نتایج جستجو برای: nonparametric topological data analysis

تعداد نتایج: 4542861  

Journal: :Journal of Statistical Planning and Inference 2017

Journal: :Operations Research 2010
Timo Kuosmanen Andrew L. Johnson

Data Envelopment Analysis (DEA) is known as a nonparametric mathematical programming approach to productive efficiency analysis. In this paper we show that DEA can be alternatively interpreted as nonparametric least squares regression subject to shape constraints on frontier and sign constraints on residuals. This reinterpretation reveals the classic parametric programming model by Aigner and C...

Journal: :Journal of Statistical Planning and Inference 2016

Journal: :Mathematics 2021

We are interested in evaluating the state of drivers to determine whether they attentive road or not by using motion sensor data collected from car driving experiments. That is, our goal is design a predictive model that can estimate given sensors. For purpose, we leverage recent developments topological analysis (TDA) analyze and transform coming time series build machine learning based on fea...

Journal: :Foundations of Computational Mathematics 2014
Andrew J. Blumberg Itamar Gal Michael A. Mandell Matthew Pancia

We study distributions of persistent homology barcodes associated to taking subsamples of a fixed size from metric measure spaces. We show that such distributions provide robust invariants of metric measure spaces, and illustrate their use in hypothesis testing and providing confidence intervals for topological data analysis.

2012
Eric M. Hanson Francis C. Motta Chris Peterson Lori Ziegelmeier

Persistent homology is a relatively new tool from topological data analysis that has transformed, for many, the way data sets (and the information contained in those sets) are viewed. It is derived directly from techniques in computational homology but has the added feature that it is able to capture structure at multiple scales. One way that this multi-scale information can be presented is thr...

Journal: :Journal of physics 2021

Abstract We use methods from computational algebraic topology to study functional brain networks in which nodes represent regions and weighted edges encode the similarity of magnetic resonance imaging (fMRI) time series each region. With these tools, allow one characterize topological invariants such as loops high-dimensional data, we are able gain understanding low-dimensional structures a way...

2015

PROTEIN STABILITY Taylor Dispersion Analysis (TDA) is a microcapillary flow-based technique whereby a nanoliter-scale sample pulse is injected into the laminar flow of run buffer, which then spreads out axially due to the combined actions of convection and radial diffusion. Detection of the equilibrium concentration profile (or Taylorgram) of the dispersed sample pulse allows the molecular diff...

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