Regularization for Continuously Observed Ordinal Response Variables with Piecewise-Constant Functional Predictors

Abstract

Many engineering applications involve the collection of functional data in which the unit of measurement is a curve measured over a continuous time domain. In this manuscript, we consider a case study involving a Follow-On Operational Test and Evaluation (FOT and E) conducted by the United States Army on the RQ-7BV2 Shadow, a tactical unmanned air vehicle system tasked with, among other tasks, providing full motion video to supported ground units. The quality of full motion video was the response variable of interest, and it was recorded on an ordinal scale continuously over the duration of each mission.1 In addition, important covariates, such as the air vehicles altitude and the distance from the air vehicle to the supported unit, were also observed continuously over time.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2016
Accession Number
AD1002101

Entities

People

  • Laura Freeman
  • Mark Orndorff
  • Matthew Avery
  • Timothy J Robinson

Organizations

  • Institute for Defense Analyses

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • Human Systems

DTIC Thesaurus Topics

  • Aircrafts
  • Algorithms
  • Case Studies
  • Computational Science
  • Data Analysis
  • Data Mining
  • Data Science
  • Data Sets
  • Department Of Defense
  • Full Motion Video
  • Information Science
  • Predictive Modeling
  • Probability
  • Step Functions
  • Test And Evaluation
  • United States
  • Unmanned Aerial Vehicles

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Regression Analysis.
  • Unmanned Aerial System (UAS) Autonomous Capabilities and Mission Reconnaissance.

Technology Areas

  • Autonomy
  • Autonomy - UAVs