Results 71 to 80 of about 16,329,521 (81)
Dianxin kexue, 2016 An improved algorithm called CLTree-R was proposed.It could compensate the shortcoming of CLTree algorithm such as low accurate and inefficiency.Then CLTree-R was applied in clustering analysis for UCI data sets.In order to improve the efficiency，data ...
Zhuohang LI
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From Spider-Man to Hero — Archetypal Analysis in R
Journal of Statistical Software, 2009 Archetypal analysis has the aim to represent observations in a multivariate data setas convex combinations of extremal points. This approach was introduced by Cutler andBreiman (1994); they dened the concrete problem, laid out the theoretical ...
Manuel J. A. Eugster, Friedrich Leisch
doaj
EURASIP Journal on Information SecurityIn recent years, various smart devices based on IoT technology, such as smart homes, healthcare, detection, and logistics systems, have emerged. However, as the number of IoT-connected devices increases, securing the IoT is becoming increasingly ...
Lin Yang
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Decentralised Coordination of Unmanned Aerial Vehicles for Target Search using the Max-Sum Algorithm
, 2010 This paper considers the coordination of a team of Unmanned Aerial Vehicles (UAVs) that are deployed to search for a moving target within a continuous space.
Xu, Zhe +3 more
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Support in R for state space estimation via Kalman filtering was limited to one package, until fairly recently. In the last five years, the situation has changed with no less than four additional packages offering general implementations of the Kalman ...
Fernando Tusell
core
R-VGAL: a sequential variational Bayes algorithm for generalised linear mixed models
Models with random effects, such as generalised linear mixed models (GLMMs), are often used for analysing clustered data. Parameter inference with these models is difficult because of the presence of cluster-specific random effects, which must be ...
David Gunawan (5193539) +2 more
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The Expectation-Maximization (EM) algorithm is a broadly applicable approach to the iterative computation of maximum likelihood (ML) estimates, useful in a variety of incomplete-data problems.
Ng, See Ket +2 more
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Multidimensional Scaling Using Majorization: SMACOF in R [PDF]
In this paper we present the methodology of multidimensional scaling problems (MDS) solved by means of the majorization algorithm. The objective function to be minimized is known as stress and functions which majorize stress are elaborated. This strategy
Patrick Mair, Jan de Leeuw
core
topicmodels: An R Package for Fitting Topic Models [PDF]
Topic models allow the probabilistic modeling of term frequency occurrences in documents. The fitted model can be used to estimate the similarity between documents as well as between a set of specified keywords using an additional layer of latent ...
Bettina Grün, Kurt Hornik
core
The xdvir package provides functions for rendering LaTeX fragments as labels, annotations, and data symbols in R plots. There are convenient high-level functions for rendering LaTeX fragments, including labels on ggplot2 plots, plus lower-level functions
Murrell, Paul
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