Provides a simple approach for constructing dynamic materials
 modeling suggested by Prasad and Gegel (1984) <doi:10.1007/BF02664902>. It
 can easily generate various processing-maps based on this model as well. The
 calculation result in this package contains full materials constants, information
 about power dissipation efficiency factor, and rheological properties, can
 be exported completely also, through which further analysis and customized
 plots will be applicable as well.

Estimation of transition probabilities for the
	illness-death model and or the three-state progressive model.

Provide data generation and estimation tools for the truncated positive normal (tpn)
             model discussed in Gomez, Olmos, Varela and Bolfarine (2018) 
             <doi:10.1007/s11766-018-3354-x>, the slash tpn distribution discussed in Gomez, 
             Gallardo and Santoro (2021) <doi:10.3390/sym13112164>, the bimodal tpn distribution 
             discussed in Gomez et al. (2022) <doi:10.3390/sym14040665>, the flexible tpn model
	     <doi:10.3390/math11214431> and the unit tpn distribution <doi:10.1016/j.chemolab.2025.105322>.

Regression models for temporal process responses with
        time-varying coefficient.

Density, distribution function, the quantile function, 
    random generation function, and maximum likelihood estimation.

The two-parameter Xgamma and Poisson Xgamma distributions are analyzed, covering standard distribution and regression functions, maximum likelihood estimation, quantile functions, probability density and mass functions, cumulative distribution functions, and random number generation. References include: "Sen, S., Chandra, N. and Maiti, S. S. (2018). On properties and applications of a two-parameter XGamma distribution. Journal of Statistical Theory and Applications, 17(4): 674--685. <doi:10.2991/jsta.2018.17.4.9>." "Wani, M. A., Ahmad, P. B., Para, B. A. and Elah, N. (2023). A new regression model for count data with applications to health care data. International Journal of Data Science and Analytics. <doi:10.1007/s41060-023-00453-1>."