6 papers · 1 filter
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…
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…
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…
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…
Decomposing Gaussians with Unknown Covariance
Ameer Dharamshi, Anna Neufeld, Lucy L. Gao +2
Common workflows in machine learning and statistics rely on the ability to partition the information in a data set into independent portions. Recent work has shown that this may be…
Discussion of "Data fission: splitting a single data point"
Anna Neufeld, Ameer Dharamshi, Lucy L. Gao +2
Leiner et al. [2023] introduce an important generalization of sample splitting, which they call data fission. They consider two cases of data fission: P1 fission and P2 fission. Wh…