Builds the 
  coincident profile proposed by Martinez, W and Nieto, Fabio H and Poncela, P (2016) 
  <doi:10.1016/j.spl.2015.11.008>.
  This methodology studies the relationship between a couple of
  time series based on the the set of turning points of each
  time series. The coincident profile establishes if two time
  series are coincident, or one of them leads the second.

A comprehensive high-level package, for composite indicator construction and analysis. It is a "development environment"
    for composite indicators and scoreboards, which includes utilities for construction (indicator selection, denomination, imputation,
    data treatment, normalisation, weighting and aggregation) and analysis (multivariate analysis, correlation plotting, short cuts for
    principal component analysis, global sensitivity analysis, and more). A composite indicator is completely encapsulated inside a single
    hierarchical list called a "coin". This allows a fast and efficient work flow, as well as making quick copies, testing methodological variations and making comparisons.
    It also includes many plotting options, both statistical (scatter plots, distribution plots) as well as for presenting results.

A unified toolkit for cointegration testing including
    Fourier-based cointegration tests (FADL, FEG, FEG2, Tsong) that
    accommodate smooth structural breaks via flexible Fourier terms, and
    panel CADF cointegration tests with structural breaks using the Common
    Correlated Effects (CCE) estimator following Banerjee, Arcabic and Lee
    (2017) <doi:10.1016/j.econmod.2017.03.004>, Tsong, Lee, Tsai and Hu
    (2016) <doi:10.1007/s00181-015-1028-6>, and Banerjee and
    Carrion-i-Silvestre (2025) <doi:10.1080/07350015.2024.2327844>.

We propose a consistent monitoring procedure to detect a
    structural change from a cointegrating relationship to a spurious
    relationship. The procedure is based on residuals from modified least
    squares estimation, using either Fully Modified, Dynamic or Integrated
    Modified OLS. It is inspired by Chu et al. (1996) <DOI:10.2307/2171955> in
    that it is based on parameter estimation on a pre-break "calibration" period
    only, rather than being based on sequential estimation over the full sample.
    See the discussion paper <DOI:10.2139/ssrn.2624657> for further information.
    This package provides the monitoring procedures for both the cointegration
    and the stationarity case (while the latter is just a special case of the
    former one) as well as printing and plotting methods for a clear
    presentation of the results.