Collection of functions for quality control (QC) of climatological daily time series (e.g. the ECA&D station data).

For environmental chemists, ecologists, researchers and agricultural scientists to understand the dissipation kinetics, calculate the half-life periods and rate constants of compounds, pesticides, contaminants in different matrices.

A user-friendly interface, using Shiny, to analyse glucose-stimulated insulin secretion (GSIS) 
    assays in pancreatic beta cells or islets.
    The package allows the user to import several sets of experiments from different spreadsheets 
    and to perform subsequent steps: summarise in a tidy format, visualise data quality 
    and compare experimental conditions without omitting to account for technical confounders 
    such as the date of the experiment or the technician.
    Together, insane is a comprehensive method that optimises pre-processing and analyses of 
    GSIS experiments in a friendly-user interface.
    The Shiny App was initially designed for EndoC-betaH1 cell line following method described 
    in Ndiaye et al., 2017 (<doi:10.1016/j.molmet.2017.03.011>).

Provides tools for probabilistic taxon assignment with informatic sequence classification trees. See Wilkinson et al (2018) <doi:10.7287/peerj.preprints.26812v1>.

Using embedded sdmx queries, get the data of more than 150 000 insee series from 'bdm' macroeconomic database.

A tool to provide an easy, intuitive and consistent
    access to information contained in various R models, like model
    formulas, model terms, information about random effects, data that was
    used to fit the model or data from response variables. 'insight'
    mainly revolves around two types of functions: Functions that find
    (the names of) information, starting with 'find_', and functions that
    get the underlying data, starting with 'get_'. The package has a
    consistent syntax and works with many different model objects, where
    otherwise functions to access these information are missing.