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mlmts (version 1.1.2)

dis_qcd: Constructs a pairwise distance matrix based on the quantile cross-spectral density (QCD)

Description

dis_qcd returns a pairwise distance matrix based on the dissimilarity introduced by lopez2021quantile;textualmlmts.

Usage

dis_qcd(X, levels = c(0.1, 0.5, 0.9), freq = NULL, features = FALSE, ...)

Value

If features = FALSE (default), returns a distance matrix based on the distance \(d_{QCD}\). Otherwise, the function returns a dataset of feature vectors, i.e., each row in the dataset contains the features employed to compute the distance \(d_{QCF}\).

Arguments

X

A list of MTS (numerical matrices).

levels

The set of probability levels.

freq

Vector of frequencies in which the smoothed CCR-periodograms must be computed. If freq=NULL (default), the set of Fourier frequencies is considered.

features

Logical. If features = FALSE (default), a distance matrix is returned. Otherwise, the function returns a dataset of feature vectors.

...

Additional parameters for the function. See smoothedPG.

Author

Ángel López-Oriona, José A. Vilar

Details

Given a collection of MTS, the function returns the pairwise distance matrix, where the distance between two MTS \(\boldsymbol X_T\) and \(\boldsymbol Y_T\) is defined as $$d_{QCF}(\boldsymbol X_T, \boldsymbol Y_T)=\Bigg[\sum_{j_1=1}^{d}\sum_{j_2=1}^{d}\sum_{i=1}^{r} \sum_{i'=1}^{r}\sum_{k=1}^{K}\Big(\Re\big({\widehat G_{j_1,j_2}^{\boldsymbol X_T}(\omega_{k}, \tau_{i}, \tau_{i^ {\prime}})}\big) -\Re\big({\widehat G_{j_1,j_2}^{\boldsymbol Y_T}(\omega_{k}, \tau_{i}, \tau_{i^ {\prime}})\big)}\Big)^2+$$ $$\sum_{j_1=1}^{d}\sum_{j_2=1}^{d}\sum_{i=1}^{r}\sum_{i'=1}^{r}\sum_{k=1}^{K}\Big(\Im\big({\widehat G_{j_1,j_2} ^{\boldsymbol X_T}(\omega_{k}, \tau_{i}, \tau_{i^ {\prime}})}\big) -\Im\big({\widehat G_{j_1,j_2}^{\boldsymbol Y_T}(\omega_{k}, \tau_{i}, \tau_{i^ {\prime}})\big)}\Big)^2\Bigg]^{1/2},$$ where \({\widehat G_{j_1,j_2}^{\boldsymbol X_T}(\omega_{k}, \tau_{i}, \tau_{i^ {\prime}})}\) and \({\widehat G_{j_1,j_2}^{\boldsymbol Y_T}(\omega_{k}, \tau_{i}, \tau_{i^ {\prime}})}\) are estimates of the quantile cross-spectral densities (so-called smoothed CCR-periodograms) with respect to the variables \(j_1\) and \(j_2\) and probability levels \(\tau_i\) and \(\tau_{i^\prime}\) for series \(\boldsymbol X_T\) and \(\boldsymbol Y_T\), respectively, and \(\Re(\cdot)\) and \(\Im(\cdot)\) denote the real part and imaginary part operators, respectively.

References

lopez2021quantilemlmts

See Also

dis_qcf

Examples

Run this code
toy_dataset <- AtrialFibrillation$data[1 : 4] # Selecting the first 4 MTS from the
# dataset AtrialFibrillation
distance_matrix <- dis_qcd(toy_dataset) # Computing the pairwise
# distance matrix based on the distance dis_qcd
distance_matrix <- dis_qcd(toy_dataset, levels = c(0.4, 0.8)) # Changing
# the probability levels to compute the QCD-based estimators
distance_matrix <- dis_qcd(toy_dataset, freq = 0.5) # Considering only
# a single frequency for the computation of d_qcd
feature_dataset <- dis_qcd(toy_dataset, features = TRUE) # Computing
# the corresponding dataset of features

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