Given an OTS of length \(T\) with range \(\mathcal{S}=\{s_0, s_1, \ldots, s_n\}\),
\(\overline{X}_t=\{\overline{X}_1,\ldots, \overline{X}_T\}\), and
the cumulative binarized time series, which is defined as
\(\overline{\boldsymbol Y}_t=\{\overline{\boldsymbol Y}_1, \ldots, \overline{\boldsymbol Y}_T\}\),
with \(\overline{\boldsymbol Y}_k=(\overline{Y}_{k,0}, \ldots, \overline{Y}_{k,n-1})^\top\)
such that \(\overline{Y}_{k,i}=1\) if \(\overline{X}_k\leq s_i\) (\(k=1,\ldots,T,
, i=0,\ldots,n-1\)), the function computes the estimated average \(\widehat{\Psi}(l)^c=\frac{1}{n^2}\sum_{i,j=0}^{n-1}\widehat{\psi}_{ij}(l)^2\),
where \(\widehat{\psi}_{ij}(l)\) is the estimated correlation
\(\widehat{Corr}(Y_{t, i}, Y_{t-l, j})\), \(i,j=0, 1,\ldots,n-1\). If features = TRUE, the function
returns a matrix whose components are the quantities \(\widehat{\psi}_{ij}(l)\),
\(i,j=0,1, \ldots,n-1\).