Dr. rer. nat. Boris Aleksandrov

Raum:

1371

Telefon:

+49-40-6541-3608

E-Mail:

aleksanb (at) hsu-hh.de

Besucheranschrift

Helmut-Schmidt-Universität

Gebäude H1

Holstenhofweg 85

22043 Hamburg

Postanschrift

Dr. Boris Aleksandrov

Fächergruppe Mathematik/Statistik

Helmut-Schmidt-Universität

Postfach 700822

22008 Hamburg

Publikationen:

• Aleksandrov, Weiß, Jentsch (2021)
  Aleksandrov, B., Weiß, C.H., Jentsch, C.: Goodness-of-Fit Tests for Poisson Count Time Series based on the Stein-Chen Identity.
  Statistica Neerlandica, 76(1), pp. 35-64, 2022.
• Weiß & Aleksandrov (2020)
  Weiß, C.H., Aleksandrov, B.: Computing (Bivariate) Poisson Moments using Stein–Chen Identities.
  Accepted for publication in The American Statistician, 2020.
• Aleksandrov & Weiß (2020)
  Aleksandrov, B., Weiß, C.H.: Testing the Dispersion Structure of Count Time Series Using Pearson Residuals.
  AStA Advances in Statistical Analysis 104(3), pp. 325-361, 2020
• Weiß, Scherer, Aleksandrov, Feld (2020)
  Weiß, C.H., Scherer, L., Aleksandrov, B., Feld, M.H.-J.M.: Checking Model Adequacy for Count Time Series by Using Pearson Residuals.
  Journal of Time Series Econometrics 12(1), 20180018, 2020
• Aleksandrov & Weiß (2020)
  Aleksandrov , B. &  Weiß, C.H., Parameter estimation and diagnostic tests for INMA(1) processes.
  TEST (An Official Journal of the Spanish Society of Statistics and Operations Research) 29(1), pp. 196-232, 2020
• Aleksandrov (2019)
  Aleksandrov, B., A Negative-Binomial Index Considering Dispersion and Zero Probability.
  Published for the conference book, ’14th Workshop on Stochastic Models, Statistics and their Application; SMSA 2019′, 2019.
• Weiß, C.H., Aleksandrov, B. (2019)
  Weiß, C.H., Aleksandrov, B., Model diagnostics for Poisson INARMA processes using bivariate dispersion indexes.  Journal of Statistical Theory and Practice, 2019.

Vorträge:

• Pearson residuals for checking conditional dispersion in count time series (15. Doktorandentreffen Stochastik)
• Checking Model Adequacy for Count Time Series by Using Pearson Residuals (The 14th Workshop on Stochastic Models, Statistics and their Application (SMSA) ,March 6th to 8th, 2019 at TU Dresden.)
• Parameter Estimation and Diagnostic Tests for INMA(1) Processes (13th German Probability and Statistics Days 2018 – Freiburger Stochastik-Tage)
• Goodness-of-Fit Tests for Poisson Count Time Series based on theStein–Chen Identity (Doktorandentreffen LMU dts 2021)
• Novel Goodness-of-Fit Tests for Binomial Count Time Series (GPSD Mannheim 2021)

Lehrveranstaltungen:

• Übung Quantitative Methoden II (WT 2020)
• Übung Quantitative Methoden I (HT 2019)
• Übung Statistik II (FT 2019)
• Übung Statistik I (WT 2019)
• Übung zur Mathematik für Wirtschaftswissenschaftler ( HT 2018)
• Übung zur Statistik für Politologen ( FT 2018)
• Übung zur Zeitreihenanalyse ( FT 2018)
• Übung zur Fortgeschrittenen Mathematik für Ökonomen ( WT 2018)
• Vorkurs Mathematik für Wirtschaftswissenschaftler ( HT 2017)

Workshops attended:

Modern Topics in Time Series Analysis (2019) Sep 9th – Sep 13th in Bielefeld, Germany.