Entropy estimate by a randomness criterion

We propose a new criterion for randomness of a word $x_{1}x_{2}\cdots x_{n}\in \mathbb{A}^{n}$ over a finite alphabet $\mathbb{A}$ defined by $$\begin{eqnarray}\unicode[STIX]{x1D6EF}^{n}(x_{1}x_{2}\cdots x_{n})=\mathop{\sum }_{\unicode[STIX]{x1D709}\in \mathbb{A}^{+}}\unicode[STIX]{x1D713}(|x_{1}x_{2}\cdots x_{n}|_{\unicode[STIX]{x1D709}}),\end{eqnarray}$$ where $\mathbb{A}^{+}=\bigcup _{k=1}^{\infty }\mathbb{A}^{k}$ is the set of non-empty finite words over $\mathbb{A}$, for $\unicode[STIX]{x1D709}\in \mathbb{A}^{k}$, $$\begin{eqnarray}|x_{1}x_{2}\cdots x_{n}|_{\unicode[STIX]{x1D709}}=\#\{i;~1\leq i\leq n-k+1,~x_{i}x_{i+1}\cdots x_{i+k-1}=\unicode[STIX]{x1D709}\},\end{eqnarray}$$ and for $t\geq 0$, $\unicode[STIX]{x1D713}(0)=0$ and $\unicode[STIX]{x1D713}(t)=t\log t~(t>0)$. This value represents how random the word $x_{1}x_{2}\cdots x_{n}$ is from the viewpoint of the block frequency. In fact, we define a randomness criterion as $$\begin{eqnarray}Q(x_{1}x_{2}\cdots x_{n})=(1/2)(n\log n)^{2}/\unicode[STIX]{x1D6EF}^{n}(x_{1}x_{2}\cdots x_{n}).\end{eqnarray}$$ Then, $$\begin{eqnarray}\lim _{n\rightarrow \infty }(1/n)Q(X_{1}X_{2}\cdots X_{n})=h(X)\end{eqnarray}$$ holds with probability 1 if $X_{1}X_{2}\cdots \,$ is an ergodic, stationary process over $\mathbb{A}$ either with a finite energy or $h(X)=0$, where $h(X)$ is the entropy of the process. Another criterion for randomness using $t^{2}$ instead of $t\log t$ has already been proposed in Kamae and Xue [An easy criterion for randomness. Sankhya A77(1) (2015), 126–152]. In comparison, our new criterion provides a better fit with the entropy. We also claim that our criterion not only represents the entropy asymptotically but also gives a good representation of the randomness of fixed finite words.