This package creates plots of peptides from shotgun proteomics analysis of secretome and lysate samples. These plots contain associated protein features and scores for potential secretion and truncation.

Providing a method for Local Discrimination via Latent Class Models. The approach is described in <https://www.r-project.org/conferences/useR-2009/abstracts/pdf/Bucker.pdf>.

This package provides a collection of helper functions for multiple regression models fitted by lm(). Most of them are simple functions for simple tasks which can be done with coding, but may not be easy for occasional users of R. Most of the tasks addressed are those sometimes needed when using the manymome package (Cheung and Cheung, 2023, <doi:10.3758/s13428-023-02224-z>) and stdmod package (Cheung, Cheung, Lau, Hui, and Vong, 2022, <doi:10.1037/hea0001188>). However, they can also be used in other scenarios.

Fits sex-specific life-history models for fish and other taxa where some of the individuals have unknown sex.

Linear splines with convenient parametrisations such that (1) coefficients are slopes of consecutive segments or (2) coefficients are slope changes at consecutive knots. Knots can be set manually or at break points of equal-frequency or equal-width intervals covering the range of x'. The implementation follows Greene (2003), chapter 7.2.5.

This package provides a complete framework for frequency analysis is provided by LMoFit'. It has functions related to the determination of sample L-moments as in Hosking, J.R.M. (1990) <doi:10.1111/j.2517-6161.1990.tb01775.x>, the fitting of various distributions as in Zaghloul et al. (2020) <doi:10.1016/j.advwatres.2020.103720> and Hosking, J.R.M. (2019) <https://CRAN.R-project.org/package=lmom>, besides plotting and manipulating L-space diagrams as in Papalexiou, S.M. & Koutsoyiannis, D. (2016) <doi:10.1016/j.advwatres.2016.05.005> for two-shape parametric distributions on the L-moment ratio diagram. Additionally, the quantile, probability density, and cumulative probability functions of various distributions are provided in a user-friendly manner.

The solution of equality constrained least squares problem (LSE) is given through four analytics methods (Generalized QR Factorization, Lagrange Multipliers, Direct Elimination and Null Space method). We expose the orthogonal decomposition called Generalized QR Factorization (GQR) and also RQ factorization. Finally some codes for the solution of LSE applied in quaternions.

Crabs in the English channel, deer skulls, English monarchs, half-caste Manga characters, Jamaican cities, Shakespeare's The Tempest, drugged up cyclists and sexually transmitted diseases.

Computation of linkage disequilibrium of ancestry (LDA) and linkage disequilibrium of ancestry score (LDAS). LDA calculates the pairwise linkage disequilibrium of ancestry between single nucleotide polymorphisms (SNPs). LDAS calculates the LDA score of SNPs. The methods are described in Barrie W, Yang Y, Irving-Pease E.K, et al (2024) <doi:10.1038/s41586-023-06618-z>.

Implementation of LT-FH++, an extension of the liability threshold family history (LT-FH) model. LT-FH++ uses a Gibbs sampler for sampling from the truncated multivariate normal distribution and allows for flexible family structures. LT-FH++ was first described in Pedersen, Emil M., et al. (2022) <doi:10.1016/j.ajhg.2022.01.009> as an extension to LT-FH with more flexible family structures, and again as the age-dependent liability threshold (ADuLT) model Pedersen, Emil M., et al. (2023) <https://www.nature.com/articles/s41467-023-41210-z> as an alternative to traditional time-to-event genome-wide association studies, where family history was not considered.

Dimensionality reduction techniques for binary data including logistic PCA.

This package contains LUE_BIOMASS(),LUE_BIOMASS_VPD(), LUE_YIELD() and LUE_YIELD_VPD() to estimate aboveground biomass and crop yield firstly by calculating the Absorbed Photosynthetically Active Radiation (APAR) and secondly the actual values of light use efficiency with and without vapour presure deficit Shi et al.(2007) <doi:10.2134/agronj2006.0260>.

Lazy read for drawings. A dplyr back end for data sources supported by GDAL vector drivers, that allows working with local or remote sources as if they are in-memory data frames. Basic features works with any drawing format ('GDAL vector data source') supported by the sf package.

This is an extension package to logrx', which is a log creation program focused on Clinical Reporting within the Pharma Industry. This package enables a simple shiny-based Add-in that provides a point and click interface to produce a log for a single program.

This package provides a very simple implementation of a class for longitudinal data.

Reads raw files from Li-COR gas analyzers and produces a dataframe that can directly be used with fluxible <https://cran.r-project.org/package=fluxible>.

This package produces Labour Market Areas from commuting flows available at elementary territorial units. It provides tools for automatic tuning based on spatial contiguity. It also allows for statistical analyses and visualisation of the new functional geography.

Client for programmatic access to the Lake Multi-scaled Geospatial and Temporal database <https://lagoslakes.org>, with functions for accessing lake water quality and ecological context data for the US.

This package provides three classes: Queue, PriorityQueue and Stack. Queue is just a "plain vanilla" FIFO queue; PriorityQueue orders items according to priority. Stack implements LIFO.

Each function replaces multiple standard R functions. For example, two function calls, Read() and CountAll(), generate summary statistics for all variables in the data frame, plus histograms and bar charts. Other functions provide data aggregation via pivot tables; comprehensive regression, ANOVA, and t-test; visualizations including integrated Violin/Box/Scatter plot for a numerical variable, bar chart, histogram, box plot, density curves, calibrated power curve; reading multiple data formats with the same call; variable labels; time series with aggregation and forecasting; color themes; and Trellis (facet) graphics. Also includes a confirmatory factor analysis of multiple-indicator measurement models, pedagogical routines for data simulation (e.g., Central Limit Theorem), generation and rendering of regression instructions for interpretative output, and both interactive construction of visualizations and interactive visualizations with plotly.

This package provides a dataset containing several color naming conventions established by multiple sources, along with associated color metadata. The package also provides related helper functions for mapping among the different Lego color naming conventions and between Lego colors, hex colors, and R color names, making it easy to convert any color palette to one based on existing Lego colors while keeping as close to the original color palette as possible. The functions use nearest color matching based on Euclidean distance in RGB space. Naming conventions for color mapping include those from BrickLink (<https://www.bricklink.com>), The Lego Group (<https://www.lego.com>), LDraw (<https://www.ldraw.org/>), and Peeron (<http://www.peeron.com/>).

Helper functions to build SQL statements for dbGetQuery or dbSendQuery under program control. They are intended to increase speed of coding and to reduce coding errors. Arguments are carefully checked, in particular SQL identifiers such as names of tables or columns. More patterns will be added as required.

Based on right or interval censored data, compute the maximum likelihood estimator of a (sub)probability density under the assumption that it is log-concave. For further information see Duembgen, Rufibach and Schuhmacher (2014) <doi:10.1214/14-EJS930>.

This package contains some functions to learn and teach basic plane Geometry at undergraduate level with the aim of being helpful to young students with little programming skills.