[likelihood] fixed exercise
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@ -51,10 +51,10 @@ of the standard deviation.
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\question \qt{Maximum-likelihood estimator of a line through the origin}
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In the lecture we derived the following equation for an
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maximum-likelihood estimate of the slope $\theta$ of a straight line
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maximum-likelihood estimate of the slope $m$ of a straight line
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through the origin fitted to $n$ pairs of data values $(x_i|y_i)$ with
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standard deviation $\sigma_i$:
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\[\theta = \frac{\sum_{i=1}^n \frac{x_i y_i}{\sigma_i^2}}{ \sum_{i=1}^n
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\[ m = \frac{\sum_{i=1}^n \frac{x_i y_i}{\sigma_i^2}}{ \sum_{i=1}^n
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\frac{x_i^2}{\sigma_i^2}} \]
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\begin{parts}
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\part \label{mleslopefunc} Write a function that takes two vectors
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@ -105,7 +105,7 @@ normally-distributed data. Such parameter need to be estimated
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numerically by means of maximum-likelihood from the data.
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Let us demonstrate this approach by means of data that are drawn from a
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gamma distribution,
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gamma distribution.
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\begin{parts}
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\part Find out which \code{matlab} function computes the
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probability-density function of the gamma distribution.
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@ -123,7 +123,7 @@ gamma distribution,
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\part Compute and plot a properly normalized histogram of these
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random numbers.
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\part Find out which \code{matlab} function fit a distribution to a
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\part Find out which \code{matlab} function fits a distribution to a
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vector of random numbers according to the maximum-likelihood method.
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How do you need to use this function in order to fit a gamma
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distribution to the data?
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