10 citations · 34 across the 12 of their papers we have counts for
12 papers
Random Invariance Testing on Quadratic Form Statistics with Application to Autocorrelation
Amitakshar Biswas, Adam B Kashlak
Randomization testing with permutations is a very common nonparametric approach to hypothesis testing. However, randomization testing can be done with other group transformations i…
Asymptotic symmetry and group invariance for randomization
Adam B Kashlak
Symmetry is a cornerstone of much of mathematics, and many probability distributions possess symmetries characterized by their invariance to a collection of group actions. Thus, ma…
Topological Hidden Markov Models
Adam B Kashlak, Prachi Loliencar, Giseon Heo
The hidden Markov model (HMM) is a classic modeling tool with a wide swath of applications. Its inception considered observations restricted to a finite alphabet, but it was quickl…
Local Statistics for Spatial Panel Models with Application to the US Electorate
Jianfeng Wang, Adam B Kashlak
The spatial panel regression model has shown great success in modelling econometric and other types of data that are observed both spatially and temporally with associated predicto…
A reproducing kernel Hilbert space framework for functional data classification
Peijun Sang, Adam B Kashlak, Linglong Kong
We encounter a bottleneck when we try to borrow the strength of classical classifiers to classify functional data. The major issue is that functional data are intrinsically infinit…
Computation-free Nonparametric testing for Local and Global Spatial Autocorrelation with application to the Canadian Electorate
Adam B Kashlak, Weicong Yuan
Measures of local and global spatial association are key tools for exploratory spatial data analysis. Many such measures exist including Moran's , Geary's , and the Getis-Ord…
Functional Response Designs via the Analytic Permutation Test
Adam B Kashlak, Sergii Myroshnychenko, Susanna Spektor
Vast literature on experimental design extends from Fisher and Snedecor to the modern day. When data lies beyond the assumption of univariate normality, nonparametric methods inclu…
Diagnosis of Pediatric Obstructive Sleep Apnea via Face Classification with Persistent Homology and Convolutional Neural Networks
Milad Kiaee, Adam B Kashlak, Jisu Kim +1
Obstructive sleep apnea is a serious condition causing a litany of health problems especially in the pediatric population. However, this chronic condition can be treated if diagnos…
Non-asymptotic error controlled sparse high dimensional precision matrix estimation
Adam B Kashlak
Estimation of a high dimensional precision matrix is a critical problem to many areas of statistics including Gaussian graphical models and inference on high dimensional data. Work…
Nonasymptotic estimation and support recovery for high dimensional sparse covariance matrices
Adam B Kashlak, Linglong Kong
We propose a general framework for nonasymptotic covariance matrix estimation making use of concentration inequality-based confidence sets. We specify this framework for the estima…
Improved Rademacher symmetrization through a Wasserstein based measure of asymmetry
Adam B Kashlak
We propose of an improved version of the ubiquitous symmetrization inequality making use of the Wasserstein distance between a measure and its reflection in order to quantify the s…
Inference on covariance operators via concentration inequalities: k-sample tests, classification, and clustering via Rademacher complexities
Adam B. Kashlak, John A. D. Aston, Richard Nickl
We propose a novel approach to the analysis of covariance operators making use of concentration inequalities. First, non-asymptotic confidence sets are constructed for such operato…