# name for $\underset{x}{\operatorname{argmin}} \displaystyle\sum\limits_{i=1}^n |x_i - x|$

Given a real-valued data set $x_1, \dots, x_n$, what do you call the quantity

$$\underset{x}{\operatorname{argmin}} \displaystyle\sum\limits_{i=1}^n |x_i - x|$$

This seems like a pretty basic thing to ask for. For example, in a game in which I have to guess the number you're thinking of, and I have to pay you the difference between what I guessed and what you were thinking, the optimal strategy is to guess this quantity. This game seems like a decent model for, say, predicting the stock market and buying and selling accordingly.

I realize that the quantity is not in general unique, but that doesn't mean it isn't useful. Why haven't I heard more about this quantity? Are there any applications in which it is used?

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In your guessing game, wouldn't you want to minimize, rather than maximize, the sum of differences? – Sridhar Ramesh Jul 2 '11 at 4:38
Yes, it should be the minimum (the maximum is infinite). This actually gives the median of $x_1,\dots,x_n$. Specifically, suppose $x_1 < x_2 < \dots < x_n$. If $n=2k+1$, then $x=x_{k+1}$ is the unique minimizer. If $n=2k$, then every $x$ from $x_k$ to $x_{k+1}$ is a minimizer, and there are no others. – Henry Cohn Jul 2 '11 at 4:59
I would call this the "empirical risk minimizing action under absolute loss". This is consistent with David Harris' answer below. – R Hahn Jul 2 '11 at 10:32

The value of $x$ that satisfies this is the median of $x_i$. It minimizes $L_1$ loss.
Note that the mean of $x_i$ is the value of $x$ minimizing $\sum(x_i - x)^2$, the $L_2$ loss.