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otsfeatures (version 1.0.0)

conditional_probabilities: Computes the conditional probabilities of an ordinal time series

Description

conditional_probabilities returns a matrix with the conditional probabilities of an ordinal time series

Usage

conditional_probabilities(series, lag = 1, states)

Value

A matrix with the conditional probabilities.

Arguments

series

An OTS.

lag

The considered lag (default is 1).

states

A numerical vector containing the corresponding states.

Author

Ángel López-Oriona, José A. Vilar

Details

Given an OTS of length \(T\) with range \(\mathcal{S}=\{s_0, s_1, s_2, \ldots, s_n\}\) (\(s_0 < s_1 < s_2 < \ldots < s_n\)), \(\overline{X}_t=\{\overline{X}_1,\ldots, \overline{X}_T\}\), the function computes the matrix \(\widehat{\boldsymbol P}^c(l) = \big(\widehat{p}^c_{i-1j-1}(l)\big)_{1 \le i, j \le n+1}\), with \(\widehat{p}^c_{ij}(l)=\frac{TN_{ij}(l)}{(T-l)N_i}\), where \(N_i\) is the number of elements equal to \(s_i\) in the realization \(\overline{X}_t\) and \(N_{ij}(l)\) is the number of pairs \((\overline{X}_t, \overline{X}_{t-l})=(s_i,s_j)\) in the realization \(\overline{X}_t\).

References

weiss2019distanceotsfeatures

Examples

Run this code
matrix_cp <- conditional_probabilities(series = AustrianWages$data[[100]],
states = 0 : 5) # Computing the matrix of
# conditional probabilities for one series in dataset AustrianWages

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