Developed to Solve the Multi-Criteria Decision Making Problems with Decision Making Trial and Evaluation Laboratory Technique in R.

Generalized Deming regression, Theil-Sen regression and Passing-Bablock regression functions.

Fits, bootstraps, and evaluates two-component normal and lognormal mixture models. Includes diagnostic plots and statistical evaluation of mixture model fits using differential evolution optimization.

Three general demographic decomposition methods: Pseudo-continuous decomposition proposed by Horiuchi, Wilmoth, and Pletcher (2008) <doi:10.1353/dem.0.0033>, stepwise replacement decomposition proposed by Andreev, Shkolnikov and Begun (2002) <doi:10.4054/DemRes.2002.7.14>, and lifetable response experiments proposed by Caswell (1989) <doi:10.1016/0304-3800(89)90019-7>.

Designed to support the visualization, numerical computation,
     qualitative analysis, model-data fusion, and stochastic simulation for
     autonomous systems of differential equations. Euler and Runge-Kutta methods
     are implemented, along with tools to visualize the two-dimensional
     phaseplane. Likelihood surfaces and a simple Markov Chain Monte Carlo
     parameter estimator can be used for model-data fusion of differential
     equations and empirical models. The Euler-Maruyama method is provided for
     simulation of stochastic differential equations. The package was originally
     written for internal use to support teaching by Zobitz, and refined to
     support the text "Exploring modeling with data and differential equations
     using R" by John Zobitz (2021) <https://jmzobitz.github.io/ModelingWithR/index.html>.

Construction and analysis of matrix population models in R.

The Demographic Table in R combines contingency table for categorical variables, mean and standard deviation for continuous variables. t-test, chi-square test and Fisher's exact test calculated the p-value of two groups. The standardized mean difference were performed with 95 % confident interval, and writing table into document file.