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r-easysvg
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public |
This SVG elements generator can easily generate SVG elements such as rect, line, circle, ellipse, polygon, polyline, text and group. Also, it can combine and output SVG elements into a SVG file.
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2025-04-22 |
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r-easyreg
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public |
Performs analysis of regression in simple designs with quantitative treatments, including mixed models and non linear models.
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2025-04-22 |
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r-easypubmed
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public |
Query NCBI Entrez and retrieve PubMed records in XML or text format. Process PubMed records by extracting and aggregating data from selected fields. A large number of records can be easily downloaded via this simple-to-use interface to the NCBI PubMed API.
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2025-04-22 |
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r-easynls
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Fit and plot some nonlinear models.
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2025-04-22 |
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r-easycsv
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public |
Allows users to easily read multiple comma separated tables and create a data frame under the same name. Is able to read multiple comma separated tables from a local directory, a zip file or a zip file on a remote directory.
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2025-04-22 |
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r-easyanova
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public |
Perform analysis of variance and other important complementary analyses. The functions are easy to use. Performs analysis in various designs, with balanced and unbalanced data.
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2025-04-22 |
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r-easyahp
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public |
Given the scores from decision makers, the analytic hierarchy process can be conducted easily.
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2025-04-22 |
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r-dzexpm
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public |
MCMC method to estimate and predict skewed spatial processes. A real data set is included. Reference: Wang, Yang and Majumdar (2018) <doi.org/10.1007/s00180-017-0741-3>.
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2025-04-22 |
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r-dynprog
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public |
A domain-specific language for specifying translating recursions into dynamic-programming algorithms. See <https://en.wikipedia.org/wiki/Dynamic_programming> for a description of dynamic programming.
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2025-04-22 |
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r-dynpanel
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public |
Computes the first stage GMM estimate of a dynamic linear model with p lags of the dependent variables.
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2025-04-22 |
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r-dynia
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public |
Fit dynamic intervention model using the arima() function.
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2025-04-22 |
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r-dynetnlaresistance
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public |
An anonymization algorithm to resist neighbor label attack in a dynamic network.
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2025-04-22 |
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r-dyncomp
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public |
While there are many well-established measures for identifying critical fluctuations and phase transitions, these measures only work with many points of measurement and thus are unreliable when studying short and coarse-grained time series. This package provides a measure for complexity in a time series that does not rely on long time series (Kaiser (2017), <doi:10.17605/OSF.IO/GWTKX>).
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2025-04-22 |
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r-dynclust
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DynClust is a two-stage procedure for the denoising and clustering of stack of noisy images acquired over time. Clustering only assumes that the data contain an unknown but small number of dynamic features. The method first denoises the signals using local spatial and full temporal information. The clustering step uses the previous output to aggregate voxels based on the knowledge of their spatial neighborhood. Both steps use a single keytool based on the statistical comparison of the difference of two signals with the null signal. No assumption is therefore required on the shape of the signals. The data are assumed to be normally distributed (or at least follow a symmetric distribution) with a known constant variance. Working pixelwise, the method can be time-consuming depending on the size of the data-array but harnesses the power of multicore cpus.
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2025-04-22 |
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r-dynamictreecut
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Contains methods for detection of clusters in hierarchical clustering dendrograms.
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2025-04-22 |
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r-dynamicdistribution
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public |
The package is aimed at dynamically visualizing probability distributions and their moments and all the commonly used distributions are included.
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2025-04-22 |
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r-dynamac
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public |
While autoregressive distributed lag (ARDL) models allow for extremely flexible dynamics, interpreting substantive significance of complex lag structures remains difficult. This package is designed to assist users in dynamically simulating and plotting the results of various ARDL models. It also contains post-estimation diagnostics, including a test for cointegration when estimating the error-correction variant of the autoregressive distributed lag model (Pesaran, Shin, and Smith 2001 <doi:10.1002/jae.616>).
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2025-04-22 |
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r-dyn
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public |
Time series regression. The dyn class interfaces ts, irts(), zoo() and zooreg() time series classes to lm(), glm(), loess(), quantreg::rq(), MASS::rlm(), MCMCpack::MCMCregress(), quantreg::rq(), randomForest::randomForest() and other regression functions allowing those functions to be used with time series including specifications that may contain lags, diffs and missing values.
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2025-04-22 |
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r-dym
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public |
Add a "Did You Mean" feature to the R interactive. With this package, error messages for misspelled input of variable names or package names suggest what you really want to do in addition to notification of the mistake.
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2025-04-22 |
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r-dykstra
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public |
Solves quadratic programming problems using Richard L. Dykstra's cyclic projection algorithm. Routine allows for a combination of equality and inequality constraints. See Dykstra (1983) <doi:10.1080/01621459.1983.10477029> for details.
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2025-04-22 |
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r-dydea
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Finds regular and chaotic intervals in the data using the 0-1 test for chaos proposed by Gottwald and Melbourne (2004) <DOI:10.1137/080718851>.
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2025-04-22 |
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r-dyads
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Contains functions for the MCMC simulation of dyadic network models j2 (Zijlstra, 2017, <doi:10.1080/0022250X.2017.1387858>) and p2 (Van Duijn, Snijders & Zijlstra, 2004, <doi: 10.1046/j.0039-0402.2003.00258.x>) as described in Zijlstra, Van Duijn & Snijders (2009) <doi: 10.1348/000711007X255336>.
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2025-04-22 |
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r-dwlm
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This linear model solution is useful when both predictor and response have associated uncertainty. The doubly weights linear model solution is invariant on which quantity is used as predictor or response. Based on the results by Reed(1989) <doi:10.1119/1.15963> and Ripley & Thompson(1987) <doi:10.1039/AN9871200377>.
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2025-04-22 |
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r-dwdlarger
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public |
Solving large scale distance weighted discrimination. The main algorithm is a symmetric Gauss-Seidel based alternating direction method of multipliers (ADMM) method. See Lam, X.Y., Marron, J.S., Sun, D.F., and Toh, K.C. (2018) <arXiv:1604.05473> for more details.
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2025-04-22 |
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r-dunn.test
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Computes Dunn's test (1964) for stochastic dominance and reports the results among multiple pairwise comparisons after a Kruskal-Wallis test for stochastic dominance among k groups (Kruskal and Wallis, 1952). The interpretation of stochastic dominance requires an assumption that the CDF of one group does not cross the CDF of the other. 'dunn.test' makes k(k-1)/2 multiple pairwise comparisons based on Dunn's z-test-statistic approximations to the actual rank statistics. The null hypothesis for each pairwise comparison is that the probability of observing a randomly selected value from the first group that is larger than a randomly selected value from the second group equals one half; this null hypothesis corresponds to that of the Wilcoxon-Mann-Whitney rank-sum test. Like the rank-sum test, if the data can be assumed to be continuous, and the distributions are assumed identical except for a difference in location, Dunn's test may be understood as a test for median difference. 'dunn.test' accounts for tied ranks.
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2025-04-22 |
