Research groups
Research
Time series econometrics
Sparse Bayesian Learning
Wavelet methods
Statistical machine learning
Statistical Surveillance
Teaching
Lecturer and course responsible:
STAT250(V22 Cooperate with Pekka Parviainen):Monte Carlo Methods and Bayesian Statistics
STAT260(H20,H21,H23)/STATLEARN(H17,H18, H19): Statistical learning
STAT240 (V17,V21,V23), UIB: Theory of Finance
STAT231 (H16,H20,H22,H24), UIB: Nonlife insurance mathematics
STAT111 (V16, V18), UIB: Statistiske metoder (Bachelor level. Given in Norwegian)
STAT250 (H15), UIB: Monte Carlo methods in statistics
ECO403 (V15,V14), NHH: Time series analysis and prediction
MAT013 (H14), NHH:Matematisk statistikk (Bachelor level. Given in Norwegian)
External grading sensor (2017-):
ENE473 Real Options Analysis of Electricity Markets, NHH
BEA525 Financial Engineering in Energy Markets using Real Options, NHH
GRA 4136/41363 Predictive Analytics and Machine Learning/ Machine Learning for Business, BI OSLO
TMA4268 Statistisk læring, NTNU
TMA4900 Industriell matematikk /Datateknologi, masteroppgave, NTNU
IT3920/3903 Masteroppgave for MSIT/ Masteroppgave i informatikk: Kunstig intelligens, NTNU
Supervised Ph.D. project:
(June 2023, UIB) Ingvild M. Helgøy, Sparse Bayesian learning methods and statistical survival models
Supervised Master projects:
(V12 Lund University) Simon Reese: “Are tests for smooth structural change affected by data inaccuracies?”, Co-supervisor: Fredrik N G Andersson
(V15 NHH) Midtdal S. Tollefsen & Hans Thomas: "En analyse av regionale prisforskjeller i det norske boligmarkedet : en tidsserieanalyse 1993-2013" , Co-supervisor: Ola Honningdal Grytten
(V18 UIB) Therese Grindheim: "Time Series: Forecasting and Evaluation Methods With Concentration On Evaluation Methods for Density Forecasting"
(H18 UIB) Victoria Foster: Empirical time series analysis with focus on wavelet methods and economic data from Norway
(V19 UIB) Francine D. D. Rogowski: A Comprehensive Study of Kernels and Feature Selection in Support Vector Regression, Co-supervisor: Bjørn Gunnar Hansen
(H19 UIB) Fredrik H. Bentsen: Model Construction with Support Vector Machines and Gaussian Processes through Kernel Search
(V20 UIB) Elise F.F. Isaksen: Generative and Discriminative Classifiers: from Theory to Implementation
(V21 UIB) Sandra Heimsæter: A Dimensionality Reducing Extension of Bayesian Relevance Learning, Co-supervisor: Ingvild M. Helgøy
(V21 UIB) Arne L. Waagbø: APARCH Models Estimated by Support Vector Regression
(V23 UIB) Mathias E. Ostnes: Modern Variable Selection Methods with Empirical Analysis,Co-supervisor: Ingvild M. Helgøy
2017-2022: 6 bachelor thesis (STAT292 UIB Project in Statistics)
Publications
Academic article
- Helgøy, Ingvild Margrethe; Skaug, Hans Julius; Li, Yushu (2024). Sparse Bayesian learning using TMB (Template Model Builder). (external link)
- Hansen, Bjørn Gunnar; Li, Yushu; Sun, Ruohao et al. (2024). Forecasting milk delivery to dairy – How modern statistical and machine learning methods can contribute. (external link)
- Helgøy, Ingvild Margrethe; Li, Yushu (2023). A Bayesian Lasso based sparse learning model. (external link)
- Li, Yushu; Karlsson, Hyunjoo Kim (2022). Investigating the Asymmetric Behavior of Oil Price Volatility Using Support Vector Regression. (external link)
- Li, Yushu; Andersson, Fredrik (2020). A simple wavelet-based test for serial correlation in panel data models. (external link)
- Li, Yushu; Andersson, Lars Jonas (2019). A likelihood ratio and Markov chain‐based method to evaluate density forecasting. (external link)
- Andersson, Fredrik N. G.; Li, Yushu (2019). Are Central Bankers Inflation Nutters? An MCMC Estimator of the Long-Memory Parameter in a State Space Model. (external link)
- Karlsoon, Hyunjoo Kim; Li, Yushu; Shukur, Ghazi (2018). The Causal Nexus between Oil Prices, Interest Rates, and Unemployment in Norway Using Wavelet Methods . (external link)
- Hansen, Bjørn Gunnar; Li, Yushu (2017). An Analysis of Past World Market Prices of Feed and Milk and Predictions for the Future. (external link)
- Reese, Simon; Li, Yushu (2015). Testing for structural breaks in the presence of data perturbations: impacts and wavelet-based improvements. (external link)
- Li, Yushu (2014). Estimating and forecasting APARCH-Skew-t model by wavelet support vector machines. (external link)
- Li, Yushu; Reese, Simon (2014). Wavelet improvement in turning point detection using a hidden Markov model: from the aspects of cyclical identification and outlier correction. (external link)
- Li, Yushu (2014). Estimate Long Memory Causality Relationship by Wavelet Method. (external link)
- Li, Yushu (2013). Wavelet Based Outlier Correction for Power Controlled Turning Point Detection in Surveillance Systems. (external link)
- Li, Yushu; Shukur, Ghazi (2011). Wavelet Improvement of the Over-rejection of Unit root test under GARCH errors: An Application to Swedish Immigration Data” . (external link)
- Li, Yushu; Shukur, Ghazi (2011). inear and Nonlinear Causality Test in LSTAR Models: Wavelet Decomposition in Nonlinear Environment . (external link)
- Li, Yushu; Shukur, Ghazi (2011). Testing for unit roots in panel data using wavelet ratio method . (external link)
- Li, Yushu; Shukur, Ghazi (2010). Testing for Unit Root Against LSTAR Models: Wavelet Improvement under GARCH Distortion . (external link)
Projects
Involved Research Projects
2018-2021 “Strategic Risk Adoption in Real Options under Multi-Horizon Regime Switching and Uncertainty” (project number 274569). Funded by Finance Market Fund, Norwegian research council, project leader Yushu Li.
2020- 2023 “Assimilating 4D Seismic Data: Big Data into Big Models”. Funded by Research Council of Norway Petromaks-2, project leader Dean Oliver, NORCE.
2021- “Digital technology for personalised management and therapy of hypertensive nephropathy”. Funded by Helse Vest, project leader Hans-Peter Marti, Department of Medicine, UIB
2021- 2022 “Predicting Milk Production with Automated Milking System Data”. Funded by Forskningsmidlene for jordbruk og matindustri, project leader Ruohao Sun, Tine SA
Educational Project
2022-2023 Utvikling av felleskurs og deling og utvikling av undervisning og læring i statistikk/ datascience/ maskinlæring, funded by UHR-MNT. Reference no. of commitment letter: 21/135-9, project responsible person Yushu Li