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Mapping tools that convert place names to coordinates on the fly. These ggplot2 extensions make maps from a data frame where one of the columns contains place names, without having to directly work with the underlying geospatial data and tools. The corresponding map data must be registered with cartographer either by the user or by another package.
This package provides a fast and flexible general-purpose implementation of Particle Swarm Optimization (PSO) and Differential Evolution (DE) for solving global minimization problems is provided. It is designed to handle complex optimization tasks with nonlinear, non-differentiable, and multi-modal objective functions defined by users. There are five types of PSO variants: Particle Swarm Optimization (PSO, Eberhart & Kennedy, 1995) <doi:10.1109/MHS.1995.494215>, Quantum-behaved particle Swarm Optimization (QPSO, Sun et al., 2004) <doi:10.1109/CEC.2004.1330875>, Locally convergent rotationally invariant particle swarm optimization (LcRiPSO, Bonyadi & Michalewicz, 2014) <doi:10.1007/s11721-014-0095-1>, Competitive Swarm Optimizer (CSO, Cheng & Jin, 2015) <doi:10.1109/TCYB.2014.2322602> and Double exponential particle swarm optimization (DExPSO, Stehlik et al., 2024) <doi:10.1016/j.asoc.2024.111913>. For the DE algorithm, six types in Storn, R. & Price, K. (1997) <doi:10.1023/A:1008202821328> are included: DE/rand/1, DE/rand/2, DE/best/1, DE/best/2, DE/rand_to-best/1 and DE/rand_to-best/2.
This package contains all the data and functions used in Generalized Linear Models, 2nd edition, by Jeff Gill and Michelle Torres. Examples to create all models, tables, and plots are included for each data set.
Computational representations of glycan compositions and structures, including details such as linkages, anomers, and substituents. Supports varying levels of monosaccharide specificity (e.g., "Hex" or "Gal") and ambiguous linkages. Provides robust parsing and generation of IUPAC-condensed structure strings. Optimized for vectorized operations on glycan structures, with efficient handling of duplications. As the cornerstone of the glycoverse ecosystem, this package delivers the foundational data structures that power glycomics and glycoproteomics analysis workflows.
This package provides a minimal set of routines to calculate the Grantham distance <doi:10.1126/science.185.4154.862>. The Grantham distance attempts to provide a proxy for the evolutionary distance between two amino acids based on three key chemical properties: composition, polarity and molecular volume. In turn, evolutionary distance is used as a proxy for the impact of missense mutations. The higher the distance, the more deleterious the substitution is expected to be.
Interacts with the Glassdoor API <https://www.glassdoor.com/developer/index.htm>. Allows the user to search job statistics, employer statistics, and job progression, where Glassdoor provides a breakdown of other jobs a person did after their current one.
Package for Genetic Epidemiologic Methods Developed at MSKCC. It contains functions to calculate haplotype specific odds ratio and the power of two stage design for GWAS studies.
This package provides a ggplot2 extension that supports arbitrary hand-crafted colourable & fillable shapes. New shapes may be feature requested via a Github issue.
Sankey and alluvial diagrams visualise flows of quantities across stages in stacked bars. This package makes it easy to create such diagrams using ggplot2'.
This package provides a compilation of tools to complete common tasks for studying gerrymandering. This focuses on the geographic tool side of common problems, such as linking different levels of spatial units or estimating how to break up units. Functions exist for creating redistricting-focused data for the US.
Aligns peak based on peak retention times and matches homologous peaks across samples. The underlying alignment procedure comprises three sequential steps. (1) Full alignment of samples by linear transformation of retention times to maximise similarity among homologous peaks (2) Partial alignment of peaks within a user-defined retention time window to cluster homologous peaks (3) Merging rows that are likely representing homologous substances (i.e. no sample shows peaks in both rows and the rows have similar retention time means). The algorithm is described in detail in Ottensmann et al., 2018 <doi:10.1371/journal.pone.0198311>.
This package provides a ggplot2 extension that provides tools for automatically creating scales to focus on subgroups of the data plotted without losing other information.
When comparing discrete data mini bubble plots allow displaying more information than traditional bubble plots via colour, shape or labels. Exact overlapping coordinates will be transformed so they surround the original point circularly without overlapping. This is implemented as a position_surround() function for ggplot2'.
This package provides a set of geometries to make line plots a little bit nicer. Use along with ggplot2 to: - Improve the clarity of line plots with many overlapping lines - Draw more realistic worms.
Providing various equations to calculate Gini coefficients. The methods used in this package can be referenced from Brown MC (1994) <doi: 10.1016/0277-9536(94)90189-9>.
Data-driven approach for arriving at person-specific time series models. The method first identifies which relations replicate across the majority of individuals to detect signal from noise. These group-level relations are then used as a foundation for starting the search for person-specific (or individual-level) relations. See Gates & Molenaar (2012) <doi:10.1016/j.neuroimage.2012.06.026>.
This package provides statistical methods to check if a parametric family of conditional density functions fits to some given dataset of covariates and response variables. Different test statistics can be used to determine the goodness-of-fit of the assumed model, see Andrews (1997) <doi:10.2307/2171880>, Bierens & Wang (2012) <doi:10.1017/S0266466611000168>, Dikta & Scheer (2021) <doi:10.1007/978-3-030-73480-0> and Kremling & Dikta (2024) <doi:10.48550/arXiv.2409.20262>. As proposed in these papers, the corresponding p-values are approximated using a parametric bootstrap method.
Supply implementation to model generalized multivariate functional data using Bayesian additive mixed models of R package bamlss via a latent Gaussian process (see Umlauf, Klein, Zeileis (2018) <doi:10.1080/10618600.2017.1407325>).
An event-Based framework for building Shiny apps. Instead of relying on standard Shiny reactive objects, this package allow to relying on a lighter set of triggers, so that reactive contexts can be invalidated with more control.
This package provides a collection of palettes and themes for ggplot2', offering a light, pastel aesthetic. Syntax follows the viridis package.
This package provides complete detailed preprocessing of two-dimensional gas chromatogram (GCxGC) samples. Baseline correction, smoothing, peak detection, and peak alignment. Also provided are some analysis functions, such as finding extracted ion chromatograms, finding mass spectral data, targeted analysis, and nontargeted analysis with either the National Institute of Standards and Technology Mass Spectral Library or with the mass data. There are also several visualization methods provided for each step of the preprocessing and analysis.
This package provides methods for processing spatial data for decision-making. This package is an R implementation of methods provided by the open source software GeoFIS <https://www.geofis.org> (Leroux et al. 2018) <doi:10.3390/agriculture8060073>. The main functionalities are the management zone delineation (Pedroso et al. 2010) <doi:10.1016/j.compag.2009.10.007> and data aggregation (Mora-Herrera et al. 2020) <doi:10.1016/j.compag.2020.105624>.
Facilitate reporting for regression and correlation modeling, hypothesis testing, variance analysis, outlier detection, and detailed descriptive statistics.
An iterative algorithm that improves the proximity matrix (PM) from a random forest (RF) and the resulting clusters as measured by the silhouette score.