Longitudinal Graphical Lasso

For high-dimensional correlated observations, this package carries out the L_1 penalized maximum likelihood estimation of the precision matrix (network) and the correlation parameters. The correlated data can be longitudinal data (may be irregularly spaced) with dampening correlation or clustered data with uniform correlation. For the details of the algorithms, please see the paper Jie Zhou et al. Identifying Microbial Interaction Networks Based on Irregularly Spaced Longitudinal 16S rRNA sequence data .

Yeast-Proteome Secondary-Structure Calculator

An extension for 'NetSurfP-2.0' (Klausen et al. (2019) ) which is specifically designed to analyze the results of bottom-up-proteomics that is primarily analyzed with 'MaxQuant' (Cox, J., Mann, M. (2008) ). This tool is designed to process a large number of yeast peptides that produced as a results of whole yeast cell-proteome digestion and provide a coherent picture of secondary structure of proteins.

Find Related Items and Lexical Dimensions in a Lexicon

Implements code to identify lexical competitors in a given list of words. We include many of the standard competitor types used in spoken word recognition research, such as functions to find cohorts, neighbors, and rhymes, amongst many others. The package includes documentation for using a variety of lexicon files, including those with form codes made up of multiple letters (i.e., phoneme codes) and also basic orthographies. Importantly, the code makes use of multiple CPU cores and vectorization when possible, making it extremely fast and able to handle large lexicons. Additionally, the package contains documentation for users to easily write new functions, allowing researchers to examine other relationships within a lexicon. Preprint: < https://osf.io/preprints/psyarxiv/8dyru/>. Open access: . Citation: Li, Z., Crinnion, A.M. & Magnuson, J.S. (2021). .

Nonlinear Mixed Effects Models in Population PK/PD

Fit and compare nonlinear mixed-effects models in differential equations with flexible dosing information commonly seen in pharmacokinetics and pharmacodynamics (Almquist, Leander, and Jirstrand 2015 ). Differential equation solving is by compiled C code provided in the 'rxode2' package (Wang, Hallow, and James 2015 ).

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.

Read and Write Standard 'C' Types from Files, Connections and Raw Vectors

Interacting with binary files can be difficult because R's types are a subset of what is generally supported by 'C'. This package provides a suite of functions for reading and writing binary data (with files, connections, and raw vectors) using 'C' type descriptions. These functions convert data between 'C' types and R types while checking for values outside the type limits, 'NA' values, etc.

Root Expected Proportion Squared Difference for Detecting DIF

Root Expected Proportion Squared Difference (REPSD) is a nonparametric differential item functioning (DIF) method that (a) allows practitioners to explore for DIF related to small, fine-grained focal groups of examinees, and (b) compares the focal group directly to the composite group that will be used to develop the reported test score scale. Using your provided response matrix with a column that identifies focal group membership, this package provides the REPSD values, a simulated null distribution of possible REPSD values, and the simulated p-values identifying items possibly displaying DIF without requiring enormous sample sizes.

Efficient Voting Methods for Committee Selection

A fast 'Rcpp'-based implementation of polynomially-computable voting theory methods for committee ranking and scoring. The package includes methods such as Approval Voting (AV), Satisfaction Approval Voting (SAV), sequential Proportional Approval Voting (PAV), and sequential Phragmen's Rule. Weighted variants of these methods are also provided, allowing for differential voter influence.

Tools for Summarising and Analysing Soundscape Data

A variety of tools relevant to the analysis of marine soundscape data. There are tools for downloading AIS (automatic identification system) data from Marine Cadastre < https://hub.marinecadastre.gov>, connecting AIS data to GPS coordinates, plotting summaries of various soundscape measurements, and downloading relevant environmental variables (wind, swell height) from the National Center for Atmospheric Research data server < https://rda.ucar.edu/datasets/ds084.1/>. Most tools were developed to work well with output from 'Triton' software, but can be adapted to work with any similar measurements.

Visualize 'Confounder' Control in Meta-Analyses

Visualize 'confounder' control in meta-analysis. 'metaconfoundr' is an approach to evaluating bias in studies used in meta-analyses based on the causal inference framework. Study groups create a causal diagram displaying their assumptions about the scientific question. From this, they develop a list of important 'confounders'. Then, they evaluate whether studies controlled for these variables well. 'metaconfoundr' is a toolkit to facilitate this process and visualize the results as heat maps, traffic light plots, and more.