collaborators

6 papers

stat.ME2026

Testing hypotheses via orthogonalization

Ameer Dharamshi, Runjia Zou, Daniela Witten

Classical hypothesis testing frameworks break down in contemporary settings in which null hypotheses are increasingly abstract, the same data are used to both generate and test hyp…

stat.AP2026

Estimating Residential Displacement in the Central Puget Sound Region using Household Survey Data

Ameer Dharamshi, Mary Richards, Suzanne Childress +2

Housing instability is a persistent challenge faced by households in cities across the United States. In worst-case scenarios, households are displaced from their residences and fo…

stat.ME2025

Generalized Data Thinning Using Sufficient Statistics

Ameer Dharamshi, Anna Neufeld, Keshav Motwani +3

Our goal is to develop a general strategy to decompose a random variable into multiple independent random variables, without sacrificing any information about unknown parameter…

stat.ME2025

Exact variance estimation for model-assisted survey estimators using U- and V-statistics

Ameer Dharamshi, Peter Gao, Jon Wakefield

Model-assisted estimation combines sample survey data with auxiliary information to increase precision when estimating finite population quantities. Accurately estimating the varia…

stat.ME2025

Thinning a Wishart Random Matrix

Ameer Dharamshi, Anna Neufeld, Lucy L. Gao +2

Recent work has explored data thinning, a generalization of sample splitting that involves decomposing a (possibly matrix-valued) random variable into independent components. In th…

stat.ME2025

Small Area Estimation of Education Levels in Low- and Middle-Income Countries

Yunhan Wu, Ameer Dharamshi, Jon Wakefield

Education is a key driver of social and economic mobility, yet disparities in attainment persist, particularly in low- and middle-income countries (LMICs). Existing indicators, suc…