* Return the array of supernode-to-column mapping */

r""" Calculate the Average Drawdown (ADD) of a returns series using uncompounded cumulative returns. .. math:: \text{ADD}(X) = \f

r""" Calculate the Average Drawdown (ADD) of a returns series using cumpounded cumulative returns. .. math:: \text{ADD}(X) = \fra

r""" Calculate the Conditional Drawdown at Risk (CDaR) of a returns series using uncompounded cumulative returns. .. math:: \text

r""" Calculate the Conditional Drawdown at Risk (CDaR) of a returns series using cumpounded cumulative returns. .. math:: \text{C

r""" Calculate the CVaR range of a returns series. Parameters ---------- X : np.array Returns series, must have Tx1 size.

r""" Calculate the Conditional Value at Risk (CVaR) of a returns series. .. math:: \text{CVaR}_{\alpha}(X) = \text{VaR}_{\alpha}(X) +

r""" Calculate the Drawdown at Risk (DaR) of a returns series using uncompounded cumulative returns. .. math:: \text{DaR}_{\alpha

r""" Calculate the Drawdown at Risk (DaR) of a returns series using cumpounded cumulative returns. .. math:: \text{DaR}_{\alpha}(

r""" Calculate the Entropic Drawdown at Risk (EDaR) of a returns series using uncompounded cumulative returns. .. math:: \text{ED

r""" Calculate the Entropic Drawdown at Risk (EDaR) of a returns series using cumpounded cumulative returns. .. math:: \text{EDaR

r""" Calculate the CVaR range of a returns series. Parameters ---------- X : np.array Returns series, must have Tx1 size.

r""" Calculate the p-th Root of Even Moment of order 2 * p of a returns series. .. math:: \text{EM}_{p}(X) = \left [ \frac{1}{T}\sum_

r""" Calculate the p-th Root of Semi Even Moment of order 2 * p of a returns series. .. math:: \text{ESM}_{p}(X) = \left [ \frac{1}{T

r""" Calculate the Gini Mean Difference (GMD) of a returns series. Parameters ---------- X : np.array Returns series, must ha

r""" Calculate the Square Root Kurtosis of a returns series. .. math:: \text{Kurt}(X) = \left [ \frac{1}{T}\sum_{t=1}^{T} (X_

r""" Calculate the Mean Absolute Deviation (MAD) of a returns series. .. math:: \text{MAD}(X) = \frac{1}{T}\sum_{t=1}^{T} | X

r""" Calculate the Maximum Drawdown (MDD) of a returns series using uncompounded cumulative returns. .. math:: \text{MDD}(X) = \m

r""" Calculate the Maximum Drawdown (MDD) of a returns series using cumpounded cumulative returns. .. math:: \text{MDD}(X) = \max

PopBack removes and returns the last elements in the queue.

r""" Calculate the range of a returns series. Parameters ---------- X : np.array Returns series, must have Tx1 size. Rai

r""" Calculate the Relativistic Drawdown at Risk (RLDaR) of a returns series using uncompounded cumulative returns. I recommend only use this

r""" Calculate the Relativistic Drawdown at Risk (RLDaR) of a returns series using compounded cumulative returns. I recommend only use this fu

r""" Calculate the CVaR range of a returns series. Parameters ---------- X : np.array Returns series, must have Tx1 size.

r""" Calculate the Semi Deviation of a returns series. .. math:: \text{SemiDev}(X) = \left [ \frac{1}{T-1}\sum_{t=1}^{T} \min

r""" Calculate the Semi Square Root Kurtosis of a returns series. .. math:: \text{SemiKurt}(X) = \left [ \frac{1}{T}\sum_{t=1}^{T}

r""" Calculate the Tail Gini of a returns series. Parameters ---------- X : np.array Returns series, must have Tx1 size.

r""" Calculate the Tail Gini range of a returns series. Parameters ---------- X : np.array Returns series, must have Tx1 size

r""" Calculate the Ulcer Index (UCI) of a returns series using uncompounded cumulative returns. .. math:: \text{UCI}(X) =\sqrt{\f

r""" Calculate the Ulcer Index (UCI) of a returns series using cumpounded cumulative returns. .. math:: \text{UCI}(X) =\sqrt{\fra

r""" Calculate the VaR range of a returns series. Parameters ---------- X : np.array Returns series, must have Tx1 size.

r""" Calculate the Worst Realization (WR) or Worst Scenario of a returns series. .. math:: \text{WR}(X) = \max(-X) Parameters

\brief Adjoint (conjugate transpose) of the Householder sequence. */

* Empty the pointer list */

\sa MatrixBase::coeff() * \warning the coordinates must fit into the referenced triangular part */

r""" Generate a correlation matrix from a covariance matrix cov. Parameters ---------- cov : DataFrame of shape (n_assets, n_assets)

r""" Calculate the covariance matrix using the selected method. Parameters ---------- X : DataFrame of shape (n_samples, n_assets)

\returns the size of the main diagonal, which is min(rows(),cols()). * \sa rows(), cols(), SizeAtCompileTime. */

\sa MatrixBase::fill() */

\returns the first element \f$ a_0 \f$ in the sequence */

\returns The value of the third angle. */