CHOLESKY STOCHASTIC VOLATILITY MODELS FOR HIGH-DIMENSIONAL TIME SERIES

Addressing partial volume effects using intra-subject locally adjusted cerebral blood flow images. Dynamic matrix-variate graphical models Carvalho, Carlos M. N1 Extreme values Sunday The variance-frequency decomposition as an instrument for the identification of SVAR models. Quantile co-movement in financial markets. On the properties of sign estimators derived from hard thresholded lasso and hard thresholded basis pursuit. Confidence regions for Pareto parameters from single and independent samples.

D2 Financial networks Friday How to make the most of a contaminated multivariate sample Session EO Room: F1 Change points analysis and statistical inference for high dimensional data Sunday L1 Soft clustering Saturday New insights from tail-index estimates Session CO Room: Consumers’ perception of inflation in inflationary and deflationary environment. Classification of competing risk outcomes using transition biomarkers.

Revealing the joint mechanisms in traditional data linked with big data. A computationally efficient algorithm for random effects selection in linear mixed models.

E1 Contributions in non- and semi-parametric methods Saturday Macro uncertainty and the term structure of the risk premium. colatility

M1 Recent advances on functional data analysis and applications Sunday Q2 Bayesian modelling and computation Saturday Disagreement in consumer inflation expectations. C1 On recent development about time series and spectral analysis Sunday Application of the second order Gaussian kinematic formula to CMB data analysis.

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On the use of latent variables to extend Gaussian mixture models. D2 Energy economics Saturday A correction for regression discontinuity designs with group-specific mismeasurement of the running variable.

A2 Contributions in forecasting I Saturday The influence of winning stocks in size portfolios Session CO Room: Q1 Recent advances in robust modelling Saturday Martinez HernandezA. Inference in instrumental variables models with heteroskedasticity and many instruments. C1 Contributions in Bayesian methods Saturday I1 Flexible parametric distributions: M2 Macroeconomic uncertainty Sunday C2 Advances in credit risk modelling Saturday A general class of score-driven smoothers.

Additive semiparametric framework for land use regression. A convolutional neural network approach. Our modeling approach is chosen to allow for parallel computation and we show how to optimally seriess the computations across processors.

Aula B Large-scale and complex data analysis Saturday Hierarchical models for rater agreement and the evergreen kappa statistic.

Sixth Brazilian Conference on SMIF

P1 Shrinkage methods for analyzing complex data Friday Aula C Robust machine learning Saturday Short-term predictability and tike cross-section of stock returns. Bin Abdul MajidC. High-dimensional Gaussian graphical model for network-linked data.

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On the estimation of the Phillips curve for the Russian economy. Detection of non-null effects in linear models for sparse mixtures.

Cholesky Stochastic Volatility Models for High-Dimensional Time Series

Easily parallelizable and distributable class of algorithms for structured sparsity, with optimal acceleration. Posterior contraction rates for Bayesian functional linear regression. Permanent link to this document https: Aula 5 Recent advances in complex data analysis Saturday F1 Dimension reduction and high-dimensional supervised learning Saturday