
Sparse Functional Boxplots for Multivariate Curves
This paper introduces the sparse functional boxplot and the intensity sp...
read it

Forecasting HighFrequency SpatioTemporal Wind Power with Dimensionally Reduced Echo State Networks
Fast and accurate hourly forecasts of wind speed and power are crucial i...
read it

Tractable Bayes of SkewElliptical Link Models for Correlated Binary Data
Correlated binary response data with covariates are ubiquitous in longit...
read it

A Generalized Heckman Model With Varying Sample Selection Bias and Dispersion Parameters
Many proposals have emerged as alternatives to the Heckman selection mod...
read it

Assessing the Reliability of Wind Power Operations under a Changing Climate with a NonGaussian Distributional Adjustment
Facing increasing societal and economic pressure, many countries have es...
read it

Scalable computation of predictive probabilities in probit models with Gaussian process priors
Predictive models for binary data are fundamental in various fields, and...
read it

Are You All Normal? It Depends!
The assumption of normality has underlain much of the development of sta...
read it

Visualization of Covariance Structures for Multivariate SpatioTemporal Random Fields
The prevalence of multivariate spacetime data collected from monitoring...
read it

High Performance Multivariate Spatial Modeling for Geostatistical Data on Manycore Systems
Modeling and inferring spatial relationships and predicting missing valu...
read it

Conditional Normal ExtremeValue Copulas
We propose a new class of extremevalue copulas which are extremevalue ...
read it

Exploiting Low Rank Covariance Structures for Computing HighDimensional Normal and Studentt Probabilities
We present a preconditioned Monte Carlo method for computing highdimens...
read it

A Pairwise Hotelling Method for Testing HighDimensional Mean Vectors
For highdimensional small sample size data, Hotelling's T2 test is not ...
read it

Nonparametric Trend Estimation in Functional Time Series with Application to Annual Mortality Rates
Here, we address the problem of trend estimation for functional time ser...
read it

Vector Autoregressive Models with Spatially Structured Coefficients for Time Series on a Spatial Grid
We propose a parsimonious spatiotemporal model for time series data on a...
read it

Recent Developments in Complex and Spatially Correlated Functional Data
As highdimensional and highfrequency data are being collected on a lar...
read it

Efficiency Assessment of Approximated Spatial Predictions for Large Datasets
Due to the wellknown computational showstopper of the exact Maximum Lik...
read it

Generalized Records for Functional Time Series with Application to Unit Root Tests
A generalization of the definition of records to functional data is prop...
read it

ExaGeoStatR: A Package for LargeScale Geostatistics in R
Parallel computing in Gaussian process calculation becomes a necessity f...
read it

Improving Bayesian Local Spatial Models in Large Data Sets
Environmental processes resolved at a sufficiently small scale in space ...
read it

Trajectory Functional Boxplots
With the development of datamonitoring techniques in various fields of ...
read it

Spatial Blind Source Separation
Recently a blind source separation model was suggested for multivariate ...
read it

Functional Outlier Detection and Taxonomy by Sequential Transformations
Functional data analysis can be seriously impaired by abnormal observati...
read it

Parallel Approximation of the Maximum Likelihood Estimation for the Prediction of LargeScale Geostatistics Simulations
Maximum likelihood estimation is an important statistical technique for ...
read it

Tile LowRank Approximation of LargeScale Maximum Likelihood Estimation on Manycore Architectures
Maximum likelihood estimation is an important statistical technique for ...
read it

Bayesian Modeling of Air Pollution Extremes Using Nested Multivariate MaxStable Processes
Capturing the potentially strong dependence among the peak concentration...
read it

A MultiResolution Spatial Model for Large Datasets Based on the Skewt Distribution
Large, nonGaussian spatial datasets pose a considerable modeling challe...
read it

A Stochastic Generator of Global Monthly Wind Energy with Tukey gandh Autoregressive Processes
Quantifying the uncertainty of wind energy potential from climate models...
read it

Likelihood Approximation With Hierarchical Matrices For Large Spatial Datasets
We use available measurements to estimate the unknown parameters (varian...
read it

An Outlyingness Matrix for Multivariate Functional Data Classification
The classification of multivariate functional data is an important task ...
read it
Marc G. Genton
is this you? claim profile