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examples/mixture_models/dependent_density_regression.ipynb

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"$$w_i\\ |\\ x = v_i\\ |\\ x \\cdot \\prod_{j = 1}^{i - 1} (1 - v_j\\ |\\ x).$$\n",
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"For the LIDAR data set, we use independent normal priors $\\alpha_i \\sim N(0, 5^2)$ and $\\beta_i \\sim N(0, 5^2)$. We now express this this model for the conditional mixture weights using `PyMC`."
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"For the LIDAR data set, we use independent normal priors $\\alpha_i \\sim N(0, 5^2)$ and $\\beta_i \\sim N(0, 5^2)$. We now express this model for the conditional mixture weights using `PyMC`."
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examples/mixture_models/dependent_density_regression.myst.md

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$$w_i\ |\ x = v_i\ |\ x \cdot \prod_{j = 1}^{i - 1} (1 - v_j\ |\ x).$$
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For the LIDAR data set, we use independent normal priors $\alpha_i \sim N(0, 5^2)$ and $\beta_i \sim N(0, 5^2)$. We now express this this model for the conditional mixture weights using `PyMC`.
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For the LIDAR data set, we use independent normal priors $\alpha_i \sim N(0, 5^2)$ and $\beta_i \sim N(0, 5^2)$. We now express this model for the conditional mixture weights using `PyMC`.
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```{code-cell} ipython3
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:id: 5EgbxpkUg8LE

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