  We study how to verify specific frequency distributions when we observe a
stream of $N$ data items taken from a universe of $n$ distinct items. We
introduce the \emph{relative Fr\'echet distance} to compare two frequency
functions in a homogeneous manner. We consider two streaming models: insertions
only and sliding windows. We present a Tester for a certain class of functions,
which decides if $f $ is close to $g$ or if $f$ is far from $g$ with high
probability, when $f$ is given and $g$ is defined by a stream. If $f$ is
uniform we show a space $\Omega(n)$ lower bound. If $f$ decreases fast enough,
we then only use space $O(\log^2 n\cdot \log\log n)$. The analysis relies on
the Spacesaving algorithm \cite{MAE2005,Z22} and on sampling the stream.
