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Quantify stratigraphic disorder using the metrics defined by Burgess (2016) <doi:10.2110/jsr.2016.10>. Contains a range of utility tools to construct and manipulate stratigraphic columns.
This package performs hybrid multi-stage factor analytic procedure for controlling acquiescence in restricted solutions (Ferrando & Lorenzo-Seva, 2000 <https://www.uv.es/revispsi/articulos3.00/ferran7.pdf>).
Computes multivariate normal (MVN) densities, and samples from MVN distributions, when the covariance or precision matrix is sparse.
Basic and model-based soil physical analyses.
This package provides methods for inference using stacked multiple imputations augmented with weights. The vignette provides example R code for implementation in general multiple imputation settings. For additional details about the estimation algorithm, we refer the reader to Beesley, Lauren J and Taylor, Jeremy M G (2020) â A stacked approach for chained equations multiple imputation incorporating the substantive modelâ <doi:10.1111/biom.13372>, and Beesley, Lauren J and Taylor, Jeremy M G (2021) â Accounting for not-at-random missingness through imputation stackingâ <arXiv:2101.07954>.
Catch advice for data-limited vertebrate and invertebrate fisheries managed by harvest slot limits using the SlotLim harvest control rule. The package accompanies the manuscript "SlotLim: catch advice for data-limited vertebrate and invertebrate fisheries managed by harvest slot limits" (Pritchard et al., in prep). Minimum data requirements: at least two consecutive years of catch data, lengthâ frequency distributions, and biomass or abundance indices (all from fishery-dependent sources); species-specific growth rate parameters (either von Bertalanffy, Gompertz, or Schnute); and either the natural mortality rate ('M') or the maximum observed age ('tmax'), from which M is estimated. The following functions have optional plotting capabilities that require ggplot2 installed: prop_target(), TBA(), SAM(), catch_advice(), catch_adjust(), and slotlim_once().
This package implements a set of distribution modeling methods that are suited to species with small sample sizes (e.g., poorly sampled species or rare species). While these methods can also be used on well-sampled taxa, they are united by the fact that they can be utilized with relatively few data points. More details on the currently implemented methodologies can be found in Maitner et al. (2026) <doi:10.1002/ecog.08112>, Drake and Richards (2018) <doi:10.1002/ecs2.2373>, Drake (2015) <doi:10.1098/rsif.2015.0086>, and Drake (2014) <doi:10.1890/ES13-00202.1>.
The notion of power index has been widely used in literature to evaluate the influence of individual players (e.g., voters, political parties, nations, stockholders, etc.) involved in a collective decision situation like an electoral system, a parliament, a council, a management board, etc., where players may form coalitions. Traditionally this ranking is determined through numerical evaluation. More often than not however only ordinal data between coalitions is known. The package socialranking offers a set of solutions to rank players based on a transitive ranking between coalitions, including through CP-Majority, ordinal Banzhaf or lexicographic excellence solution summarized by Tahar Allouche, Bruno Escoffier, Stefano Moretti and Meltem à ztürk (2020, <doi:10.24963/ijcai.2020/3>).
Pull data from the STAT Search Analytics API <https://help.getstat.com/knowledgebase/api-services/>. It was developed by the Search Discovery team to help analyze keyword ranking data.
Fits Bayesian spatio-temporal models and makes predictions on stream networks using the approach by Santos-Fernandez, Edgar, et al. (2022)."Bayesian spatio-temporal models for stream networks". <arXiv:2103.03538>. In these models, spatial dependence is captured using stream distance and flow connectivity, while temporal autocorrelation is modelled using vector autoregression methods.
This package provides a sunburst plot based on the d3.js library as an HTML shiny widget.
Enables instrumentation of Shiny apps for tracking user session events such as input changes, browser type, and session duration. These events can be sent to any of the available storage backends and analyzed using the included Shiny app to gain insights about app usage and adoption.
An Optimization Algorithm Applied to Stratification Problem.This function aims at constructing optimal strata with an optimization algorithm based on a global optimisation technique called Biased Random Key Genetic Algorithms.
This package implements the synthetic control group method for comparative case studies as described in Abadie and Gardeazabal (2003) and Abadie, Diamond, and Hainmueller (2010, 2011, 2014). The synthetic control method allows for effect estimation in settings where a single unit (a state, country, firm, etc.) is exposed to an event or intervention. It provides a data-driven procedure to construct synthetic control units based on a weighted combination of comparison units that approximates the characteristics of the unit that is exposed to the intervention. A combination of comparison units often provides a better comparison for the unit exposed to the intervention than any comparison unit alone.
This package provides access to granular sub-national income data from the MCC-PIK Database Of Sub-national Economic Output (DOSE). The package downloads and processes the data from its open repository on Zenodo (<https://zenodo.org/records/20035157>). Functions are provided to fetch data at multiple geographic levels, match coordinates to administrative regions, and access associated geometries.
This package provides tools to calculate the alpha parameter of the Weibull distribution, given beta and the age-specific fertility of a species, so that the population remains stable and stationary. Methods are inspired by "Survival profiles from linear models versus Weibull models: Estimating stable and stationary population structures for Pleistocene large mammals" (Martà n-González et al. 2019) <doi:10.1016/j.jasrep.2019.03.031>.
Implementation of single-source capture-recapture methods for population size estimation using zero-truncated, zero-one truncated and zero-truncated one-inflated Poisson, Geometric and Negative Binomial regression as well as Zelterman's, Chao's and ratio-regression estimators. Package includes point and interval estimators for the population size with variances estimated using analytical or bootstrap method. Details can be found in: van der Heijden et all. (2003) <doi:10.1191/1471082X03st057oa>, Böhning and van der Heijden (2019) <doi:10.1214/18-AOAS1232>, Böhning et al. (2020) Capture-Recapture Methods for the Social and Medical Sciences or Böhning and Friedl (2021) <doi:10.1007/s10260-021-00556-8>.
Ozone, NOx (= Sum of nitrogen monoxide and nitrogen dioxide), nitrogen monoxide, ambient temperature, dew point, wind speed and wind direction at 3 sites around lake of Lucerne in Central Switzerland in 30 min time resolution for year 2004.
Helpers for addressing the issue of disconnected spatial units. It allows for convenient adding and removal of neighbourhood connectivity between areal units prior to modelling, with the visual aid of maps. Post-modelling, it reduces the human workload for extracting, tidying and mapping predictions from areal models.
Forms queries to submit to the Cleveland Federal Reserve Bank web site's financial stress index data site. Provides query functions for both the composite stress index and the components data. By default the download includes daily time series data starting September 25, 1991. The functions return a class of either type easing or cfsi which contain a list of items related to the query and its graphical presentation. The list includes the time series data as an xts object. The package provides four lattice time series plots to render the time series data in a manner similar to the bank's own presentation.
This package implements Bayesian hierarchical models for estimating antibody kinetic parameters from longitudinal serological data. Fits two-phase within-host models capturing antibody rise, peak, and decay following pathogen infection, using JAGS for posterior inference. Designed as the upstream companion to the serocalculator package for end-to-end seroepidemiological analysis. Methods are described in Teunis and colleagues (2016) <doi:10.1016/j.epidem.2016.04.001> and Teunis and van Eijkeren (2020) <doi:10.1002/sim.8578>.
This package provides a sparklyr <https://spark.posit.co/> extension that provides an R interface for XGBoost <https://github.com/dmlc/xgboost> on Apache Spark'. XGBoost is an optimized distributed gradient boosting library.
We provide functions for estimation and inference of nonlinear and non-stationary time series regression using the sieve methods and bootstrapping procedure.
Connect to a remote server over SSH to transfer files via SCP, setup a secure tunnel, or run a command or script on the host while streaming stdout and stderr directly to the client.