The digits of the old version (before 2000 year) of 'Chinese ID Card Number' is 15, this package aims to update to the current version of 18 digits. Besides, this package can help check whether the given 'ID' is right or not.

Provides access to the 
    Idea Data Center (IDC) application for conducting 
    nonresponse bias analysis (NRBA). The IDC NRBA app is an
    interactive, browser-based Shiny application that can be used to 
    analyze survey data with respect to response rates,
    representativeness, and nonresponse bias. This app provides a user-friendly
    interface to statistical methods implemented by the 'nrba' package.
    Krenzke, Van de Kerckhove, and Mohadjer (2005) 
    <http://www.asasrms.org/Proceedings/y2005/files/JSM2005-000572.pdf>
    and Lohr and Riddles (2016) 
    <https://www150.statcan.gc.ca/n1/en/pub/12-001-x/2016002/article/14677-eng.pdf?st=q7PyNsGR>
    provide an overview of the statistical methods implemented in the application.

The Integro-Difference Equation model is a linear, dynamical model used to model
   phenomena that evolve in space and in time; see, for example, Cressie and Wikle (2011,
   ISBN:978-0-471-69274-4) or Dewar et al. (2009) <doi:10.1109/TSP.2008.2005091>. At the
   heart of the model is the kernel, which dictates how the process evolves from one time
   point to the next. Both process and parameter reduction are used to facilitate computation,
   and spatially-varying kernels are allowed. Data used to estimate the parameters are assumed
   to be readings of the process corrupted by Gaussian measurement error. Parameters are fitted
   by maximum likelihood, and estimation is carried out using an evolution algorithm.

When added to an existing shiny app, users may subset any
    developer-chosen R data.frame on the fly. That is, users are empowered to
    slice & dice data by applying multiple (order specific) filters using the
    AND (&) operator between each, and getting real-time updates on the number
    of rows effected/available along the way. Thus, any downstream processes
    that leverage this data source (like tables, plots, or statistical procedures)
    will re-render after new filters are applied. The shiny module’s user interface has
    a 'minimalist' aesthetic so that the focus can be on the data &
    other visuals. In addition to returning a reactive (filtered) data.frame,
    'IDEAFilter' as also returns 'dplyr' filter statements used to actually slice
    the data.