Python: Predictive Distribution of the Least Square Estimate

If you want to see the code with syntax highlighting, download the gits for this post from my github. In the ┬áprevious post, we looked at the numerical calculation of the maximum likelihood estimate (MLE). As you might know, we can obtain the same solution in a much easier way using the method of least squares. It can be shown that solving for the maximum … Continue reading Python: Predictive Distribution of the Least Square Estimate

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Python: Maximum Likelihood Estimate

In this post I want to talk about regression and the maximum likelihood estimate. Instead of going the usual way of deriving the least square (LS) estimate which conincides with the maximum likelihood (ML) under the assumption of normally distributed noise, I want to take a different route. Here, instead of using the analytical LS solution, I want to show you, how we can numerically … Continue reading Python: Maximum Likelihood Estimate