Minimum instead of maximum (#453)
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@ -192,7 +192,7 @@ sim1_mod <- lm(y ~ x, data = sim1)
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coef(sim1_mod)
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```
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These are exactly the same values we got with `optim()`! Behind the scenes `lm()` doesn't use `optim()` but instead takes advantage of the mathematical structure of linear models. Using some connections between geometry, calculus, and linear algebra, `lm()` actually finds the closest model by (effectively) inverting a matrix. This approach is both faster, and guarantees that there is a global maximum.
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These are exactly the same values we got with `optim()`! Behind the scenes `lm()` doesn't use `optim()` but instead takes advantage of the mathematical structure of linear models. Using some connections between geometry, calculus, and linear algebra, `lm()` actually finds the closest model by (effectively) inverting a matrix. This approach is both faster, and guarantees that there is a global minimum.
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### Exercises
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