Tu & Zhou (1999) <doi:10.1002/(SICI)1097-0258(19991030)18:20%3C2749::AID-SIM195%3E3.0.CO;2-C> showed that comparing the means of populations whose data-generating distributions are non-negative with excess zero observations is a problem of great importance in the analysis of medical cost data. In the same study, Tu & Zhou discuss that it can be difficult to control type-I error rates of general-purpose statistical tests for comparing the means of these particular data sets. This package allows users to perform a modified bootstrap-based t-test that aims to better control type-I error rates in these situations.

Residual balancing is a robust method of constructing weights for
  marginal structural models, which can be used to estimate (a) the average treatment effect in 
  a cross-sectional observational study, (b) controlled direct/mediator effects in causal mediation
  analysis, and (c) the effects of time-varying treatments in panel data (Zhou and Wodtke 2020
  <doi:10.1017/pan.2020.2>). This package provides three functions, rbwPoint(), rbwMed(), and rbwPanel(),
  that produce residual balancing weights for estimating (a), (b), (c), respectively.

Data for the examples and exercises in the book "R by Example".  
    Jim Albert and Maria Rizzo (2012, ISBN 978-1-4614-1365-3).

Relational Class Analysis (RCA) is a method for detecting
        heterogeneity in attitudinal data (as described in Goldberg
        A., 2011, Am. J. Soc, 116(5)).

Classify hemispherical 
    photographs of the plant canopy with algorithms specially developed for 
    such a task and well documented in 
    Díaz and Lencinas (2015) <doi:10.1109/lgrs.2015.2425931> and 
    Díaz and Lencinas (2018) <doi:10.1139/cjfr-2018-0006>. It supports 
    non-circular hemispherical photography, such as those acquired with  
    15mm lenses or with auxiliary fish-eye lenses attached to mobile devices. 
    For smartphone-based hemispherical photography see 
    Díaz (2023) <doi:10.1111/2041-210x.14059>. Most of the functions also 
    support restricted view photography.