It calculates the alpha-quantile proposed by Daouia and Simar (2007) <doi:10.1016/j.jeconom.2006.07.002> and order-m efficiency score in multi-dimension proposed by Daouia and Gijbels (2011) <doi:10.1016/j.jeconom.2010.12.002> and computes several summaries and representation of the associated frontiers in 2d and 3d.

Extracts and parses structured metadata ('YAML' or 'TOML')
    from the beginning of text documents. Front matter is a common pattern
    in 'Quarto' documents, 'R Markdown' documents, static site generators,
    documentation systems, content management tools and even 'Python' and
    'R' scripts where metadata is placed at the top of a document,
    separated from the main content by delimiter fences.

An R API to MET Norway's 'Frost' API <https://frost.met.no/index.html> 
    to retrieve data as data frames. The 'Frost' API, and the underlying data, is 
    made available by the Norwegian Meteorological Institute (MET Norway). The data
    and products are distributed under the 
    Norwegian License for Open Data 2.0 (NLOD) <https://data.norge.no/nlod/en/2.0>
    and Creative Commons 4.0 <https://creativecommons.org/licenses/by/4.0/>.

Emulates a 'Forth' programming environment with added features to 
  interface between R and 'Forth'. Implements most of the functionality described 
  in the original "Starting Forth" textbook <https://www.forth.com/starting-forth/>.

Automatically perform 
             a reanalysis series
             on a data set using CNA, and calculate the fit-robustness
             of the resulting models, as described in 
             Parkkinen and Baumgartner (2021) <doi:10.1177/0049124120986200>.

Climate is a critical component limiting growing range of plant species, which
    also determines cultivar adaptation to a region. The evaluation of climate influence on
    fruit production is critical for decision-making in the design stage of orchards and 
    vineyards and in the evaluation of the potential consequences of future climate. Bio-
    climatic indices and plant phenology are commonly used to describe the suitability of 
    climate for growing quality fruit and to provide temporal and spatial information about 
    regarding ongoing and future changes. 'fruclimadapt' streamlines the assessment of 
    climate adaptation and the identification of potential risks for grapevines and fruit 
    trees. Procedures in the package allow to i) downscale daily meteorological variables
    to hourly values (Forster et al (2016) <doi:10.5194/gmd-9-2315-2016>),
    ii) estimate chilling and forcing heat accumulation (Miranda et al (2019)
    <https://ec.europa.eu/eip/agriculture/sites/default/files/fg30_mp5_phenology_critical_temperatures.pdf>),
    iii) estimate plant phenology (Schwartz (2012) <doi:10.1007/978-94-007-6925-0>), iv) 
    calculate bioclimatic indices to evaluate fruit tree and grapevine adaptation (e.g. Badr 
    et al (2017) <doi:10.3354/cr01532>), v) estimate the incidence of weather-related disorders 
    in fruits (e.g. Snyder and de Melo-Abreu (2005, ISBN:92-5-105328-6) and vi)
    estimate plant water requirements (Allen et al (1998, ISBN:92-5-104219-5)).