Easily Manage Options Files for your Packages and Scripts (simpleroptions)
A framework to easily setup and maintain options files in your R packages and scripts.

Reproducible, Accessible & Shareable Species Distribution Modelling (zoon)
Reproducible and remixable species distribution modelling. The package reads user submitted modules from an online repository, runs full SDM workflows and returns output that is fully reproducible.

Apply Function to Elements in Parallel using Futures (future.apply)
Implementations of apply(), lapply(), sapply() and friends that can be resolved using any future-supported backend, e.g. parallel on the local machine or distributed on a compute cluster. These future_*apply() functions comes with the same pros and cons as the corresponding base-R *apply() functions but with the additional feature of being able to be processed via the future framework.

Permutation Tests for Regression, (Repeated Measures) ANOVA/ANCOVA and Comparison of Signals (permuco)
Functions to compute p-values based on permutation tests. Regression, ANOVA and ANCOVA, omnibus F-tests, marginal unilateral and bilateral t-tests are available. Several methods to handle nuisance variables are implemented (Kherad-Pajouh, S., & Renaud, O. (2010) <doi:10.1016/j.csda.2010.02.015> ; Kherad-Pajouh, S., & Renaud, O. (2014) <doi:10.1007/s00362-014-0617-3> ; Winkler, A. M., Ridgway, G. R., Webster, M. A., Smith, S. M., & Nichols, T. E. (2014) <doi:10.1016/j.neuroimage.2014.01.060>). An extension for the comparison of signals issued from experimental conditions (e.g. EEG/ERP signals) is provided. Several corrections for multiple testing are possible, including the cluster-mass statistic (Maris, E., & Oostenveld, R. (2007) <doi:10.1016/j.jneumeth.2007.03.024>) and the threshold-free cluster enhancement (Smith, S. M., & Nichols, T. E. (2009) <doi:10.1016/j.neuroimage.2008.03.061>).

Compute Krippendorff’s Alpha (icr)
Provides functions to compute and plot Krippendorff’s inter-coder reliability coefficient alpha and bootstrapped uncertainty estimates (Krippendorff 2004, ISBN:0761915443).

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