Small self-contained plots for use in larger plots or to
    delegate plotting in other functions. Also contains a number of
    alternative color palettes and HSL color space based tools to modify
    colors or palettes.

Prediction limits for the Poisson distribution
  are produced from both frequentist and Bayesian viewpoints. Limiting results
  are provided in a Bayesian setting with uniform, Jeffreys and gamma as prior
  distributions. More details on the methodology are discussed in Bejleri and
  Nandram (2018) <doi:10.1080/03610926.2017.1373814> and Bejleri, Sartore and
  Nandram (2021) <doi:10.1007/s42952-021-00157-x>.

Power logit regression models for bounded
  continuous data, in which the density generator may be normal, Student-t, 
  power exponential, slash, hyperbolic, sinh-normal, or type II logistic. 
  Diagnostic tools associated with the fitted model, such as the residuals, 
  local influence measures, leverage measures, and goodness-of-fit statistics,
  are implemented. The estimation process follows the maximum likelihood approach
  and, currently, the package supports two types of estimators: the usual maximum 
  likelihood estimator and the penalized maximum likelihood estimator. More details
  about power logit regression models are described in 
  Queiroz and Ferrari (2022) <arXiv:2202.01697>.

Contains statistical inference tools applied to Partial Linear Regression (PLR) models. Specifically, point estimation, confidence intervals estimation, bandwidth selection, goodness-of-fit tests and analysis of covariance are considered. Kernel-based methods, combined with ordinary least squares estimation, are used and time series errors are allowed. In addition, these techniques are also implemented for both parametric (linear) and nonparametric regression models.

Multivariate regression methods
	Partial Least Squares Regression (PLSR), Principal Component
	Regression (PCR) and Canonical Powered Partial Least Squares (CPPLS).

Different methods for PLS analysis of one or two data tables such as Tucker's Inter-Battery, NIPALS, SIMPLS, SIMPLS-CA, PLS Regression, and PLS Canonical Analysis. The main reference for this software is the awesome book (in French) 'La Regression PLS: Theorie et Pratique' by Michel Tenenhaus.