Zobrazeno 1 - 10
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pro vyhledávání: '"R-package"'
Publikováno v:
Diversity and Distributions, 2024 Apr 01. 30(4), 1-14.
Externí odkaz:
https://www.jstor.org/stable/48764475
Motivation Network visualization is critical for effective communication in various fields of knowledge. Currently, a gap separates network manipulation from network visualization in programming environments. Users often export network data to be lai
Externí odkaz:
http://arxiv.org/abs/2409.18280
In the context of paid research studies and clinical trials, budget considerations and patient sampling from available populations are subject to inherent constraints. We introduce the R package CDsampling, which is the first to our knowledge to inte
Externí odkaz:
http://arxiv.org/abs/2410.20606
Autor:
Diop, Awa, Sirois, Caroline, Guertin, Jason R., Schnitzer, Mireille E., Brophy, James M., Talbot, Denis
The R package trajmsm provides functions designed to simplify the estimation of the parameters of a model combining latent class growth analysis (LCGA), a trajectory analysis technique, and marginal structural models (MSMs) called LCGA-MSM. LCGA summ
Externí odkaz:
http://arxiv.org/abs/2410.19682
The challenge of location testing for high-dimensional data in statistical inference is notable. Existing literature suggests various methods, many of which impose strong regularity conditions on underlying covariance matrices to ensure asymptotic no
Externí odkaz:
http://arxiv.org/abs/2410.16702
Autor:
Li, Mo
Genetic algorithm (GA) are stochastic search techniques designed to address combinatorial optimization problems by mimicking the principles of natural selection and evolution. GAs have proven effective in both single and multiple changepoint analyses
Externí odkaz:
http://arxiv.org/abs/2410.15571
Fast and Efficient Bayesian Analysis of Structural Vector Autoregressions Using the R Package bsvars
Autor:
Woźniak, Tomasz
The R package bsvars provides a wide range of tools for empirical macroeconomic and financial analyses using Bayesian Structural Vector Autoregressions. It uses frontier econometric techniques and C++ code to ensure fast and efficient estimation of t
Externí odkaz:
http://arxiv.org/abs/2410.15090
Autor:
Bolos, Vicente J., Benitez, Rafael
Publikováno v:
The R Journal, 14/2 (2022), 164-185
In this work we present the wavScalogram R package, which contains methods based on wavelet scalograms for time series analysis. These methods are related to two main wavelet tools: the windowed scalogram difference and the scale index. The windowed
Externí odkaz:
http://arxiv.org/abs/2410.14274
We introduce GPTreeO, a flexible R package for scalable Gaussian process (GP) regression, particularly tailored to continual learning problems. GPTreeO builds upon the Dividing Local Gaussian Processes (DLGP) algorithm, in which a binary tree of loca
Externí odkaz:
http://arxiv.org/abs/2410.01024
Autor:
Manso, Julia
This paper introduces GephiForR, an R package designed to replicate Java-based Gephi's key plotting tools in R. The package is accessible to those with minimal R experience and, in particular, implements ForceAtlas2, the key layout feature developed
Externí odkaz:
http://arxiv.org/abs/2409.18646