This package provides a toolkit to predict antimicrobial peptides from protein sequences on a genome-wide scale. It incorporates two support vector machine models ("precursor" and "mature") trained on publicly available antimicrobial peptide data using calculated physico-chemical and compositional sequence properties described in Meher et al. (2017) <doi:10.1038/srep42362>. In order to support genome-wide analyses, these models are designed to accept any type of protein as input and calculation of compositional properties has been optimised for high-throughput use. For best results it is important to select the model that accurately represents your sequence type: for full length proteins, it is recommended to use the default "precursor" model. The alternative, "mature", model is best suited for mature peptide sequences that represent the final antimicrobial peptide sequence after post-translational processing. For details see Fingerhut et al. (2020) <doi:10.1093/bioinformatics/btaa653>. The ampir package is also available via a Shiny based GUI at <https://ampir.marine-omics.net/>.

Consider autoregressive model of order p where the distribution function of innovation is unknown, but innovations are independent and symmetrically distributed. The package contains a function named ARMDE which takes X (vector of n observations) and p (order of the model) as input argument and returns minimum distance estimator of the parameters in the model.

This package provides a collection of measures for measuring ecological diversity. Ecological diversity comes in two flavors: alpha diversity measures the diversity within a single site or sample, and beta diversity measures the diversity across two sites or samples. This package overlaps considerably with other R packages such as vegan', gUniFrac', betapart', and fossil'. We also include a wide range of functions that are implemented in software outside the R ecosystem, such as scipy', Mothur', and scikit-bio'. The implementations here are designed to be basic and clear to the reader.

This package provides a toolbox for programming Clinical Data Standards Interchange Consortium (CDISC) compliant Analysis Data Model (ADaM) datasets in R. ADaM datasets are a mandatory part of any New Drug or Biologics License Application submitted to the United States Food and Drug Administration (FDA). Analysis derivations are implemented in accordance with the "Analysis Data Model Implementation Guide" (CDISC Analysis Data Model Team, 2021, <https://www.cdisc.org/standards/foundational/adam>). The package is an extension package of the admiral package for pediatric clinical trials.

Named after the Irish name for weather, this package contains tidied data from the Irish Meteorological Service's hourly observations for 2017. In all, the data sets include observations from 25 weather stations, and also latitude and longitude coordinates for each weather station. Now includes energy generation data for Ireland and Northern Ireland (2017), including Wind Generation data.

This package provides a developer-facing interface to the Arrow Database Connectivity ('ADBC') PostgreSQL driver for the purposes of building high-level database interfaces for users. ADBC <https://arrow.apache.org/adbc/> is an API standard for database access libraries that uses Arrow for result sets and query parameters.

This software solves an Advection Bi-Flux Diffusive Problem using the Finite Difference Method FDM. Vasconcellos, J.F.V., Marinho, G.M., Zanni, J.H., 2016, Numerical analysis of an anomalous diffusion with a bimodal flux distribution. <doi:10.1016/j.rimni.2016.05.001>. Silva, L.G., Knupp, D.C., Bevilacqua, L., Galeao, A.C.N.R., Silva Neto, A.J., 2014, Formulation and solution of an Inverse Anomalous Diffusion Problem with Stochastic Techniques. <doi:10.5902/2179460X13184>. In this version, it is possible to include a source as a function depending on space and time, that is, s(x,t).

This package provides a weekly summary of Hass Avocado sales for the contiguous US from January 2017 through December 20204. See the package website for more information, documentation, and examples. Data source: Haas Avocado Board <https://hassavocadoboard.com/category-data/>.

This package provides a high-performance, flexible and extensible framework to develop continuous-time agent based models. Its high performance allows it to simulate millions of agents efficiently. Agents are defined by their states (arbitrary R lists). The events are handled in chronological order. This avoids the multi-event interaction problem in a time step of discrete-time simulations, and gives precise outcomes. The states are modified by provided or user-defined events. The framework provides a flexible and customizable implementation of state transitions (either spontaneous or caused by agent interactions), making the framework suitable to apply to epidemiology and ecology, e.g., to model life history stages, competition and cooperation, and disease and information spread. The agent interactions are flexible and extensible. The framework provides random mixing and network interactions, and supports multi-level mixing patterns. It can be easily extended to other interactions such as inter- and intra-households (or workplaces and schools) by subclassing an R6 class. It can be used to study the effect of age-specific, group-specific, and contact- specific intervention strategies, and complex interactions between individual behavior and population dynamics. This modeling concept can also be used in business, economical and political models. As a generic event based framework, it can be applied to many other fields. More information about the implementation and examples can be found at <https://github.com/junlingm/ABM>.

Estimate the Å estákâ Berggren kinetic model (degradation model) from experimental data. A closed-form (analytic) solution to the degradation model is implemented as a non-linear fit, allowing for the extrapolation of the degradation of a drug product - both in time and temperature. Parametric bootstrap, with kinetic parameters drawn from the multivariate t-distribution, and analytical formulae (the delta method) are available options to calculate the confidence and prediction intervals. The results (modelling, extrapolations and statistical intervals) can be visualised with multiple plots. The examples illustrate the accelerated stability modelling in drugs and vaccines development.

Existing adaptive design methods in clinical trials. The package includes power, stopping boundaries (sample size) calculation functions for two-group group sequential designs, adaptive design with coprimary endpoints, biomarker-informed adaptive design, etc.

Align-GVGD ('A-GVGD') is a method to predict the impact of missense substitutions based on the properties of amino acid side chains and protein multiple sequence alignments <doi:10.1136/jmg.2005.033878>. A-GVGD is an extension of the original Grantham distance to multiple sequence alignments. This package provides an alternative R implementation to the web version found on <http://agvgd.hci.utah.edu/>.

This package provides functions to convert origin-destination data, represented as straight desire lines in the sf Simple Features class system, into JSON files that can be directly imported into A/B Street <https://www.abstreet.org>, a free and open source tool for simulating urban transport systems and scenarios of change <doi:10.1007/s10109-020-00342-2>.

Estimate ideal efficiencies of aerosol sampling through sample lines. Functions were developed consistent with the approach described in Hogue, Mark; Thompson, Martha; Farfan, Eduardo; Hadlock, Dennis, (2014), "Hand Calculations for Transport of Radioactive Aerosols through Sampling Systems" Health Phys 106, 5, S78-S87, <doi:10.1097/HP.0000000000000092>.

Runs projections of groups of matrix projection models (MPMs), allowing density dependence mechanisms to work across MPMs. This package was developed to run both adaptive dynamics simulations such as pairwise and multiple invasibility analyses, and community projections in which species are represented by MPMs. All forms of MPMs are allowed, including integral projection models (IPMs). Also includes individual-based modeling (IBM) versions of these.

Easy data analysis and quality checks which are commonly used in data science. It combines the tabular and graphical visualization for easier usability. This package also creates an R Notebook with detailed data exploration with one function call. The notebook can be made interactive.

This package provides functions for Posterior estimates of Accelerated Failure Time(AFT) model with MCMC and Maximum likelihood estimates of AFT model without MCMC for univariate and multivariate analysis in high dimensional gene expression data are available in this afthd package. AFT model with Bayesian framework for multivariate in high dimensional data has been proposed by Prabhash et al.(2016) <doi:10.21307/stattrans-2016-046>.

Adaptive and Robust Transfer Learning (ART) is a flexible framework for transfer learning that integrates information from auxiliary data sources to improve model performance on primary tasks. It is designed to be robust against negative transfer by including the non-transfer model in the candidate pool, ensuring stable performance even when auxiliary datasets are less informative. See the paper, Wang, Wu, and Ye (2023) <doi:10.1002/sta4.582>.

This package provides direct access to the ALFRED (<https://alfred.stlouisfed.org>) and FRED (<https://fred.stlouisfed.org>) databases. Its functions return tidy data frames for different releases of the specified time series. Note that this product uses the FRED© API but is not endorsed or certified by the Federal Reserve Bank of St. Louis.

This package provides tools for designing and analyzing Acceptance Sampling plans. Supports both Attributes Sampling (Binomial and Poisson distributions) and Variables Sampling (Normal and Beta distributions), enabling quality control for fractional and compositional data. Uses nonlinear programming for sampling plan optimization, minimizing sample size while controlling producer's and consumer's risks. Operating Characteristic curves are available for plan visualization.

RStudio allows to show and navigate for the outline of a R Markdown file, but not for R Markdown projects with multiple files. For this reason, I have developed several RStudio addins capable of show project outline. Each addin is specialized in showing projects of different types: R Markdown project, bookdown package project and LaTeX project. There is a configuration file that allows you to customize additional searches.

This package provides functions to analyse overdispersed counts or proportions. These functions should be considered as complements to more sophisticated methods such as generalized estimating equations (GEE) or generalized linear mixed effect models (GLMM). aods3 is an S3 re-implementation of the deprecated S4 package aod.

This package provides tools for the analysis of growth data: to extract an LMS table from a gamlss object, to calculate the standard deviation scores and its inverse, and to superpose two wormplots from different models. The package contains a some varieties of reference tables, especially for The Netherlands.

Lite interface for finding locations of addresses or businesses around the world using the ArcGIS REST API service <https://developers.arcgis.com/rest/geocode/api-reference/overview-world-geocoding-service.htm>. Address text can be converted to location candidates and a location can be converted into an address. No API key required.