Categorical Regression Splines

Regression splines that handle a mix of continuous and categorical (discrete) data often encountered in applied settings. I would like to gratefully acknowledge support from the Natural Sciences and Engineering Research Council of Canada (NSERC, < https://www.nserc-crsng.gc.ca>), the Social Sciences and Humanities Research Council of Canada (SSHRC, < https://www.sshrc-crsh.gc.ca>), and the Shared Hierarchical Academic Research Computing Network (SHARCNET, < https://www.sharcnet.ca>). We would also like to acknowledge the contributions of the GNU GSL authors. In particular, we adapt the GNU GSL B-spline routine gsl_bspline.c adding automated support for quantile knots (in addition to uniform knots), providing missing functionality for derivatives, and for extending the splines beyond their endpoints.

Simple Bootstrap Routines

Simple bootstrap routines.

Colour Palettes for Data

Colour palettes for data, based on some well known public data sets. Includes helper functions to map absolute values to known palettes, and capture the work of image colour mapping as raster data sets.

Topic Models

Provides an interface to the C code for Latent Dirichlet Allocation (LDA) models and Correlated Topics Models (CTM) by David M. Blei and co-authors and the C++ code for fitting LDA models using Gibbs sampling by Xuan-Hieu Phan and co-authors.

Tracking Data

Access and manipulate spatial tracking data, with straightforward coercion from and to other formats. Filter for speed and create time spent maps from tracking data. There are coercion methods to convert between 'trip' and 'ltraj' from 'adehabitatLT', and between 'trip' and 'psp' and 'ppp' from 'spatstat'. Trip objects can be created from raw or grouped data frames, and from types in the 'sp', sf', 'amt', 'trackeR', 'mousetrap', and other packages, Sumner, MD (2011) < https://figshare.utas.edu.au/articles/thesis/The_tag_location_problem/23209538>.

Distribution Functions and Parameter Estimates for the Triangle Distribution

Provides the "r, q, p, and d" distribution functions for the triangle distribution. Also includes maximum likelihood estimation of parameters.

R Package for Aqua Culture

Solves the individual bioenergetic balance for different aquaculture sea fish (Sea Bream and Sea Bass; Brigolin et al., 2014 ) and shellfish (Mussel and Clam; Brigolin et al., 2009 ; Solidoro et al., 2000 ). Allows for spatialized model runs and population simulations.

Identifying Stocks in Genetic Data

Provides a mixture model for clustering individuals (or sampling groups) into stocks based on their genetic profile. Here, sampling groups are individuals that are sure to come from the same stock (e.g. breeding adults or larvae). The mixture (log-)likelihood is maximised using the EM-algorithm after finding good starting values via a K-means clustering of the genetic data. Details can be found in: Foster, S. D.; Feutry, P.; Grewe, P. M.; Berry, O.; Hui, F. K. C. & Davies (2020) .

Decision Curve Analysis for Model Evaluation

Diagnostic and prognostic models are typically evaluated with measures of accuracy that do not address clinical consequences. Decision-analytic techniques allow assessment of clinical outcomes, but often require collection of additional information may be cumbersome to apply to models that yield a continuous result. Decision curve analysis is a method for evaluating and comparing prediction models that incorporates clinical consequences, requires only the data set on which the models are tested, and can be applied to models that have either continuous or dichotomous results. See the following references for details on the methods: Vickers (2006) , Vickers (2008) , and Pfeiffer (2020) .

Coupled Chain Radiative Transfer Models

A set of radiative transfer models to quantitatively describe the absorption, reflectance and transmission of solar energy in vegetation, and model remotely sensed spectral signatures of vegetation at distinct spatial scales (leaf,canopy and stand). The main principle behind ccrtm is that many radiative transfer models can form a coupled chain, basically models that feed into each other in a linked chain (from leaf, to canopy, to stand, to atmosphere). It allows the simulation of spectral datasets in the solar spectrum (400-2500nm) using leaf models as PROSPECT5, 5b, and D which can be coupled with canopy models as 'FLIM', 'SAIL' and 'SAIL2'. Currently, only a simple atmospheric model ('skyl') is implemented. Jacquemoud et al 2008 provide the most comprehensive overview of these models .