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

Two general demographic decomposition methods are offered: Pseudo-continuous decomposition proposed by Horiuchi, Wilmoth, and Pletcher (2008) <doi:10.1353/dem.0.0033> and stepwise replacement decomposition proposed by Andreev, Shkolnikov and Begun (2002) <doi:10.4054/DemRes.2002.7.14>.

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.

Connects to the <https://genderize.io/>, <https://agify.io/> and <https://nationalize.io/> APIs to estimate gender, age and nationality of a first name.

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.

Functions for creating demographic table
      with simple summary statistics, with optional
      comparison(s) over one or more groups.  Numeric
      variables are summarized in means, standard
      deviations, medians, inter-quartile-ranges (IQR),
      skewness, Shapiro-Wilk normality test and ranges,
      and compared using two-sample t-test, Wilcoxon
      test, ANOVA and/or Kruskal-Wallis test. Logical
      and factor variables are summarized in counts and
      percentages and compared using chi-squared test
      and/or Fisher's exact test.