Given a project schedule and associated costs, this package calculates the earned value to date. It is an implementation of Project Management Body of Knowledge (PMBOK) methodologies (reference Project Management Institute. (2021). A guide to the Project Management Body of Knowledge (PMBOK guide) (7th ed.). Project Management Institute, Newtown Square, PA, ISBN 9781628256673 (pdf)).

The Food and Agriculture Organization-56 Penman-Monteith is one of the important method for estimating evapotranspiration from vegetated land areas. This package helps to calculate reference evapotranspiration using the weather variables collected from weather station. Evapotranspiration is the process of water transfer from the land surface to the atmosphere through evaporation from soil and other surfaces and transpiration from plants. The package aims to support agricultural, hydrological, and environmental research by offering accurate and accessible reference evapotranspiration calculation. This package has been developed using concept of Córdova et al. (2015)<doi:10.1016/j.apm.2022.09.004> and Debnath et al. (2015) <doi:10.1007/s40710-015-0107-1>.

Conduct internal validation of a clinical prediction model for a binary outcome.
  Produce bias corrected performance metrics (c-statistic, Brier score, calibration intercept/slope)
  via bootstrap (simple bootstrap, bootstrap optimism, .632 optimism) and cross-validation (CV optimism,
  CV average). Also includes functions to assess model stability via bootstrap resampling.
  See Steyerberg et al. (2001) <doi:10.1016/s0895-4356(01)00341-9>;
  Harrell (2015) <doi:10.1007/978-3-319-19425-7>;
  Riley and Collins (2023) <doi:10.1002/bimj.202200302>.

Check available classification and regression data sets from the PMLB repository and download them.
    The PMLB repository (<https://github.com/EpistasisLab/pmlbr>) contains a curated collection of data sets for evaluating and comparing machine learning algorithms.
    These data sets cover a range of applications, and include binary/multi-class classification problems and 
    regression problems, as well as combinations of categorical, ordinal, and continuous features.
    There are currently over 150 datasets included in the PMLB repository.