Contains a sample of the 2005 Grade 8 Mathematics data from the National Assessment of Educational Progress (NAEP). This data set is called the NAEP Primer.

For use in summary functions to omit missing values 
    conditionally using specified checks.

A set of convenience functions as well as geographical/political
  data about Nigeria, aimed at simplifying work with data and information that
  are specific to the country.

A small package designed for interpreting continuous and categorical latent variables. You provide a data set with a latent variable you want to understand and some other explanatory variables. It provides a description of the latent variable based on the explanatory variables. It also provides a name to the latent variable.

An application for the empirical extrapolation of time features selecting and summarizing the most relevant patterns in time sequences.

In this implementation of the Naive Bayes classifier
    following class conditional distributions are available: 'Bernoulli',
    'Categorical', 'Gaussian', 'Poisson', 'Multinomial' and non-parametric
    representation of the class conditional density estimated via Kernel
    Density Estimation. Implemented classifiers handle missing data and
    can take advantage of sparse data.

In empirical studies, instrumental variable (IV) regression is the signature method to solve the endogeneity problem. If we enforce the exogeneity condition of the IV, it is likely that we end up with a large set of IVs without knowing which ones are good. Also, one could face the model uncertainty for structural equation, as large micro dataset is commonly available nowadays. This package uses adaptive group lasso and B-spline methods to select the nonparametric components of the IV function, with the linear function being a special case (naivereg). The package also incorporates two stage least squares estimator (2SLS), generalized method of moment (GMM), generalized empirical likelihood (GEL) methods post instrument selection, logistic-regression instrumental variables estimator (LIVE, for dummy endogenous variable problem), double-selection plus instrumental variable estimator (DS-IV) and double selection plus logistic regression instrumental variable estimator (DS-LIVE), where the double selection methods are useful for high-dimensional structural equation models. The naivereg is nonparametric version of 'ivregress' in 'Stata' with IV selection and high dimensional features. The package is based on the paper by Q. Fan and W. Zhong, "Nonparametric Additive Instrumental Variable Estimator: A Group Shrinkage Estimation Perspective" (2018), Journal of Business & Economic Statistics <doi:10.1080/07350015.2016.1180991> as well as a series of working papers led by the same authors.