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Yushu Li

Associate Professor
  • E-mailYushu.Li@uib.no
  • Phone+47 55 58 48 83+47 472 84 929
  • Visitor Address
    Allégaten 41
    Realfagbygget
    5007 Bergen
  • Postal Address
    Postboks 7803
    5020 Bergen

Time series econometrics  

Sparse Bayesian Learning

Wavelet methods

Statistical machine learning 

Statistical Surveillance

STAT250(V22 Cooperate with Pekka Parviainen):Monte Carlo Methods and Bayesian Statistics

STAT260 (H20,H21)/STATLEARN (H17,H18, H19), UIB: Statistical learning

STAT240 (V17,V21), UIB: Theory of Finance

STAT231 (H16,H20), UIB: Nonlife insurance mathematics

STAT111 (V16, V18), UIB: Statistiske metoder

STAT250 (H15), UIB: Monte Carlo methods in statistics

ECO403 (V15,V14), NHH: Time series analysis and prediction

MAT013 (H14), NHH:Matematisk statistikk

15. Yushu Li and Hyunjoo Kim Karlsson (2022) 

 Investigating the Asymmetric Behavior of Oil Price Volatility Using Support Vector Regression,  (Online 06 May 2022), Computational Economics.

14. 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

13. 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, pages 529–549.

12. Yushu Li and  Jonas Andersson (2019)

A Likelihood Ratio and Markov Chain Based Method to Evaluate Density Forecasting, (Online 17 May 2019), Journal of forecasting

11. 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 201810(8), 2792

10.  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

9.    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, 2015, 85(17), pp. 3468-3479

8.       Yushu Li (2015)

Estimate long memory causality relationship by wavelet method, Computational Economics, 2015, 45(4), pp. 531-544

7.       Yushu Li (2014)

Estimating and Forecasting APARCH-Skew-t Model by Wavelet Support Vector Machines, Journal of Forecasting, 2014, 33(4), pp. 259-269

6.       Yushu Li and Simon Reese (2014)

Wavelet improvement in turning point detection using a HMM model - from the aspects of cyclical identification and outlier correction, Computational Statistic,, 2014, 29(6), pp.1481-1496

5.      Yushu Li (2013)

 Wavelet Based Outlier Correction for Power Controlled Turning Point Detection in Surveillance Systems”, Economic modeling, 30, pp. 317-321

4.       Yushu Li and Shukur Ghazi (2013)

Testing for unit roots in panel data using wavelet ratio method, Computational Economics, 41, pp. 59–69

3.       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

2.       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, Issue 13, pp. 2385-2396

1.      Yushu Li and Shukur Ghazi (2010)

 “Testing for Unit Root Against LSTAR Models: Wavelet Improvement under GARCH Distortion”, Communications in Statistics, Simulation and Computation, 39, Issue 2 pp. 277 – 286

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Academic article
  • Show author(s) (2020). A simple wavelet-based test for serial correlation in panel data models. Empirical Economics.
  • Show author(s) (2019). Are Central Bankers Inflation Nutters? An MCMC Estimator of the Long-Memory Parameter in a State Space Model. Computational Economics. 1-21.
  • Show author(s) (2019). A likelihood ratio and Markov chain‐based method to evaluate density forecasting. Journal of Forecasting. 1-9.
  • Show author(s) (2018). The Causal Nexus between Oil Prices, Interest Rates, and Unemployment in Norway Using Wavelet Methods . Sustainability. 1-15.
  • Show author(s) (2017). An Analysis of Past World Market Prices of Feed and Milk and Predictions for the Future. Agribusiness. 175-193.
  • Show author(s) (2015). Testing for structural breaks in the presence of data perturbations: impacts and wavelet-based improvements. Journal of Statistical Computation and Simulation. 3468-3479.
  • Show author(s) (2014). Wavelet improvement in turning point detection using a hidden Markov model: from the aspects of cyclical identification and outlier correction. Computational statistics (Zeitschrift). 1481-1496.
  • Show author(s) (2014). Estimating and forecasting APARCH-Skew-t model by wavelet support vector machines. Journal of Forecasting. 259-269.
  • Show author(s) (2014). Estimate Long Memory Causality Relationship by Wavelet Method. Computational Economics. 531-544.
  • Show author(s) (2013). Wavelet Based Outlier Correction for Power Controlled Turning Point Detection in Surveillance Systems. Economic Modelling. 317-321.
  • Show author(s) (2011). inear and Nonlinear Causality Test in LSTAR Models: Wavelet Decomposition in Nonlinear Environment . Journal of Statistical Computation and Simulation. 1913-1925.
  • Show author(s) (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. 2385-2396.
  • Show author(s) (2011). Testing for unit roots in panel data using wavelet ratio method . Computational Economics. 1-11.
  • Show author(s) (2010). Testing for Unit Root Against LSTAR Models: Wavelet Improvement under GARCH Distortion . Communications in Statistics - Simulation and Computation. 277-286.
Report
  • Show author(s) (2015). Future world market prices of milk and feed looking into the crystal ball. 17. 17. .
  • Show author(s) (2014). Wavelet improvement in turning point detection using a Hidden Markov Model. 10. 10. .
  • Show author(s) (2014). Are Central Bankers Inflation Nutters? - A Bayesian MCMC Estimator of the Long Memory Parameter in a State Space Model. 38. 38. .
  • Show author(s) (2014). A simple wavelet-based test for serial correlation in panel data models. 11. 11. .
  • Show author(s) (2014). A Likelihood Ratio and Markov Chain Based Method to Evaluate Density Forecasting. 12. 12. .
Lecture
  • Show author(s) (2021). A Noise-Robust Fast Sparse Bayesian Learning Model.
  • Show author(s) (2019). A Likelihood Ratio and Markov Chain Based Method to Evaluate Density Forecasting.
  • Show author(s) (2018). Introduction to SVM and RVM.
Academic lecture
  • Show author(s) (2019). The Value of Turning-Point Detection for Optimal Investment .
  • Show author(s) (2019). Estimating APGARCH-Skew-t model by Wavelet Support Vector Machines.
  • Show author(s) (2019). A noise-robust Fast Sparse Bayesian Learning Model.
  • Show author(s) (2016). Testing for Structural Breaks in the Presence of Data Perturbations.
  • Show author(s) (2015). A Likelihood Ratio and Markov Chain Based Method to Evaluate Density Forecasting.
  • Show author(s) (2014). Some aspect in wavelet analysis, statistical surveillance and support vector machine.
  • Show author(s) (2014). A simple wavelet-based test for serial correlation in panel data models.
  • Show author(s) (2013). Use Wavelet Methods to Deal with Irregular and Large Time Series Data.

More information in national current research information system (CRIStin)

INVOLVED FUNDED Research PROJECT

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      

FUNDED 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

                                                                       

   

                                                                                                                        

(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. BentsenModel 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 HeimsæterA Dimensionality Reducing Extension of Bayesian Relevance Learning, Co-supervisor: Ingvild M. Helgøy

(V21 UIB) Arne L. WaagbøAPARCH Models Estimated by Support Vector Regression