Title: Analysis of Symmetry of Parasitic Infections
Description: Tools for the analysis and visualization of bilateral asymmetry in parasitic infections.

Title: Spline Regression with Adaptive Knot Selection
Description: Perform one-dimensional spline regression with automatic knot selection.
This package uses a penalized approach to select the most relevant knots.
B-splines of any degree can be fitted. More details in Goepp et al. (2018),
"Spline Regression with Automatic Knot Selection", <arXiv:1808.01770>.
Imports: magrittr, ggplot2, dplyr, tidyr, splines2, Rcpp, Matrix, mgcv,
Suggests: testthat, knitr, markdown, rmarkdown, covr
Author: Vivien Goepp [aut, cre] (<https://orcid.org/0000-0001-6961-4260>),

B-splines of any degree can be fitted. More details in 'Goepp et al. (2018)',
Imports: magrittr, ggplot2, dplyr, tidyr, splines2, Rcpp, mgcv, rlang
Suggests: knitr, markdown, rmarkdown, covr

Title: Augments the Use of 'Asreml' in Fitting Mixed Models
Description: Provides functions that assist in automating the testing of terms
in mixed models when 'asreml' is used to fit the models. The package 'asreml'
is marketed by 'VSNi' (http://www.vsni.co.uk/) as 'asreml-R' and provides a
computationally efficient algorithm for fitting mixed models using
Residual Maximum Likelihood. The content falls into the following natural
groupings: (i) Data, (ii) Object manipulation functions, (iii) Model modification
functions, (iv) Model testing functions, (v) Model diagnostics functions,
(vi) Prediction production and presentation functions, (vii) Response
transformation functions, and (viii) Miscellaneous functions.
A history of the fitting of a sequence of models is kept in a data frame.
Procedures are available for choosing models that conform to the hierarchy or
marginality principle and for displaying predictions for significant terms

Description: Assists in automating the testing of terms in mixed models when 'asreml' is used
to fit the models. The content falls into the following natural groupings: (i) Data, (ii) Object
manipulation functions, (iii) Model modification functions, (iv) Model testing functions,
(v) Model diagnostics functions, (vi) Prediction production and presentation functions,
(vii) Response transformation functions, and (viii) Miscellaneous functions. A history of the
fitting of a sequence of models is kept in a data frame. Procedures are available for choosing
models that conform to the hierarchy or marginality principle and for displaying predictions
for significant terms in tables and graphs. The package 'asreml' provides a computationally
efficient algorithm for fitting mixed models using Residual Maximum Likelihood. It can be
purchased from 'VSNi' (http://www.vsni.co.uk/) as 'asreml-R', who will supply a zip file for