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r-dhh
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The density, cumulative distribution, quantiles, and i.i.d random variables of a heavy-headed distribution. For more information, please see the vignette.
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2025-04-22 |
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r-dgodata
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Provides data used by package 'dgo' in examples and vignettes.
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2025-04-22 |
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r-dgmb
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A set of functions have been implemented to generate random data to perform Monte Carlo simulations on structural models with formative constructs and interaction and nonlinear effects (Two-Step PLS Mode B structural models). The setup of the true model considers a simple structure with three formative exogenous constructs related to one formative endogenous construct. The routines take into account the interaction and nonlinear effects of the exogenous constructs on the endogenous construct.
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2025-04-22 |
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r-dga
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Performs Bayesian model averaging for capture-recapture. This includes code to stratify records, check the strata for suitable overlap to be used for capture-recapture, and some functions to plot the estimated population size.
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2025-04-22 |
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r-dfoptim
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Derivative-Free optimization algorithms. These algorithms do not require gradient information. More importantly, they can be used to solve non-smooth optimization problems.
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2025-04-22 |
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r-dfcrm
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Provides functions to run the CRM and TITE-CRM in phase I trials and calibration tools for trial planning purposes.
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2025-04-22 |
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r-dfcompare
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Compares two dataframes with a common key and returns the delta records. The package will return three dataframes that contain the added, changed, and deleted records.
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2025-04-22 |
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r-dfadjust
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Computes small-sample degrees of freedom adjustment for heteroskedasticity robust standard errors, and for clustered standard errors in linear regression. See Imbens and Kolesár (1994) <doi:10.1162/REST_a_00552> for a discussion of these adjustments.
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2025-04-22 |
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r-df2json
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It handles numerics, characters, factors, and logicals.
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2025-04-22 |
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r-devrate
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A set of functions to quantify the relationship between development rate and temperature and to build phenological models. The package comprises a set of models and estimated parameters borrowed from a literature review in ectotherms. The methods and literature review are described in Rebaudo et al. (2018) <doi:10.1111/2041-210X.12935> and Rebaudo and Rabhi (2018) <doi:10.1111/eea.12693>. An example can be found in Rebaudo et al. (2017) <doi:10.1007/s13355-017-0480-5>.
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2025-04-22 |
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r-devore7
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Data sets and sample analyses from Jay L. Devore (2008), "Probability and Statistics for Engineering and the Sciences (7th ed)", Thomson.
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2025-04-22 |
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r-devfunc
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A concise check of the format of one or multiple input arguments (data type, length or value) is provided. Since multiple input arguments can be tested simultaneously, a lengthly list of checks at the beginning of your function can be avoided, hereby enhancing the readability and maintainability of your code.
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2025-04-22 |
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r-detpack
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Density estimation for possibly large data sets and conditional/unconditional random number generation or bootstrapping with distribution element trees. The function 'det.construct' translates a dataset into a distribution element tree. To evaluate the probability density based on a previously computed tree at arbitrary query points, the function 'det.query' is available. The functions 'det1' and 'det2' provide density estimation and plotting for one- and two-dimensional datasets. Conditional/unconditional smooth bootstrapping from an available distribution element tree can be performed by 'det.rnd'. For more details on distribution element trees, see: Meyer, D.W. (2016) <arXiv:1610.00345> or Meyer, D.W., Statistics and Computing (2017) <doi:10.1007/s11222-017-9751-9> and Meyer, D.W. (2017) <arXiv:1711.04632> or Meyer, D.W., Journal of Computational and Graphical Statistics (2018) <doi:10.1080/10618600.2018.1482768>.
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2025-04-22 |
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r-detector
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Allows users to quickly and easily detect data containing Personally Identifiable Information (PII) through convenience functions.
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2025-04-22 |
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r-det
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Builds both ROC (Receiver Operating Characteristic) and DET (Detection Error Tradeoff) curves from a set of predictors, which are the results of a binary classification system. The curves give a general vision of the performance of the classifier, and are useful for comparing performance of different systems.
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2025-04-22 |
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r-desnowball
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This package implements a statistical data mining method to compare whole genome gene expression profiles, with respect to the presence of a recurrent genetic disturbance event, to identify the affected target genes.
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2025-04-22 |
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r-desirability
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S3 classes for multivariate optimization using the desirability function by Derringer and Suich (1980).
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2025-04-22 |
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r-desir
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Functions for (1) ranking, selecting, and prioritising genes, proteins, and metabolites from high dimensional biology experiments, (2) multivariate hit calling in high content screens, and (3) combining data from diverse sources.
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2025-04-22 |
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r-designglmm
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Use simulated annealing to find optimal designs for Poisson regression models with blocks.
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2025-04-22 |
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r-designgg
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The package provides R scripts for designing genetical genomics experiments.
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2025-04-22 |
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r-describer
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Allows users to quickly and easily describe data using common descriptive statistics.
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2025-04-22 |
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r-descomponer
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Decompose a time series into seasonal, trend and irregular components using transformations to amplitude-frequency domain.
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2025-04-22 |
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r-des
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Discrete event simulation (DES) involves modeling of systems having discrete, i.e. abrupt, state changes. For instance, when a job arrives to a queue, the queue length abruptly increases by 1. This package is an R implementation of the event-oriented approach to DES; see the tutorial in Matloff (2008) <http://heather.cs.ucdavis.edu/~matloff/156/PLN/DESimIntro.pdf>.
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2025-04-22 |
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r-derivmkts
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A set of pricing and expository functions that should be useful in teaching a course on financial derivatives.
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2025-04-22 |
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r-deriv
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R-based solution for symbolic differentiation. It admits user-defined function as well as function substitution in arguments of functions to be differentiated. Some symbolic simplification is part of the work.
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2025-04-22 |
