50 citations · 137 across the 11 of their papers we have counts for
11 papers
Interpretable contour level selection for heat maps for gridded data
Tarn Duong
Gridded data formats, where the observed multivariate data are aggregated into grid cells, ensure confidentiality and reduce storage requirements, with the trade-off that access to…
Statistical visualisation for tidy and geospatial data in R via kernel smoothing methods in the eks package
Tarn Duong
Kernel smoothers are essential tools for data analysis due to their ability to convey complex statistical information with concise graphical visualisations. Their inclusion in the…
Relaxing door-to-door matching reduces passenger waiting times: a workflow for the analysis of driver GPS traces in a stochastic carpooling service
Panayotis Papoutsis, Safa Fennia, Constant Bridon +1
Carpooling has the potential to transform itself into a mass transportation mode by abandoning its adherence to deterministic passenger-driver matching for door-to-door journeys, a…
Higher order differential analysis with vectorized derivatives
José E. Chacón, Tarn Duong
Higher order derivatives of functions are structured high dimensional objects which lend themselves to many alternative representations, with the most popular being multi-index, ma…
Bayesian hierarchical models for the prediction of the driver flow and passenger waiting times in a stochastic carpooling service
Panayotis Papoutsis, Bertrand Michel, Anne Philippe +1
Carpooling is an integral component in smart carbon-neutral cities, in particular to facilitate homework commuting. We study an innovative carpooling service developed by the start…
Nearest Neighbor Median Shift Clustering for Binary Data
Gaël Beck, Tarn Duong, Mustapha Lebbah +1
We describe in this paper the theory and practice behind a new modal clustering method for binary data. Our approach (BinNNMS) is based on the nearest neighbor median shift. The me…
A Distributed and Approximated Nearest Neighbors Algorithm for an Efficient Large Scale Mean Shift Clustering
Gaël Beck, Tarn Duong, Mustapha Lebbah +2
In this paper we target the class of modal clustering methods where clusters are defined in terms of the local modes of the probability density function which generates the data. T…
Exploratory data analysis for moderate extreme values using non-parametric kernel methods
Boris Beranger, Tarn Duong, Sarah E. Perkins-Kirkpatrick +1
In many settings it is critical to accurately model the extreme tail behaviour of a random process. Non-parametric density estimation methods are commonly implemented as explorator…
Efficient recursive algorithms for functionals based on higher order derivatives of the multivariate Gaussian density
José E. Chacón, Tarn Duong
Many developments in Mathematics involve the computation of higher order derivatives of Gaussian density functions. The analysis of univariate Gaussian random variables is a well-e…
Joint Modeling and Registration of Cell Populations in Cohorts of High-Dimensional Flow Cytometric Data
Saumyadipta Pyne, Kui Wang, Jonathan Irish +10
In systems biomedicine, an experimenter encounters different potential sources of variation in data such as individual samples, multiple experimental conditions, and multi-variable…
Data-driven density derivative estimation, with applications to nonparametric clustering and bump hunting
José E. Chacón, Tarn Duong
Important information concerning a multivariate data set, such as clusters and modal regions, is contained in the derivatives of the probability density function. Despite this impo…