Tools facilitating access to the 'macro_data' service of the
    'La Societe Nouvelle' API. It ensures an easy and fully-disclosed
    access to all macro-level data used in the 'La Societe Nouvelle'
    systems and the related metadata.  Related API can be accessed from
    <https://api.lasocietenouvelle.org/>.

Tools for statistical analysis using partitioning-based least squares regression as described in Cattaneo, Farrell and Feng (2019a, <arXiv:1804.04916>) and Cattaneo, Farrell and Feng (2019b, <arXiv:1906.00202>): lsprobust() for nonparametric point estimation of regression functions and their derivatives and for robust bias-corrected (pointwise and uniform) inference; lspkselect() for data-driven selection of the IMSE-optimal number of knots; lsprobust.plot() for regression plots with robust confidence intervals and confidence bands; lsplincom() for estimation and inference for linear combinations of regression functions from different groups.

Creates plots of peptides from shotgun proteomics analysis of secretome and lysate samples. These plots contain associated protein features and scores for potential secretion and truncation.

Linear splines with convenient parametrisations such that 
  (1) coefficients are slopes of consecutive segments or (2) coefficients are 
  slope changes at consecutive knots. Knots can be set manually or at break points
  of equal-frequency or equal-width intervals covering the range of 'x'.
  The implementation follows Greene (2003), chapter 7.2.5.

Implements the LS-PLS (least squares - partial least squares)
  method described in for instance Jørgensen, K., Segtnan, V. H., Thyholt, K.,
  Næs, T. (2004)  "A Comparison of Methods for Analysing Regression Models with
  Both Spectral and Designed Variables"
  Journal of Chemometrics, 18(10), 451--464, <doi:10.1002/cem.890>.

A collection of tools intended to make introductory 
    statistics easier to teach, including wrappers for common 
    hypothesis tests and basic data manipulation. It accompanies 
    Navarro, D. J. (2015). Learning Statistics with R: A Tutorial 
    for Psychology Students and Other Beginners, Version 0.6.