Functions Related to ICES Advice

A collection of functions that facilitate computational steps related to advice for fisheries management, according to ICES guidelines. These include methods for calculating reference points and model diagnostics.

Modelling Framework for the Estimation of Salmonid Abundance

A set of functions to estimate capture probabilities and densities from multipass pass removal data.

Fit the Gambin Model to Species Abundance Distributions

Fits unimodal and multimodal gambin distributions to species-abundance distributions from ecological data, as in in Matthews et al. (2014) . 'gambin' is short for 'gamma-binomial'. The main function is fit_abundances(), which estimates the 'alpha' parameter(s) of the gambin distribution using maximum likelihood. Functions are also provided to generate the gambin distribution and for calculating likelihood statistics.

High-Performance 'WebGl' Rendering for Package 'leaflet'

Provides bindings to the 'Leaflet.glify' JavaScript library which extends the 'leaflet' JavaScript library to render large data in the browser using 'WebGl'.

DATRAS Trawl Survey Database Web Services

R interface to access the web services of the ICES (International Council for the Exploration of the Sea) DATRAS trawl survey database < https://datras.ices.dk/WebServices/Webservices.aspx>.

String Distance Calculation with Tidy Data Principles

Calculation of string distance following the tidy data principles. Built on top of the 'stringdist' package.

Read and Process 'Pamguard' Binary Data

Functions for easily reading and processing binary data files created by 'Pamguard' (< https://www.pamguard.org/>). All functions for directly reading the binary data files are based on 'MATLAB' code written by Michael Oswald.

Functions to Support the ICES Transparent Assessment Framework

Functions to support the ICES Transparent Assessment Framework < https://taf.ices.dk> to organize data, methods, and results used in ICES assessments. ICES is an organization facilitating international collaboration in marine science.

Gillespie's Stochastic Simulation Algorithm (SSA)

Provides a simple to use, intuitive, and extensible interface to several stochastic simulation algorithms for generating simulated trajectories of finite population continuous-time model. Currently it implements Gillespie's exact stochastic simulation algorithm (Direct method) and several approximate methods (Explicit tau-leap, Binomial tau-leap, and Optimized tau-leap). The package also contains a library of template models that can be run as demo models and can easily be customized and extended. Currently the following models are included, 'Decaying-Dimerization' reaction set, linear chain system, logistic growth model, 'Lotka' predator-prey model, Rosenzweig-MacArthur predator-prey model, 'Kermack-McKendrick' SIR model, and a 'metapopulation' SIRS model. Pineda-Krch et al. (2008) .

Two-Sample Test of many Functional Means using the Energy Method

Given two samples of size n_1 and n_2 from a data set where each sample consists of K functional observations (channels), each recorded on T grid points, the function energy method implements a hypothesis test of equality of channel-wise mean at each channel using the bootstrapped distribution of maximum energy to control family wise error. The function energy_method_complex accomodates complex valued functional observations.