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Update bayes_opt.Rmd
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This vignette demonstrates how to utilize and repurpose my favorite `design()` function in `dgpsi` to implement Bayesian optimization using the (D)GP surrogate models provided by the package.
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This vignette demonstrates how to utilize and repurpose the `design()` function in `dgpsi` to implement Bayesian optimization using the (D)GP surrogate models provided by the package.
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## Load the packages
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The domain of the input parameters for our Bayesian optimization, within which the global minima are searched, is defined as $[0,1]^2$:
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The domain of the input for the Shubert function, within which the global minima are searched by the Bayesian optimization, is defined as $[0,1]^2$:
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```{r}
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lim <- rbind(c(0, 1), c(0, 1))

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