The 'ntfy' (pronounce: notify) service is a simple HTTP-based pub-sub
    notification service. It allows you to send notifications to your phone or 
    desktop via scripts from any computer, entirely without signup, cost or 
    setup. It's also open source if you want to run your own. 
    Visit <https://ntfy.sh> for more details.

Implements statistical tools for analyzing, simulating, and computing properties of the New Topp-Leone Kumaraswamy Inverse Exponential (NTLKwIEx) distribution. See Atchadé M, Otodji T, and Djibril A (2024) <doi:10.1063/5.0179458> and Atchadé M, Otodji T, Djibril A, and N'bouké M (2023) <doi:10.1515/phys-2023-0151> for details.

Dealing with neutrosophic data of the form N=D+I(where N is a Neutrosophic number
   ,D is the determinant part of the number and I is  the indeterminacy part)
   using the neutrosophic two way anova test keeps the type I error low.
   This algorithm calculates the fisher statistics when we have a neutrosophic
   data, also tests two hypothesizes, first is to test differences between treatments,
   and second is to test differences between sectors. For more information see
    Miari, Mahmoud; Anan, Mohamad Taher; Zeina, Mohamed Bisher(2022)
    <https://www.americaspg.com/articleinfo/21/show/1058>.

Simulation, estimation, prediction procedure, and model identification methods for nonlinear time series analysis, including threshold autoregressive models, Markov-switching models, convolutional functional autoregressive models, nonlinearity tests, Kalman filters and various sequential Monte Carlo methods. More examples and details about this package can be found in the book "Nonlinear Time Series Analysis" by Ruey S. Tsay and Rong Chen, John Wiley & Sons, 2018 (ISBN: 978-1-119-26407-1).

Provides a collection of datasets related to neutrosophic sets for statistical modeling and analysis.

Computes the pdf, cdf, quantile function and generating random numbers for neutrosophic distributions. This family have been developed by different authors in the recent years. See Patro and Smarandache (2016) <doi:10.5281/zenodo.571153> and Rao et al (2023) <doi:10.5281/zenodo.7832786>.