Ridgeline Plots in ‘ggplot2’ (ggridges)
Ridgeline plots provide a convenient way of visualizing changes in distributions over time or space. This package enables the creation of such plots in ‘ggplot2’.

X Ray Vision on your Datasets (xray)
Tools to analyze datasets previous to any statistical modeling. Has various functions designed to find inconsistencies and understanding the distribution of the data.

Coloured Formatting for Columns (pillar)
Provides a ‘pillar’ generic designed for formatting columns of data using the full range of colours provided by modern terminals.

Principal Components Analysis using NIPALS with Gram-Schmidt Orthogonalization (nipals)
Principal Components Analysis of a matrix using Non-linear Iterative Partial Least Squares with Gram-Schmidt orthogonalization of the scores and loadings. Optimized for speed. See Andrecut (2009) <doi:10.1089/cmb.2008.0221>.

Simulation-Based Quasi-Likelihood Estimation (qle)
A simulation-based quasi-likelihood method (Baaske, M. (2014) <doi:10.5566/ias.v33.p107-119>) for parameter estimation of parametric statistical models for which closed-form representations of distributional characteristics are unavailable and can only be obtained by computationally intensive simulations of the model.

Spatial Inference using Integrated Nested Laplace Approximation (inlabru)
Facilitates spatial modeling using integrated nested Laplace approximation via the INLA package (<http://www.r-inla.org> ). Additionally, implements a log Gaussian Cox process likelihood for modeling univariate and spatial point processes based on ecological survey data. See Yuan Yuan, Fabian E. Bachl, Finn Lindgren, David L. Borchers, Janine B. Illian, Stephen T. Buckland, Havard Rue, Tim Gerrodette (2017), <arXiv:1604.06013>.

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