Time series econometrics  

Sparse Bayesian Learning

Wavelet methods

Statistical machine learning 

Statistical Surveillance

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)

Academic article

• 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; Skaug, Hans Julius; Li, Yushu (2024). Sparse Bayesian learning using TMB (Template Model Builder). (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). Estimate Long Memory Causality Relationship by Wavelet Method. (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 (2013). Wavelet Based Outlier Correction for Power Controlled Turning Point Detection in Surveillance Systems. (external link)
• Li, Yushu; Shukur, Ghazi (2011). Testing for unit roots in panel data using wavelet ratio method. (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 (2010). Testing for Unit Root Against LSTAR Models: Wavelet Improvement under GARCH Distortion. (external link)

See a complete overview of publications in Cristin.

• Ingvild M. Helgøy, Hans J. Skaug, Yushu Li (2024)
  • Sparse Bayesian learning using TMB (Template Model Builder), Statistics and Computing, Volume 34, article number 173, Springer
• Bjørn Gunnar Hansen, Yushu Li, Ruohao Sun, Ingunn Schei (2024)
  • Forecasting milk delivery to dairy – How modern statistical and machine learning methods can contribute, (on line 15 Feb.2024), Expert Systems with Applications, Elsevier
• Ingvild M. Helgøy and Yushu Li (2023)
  • A Bayesian Lasso based Sparse Learning Model. (Online, 26 Oct 2023), 
    Communications in Statistics - Simulation and Computation, Taylor & Francis
• Yushu Li and Hyunjoo Kim Karlsson (2022)
  • Investigating the Asymmetric Behavior of Oil Price Volatility Using Support Vector Regression,  (Online, May 6, 2022), Computational Economics, Springer
• Yushu Li and Fredrik N.G. Andersson (2021)
  • A simple wavelet-based test for serial correlation in panel data models, Empirical Economics, 60, pp. 2351-2363 , Springer
• Fredrik N.G. Andersson and Yushu Li (2020)
  • Are Central Bankers Inflation Nutters? An MCMC Estimator of the Long-Memory Parameter in a State Space Model, Computational Economics, 55, pp. 529-549, Springer
• Yushu Li and Jonas Andersson (2019)
  • A Likelihood Ratio and Markov Chain Based Method to Evaluate Density Forecasting (Online, May 17, 2019), Journal of Forecasting,  Wiley
• Hyunjoo Kim Karlsson, Yushu Li and Ghazi Shukur (2018)
  • The Causal Nexus between Oil Prices, Interest Rates, and Unemployment in Norway Using Wavelet Methods, Sustainability, 10(8), p. 2792
• Bjørn Gunnar Hansen and Yushu Li (2017)
  • An Analysis of Past World Market Prices of Feed and Milk and Predictions for the Future, Agribusiness, 33(2), pp. 175-193, Wiley
• Simon Reese and Yushu Li (2015)
  • Testing for structural breaks in the presence of data perturbations: impacts and wavelet-based improvements, Journal of Statistical Computation and Simulation, 85(17), pp. 3468-3479, Taylor & Francis
• Yushu Li (2015)
  • Estimate Long Memory Causality Relationship by Wavelet Method, Computational Economics, 45, pp. 531-544, Springer
• Yushu Li (2014)
  • Estimating and Forecasting APARCH-Skew-t Model by Wavelet Support Vector Machines, Journal of Forecasting, 33(4), pp. 259-269, Wiley
• Yushu Li and Simon Reese (2014)
  • Wavelet improvement in turning point detection using a hidden Markov model: from the aspects of cyclical identification and outlier correction, Computational Statistics, 29, pp.1481-1496, Springer
• Yushu Li (2013)
  • Wavelet based outlier correction for power controlled turning point detection in surveillance systems, Economic Modeling, 30, pp. 317-321, Elsevier
• Yushu Li and Shukur Ghazi (2013)
  • Testing for Unit Roots in Panel Data Using a Wavelet Ratio Method, Computational Economics, 41, pp. 59-69, Springer
• Yushu Li and Shukur Ghazi (2011)
  • Linear and Nonlinear Causality Test in LSTAR Models: Wavelet Decomposition in Nonlinear Environment, Journal of Statistical Computation and Simulation, 81(12), pp.1913-1925, Taylor & Francis
• Yushu Li and Shukur Ghazi (2011)
  • Wavelet Improvement of the Over-Rejection of Unit Root Test Under GARCH Errors: An Application to Swedish Immigration Data, Communications in Statistics, Theory and Methods, 40(13), pp. 2385-2396, Taylor & Francis
• Yushu Li and Shukur Ghazi (2010)
  • Testing for Unit Root Against LSTAR Model: Wavelet Improvement Under GARCH Distortion, Communications in Statistics, Simulation and Computation, 39(2), pp. 277-286, Taylor & Francis

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