From Data to Assessments and Decisions: Epi-Spline Technology

Abstract

Analysts in every field face the challenge of how to best use available data to estimate performance, quantify uncertainty, and predict the future. The data is almost never just right, but rather scarce, excessive, corrupted, uncertain, and incomplete. External information derived from experiences, established laws, and physical restrictions offer opportunities to remedy the situation and should be utilized. Applications in sustainable energy, natural resources, image reconstruction, financial planning, uncertainty quantification, and reliability engineering are rich with problems where decisions rely on data analysis under such circumstances. We address these problems within a framework that identifies a function that according to some criterion best represents the given data set and satisfies constraints derived from the data as well as external information. Epi-splines provide the linchpin that allows us to handle shape restrictions, information growth, and approximations.

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Document Details

Document Type
Technical Report
Publication Date
May 08, 2014
Accession Number
ADA603986

Entities

People

  • Johannes Ø. Røyset
  • Roger J-B Wets

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Computational Science
  • Curve Fitting
  • Data Analysis
  • Data Science
  • Differential Equations
  • Equations
  • Image Reconstruction
  • Operations Research
  • Probability
  • Probability Density Functions
  • Random Variables
  • Regression Analysis
  • Simulations
  • Standards
  • Statistics
  • Stochastic Processes
  • Topology

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Systems Analysis and Design