
tSNE
 Referenced in 177 articles
[sw22300]
 highdimensional data by giving each datapoint a location in a two or threedimensional ... reveals structure at many different scales. This is particularly important for highdimensional data that ... seen from multiple viewpoints. For visualizing the structure of very large data sets, we show...

Isomap
 Referenced in 11 articles
[sw31686]
 Scientists working with large volumes of highdimensional data, such as global climate patterns, stellar ... reduction: finding meaningful lowdimensional structures hidden in their highdimensional observations. The human brain ... everyday perception, extracting from its highdimensional sensory inputs30,000 auditory nerve fibers ... Here we describe an approach to solving dimensionality reduction problems that uses easily measured local...

factorcpt
 Referenced in 12 articles
[sw18260]
 highdimensional time series factor models with multiple changepoints in their secondorder structure ... detection in the secondorder structure of a highdimensional time series, into the (relatively ... point detection in the means of highdimensional panel data. Our methodology circumvents the difficult ... piecewise stationary evolution of the factor structure over time. Our methodology is implemented...

hdm
 Referenced in 7 articles
[sw21313]
 HighDimensional Metrics. Implementation of selected highdimensional statistical and econometric methods for estimation ... dimensional causal/ structural parameters are provided which appear in highdimensional approximately sparse models. Including...

GAP
 Referenced in 19 articles
[sw26294]
 highdimensional data sets. It provides direct visual perception for exploring structures of a given...

onlineCOV
 Referenced in 1 article
[sw42773]
 Online Change Point Detection in HighDimensional Covariance Structure. Implement a new stopping rule ... detect anomaly in the covariance structure of highdimensional online data. The detection procedure ... Online ChangePoint Detection in HighDimensional Covariance Structure with Application to Dynamic Networks...

LOBPCG
 Referenced in 33 articles
[sw09638]
 Preconditioned lowrank methods for highdimensional elliptic PDE eigenvalue problems. We consider elliptic ... eigenvalue problem Ax=λx exhibits Kronecker product structure. In particular, we are concerned with...

CorBin
 Referenced in 2 articles
[sw34897]
 package CorBin: Generate HighDimensional Binary Data with Correlation Structures. We design algorithms with linear ... studied correlation structures, including exchangeable, decayingproduct and Kdependent correlation structures, and extend ... efficient methods to generate highdimensional binary data with correlation structures.” Submitted...

DatabionicSwarm
 Referenced in 2 articles
[sw39852]
 able to adapt itself to structures of highdimensional data such as natural clusters characterized ... distance and/or density based structures in the data space. The first module is the parameter ... second module is the parameterfree highdimensional data visualization technique, which generates projected points ... clustering to data sets with completely different structures drawn from diverse research fields. The comparison...

FAMT
 Referenced in 34 articles
[sw11123]
 FAMT) : simultaneous tests under dependence in highdimensional data. The method proposed in this package ... dependence on the multiple testing procedures for highthroughput data as proposed by Friguet ... variables is modeled by a factor analysis structure. The number of factors considered...

naivereg
 Referenced in 1 article
[sw36604]
 could face the model uncertainty for structural equation, as large micro dataset is commonly available ... double selection methods are useful for highdimensional structural equation models. The naivereg is nonparametric...

spectralGraphTopology
 Referenced in 1 article
[sw35465]
 data and hyperconnectivity, learning highdimensional structures such as graphs from data has become...

fabisearch
 Referenced in 2 articles
[sw38226]
 package fabisearch: Change Point Detection in HighDimensional Time Series Networks. Implementation of the Factorized ... network (or clustering) structure of multivariate highdimensional time series. The method is motivated...

ROCKET
 Referenced in 13 articles
[sw30016]
 variables is of fundamental importance in highdimensional statistics, with numerous applications in biological ... literature exists on methods that estimate the structure of an undirected graphical model, however, little ... inference for edge parameters in a highdimensional transelliptical model, which generalizes Gaussian and nonparanormal...

tlrmvnmvt
 Referenced in 2 articles
[sw41644]
 rank algorithm for computing relatively highdimensional multivariate normal (MVN) and Studentt (MVT) probabilities ... Exploiting Low Rank Covariance Structures for Computing HighDimensional Normal and Student t Probabilities,” Statistics...

DBSCAN
 Referenced in 4 articles
[sw02921]
 DBSCAN has been mapped to a skeletonstructured program that performs parallel exploration of each ... performance on highdimensional data, and is general w.r.t. the spatial index structure used...

BDgraph
 Referenced in 19 articles
[sw14815]
 Bayesian structure learning in sparse Gaussian graphical models. Decoding complex relationships among large numbers ... graphical model determination which is a transdimensional Markov Chain Monte Carlo (MCMC) approach based ... implement and computationally feasible for highdimensional graphs. We show our method outperforms alternative Bayesian ... principled and, in practice, sensible approach for structure learning. We illustrate the efficiency...

beam
 Referenced in 1 article
[sw42284]
 marginal and conditional independence structures from highdimensional data. Leday and Richardson (2019), Biometrics...

LargeVis
 Referenced in 6 articles
[sw34905]
 visualizing largescale and highdimensional data in a lowdimensional (typically ... techniques that first compute a similarity structure of the data points and then ... project them into a lowdimensional space with the structure preserved. These two steps suffer ... from scaling to largescale and highdimensional data (e.g., millions of data points...

ANOVAapprox
 Referenced in 4 articles
[sw40667]
 ANOVAapprox: Learning multivariate functions with lowdimensional structures using polynomial bases. In this paper ... method for the approximation of highdimensional functions over finite intervals with respect to complete ... decomposition. For functions with a lowdimensional structure, i.e., a low superposition dimension...