R/binsreg-package.R

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#'@title Binsreg Package Document
#'@description  Binscatter provides a flexible, yet parsimonious way of visualizing and summarizing large data sets in regression
#'              settings, and has been a popular methodology in applied microeconomics and other social sciences. The binsreg package provides tools for
#'              statistical analysis using the binscatter methods developed in
#'              \href{https://arxiv.org/abs/1902.09608}{Cattaneo, Crump, Farrell and Feng (2019a)}.
#'              \code{\link{binsreg}} implements binscatter estimation with robust inference and plots, including
#'              curve estimation, pointwise confidence intervals and uniform confidence band.
#'              \code{\link{binsregtest}} implements hypothesis testing procedures for parametric specification
#'              of and nonparametric shape restrictions on the unknown regression function.
#'              \code{\link{binsregselect}} implements data-driven number of bins selectors for binscatter
#'              implementation using either quantile-spaced or evenly-spaced binning/partitioning.
#'              All the commands allow for covariate adjustment, smoothness restrictions, and clustering,
#'              among other features.
#'
#'              The companion software article,
#'              \href{https://arxiv.org/abs/1902.09615}{Cattaneo, Crump, Farrell and Feng (2019b)},
#'              provides further implementation details and empirical illustration. For related Stata and R packages
#'              useful for nonparametric data analysis and statistical inference, visit
#'              \href{https://sites.google.com/site/nppackages}{https://sites.google.com/site/nppackages}.
#'@importFrom stats complete.cases quantile weighted.mean sd rnorm qnorm dnorm lm vcov
#'@importFrom splines splineDesign
#'@importFrom sandwich vcovCL
#'@import ggplot2
#'
#'@author
#' Matias D. Cattaneo, University of Michigan, Ann Arbor, MI. \email{cattaneo@umich.edu}.
#'
#' Richard K. Crump, Federal Reserve Bank of New York, New York, NY. \email{richard.crump@ny.frb.org}.
#'
#' Max H. Farrell, University of Chicago, Chicago, IL. \email{max.farrell@chicagobooth.edu}.
#'
#' Yingjie Feng (maintainer), University of Michigan, Ann Arbor, MI. \email{yjfeng@umich.edu}.
#'
#'@references
#' Cattaneo, M. D., R. K. Crump, M. H. Farrell, and Y. Feng. 2019a: \href{https://arxiv.org/abs/1902.09608}{On Binscatter}. Working Paper.
#'
#' Cattaneo, M. D., R. K. Crump, M. H. Farrell, and Y. Feng. 2019b: \href{https://arxiv.org/abs/1902.09615}{Binscatter Regressions}. Working Paper.
#'
#'@aliases binsreg-package
"_PACKAGE"

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binsreg documentation built on May 2, 2019, 12:19 p.m.