A Review of Statistical Studies of Seakeeping Qualities.

Abstract

In Part 1, the general procedures of the conventional method of correlation or spectrum analysis of a random process (nonparametric method) are reviewed, stressing the statistical reliability of the results. A few suggestions for improving coherencies are given. In Part II, the characteristics of AR, MA, and ARMA models are discussed. The model-fitting technique supported by AIC criteria is introduced, with the examples of application to seakeeping data. In Part M, the statistical treatments of nonlinearities in random process analysis are summarized and reviewed. Conclusions are given, and future work is proposed. A review of statistical studies, Seakeeping qualities, Stochastic processes, Parametric analysis of time series, Nonparametric analysis of time series, Spectrum analysis, Nonlinear stochastic process analysis, Model fitting techniques to a time series, AR Model, MA Model, ARMA Model and AIC criterion.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1992
Accession Number
ADA271389

Entities

People

  • Yasufumi Yamanouchi

Tags

Communities of Interest

  • Ground and Sea Platforms
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Computational Science
  • Data Mining
  • Data Science
  • Differential Equations
  • Fokker Planck Equations
  • Gaussian Processes
  • Information Processing
  • Information Science
  • Mathematical Filters
  • Naval Architecture
  • Probability Density Functions
  • Random Variables
  • Stationary Processes
  • Statistical Algorithms
  • Statistical Analysis
  • Stochastic Processes
  • United States Naval Academy

Readers

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