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Nonlinear models Hill et al Chapter 10

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Types of nonlinear models Linear in the parameters. –Includes models that can be made linear by transformation: Nonlinear in the parameters –Require nonlinear least squares.

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Polynomial terms in a regression For U-shaped curve we expect 2 0 U-shaped marginal cost curve 2 >0, 3 0

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Interactions between continuous variables Is it reasonable that these effects are independent of income and age?

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An alternative model

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Empirical example

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Nonlinear least squares Minimise sum of squared errors b = 1.1612 se(b) = 0.129 Simple expressions for the value of beta that minimises S cannot be found. Similarly expressions for the se(beta) cannot be found. The problem is solved numerically.

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A logistic growth curve

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Example: proportion of steel produced with electric arc furnace

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The poisson regression Number of visits to a lake: count data Does not have a normal distribution Poisson distribution is an alternative: is the average or mean number of visits per year, for all households Number of visits 01234567891013 Frequency615541312319872111

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Estimating the conditional mean function in the Poisson regression define the zero-mean error term

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Computing probabilities in the Poisson regression What is the probability that a household located 50 miles from the Lake, with income of $60,000, and 3 family members, visits the park less than 3 times per year?

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Generalized Linear Models All the regression models treated so far have common structure. This structure can be split up into two parts: The random part:

Generalized Linear Models All the regression models treated so far have common structure. This structure can be split up into two parts: The random part:

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