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r-tiobeindexr
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Get latest 'TIOBE' Programming Index Tables. The 'TIOBE' Programming Community index is an indicator of the popularity of programming languages from <https://www.tiobe.com/tiobe-index/>.
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2023-06-16 |
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r-timeprojection
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Extract useful time components of a date object, such as day of week, weekend, holiday, day of month, etc, and put it in a data frame. This can be used to create many predictor variables out of a single time variable, which can then be used in a regression or decision tree. Also includes function plotCalendarHeatmap which draws a calendar and overlays a heatmap based on values.
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2023-06-16 |
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r-tipom
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TIPOM is based on a methodology that was developed in the 1960s by Bernardino Bagolini. The basic idea is to use the three simple dimensions of length, width and thickness of each lithic artefact to classify them in discrete groups and infer their function.
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2023-06-16 |
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r-thinknum
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This package interacts directly with the Thinknum API to offer data in a number of formats usable in R
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2023-06-16 |
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r-tstr
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A ternary search tree is a type of prefix tree with up to three children and the ability for incremental string search. The package uses this ability for word auto-completion and spell checking. Includes a dataset with the 10001 most frequent English words.
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2023-06-16 |
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r-treecm
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The centre of mass is a crucial data for arborists in order to consolidate a tree using steel or dynamic cables. Given field-recorded data on branchiness of a tree, the package: (i) computes and plots the centre of mass of the tree itself, (ii) computes branches slenderness coefficient in order to aid the arborist identify potentially dangerous branches, and (iii) computes the force acting on a ground plinth and its best position relating to the tree centre of mass, should the tree need to be stabilized by a steel cable.
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2023-06-16 |
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r-threeboost
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This package implements a thresholded version of the EEBoost algorithm described in [Wolfson (2011, JASA)]. EEBoost is a general-purpose method for variable selection which can be applied whenever inference would be based on an estimating equation. The package currently implements variable selection based on the Generalized Estimating Equations, but can also accommodate user-provided estimating functions. Thresholded EEBoost is a generalization which allows multiple variables to enter the model at each boosting step.
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2023-06-16 |
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r-trueskill
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An implementation of the TrueSkill algorithm (Herbrich, R., Minka, T. and Grapel, T) in R; a Bayesian skill rating system with inference by approximate message passing on a factor graph. Used by Xbox to rank gamers and identify appropriate matches. http://research.microsoft.com/en-us/projects/trueskill/default.aspx Current version allows for one player per team. Will update as time permits. Requires R version 3.0 as it is written with Reference Classes. URL: https://github.com/bhoung/trueskill-in-r Acknowledgements to Doug Zongker and Heungsub Lee for their python implementations of the algorithm and for the liberal reuse of Doug's code comments (@dougz and @sublee on github).
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2023-06-16 |
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r-tpe
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This package implements the greedy approximation for tree preserving embedding.
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2023-06-16 |
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r-toxtestd
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Calculates sample size and dose allocation for binary toxicity tests, using the Fish Embryo Toxicity Test as example. An optimal test design is obtained by running (i) spoD (calculate the number of individuals to test under control conditions), (ii) setD (estimate the minimal sample size per treatment given the users precision requirements) and (iii) doseD (construct an individual dose scheme).
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2023-06-16 |
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r-tosls
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Fit an Instrumental Variables Two Stage Least Squares model
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2023-06-16 |
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r-timesboot
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Computes bootstrap CI for the sample ACF and periodogram
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2023-06-16 |
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r-tickexec
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Functions to execute orders in backtesting using tick data. A testing platform was established by the four major execution functions, namely 'LimitBuy', 'LimitSell', 'MarketBuy' and 'MarketSell', which enclosed all tedious aspects (such as queueing for order executions and calculate actual executed volumes) for order execution using tick data. Such that one can focus on the logic of strategies, rather than its execution.
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2023-06-16 |
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r-tempor
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TEMPO (TEmporal Modeling of Pathway Outliers) is a pathway-based outlier detection approach for finding pathways showing significant changes in temporal expression patterns across conditions. Given a gene expression data set where each sample is characterized by an age or time point as well as a phenotype (e.g. control or disease), and a collection of gene sets or pathways, TEMPO ranks each pathway by a score that characterizes how well a partial least squares regression (PLSR) model can predict age as a function of gene expression in the controls and how poorly that same model performs in the disease. TEMPO v1.0.3 is described in Pietras (2018) <doi:10.1145/3233547.3233559>.
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2023-06-16 |
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r-surveyoutliers
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At present, the only functionality is the calculation of optimal one-sided winsorizing cutoffs. The main function is optimal.onesided.cutoff.bygroup. It calculates the optimal tuning parameter for one-sided winsorisation, and so calculates winsorised values for a variable of interest. See the help file for this function for more details and an example.
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2023-06-16 |
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r-taoteprogramming
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Art-like behavior based on randomness
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2023-06-16 |
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r-sybil
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This Systems Biology Package (Gelius-Dietrich et. al. (2012) <doi:10.1186/1752-0509-7-125>) implements algorithms for constraint based analyses of metabolic networks, e.g. flux-balance analysis (FBA), minimization of metabolic adjustment (MOMA), regulatory on/off minimization (ROOM), robustness analysis and flux variability analysis. The package is easily extendable for additional algorithms. Most of the current LP/MILP solvers are supported via additional packages.
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2023-06-16 |
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r-taup.r
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Evaluates traveltimes and ray paths using predefined Earth (or other planet) models. Includes phase plotting routines. The IASP91 (Kennett and Engdahl, 1991 <doi:10.1111/j.1365-246X.1991.tb06724.x>) and AK135 (Kennett et al., 1995 <doi:10.1111/j.1365-246X.1995.tb03540.x>) Earth models are included, and most important arrival phases can be evaluated.
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2023-06-16 |
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r-svmplus
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Implementation of Support Vector Machines Plus (SVM+) for classification problems. See (Vladimir et. al, 2009, <doi:10.1016/j.neunet.2009.06.042>) for theoretical details and see (Li et. al, 2016, <https://github.com/okbalefthanded/svmplus_matlab>) for implementation details in 'MATLAB'.
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2023-06-16 |
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r-stockchina
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With this package, users can obtain the real-time price and volume information of stocks in China market, as well as the information of the stock index. This package adopted the API from Sina Finance (http://finance.sina.com.cn/).
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2023-06-16 |
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r-teraplusb
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This package is for the comparison of various types of A+B escalation rules for dose finding trials.
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2023-06-16 |
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r-tabulizerjars
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'Java' .jar files for the 'Tabula' <http://tabula.technology/> 'Java' library, which are required by the 'tabulizer' R package. The version numbering of this package corresponds to versions of 'tabula-java' library releases <https://github.com/tabulapdf/tabula-java/releases/>.
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2023-06-16 |
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r-suntersampling
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Functions for drawing samples according to Sunter's sampling design, and for computing first and second order inclusion probabilities
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2023-06-16 |
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r-stsm.class
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This package defines an S4 class for structural time series models and provides some basic methods to work with it.
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2023-06-16 |
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r-tfx
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Connects R to TrueFX(tm) for free streaming real-time and historical tick-by-tick market data for dealable interbank foreign exchange rates with millisecond detail.
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2023-06-16 |
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r-swissmrp
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Provides a number of useful functions to employ MrP for small area prediction in Switzerland. Based on a hierarchical model and survey data one can derive cantonal preference measures. The package allows to automatize the prediction and post-stratification steps. It further provides adequate print, summary, map, and plot functions for objects of its class.
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2023-06-16 |
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r-svapls
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Accurate identification of genes that are truly differentially expressed over two sample varieties, after adjusting for hidden subject-specific effects of residual heterogeneity.
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2023-06-16 |
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r-sue
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This is a package for the subsampling method of robust estimation of linear regression models
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2023-06-16 |
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r-tdamapper
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Topological Data Analysis using Mapper (discrete Morse theory). Generate a 1-dimensional simplicial complex from a filter function defined on the data: 1. Define a filter function (lens) on the data. 2. Perform clustering within within each level set and generate one node (vertex) for each cluster. 3. For each pair of clusters in adjacent level sets with a nonempty intersection, generate one edge between vertices. The function mapper1D uses a filter function with codomain R, while the the function mapper2D uses a filter function with codomain R^2.
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2023-06-16 |
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r-swapclass
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A null model randomizing semi-quantitative multi-classes (or ordinal) data by swapping sub-matrices while both the row and the column marginal sums are held constant.
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2023-06-16 |
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r-supermds
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Witten and Tibshirani (2011) Supervised multidimensional scaling for visualization, classification, and bipartite ranking. Computational Statistics and Data Analysis 55(1): 789-801.
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2023-06-16 |
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r-teereg
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For fitting multiple linear regressions, the ordinary least squares approach is sensitive to outliers and/or violations of model assumptions. The trimmed elemental estimators are more robust to such situations. This package contains functions for computing the trimmed elemental estimates, as well as for creating the bias-corrected and accelerated bootstrap confidence intervals based on elemental regressions.
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2023-06-16 |
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r-synet
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Infers sympatry matrices from distributional data and analyzes them in order to identify groups of species cohesively connected.
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2023-06-16 |
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r-stheoreme
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Functions implementing the procedure of entropy comparison between two data samples after the renormalization of respective probability distributions with the algorithm designed by Klimontovich (Zeitschrift fur Physik B Condensed Matter. 1987, Volume 66, Issue 1, pp 125-127) and extended by Anishchenko (Proc. SPIE 2098, Computer Simulation in Nonlinear Optics. 1994, pp.130-136). The package also includes data preparation tools which can also be used separately for various applications.
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2023-06-16 |
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r-statmeasures
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Offers useful functions to perform day-to-day data manipulation operations, data quality checks and post modelling statistical checks. One can effortlessly change class of a number of variables to factor, remove duplicate observations from the data, create deciles of a variable, perform data quality checks for continuous (integer or numeric), categorical (factor) and date variables, and compute goodness of fit measures such as auc for statistical models. The functions are consistent for objects of class 'data.frame' and 'data.table', which is an enhanced 'data.frame' implemented in the package 'data.table'.
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2023-06-16 |
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r-ssd
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ssd calculates the sample size needed to detect the differences between two sets of unordered categorical data.
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2023-06-16 |
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r-tempcyclesdata
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This is the data companion package to the package tempcycles. This package includes the metadata, linear, and cycling parameters from "Recent geographic convergence in diurnal and annual temperature cycling flattens global thermal profiles", Wang & Dillon, Nature Climate Change, 4, 988-992 (2014). doi:10.1038/nclimate2378.
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2023-06-16 |
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r-survgini
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The Gini concentration test for survival data is a nonparametric test based on the Gini index for testing the equality of two survival distributions from the point of view of concentration. The package compares different nonparametric tests (asymptotic Gini test, permutation Gini test, log-rank test, Gray-Tsiatis test and Wilcoxon test) and computes their p-values.
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2023-06-16 |
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r-stylest
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Estimates distinctiveness in speakers' (authors') style. Fits models that can be used for predicting speakers of new texts. Methods developed in Huang et al (2020) <doi:10.1017/pan.2019.49>.
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2023-06-16 |
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r-stubthat
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Create stubs of functions for use while testing.
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2023-06-16 |
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r-fgsg
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Implement algorithms for feature grouping and selection over an undirected graph, solves problems like graph fused lasso, graph OSCAR and so on.
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2023-06-16 |
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r-surveyeditor
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Help generate slides for surveys or experiments. The resulted slides allow the subject to respond with the use of the mouse (usual keyboard input is replaced with clicking on a virtual keyboard on the slide). Subjects' responses are saved to the user- specified location in the form of R-readable text file. To allow flexibility, each function in this package generates a particular type of slides thus general R function writing skills are required to compile these edited slides.
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2023-06-16 |
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r-subpathwaygmir
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Routines for identifying metabolic subpathways mediated by microRNAs (miRNAs) through topologically locating miRNAs and genes within reconstructed Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathway graphs embedded by miRNAs. (1) This package can obtain the reconstructed KEGG metabolic pathway graphs with genes and miRNAs as nodes, through converting KEGG metabolic pathways to graphs with genes as nodes and compounds as edges, and then integrating miRNA-target interactions verified by low-throughput experiments from four databases (TarBase, miRecords, mirTarBase and miR2Disease) into converted pathway graphs. (2) This package can locate metabolic subpathways mediated by miRNAs by topologically analyzing the "lenient distance" of miRNAs and genes within reconstructed KEGG metabolic pathway graphs.(3) This package can identify significantly enriched miRNA-mediated metabolic subpathways based on located subpathways by hypergenomic test. (4) This package can support six species for metabolic subpathway identification, such as caenorhabditis elegans, drosophila melanogaster, danio rerio, homo sapiens, mus musculus and rattus norvegicus, and user only need to update interested organism-specific environment variables.
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2023-06-16 |
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r-ssvd
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Fast iterative thresholding sparse SVD, together with an initialization algorithm
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2023-06-16 |
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r-subgroup.discovery
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Developed to assist in discovering interesting subgroups in high-dimensional data. The PRIM implementation is based on the 1998 paper "Bump hunting in high-dimensional data" by Jerome H. Friedman and Nicholas I. Fisher. <doi:10.1023/A:1008894516817> PRIM involves finding a set of "rules" which combined imply unusually large (or small) values of some other target variable. Specifically one tries to find a set of sub regions in which the target variable is substantially larger than overall mean. The objective of bump hunting in general is to find regions in the input (attribute/feature) space with relatively high (low) values for the target variable. The regions are described by simple rules of the type if: condition-1 and ... and condition-n then: estimated target value. Given the data (or a subset of the data), the goal is to produce a box B within which the target mean is as large as possible. There are many problems where finding such regions is of considerable practical interest. Often these are problems where a decision maker can in a sense choose or select the values of the input variables so as to optimize the value of the target variable. In bump hunting it is customary to follow a so-called covering strategy. This means that the same box construction (rule induction) algorithm is applied sequentially to subsets of the data.
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2023-06-16 |
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r-standardizetext
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Standardizes text according to a template; particularly useful for country names.
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2023-06-16 |
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r-stackoverflow
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Helper functions collected from StackOverflow.com, a question and answer site for professional and enthusiast programmers.
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2023-06-16 |
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r-tbdiag
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This package provides functions to assist researchers working in the field of tuberculosis diagnostics. Functions for the interpretation of two popular interferon-gamma release assays are provided, and additional functionality is planned.
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2023-06-16 |
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r-svdvisual
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Some visualization tools based on Singular Value Decomposition
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2023-06-16 |
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r-subcultcon
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The three functions in the package compute the maximum likelihood estimates of the informants' competence scores, tests for two answer keys with known groups, and finds "best" split of the informants into sub-culture groups.
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2023-06-16 |
