Let W denote a family of probability distributions with parameter space Τ, and WG be a subfamily of W depending on a mapping G:Θ -> Τ. Extremum estimations of the parameter vector ν ∈ Θ are considered. Some sufficient conditions are presented to ensure the uniqueness with probability one. As important applications, the maximum likelihood estimation in curved exponential families and nonlinear regression models with independent disturbances as well as the maximum likelihood estimation of the location and scale parameters of Gumbel distributions are treated.
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Paper provided by Sonderforschungsbereich 649, Humboldt University, Berlin, Germany in its series SFB 649 Discussion Papers with number
SFB649DP2006-080.
Find related papers by JEL classification: C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Estimation C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Econometric and Statistical Methods; Specific Distributions
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