Check if an externalptr is a null pointer. R does currently not have a native function for that purpose. This package contains a C function that returns TRUE in case of a null pointer.

This package provides functions to Interact with the ICES Data Submission Utility (DATSU) <https://datsu.ices.dk/web/index.aspx>.

The integrity package implements the IPD Integrity Tool, a structured and transparent framework for evaluating the integrity of individual participant data (IPD) from randomised trials (see Hunter et al. (2024) <doi:10.1002/jrsm.1738> and <doi:10.32614/RJ-2017-008>). It supports users to identify potential issues, such as unusual data patterns, implausible values, lack of expected correlations, date violations, and inconsistencies. The package provides reproducible workflows for screening, documenting and summarising integrity concerns, and may be applied by evidence synthesists, editors, and others to determine whether a randomised trial may be considered sufficiently trustworthy to contribute to the evidence base that informs policy and practice.

This package provides tools for estimating incidence from biomarker data in cross- sectional surveys, and for calibrating tests for recent infection. Implements and extends the method of Kassanjee et al. (2012) <doi:10.1097/EDE.0b013e3182576c07>.

We construct the explicit form of clamped cubic interpolating spline (both uniform - knots are equidistant and non-uniform - knots are arbitrary). Using this form, we propose a linear regression model suitable for real data smoothing.

Download official election results for Spain at polling station, municipality and province level, format them and import them to the R environment. Data are provided by the Spanish Ministry of the Interior (<https://infoelectoral.interior.gob.es/es/inicio/>).

An R client for the ipbase.com IP Geolocation API. The API requires registration of an API key. Basic features are free, some require a paid subscription. You can find the full API documentation at <https://ipbase.com/docs> .

Clustering algorithm developed for use with plot inventories of species. It groups plots by subsets of diagnostic species rather than overall species composition. There is an unsupervised and a supervised mode, the latter accepting suggestions for species with greater weight and cluster medoids.

Infix operators to detect, subset, and replace the elements matched by a given condition. The functions have several variants of operator types, including subsets, ranges, regular expressions and others. Implemented operators work on vectors, matrices, and lists.

Calculation of key bacterial growth curve parameters using fourth degree polynomial functions. Six growth curve parameters are provided including peak growth rate, doubling time, lag time, maximum growth, and etc. ipolygrowth takes time series data from individual biological samples (with technical replicates) or multiple samples.

Fits Bayesian hierarchical models of vaccine coverage by location, birth cohort, and age. Observations of vaccination status (which may span cohorts, ages, and doses) are used to fit a latent survival-style process model that decomposes coverage into a lifetime propensity to vaccinate and a time-varying force of vaccination. Hierarchical spatial structure (e.g., state, county, school) supports partial pooling via random effects. Models are implemented in Stan and fit via rstan'. Provides helpers to validate user-supplied input data, and to predict coverage from fitted models.

Computes and tests individual (species, phylogenetic and functional) diversity-area relationships, i.e., how species-, phylogenetic- and functional-diversity varies with spatial scale around the individuals of some species in a community. See applications of these methods in Wiegand et al. (2007) <doi:10.1073/pnas.0705621104> or Chacon-Labella et al. (2016) <doi:10.1007/s00442-016-3547-z>.

This package provides a set of functions to estimate interactions flexibly in the face of possibly many controls. Implements the procedures described in Blackwell and Olson (2022) <doi:10.1017/pan.2021.19>.

Computes and decomposes Gini, Bonferroni and Zenga 2007 point and synthetic concentration indexes. Decompositions are intended: by sources, by subpopulations and by sources and subpopulations jointly. References, Zenga M. M.(2007) <doi:10.1400/209575> Zenga M. (2015) <doi:10.1400/246627> Zenga M., Valli I. (2017) <doi:10.26350/999999_000005> Zenga M., Valli I. (2018) <doi:10.26350/999999_000011>.

These datasets and functions accompany Wolfe and Schneider (2017) - Intuitive Introductory Statistics (ISBN: 978-3-319-56070-0) <doi:10.1007/978-3-319-56072-4>. They are used in the examples throughout the text and in the end-of-chapter exercises. The datasets are meant to cover a broad range of topics in order to appeal to the diverse set of interests and backgrounds typically present in an introductory Statistics class.

This package provides a phylogenetic modelling approach for predicting species invasion risk, out of a given pool of local species where a subset is known to be invasive elsewhere. The package uses phylogenetic signal estimation and phylogenetic linear and logistic models to estimate probabilities of being invasive based on phylogeny and any set of additional predictors. A ranking method is implemented to evaluate prioritisation strategies. A manuscript describing these methods, by Shahar Dubiner and Tamar Guy-Haim, is in preparation.

API wrapper that contains functions to retrieve data from the IsoMemo partnership databases. Web services for API: <https://isomemodb.com/api/v1/iso-data>.

This package implements tests for the identifying assumptions of instrumental variable models, the local exclusion restriction and monotonicity conditions required for local average treatment effect identification. Covers Kitagawa (2015) <doi:10.3982/ECTA11974>, Mourifie and Wan (2017) <doi:10.1162/REST_a_00622>, and Frandsen, Lefgren, and Leslie (2023) <doi:10.1257/aer.20201860>. Includes a one-shot wrapper that runs all applicable tests on a fitted instrumental variable model. Dispatches on fixest and ivreg model objects.

The wiDB...() functions provide an interface to the public API of the wiDB <https://github.com/SPATIAL-Lab/isoWater/blob/master/Protocol.md>: build, check and submit queries, and receive and unpack responses. Data analysis functions support Bayesian inference of the source and source isotope composition of water samples that may have experienced evaporation. Algorithms adapted from Bowen et al. (2018, <doi:10.1007/s00442-018-4192-5>).

This package provides a collection of several utility functions related to binary incomplete block designs. Contains function to generate A- and D-efficient binary incomplete block designs with given numbers of treatments, number of blocks and block size. Contains function to generate an incomplete block design with specified concurrence matrix. There are functions to generate balanced treatment incomplete block designs and incomplete block designs for test versus control treatments comparisons with specified concurrence matrix. Allows performing analysis of variance of data and computing estimated marginal means of factors from experiments using a connected incomplete block design. Tests of hypothesis of treatment contrasts in incomplete block design set up is supported.

This package implements the Interval-Censored Sequence Kernel Association (ICSKAT) test for testing the association between interval-censored time-to-event outcomes and groups of single nucleotide polymorphisms (SNPs). Interval-censored time-to-event data occur when the event time is not known exactly but can be deduced to fall within a given interval. For example, some medical conditions like bone mineral density deficiency are generally only diagnosed at clinical visits. If a patient goes for clinical checkups yearly and is diagnosed at, say, age 30, then the onset of the deficiency is only known to fall between the date of their age 29 checkup and the date of the age 30 checkup. Interval-censored data include right- and left-censored data as special cases. This package also implements the interval-censored Burden test and the ICSKATO test, which is the optimal combination of the ICSKAT and Burden tests. Please see the vignette for a quickstart guide. The paper describing these methods is " Inference for Set-Based Effects in Genetic Association Studies with Interval-Censored Outcomes" by Sun R, Zhu L, Li Y, Yasui Y, & Robison L (Biometrics 2023, <doi:10.1111/biom.13636>).

Extensive penalized variable selection methods have been developed in the past two decades for analyzing high dimensional omics data, such as gene expressions, single nucleotide polymorphisms (SNPs), copy number variations (CNVs) and others. However, lipidomics data have been rarely investigated by using high dimensional variable selection methods. This package incorporates our recently developed penalization procedures to conduct interaction analysis for high dimensional lipidomics data with repeated measurements. The core module of this package is developed in C++. The development of this software package and the associated statistical methods have been partially supported by an Innovative Research Award from Johnson Cancer Research Center, Kansas State University.

This package provides user-friendly functions for programmatic access to macroeconomic data from the International Monetary Fund's SDMX 3.0 IMF Data API <https://data.imf.org/en/Resource-Pages/IMF-API>.

This package provides a set of fast, chainable image-processing operations which are applicable to images of two, three or four dimensions, particularly medical images.