Provides functionality to interact with the 
  'FieldClimate' API <https://api.fieldclimate.com/v2/docs/>.

An integrated package for constructing random forest prediction intervals using a fast implementation package 'ranger'. This package can apply the following three methods described in Haozhe Zhang, Joshua Zimmerman, Dan Nettleton, and Daniel J. Nordman (2019) <doi:10.1080/00031305.2019.1585288>: the out-of-bag prediction interval, the split conformal method, and the quantile regression forest.

A programmatic interface to 'FishBase', re-written
    based on an accompanying 'RESTful' API. Access tables describing over 30,000
    species of fish, their biology, ecology, morphology, and more. This package also
    supports experimental access to 'SeaLifeBase' data, which contains
    nearly 200,000 species records for all types of aquatic life not covered by
    'FishBase.'

Helps fisheries scientists collect measurements from calcified
    structures and back-calculate estimated lengths at previous ages using
    standard procedures and models. This is intended to replace much of the
    functionality provided by the now out-dated 'fishBC' software
    (<https://fisheries.org/bookstore/all-titles/software/70317/>).

A programmatic interface to 'openfisheries.org'. This package is
    part of the 'rOpenSci' suite (http://ropensci.org).

Provides data processing and summarization of data from FishNet2.net
  in text and graphical outputs. Allows efficient filtering of information and
  data cleaning.

Rank-based (R) estimation and inference for linear models.  Estimation
        is for general scores and a library of commonly used score
        functions is included.

Sets a significance level for  Random Forest MDI (Mean Decrease in Impurity, Gini or
             sum of squares) variable importance scores, using an empirical Bayes approach.
             See Dunne et al. (2022)  <doi:10.1101/2022.04.06.487300>.

Data for the vignette and examples in 'RFlocalfdr'. Contains a dataset of 1103547 importance values,
       and the table of variables used in the random forest splits. The data is Chromosome 22 taken from Auton et al.
       (2015) <doi:10.1038/nature15393>. It also contains a 51 samples by 22283 genes data set taken from
       Spira et al. (2004) <doi:10.1165/rcmb.2004-0273OC>.