A novel simulation method allowing for generating a wide range of simulated data, accompanied by an R package ‘specsimfts’.
Author: Tomas Rubin
Yield curve and macroeconomy interaction: evidence from the non-parametric functional lagged regression approach
In my first single-author publication I applied the tools I developed in my core PhD research to yield curve modelling.
Sparsely Observed Functional Time Series: Estimation and Prediction
Published in Electronic Journal of Statistics (2020)
Functional Lagged Regression with Sparse Noisy Observations
To appear in Journal of Time Series Analysis
European Meeting of Statisticians (EMS 2019)
In July 2019 I had the opportunity to travel to Palermo, Italy, to give a talk at the European Meeting of Statisticians, the largest statistics conference in Europe. In my talk entitled “Sparsely observed functional time series: estimation and prediction” I spoke about my first paper carrying the same name.
Doctoral day, Fribourg (2019)
The colleagues from Fribourg organised Doctoral day in June 2019 for the PhD students of the universities in western Switzerland (Conférence universitaire de Suisse occidentale, CUSO). I gave a talk on my core research around Sparsely observed functional time series.
Workshop on Multivariate Data Analysis (CRoNoS & MDA 2019)
In April 2019 I travelled to Limassol, the Republic of Cyprus, where I attended a workshop on multivariate data analysis. This workshop was the first conference where I’ve given a talk.
Workshop “New Developments in Econometrics and Time series” (2018)
In September 2018 I had chance to follow my PhD supervisor, Victor Panaretos, to Copenhagen, Denmark, and attend this workshop and listen to the presentations of leading experts on time series analysis and stochastic processes.
Summer Course on Functional Data Analysis (2018)
In September 2018 I flew to Iași, Romania, to take part in the 2nd CRoNoS Summer Course on Functional Data Analysis. I followed two summer school courses and listened to some conference talks.
Machine learning summer school (2017)
In June 2017 I travelled to Tübingen, Germany, to follow two weeks long series of lectures in machine learning. The speakers covered topics including deep learning, reinforcement learning, causality, network analysis, optimisation, Bayesian inference and much more.