the
    National Electricity Market (NEM) regions. Data is published
    by AEMO under its Copyright Permissions Notice
    <https://www.aemo.com.au/privacy-and-legal-notices/copyright-permissions>.

Developed for Computing the probability density function, cumulative 
             distribution function, random generation, estimating the parameters of asymmetric
             exponential power distribution, and robust regression analysis with error
             term that follows asymmetric exponential power distribution. The asymmetric
             exponential power distribution studied here is a special case of that introduced
             by Dongming and Zinde-Walsh (2009) <doi:10.1016/j.jeconom.2008.09.038>.