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This package provides a set of tools to extract bibliographic content from OpenAlex database using API <https://docs.openalex.org>.
When people make decisions, they may do so using a wide variety of decision rules. The package allows users to easily create obfuscation games to test the obfuscation hypothesis. It provides an easy to use interface and multiple options designed to vary the difficulty of the game and tailor it to the user's needs. For more detail: Chorus et al., 2021, Obfuscation maximization-based decision-making: Theory, methodology and first empirical evidence, Mathematical Social Sciences, 109, 28-44, <doi:10.1016/j.mathsocsci.2020.10.002>.
Classify Open Street Map (OSM) features into meaningful functional or analytical categories. Designed for OSM PBF files, e.g. from <https://download.geofabrik.de/> imported as spatial data frames. A classification consists of a list of categories that are related to certain OSM tags and values. Given a layer from an OSM PBF file and a classification, the main osm_classify() function returns a classification data table giving, for each feature, the primary and alternative categories (if there is overlap) assigned, and the tag(s) and value(s) matched on. The package also contains a classification of OSM features by economic function/significance, following Krantz (2023) <https://www.ssrn.com/abstract=4537867>.
After develop a ODK <https://opendatakit.org/> frame, we can link the frame to Google Sheets <https://www.google.com/sheets/about/> and collect data through Android <https://www.android.com/>. This data uploaded to a Google sheets'. odk2spss() function help to convert the odk frame into SPSS <https://www.ibm.com/analytics/us/en/technology/spss/> frame. Also able to add downloaded Google sheets data or read data from Google sheets by using ODK frame submission_url'.
Compound deconvolution for chromatographic data, including gas chromatography - mass spectrometry (GC-MS) and comprehensive gas chromatography - mass spectrometry (GCxGC-MS). The package includes functions to perform independent component analysis - orthogonal signal deconvolution (ICA-OSD), independent component regression (ICR), multivariate curve resolution (MCR-ALS) and orthogonal signal deconvolution (OSD) alone.
Empirical or simulated disease outbreak data, provided either as RData or as text files.
An optimal transport (OT) method, which can handle tensors of any order by learning possibly multiple transport plans. For the details of the methods, see Kerdoncuff et al. (2022) <doi:10.1609/aaai.v36i7.20695>.
Offers a suite of functions for enhancing R plots.
Calculate the ratio of iron oxides, hematite and goethite, in soil using the diffuse reflectance technique. The Kubelka-Munk theory, second derivative analysis, and spectral region amplitudes related to hematite and goethite content are used for quantification (Torrent, J., & Barron, V. (2008) <doi:10.2136/sssabookser5.5.c13>). Additionally, the package calculates soil color in the visible spectrum using Munsell and RGB color spaces, based on color theory (Viscarra et al. (2006) <doi:10.1016/j.geoderma.2005.07.017>).
Allows code to be run only once on a given computer, using lockfiles. Typical use cases include startup messages shown only when a package is loaded for the very first time.
This package provides a DBI-compatible interface to ODBC databases.
An extension to the Regression Modeling Strategies package that facilitates plotting ordinal regression model predictions together with confidence intervals for each dependent variable level. It also adds a functionality to plot the model summary as a modifiable object.
Tetra-allele cross often referred as four-way cross or double cross or four-line cross are those type of mating designs in which every cross is obtained by mating amongst four inbred lines. A tetra-allele cross can be obtained by crossing the resultant of two unrelated diallel crosses. A common triallel cross involving four inbred lines A, B, C and D can be symbolically represented as (A X B) X (C X D) or (A, B, C, D) or (A B C D) etc. Tetra-allele cross can be broadly categorized as Complete Tetra-allele Cross (CTaC) and Partial Tetra-allele Crosses (PTaC). Rawlings and Cockerham (1962)<doi:10.2307/2527461> firstly introduced and gave the method of analysis for tetra-allele cross hybrids using the analysis method of single cross hybrids under the assumption of no linkage. The set of all possible four-way mating between several genotypes (individuals, clones, homozygous lines, etc.) leads to a CTaC. If there are N number of inbred lines involved in a CTaC, the the total number of crosses, T = N*(N-1)*(N-2)*(N-3)/8. When more number of lines are to be considered, the total number of crosses in CTaC also increases. Thus, it is almost impossible for the investigator to carry out the experimentation with limited available resource material. This situation lies in taking a fraction of CTaC with certain underlying properties, known as PTaC.
Predicts spatial suitability for oyster growth from environmental survey data using Analytic Hierarchy Process (AHP) weighted scoring. Users supply sensor data from Acoustic Doppler Current Profilers (ADCP), Conductivity-Temperature-Depth (CTD) sensors, bathymetric sonar, and sidescan sonar, specify a target species, and receive per-location suitability scores, a GeoTIFF heatmap for QGIS', contour lines, and a formatted PDF or HTML report. Supports fourteen species across global aquaculture regions, including Ostrea edulis, Magallana gigas, Crassostrea virginica, Crassostrea hongkongensis, and ten further species; see list_species(). Includes season-aware scoring, tidal height correction, Bayesian tolerance parameter updating from field observations, spatial block cross-validation (Roberts et al., 2017, <doi:10.1111/ecog.02881>), permutation variable importance, wave exposure and sediment stability modules, Harmful Algal Bloom (HAB) risk and anthropogenic disturbance scoring with optional live International Council for the Exploration of the Sea (ICES) data integration, hybrid larval dispersal connectivity scoring (union-find Gaussian kernel plus optional OpenDrift or Finite Volume Community Ocean Model ('FVCOM') connectivity matrix), and batch multi-species comparison.
An algorithm for fitting interpretable additive neural networks for identifiable and visualizable feature effects using post hoc orthogonalization. Fit custom neural networks intuitively using established R formula notation, including interaction effects of arbitrary order while preserving identifiability to enable a functional decomposition of the prediction function. For more details see Koehler et al. (2025) <doi:10.1038/s44387-025-00033-7>.
The openMSE package is designed for building operating models, doing simulation modelling and management strategy evaluation for fisheries. openMSE is an umbrella package for the MSEtool (Management Strategy Evaluation toolkit), DLMtool (Data-Limited Methods toolkit), and SAMtool (Stock Assessment Methods toolkit) packages. By loading and installing openMSE', users have access to the full functionality contained within these packages. Learn more about openMSE at <https://openmse.com/>.
Consider a data matrix of n individuals with p variates. The objective general index (OGI) is a general index that combines the p variates into a univariate index in order to rank the n individuals. The OGI is always positively correlated with each of the variates. More details can be found in Sei (2016) <doi:10.1016/j.jmva.2016.02.005>.
This package provides an Interface to Open Collaboration Services OCS (<https://www.open-collaboration-services.org/>) REST API.
The supplied code allows for the generation of discrete time series of oscillating species. General shapes can be selected by means of individual functions, which are widely customizable by means of function arguments. All code was developed in the Biological Information Processing Group at the BioQuant Center at Heidelberg University, Germany.
OD-means is a hierarchical adaptive k-means algorithm based on origin-destination pairs. In the first layer of the hierarchy, the clusters are separated automatically based on the variation of the within-cluster distance of each cluster until convergence. The second layer of the hierarchy corresponds to the sub clustering process of small clusters based on the distance between the origin and destination of each cluster.
Retrieve data from the Our World in Data (OWID) Chart API <https://docs.owid.io/projects/etl/api/>. OWID provides public access to more than 5,000 charts focusing on global problems such as poverty, disease, hunger, climate change, war, existential risks, and inequality.
Setup and connect to OpenTripPlanner (OTP) <http://www.opentripplanner.org/>. OTP is an open source platform for multi-modal and multi-agency journey planning written in Java'. The package allows you to manage a local version or connect to remote OTP server to find walking, cycling, driving, or transit routes. This package has been peer-reviewed by rOpenSci (v. 0.2.0.0).
Estimate location-shift models or rating-scale models accounting for response styles (RSRS) for the regression analysis of ordinal responses.
This package implements the out-of-treatment testing from Kuelpmann and Kuzmics (2020) <doi:10.2139/ssrn.3441675> based on the Vuong Test introduced in Vuong (1989) <doi:10.2307/1912557>. Out-of treatment testing allows for a direct, pairwise likelihood comparison of theories, calibrated with pre-existing data.