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What is Parameter Estimation Techniques Explained about?

The document discusses several statistical methods for parameter estimation from observed time series data: 1. Maximum likelihood estimation finds the parameter value θ that maximizes the likelihood function L(θ;XT) defined using the observed process. 2. Bayesian estimation defines a posterior distribution over θ given the data and prior p(θ), and computes the Bayesian estimator as the expectation over this posterior. 3. Minimum distance estimation finds θ that minimizes a distance (e.g. L2 norm) betwee

Author

Lameune

Language

EN