Title: A Shiny App for Design of Experiments in Life Sciences
person(given = "North Dakota State University",
Description: A shiny design of experiments (DOE) app that aids in the creation of traditional,
un-replicated, augmented and partially-replicated designs applied to agriculture,
plant breeding, forestry, animal and biological sciences.
Imports: config, golem, shiny (>= 1.6.0), attempt, DT, glue, htmltools,
shinythemes, turner, dplyr, shinyjqui, numbers, blocksdesign,
shinycssloaders, magrittr, ggplot2, plotly, viridis, shinyalert
Suggests: testthat (>= 3.0.0), spelling, rlang
Packaged: 2021-05-18 16:07:14 UTC; didier.murilloflorez

Imports: config, golem, shiny (>= 1.6.0), htmltools, DT, shinythemes,
turner, dplyr, shinyjqui, numbers, blocksdesign,
shinycssloaders, magrittr, ggplot2, plotly, viridis,
Suggests: testthat (>= 3.0.0), spelling, rlang, glue, knitr, rmarkdown
Packaged: 2022-08-05 14:40:56 UTC; didier.murilloflorez

Packaged: 2022-09-20 21:30:03 UTC; didier.murilloflorez

Author: Alexandre Brouste <Alexandre.Brouste@imag.fr>, and
Description: This package provides routines for simulate random fields.
Packaged: Thu Sep 13 14:50:50 2007; root

Packaged: Mon Nov 19 21:55:58 2007; root

Author: Alexandre Brouste <Alexandre.Brouste@univ-lemans.fr>, and
Packaged: Mon Oct 5 14:29:32 2009; Alexandre

Author: Alexandre Brouste <Alexandre.Brouste@univ-lemans.fr>, Sophie
Depends: R (>= 2.0.0), methods, rgl, RColorBrewer

Title: Random Fields (and Bridges) Simulations
Description: Tools for random fields and bridges simulations.

Title: Simulation of Plot-Level Data in Plant Breeding Field Trials
Authors@R: c(person("Christian", "Werner", email = "werner.christian@proton.me",
person("Daniel", "Tolhurst", role = "aut",
person("Giovanny", "Covarrubias-Pazaran", role = "ctb",
person("Lorena", "Batista", role = "ctb",
Description: Simulates plot-level data in plant breeding field trials for multiple traits in multiple
environments. Its core function simulates spatially correlated plot-level errors across correlated
traits using bivariate interpolation or a two-dimensional autoregressive process of order one (AR1:AR1).
'FieldSimR' then combines this spatial error with random measurement error at a user-defined
ratio. The simulated plot-level errors can be combined with genetic values (e.g. true, simulated or
predicted) to generate plot-level phenotypes. 'FieldSimR' provides wrapper functions to simulate the
genetic values for multiple traits in multiple environments using the 'R' package 'AlphaSimR'.
Imports: fields, interp, matrixcalc, mbend
Author: Christian Werner [aut, cre] (<https://orcid.org/0000-0001-9400-5061>),