2 citations · 3 across the 10 of their papers we have counts for
10 papers
Robust Dual-Regularized Variable Selection under Outlier Contamination
Abdul-Nasah Soale, Adewale F. Lukman, Essoham Ali
Real data often contain unusual observations that can exert disproportionate effects on variable selection, especially in complex predictor settings. We propose a two-stage {\it sp…
Near-Optimal Nitrogen Recommendations for Precision Agriculture via Sequential Screening and Hierarchical Refinement
Sakshi Arya, Abdul-Nasah Soale, Hossein Moradi Rekabdarkolaee
Nitrogen fertilizer management plays a central role in balancing agricultural productivity and environmental sustainability, yet identifying optimal application strategies remains…
Adaptive Influence Diagnostics in High-Dimensional Regression
Abdul-Nasah Soale, Adewale Lukman
An adaptive Cook's distance (ACD) for diagnosing influential observations in high-dimensional single-index models with multicollinearity and outlier contamination is proposed. ACD…
On metric choice in dimension reduction for Fréchet regression
Abdul-Nasah Soale, Congli Ma, Siyu Chen +1
Fréchet regression is becoming a mainstay in modern data analysis for analyzing non-traditional data types belonging to general metric spaces. This novel regression method is espec…
Detecting influential observations in single-index Fréchet regression
Abdul-Nasah Soale
Regression with random data objects is becoming increasingly common in modern data analysis. Unfortunately, this novel regression method is not immune to the trouble caused by unus…
Sufficient dimension reduction for regression with metric space-valued responses
Abdul-Nasah Soale, Yuexiao Dong
Data visualization and dimension reduction for regression between a general metric space-valued response and Euclidean predictors is proposed. Current Fréchét dimension reduction m…
A selective review of sufficient dimension reduction for multivariate response regression
Yuexiao Dong, Abdul-Nasah Soale, Michael D. Power
We review sufficient dimension reduction (SDR) estimators with multivariate response in this paper. A wide range of SDR methods are characterized as inverse regression SDR estimato…
A Distance Covariance-based Estimator
Emmanuel Selorm Tsyawo, Abdul-Nasah Soale
This paper proposes an estimator that relaxes the conventional relevance condition in instrumental variable (IV) analyses. The method allows endogenous covariates to be weakly corr…
On sufficient dimension reduction via principal asymmetric least squares
Abdul-Nasah Soale, Yuexiao Dong
In this paper, we introduce principal asymmetric least squares (PALS) as a unified framework for linear and nonlinear sufficient dimension reduction. Classical methods such as slic…
On expectile-assisted inverse regression estimation for sufficient dimension reduction
Abdul-Nasah Soale, Yuexiao Dong
Moment-based sufficient dimension reduction methods such as sliced inverse regression may not work well in the presence of heteroscedasticity. We propose to first estimate the expe…