Estimation theory

Estimation theory is a branch of statistics that deals with estimating the values of parameters based on measured empirical data that has a random component. The parameters describe an underlying physical setting in such a way that their value affects the distribution of the measured data. An estimator attempts to approximate the unknown parameters using the measurements. In estimation theory, two approaches are generally considered: [1]

  • The probabilistic approach (described in this article) assumes that the measured data is random with probability distribution dependent on the parameters of interest
  • The set-membership approach assumes that the measured data vector belongs to a set which depends on the parameter vector.

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