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Shiny Apps to Support Capacity Building on Harvest Control Rules
Three Shiny apps are provided that introduce Harvest Control Rules (HCR) for fisheries management. 'Introduction to HCRs' provides a simple overview to how HCRs work. Users are able to select their own HCR and step through its performance, year by year. Biological variability and estimation uncertainty are introduced. 'Measuring performance' builds on the previous app and introduces the idea of using performance indicators to measure HCR performance. 'Comparing performance' allows multiple HCRs to be created and tested, and their performance compared so that the preferred HCR can be selected.
Calculations and Visualisations Related to Geometric Morphometrics
A toolset for Geometric Morphometrics and mesh processing. This includes (among other stuff) mesh deformations based on reference points, permutation tests, detection of outliers, processing of sliding semi-landmarks and semi-automated surface landmark placement.
Analysis of Adaptive Immune Receptor Repertoire Germ Line Statistics
Multiple tools are now available for inferring the personalised
germ line set from an adaptive immune receptor repertoire.
Output from these tools is converted to
a single format and supplemented with rich data such as usage and
characterisation of 'novel' germ line alleles. This data can be
particularly useful when considering the validity of novel inferences. Use
of the analysis provided is described in
Outlier Detection Using Invariant Coordinate Selection
Multivariate outlier detection is performed using invariant coordinates where the package offers different methods to choose the appropriate components. ICS is a general multivariate technique with many applications in multivariate analysis. ICSOutlier offers a selection of functions for automated detection of outliers in the data based on a fitted ICS object or by specifying the dataset and the scatters of interest. The current implementation targets data sets with only a small percentage of outliers.
Univariate Outlier Detection
Detect outliers in one-dimensional data.
Acoustic Template Detection in R
Acoustic template detection and monitoring database interface. Create, modify, save, and use templates for detection of animal vocalizations. View, verify, and extract results. Upload a MySQL schema to a existing instance, manage survey metadata, write and read templates and detections locally or to the database.
String Interpolation for Documents, Reports and Apps
Extra strength 'glue' for data-driven templates. String interpolation for 'Shiny' apps or 'R Markdown' and 'knitr'-powered 'Quarto' documents, built on the 'glue' and 'whisker' packages.
Collection of Methods to Detect Dichotomous and Polytomous Differential Item Functioning (DIF)
Methods to detect differential item functioning (DIF) in dichotomous
and polytomous items, using both classical and modern approaches. These include
Mantel-Haenszel procedures, logistic regression (including ordinal models), and
regularization-based methods such as LASSO. Uniform and non-uniform DIF effects
can be detected, and some methods support multiple focal groups. The package
also provides tools for anchor purification, rest score matching, effect size
estimation, and DIF simulation. See Magis, Beland, Tuerlinckx, and De Boeck
(2010, Behavior Research Methods, 42, 847–862,
Stack Overflow's Greatest Hits
Helper functions collected from StackOverflow.com, a question and answer site for professional and enthusiast programmers.
Scans R Projects for Vulnerable Third Party Dependencies
Collects a list of your third party R packages, and scans them with the 'OSS' Index provided by 'Sonatype', reporting back on any vulnerabilities that are found in the third party packages you use.