A Future API for Parallel Processing using ‘callr’ (future.callr)
Implementation of the Future API on top of the ‘callr’ package. This allows you to process futures, as defined by the ‘future’ package, in parallel out of the box, on your local (Linux, macOS, Windows, …) machine. Contrary to backends relying on the ‘parallel’ package (e.g. ‘future::multisession’), the ‘callr’ backend provided here can run more than 125 parallel R processes.

Blocked Weighted Bootstrap (bbw)
The blocked weighted bootstrap (BBW) is an estimation technique for use with data from two-stage cluster sampled surveys in which either prior weighting (e.g. population-proportional sampling or PPS as used in Standardized Monitoring and Assessment of Relief and Transitions or SMART surveys) or posterior weighting (e.g. as used in rapid assessment method or RAM and simple spatial sampling method or S3M surveys). The method was developed by Accion Contra la Faim, Brixton Health, Concern Worldwide, Global Alliance for Improved Nutrition, UNICEF Sierra Leone, UNICEF Sudan and Valid International. It has been tested by the Centers for Disease Control (CDC) using infant and young child feeding (IYCF) data. See Cameron et al (2008) <doi:10.1162/rest.90.3.414> for application of bootstrap to cluster samples. See Aaron et al (2016) <doi:10.1371/journal.pone.0163176> and Aaron et al (2016) <doi:10.1371/journal.pone.0162462> for application of the blocked weighted bootstrap to estimate indicators from two-stage cluster sampled surveys.

Easily Carry Out Latent Profile Analysis (tidyLPA)
An interface to the ‘mclust’ package to easily carry out latent profile analysis (‘LPA’). Provides functionality to estimate commonly-specified models. Follows a tidy approach, in that output is in the form of a data frame that can subsequently be computed on. Also has functions to interface to the commercial ‘MPlus’ software via the ‘MplusAutomation’ package.