Implements S3 classes for storing dates and date-times based on the Jalali calendar. 
    The main design goal of 'shide' is consistency with base R's 'Date' and 'POSIXct'.
    It provide features such as: date-time parsing, formatting and arithmetic.

An exact method for computing the Poisson-Binomial Distribution (PBD). The package provides a function for generating a random sample from the PBD, as well as two distinct approaches for computing the density, distribution, and quantile functions of the PBD. The first method uses direct-convolution, or a dynamic-programming approach which is numerically stable but can be slow for a large input due to its quadratic complexity. The second method is much faster on large inputs thanks to its use of Fast Fourier Transform (FFT) based convolutions. Notably in this case the package uses an exponential shift to practically guarantee the relative accuracy of the computation of an arbitrarily small tail of the PBD -- something that FFT-based methods often struggle with. This ShiftConvolvePoiBin method is described in Peres, Lee and Keich (2020) <arXiv:2004.07429> where it is also shown to be competitive with the fastest implementations for exactly computing the entire Poisson-Binomial distribution.

Detecting, visualizing and estimating shifts, 
    with a specific focus on stage-discharge rating shifts.
    The main methods are described in Darienzo et al. (2021) <doi:10.1029/2020WR028607>
    and Mansanarez et al. (2019) <doi:10.1029/2018WR023389>.
    See also 'BayDERS' <https://github.com/MatteoDarienzo/BayDERS> for similar tools, 
    and 'RatingShiftHappens' <https://github.com/Felipemendezrios/RatingShiftHappens> for an older version of this package.

Fast enrichment analysis for locally correlated statistics
        via circular permutations.
        The analysis can be performed at multiple significance thresholds
        for both primary and auxiliary data sets with
        efficient correction for multiple testing.

Provides confidence intervals in least-squares regressions when the
  variable of interest has a shift-share structure, and in instrumental
  variables regressions when the instrument has a shift-share structure. The
  confidence intervals implement the AKM and AKM0 methods developed in Adão,
  Kolesár, and Morales (2019) <doi:10.1093/qje/qjz025>.