Regression proofs and definitions

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32 Terms

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Idempotent (Gr = G where r is any integer value).

Symmetric (G = GT )

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what is R²?

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ANOVA table for general form

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Orthogonal ANOVA table

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F test statistic

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Cook’s distance

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<p>Ridge estimator</p>

Ridge estimator

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what is the Gauss-Markov theorem

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How can you apply the Gauss-Markov theorem to compare the variance of weighted LSE’s?

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what is Lasso regression

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<p>derive and formulate expectation and covariance matrix</p>

derive and formulate expectation and covariance matrix

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<p>derive and formulate expectation and covariance matrix</p>

derive and formulate expectation and covariance matrix

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<p>derive and formulate expectation and covariance matrix</p>

derive and formulate expectation and covariance matrix

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Prove Gauss-Markov theorem

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Maximum likelihood function derivation

MLE for θ: maximise log⁡ L w.r.t. θ, which is equivalent to minimising the sum of squared errors

MLE for σ2 : differentiate and set equal to 0

<p>MLE for θ: maximise log⁡ L w.r.t. θ, which is equivalent to minimising the sum of squared errors</p><p>MLE for σ<sup>2 </sup>: differentiate and set equal to 0</p>
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Formulate the expected value for SSerror

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