1 citations · 2 across the 5 of their papers we have counts for
7 papers
Spatial Principal Component Analysis and Moran Statistics for Multivariate Functional Areal Data
Dharini Pathmanathan, Issa-Mbenard Dabo, Tzung Hsuen Khoo +2
The paper introduces a multivariate functional areal spatial principal component analysis (mfasPCA) framework, together with multivariate functional Moran's I statistics, to enable…
High-dimensional analysis of ridge regression for non-identically distributed data with a variance profile
Jérémie Bigot, Issa-Mbenard Dabo, Camille Male
High-dimensional linear regression has been thoroughly studied in the context of independent and identically distributed data. We propose to investigate high-dimensional regression…
High-dimensional ridge regression with random features for non-identically distributed data with a variance profile
Issa-Mbenard Dabo, Jérémie Bigot
Random feature ridge regression is often analyzed in the high-dimensional regime under the homogeneous sampling model , where the vectors have iid entries…
Generalized dynamic functional principal component analysis
Tzung Hsuen Khoo, Issa-Mbenard Dabo, Dharini Pathmanathan +1
In this paper, we explore dimension reduction for functional time series. We propose a generalized dynamic functional principal component analysis (GDFPCA) which does not rely on s…
Reframing Three-Dimensional Morphometrics Through Functional Data Innovations
Aneesha Balachandran Pillay, Issa-Mbenard Dabo, Sophie Dabo-Niang +1
This study innovates geometric morphometrics by incorporating functional data analysis, the square-root velocity function (SRVF), and arc-length parameterisation for 3D morphometri…
A multivariate spatial regression model using signatures
Camille Frévent, Issa-Mbenard Dabo
We propose a spatial autoregressive model for a multivariate response variable and functional covariates. The approach is based on the notion of signature, which represents a funct…