NICDA Research Group
NICDA Research Group
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Pedro Galeano
Associate Professor
Carlos III University of Madrid
Latest
Detecting outliers in high dimensional time series by dynamic factor models
Structured factor copulas for modeling the systemic risk of European and United States banks
Testing for linearity in scalar on function regression with responses missing at random
Sequential detection of parameter changes in dynamic conditional correlation models
Una aplicación del análisis de series temporales funcionales a los precios horarios de la electricidad en el mercado MIBEL
A robust procedure to build dynamic factor models with cluster structure
Copula stochastic volatility in oil returns: Approximate Bayesian computation with volatility prediction
Las nuevas oportunidades de big data para las instituciones financieras
Variational inference for high dimensional structured factor copulas
Data science, big data and statistics
Estimation, imputation and prediction for the functional linear model with scalar response with responses missing at random
Parallel Bayesian inference for high-dimensional dynamic factor copulas
Particle learning for Bayesian semi-parametric stochastic volatility model
Rejoinder on: Data science, big data and statistics
Dating multiple change points in the correlation matrix
Functional principal component regression: An overview and a comparative study
Parameter estimation of the functional linear model with scalar response with responses missing at random
A Bayesian non-parametric approach to asymmetric dynamic conditional correlation model with applications to portfolio selection
Functional outlier detection by a local depth with application to NOx levels
Monitoring multivariate variance changes
Bayesian inference methods for univariate and multivariate GARCH models: A survey
The Mahalanobis distance for functional data with applications to classification
A semiparametric Bayesian approach to the analysis of financial time series with applications to value at risk estimation
Multiple break detection in the correlation structure of random variables
Spatial depth-based classification with functional data
Finding outliers in linear and nonlinear time series
Monitoring correlation change in a sequence of random variables
Additive outlier detection in seasonal ARIMA models by a modified Bayesian information criterion
Comments on: Some recent theory for autoregressive count time series
Measures of influence in the functional linear model with scalar response
Shifts in individual parameters of a GARCH model
The Gaussian mixture conditional correlation model: Parameter estimation, value at risk calculation and portfolio selection
An unified approach to model selection, discrimination, goodness of fit and outliers in time series
Influence in the functional linear model with scalar response
Outlier detection in functional data by depth measures with application to identify abnormal NOx levels
A functional analysis of NOx levels: Location and scale estimation and outlier detection
Bayesian estimation of the Gaussian mixture GARCH model
Covariance changes detection in multivariate time series
Improved model selection criteria for SETAR time series models
On the connection between model selection criteria and quadratic discrimination in time series models
The use of cumulative sums for detection of changepoints in the rate parameter of a Poisson process
Outlier detection in multivariate time series by projection pursuit
A note on prediction and interpolation errors in time series
Multivariate analysis in vector time series
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