I am reading a natural language processing paper and I came across this expression. I don't know what it means. Especially the unif part.
$$m_i \sim \operatorname{unif}\{1,n\}\text{ for } i = 1 \text{ to } k$$
I am reading a natural language processing paper and I came across this expression. I don't know what it means. Especially the unif part.
$$m_i \sim \operatorname{unif}\{1,n\}\text{ for } i = 1 \text{ to } k$$
It means you have $k$ random variables, $m_1, m_2, \ldots , m_k$, each of which was chosen from a uniform distribution with extreme values $1$ and $n$. It is fundamentally ambiguous as to whether the distribution is discrete or continuous. (Check your source.)
Example: if $k = 3$ and $n = 5$, you could have...
...in the continuous case:
$m_1 = 2.938, m_2 = 1.155, m_3 = 4.076$.
... and in discrete case:
$m_1 = 4, m_2 = 5, m_3 = 1$.
Given your source is about natural language processing having (discrete) words, I suspect (but don't know) that the latter is the case.