Search Results for author: Alejandro Cuevas

Found 3 papers, 1 papers with code

Bayesian autoregressive spectral estimation

no code implementations5 Oct 2021 Alejandro Cuevas, Sebastián López, Danilo Mandic, Felipe Tobar

Autoregressive (AR) time series models are widely used in parametric spectral estimation (SE), where the power spectral density (PSD) of the time series is approximated by that of the \emph{best-fit} AR model, which is available in closed form.

Time Series Time Series Analysis

Gaussian process imputation of multiple financial series

no code implementations11 Feb 2020 Taco de Wolff, Alejandro Cuevas, Felipe Tobar

In Financial Signal Processing, multiple time series such as financial indicators, stock prices and exchange rates are strongly coupled due to their dependence on the latent state of the market and therefore they are required to be jointly analysed.

Imputation Time Series +1

MOGPTK: The Multi-Output Gaussian Process Toolkit

1 code implementation9 Feb 2020 Taco de Wolff, Alejandro Cuevas, Felipe Tobar

We present MOGPTK, a Python package for multi-channel data modelling using Gaussian processes (GP).

Gaussian Processes Imputation

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