Maximum Likelihood Estimation
★★★★☆Undergraduate
📖Definition
Estimation method finding parameters that best explain observed data
📐Formulas
Likelihood: L(θ) = P(data|θ) = ∏P(xᵢ|θ)
Log-likelihood: ℓ(θ) = Σlog P(xᵢ|θ)
MLE: θ̂ = argmax L(θ)
✏️Examples
예제 1
Normal MLE: μ̂=x̄, σ̂²=s²
예제 2
Bernoulli MLE: p̂ = x̄
⚡Applications
Parameter estimation
Machine learning
Statistical modeling
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