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Chapters

Richie Slocum edited this page Jun 7, 2017 · 1 revision

Error Theory

This chapter will introduce error theory, the distribution of errors, co-variances, and methods for propagating errors

  • Confidence Intervals
  • PDF and CDF
  • Covariance Matrices
  • Error Ellipses
  • SLOPOV
  • GLOPOV
  • Monte Carlo
  • PDF Propagation

Statistics tests

This chapter will be a short reference with lists of statistical tests, when to use them, and especially their assumptions.

  • chi squared
  • 2 sigma
  • etc

Least Squares

This chapter will introduce least squares and give many examples of how to implement the methodology. Assumptions and pitfalls are really important.

  • Linear (OLS, WLS, GLS)
  • Nonlinear
  • Total Least Squares (Iterative Reweighted GLOPOV)
  • Robust Least Squares

RANSAC

This will introduce the concept of RANSAC and give examples

Kalman Filtering

GNSS

Geodesy and Datums

Fourier Analysis

Lidar

Computer Vision