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Umeå universitet
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Huvudmenyn dold.

Natalya Pya Arnqvist

Jag är universitetslektor i matematisk statistik. Mina huvudsakliga forskningsintressen är statistisk regressionsmodellering och funktionell dataanalys.

Kontakt

E-post
natalya.pya@umu.se
Telefon
090-786 67 09

Verksam vid

Anknytning
Universitetslektor vid Institutionen för matematik och matematisk statistik
Plats
MIT-huset, plan 3, Matematik och matematisk statistik, MIT.F.340 Umeå universitet, 901 87 Umeå
scam: Shape constrained additive models. R package version 1.2-15
Pya Arnqvist, Natalya
On some extensions of shape-constrained generalized additive modelling in R
Pya Arnqvist, Natalya
fiberLD: Fiber Length Determination. R package version 0.1-8
Pya Arnqvist, Natalya; Sjöstedt de Luna, Sara; Abramowicz, Konrad
Geometry on optimal problem
Shcherbak, Denys; Pya Arnqvist, Natalya
scam: Shape constrained additive models. R package version 1.2-13
Pya Arnqvist, Natalya
fdaMocca: Model-Based Clustering for Functional Data with Covariates. R package version 0.1-1
Pya Arnqvist, Natalya; Arnqvist, Per; Sjöstedt de Luna, Sara
fiberLD: Fiber Length Determination. R package version 0.1-7
Pya Arnqvist, Natalya; Sjöstedt de Luna, Sara; Abramowicz, Konrad
scam: Shape constrained additive models. R package version 1.2-12
Pya Arnqvist, Natalya
fdaMocca: Model-Based Clustering for Functional Data with Covariates. R package version 0.1-0
Pya Arnqvist, Natalya; Arnqvist, Per; Sjöstedt de Luna, Sara
Statistical learning of phase measuring deflectometry for defect detection and classification on specular cab body surfaces
Advances in signal processing: reviews. Volume 2, International Frequency Sensor Association Publishing 2021 : 309-342
Pya Arnqvist, Natalya; Lindahl, Eric; Yu, Jun
Efficient surface finish defect detection using reduced rank spline smoothers and probabilistic classifiers
Econometrics and Statistics, Elsevier 2021, Vol. 18 : 89-105
Pya Arnqvist, Natalya; Ngendangenzwa, Blaise; Lindahl, Eric; et al.
nilde: Nonnegative Integer Solutions of Linear Diophantine Equations with Applications. R package version 1.1-4
Pya Arnqvist, Natalya; Voinod, Vassilly; Makarov, Rashid; et al.
Non-destructive methods for assessing tree fiber length distributions in standing trees
Sjöstedt de Luna, Sara; Abramowicz, Konrad; Pya Arnqvist, Natalya
scam: Shape constrained additive models. R package version 1.2-6
Pya Arnqvist, Natalya
A statistical learning approach for defect detection and classification on specular carbody surfaces
Winter Conference in Statistics 2019 - Machine Learning, March 10-14, 2019, Hemavan, Sweden
Pya Arnqvist, Natalya; Ngendangenzwa, Blaise; Lindahl, Eric; et al.
Effective degrees of freedom for surface finish defect detection and classification
Pya Arnqvist, Natalya; Ngendangenzwa, Blaise; Nilsson, Leif; et al.
Efficient surface finish defect detection using reduced rank spline smoothers
CRoNoS & MDA 2019
Pya Arnqvist, Natalya; Ngendangenzwa, Blaise; Nilsson, Leif; et al.
Defect detection and classfiication: statistical learning approach - Part II
Pya Arnqvist, Natalya; Ngendangenzwa, Blaise; Nilsson, Leif; et al.
fiberLD: Fiber Length Determination. R package version 0.1-6
Pya Arnqvist, Natalya; Sjöstedt de Luna, Sara; Abramowicz, Konrad
nilde: Nonnegative Integer Solutions of Linear Diophantine Equations with Applications. R package version 1.1-3
Pya Arnqvist, Natalya; Voinov, Vassilly; Voinov, Yevgeniy
Defect detection and classification: statistical learning approach
Pya Arnqvist, Natalya; Ngendangenzwa, Blaise; Nilsson, Leif; et al.
Automated surface finish defect detection using statistical learning approach
SweDS2018, Umeå University, Sweden, November 20-21, 2018
Pya Arnqvist, Natalya; Ngendangenzwa, Blaise; Nilsson, Leif; et al.
Polynomial in time nonnegative integer solutions of knapsacks and similar problems in R: P=NP?
Mathematical Journal, Vol. 18, (2) : 47-58
Voinov, Vassilly; Pya Arnqvist, Natalya; Voinov, Yevgeniy
R-software for additive partitioning of positive integers
Mathematical Journal, Vol. 17, (1) : 69-76
Voinov, Vassilly; Pya Arnqvist, Natalya
A Comparison of Inferential Methods for Highly Nonlinear State Space Models in Ecology and Epidemiology
Statistical Science, Institute of Mathematical Statistics 2016, Vol. 31, (1) : 96-118
Fasiolo, Matteo; Pya, Natalya; Wood, Simon N.
mvnTest: Goodness of Fit Tests for Multivariate Normality. R package version 1.1-0
Pya Arnqvist, Natalya; Voinov, Vassilly; Makarov, Rashid; et al.
A note on basis dimension selection in generalized additive modelling
Pya Arnqvist, Natalya; Wood, Simon
On ordered categorical modelling for complex skill development
Stochastic and data analysis methods and applications in statistics and demography: book 2, ISAST 2016 : 667-686
Pya, Natalya; Kussainov, Arman
Incorporating shape constraints in generalized additive modelling of the height-diameter relationship for Norway spruce
Forest Ecosystems, Springer 2016, Vol. 3
Pya, Natalya; Schmidt, Matthias
New invariant and consistent chi-squared type goodness-of-fit tests for multivariate normality and a related comparative simulation study
Communications in Statistics - Theory and Methods, Taylor & Francis 2016, Vol. 45, (11) : 3249-3263
Voinov, Vassilly; Pya Arnqvist, Natalya; Makarov, Rashid; et al.
Smoothing parameter and model selection for general smooth models
Journal of the American Statistical Association, Vol. 111, (516) : 1548-1563
Wood, Simon N.; Pya Arnqvist, Natalya; Safken, Benjamin
Shape constrained additive models
Statistics and computing, Springer 2015, Vol. 25, (3) : 543-559
Pya, Natalya; Wood, Simon N.
Immediate challenges faced by the quantum computing in time series analysis
Vestnik KazNU/ Physics, Vol. 1 : 98-101
Kussainov, Arman; Karimova, A.; Kussainov, S.; et al.
The neutron monitor time series data communication with the quantum algorithms
Izvestiya of the National Academy of Sciences of the Republic of Kazakhstan, Physical and Mathematical Series, Vol. 4, (290) : 13-17
Kussainov, Arman; Kussainov, S. G.; Pya, N. Y.
Goodness-of-fit tests for the power-generalized Weibull probability distribution
Communications in statistics. Simulation and computation, Taylor & Francis 2013, Vol. 42, (5) : 1003-1012
Voinov, Vassilly; Pya, Natalya; Shapakov, Niyaz; et al.
Goodness-of-fit tests for two-dimensional circular normal probability distribution
AFBE Journal, Vol. 5, (2) : 201-218
Voinov, Vassilly; Pya, Natalya; Makarov, Rashid; et al.
The neutron monitor time series statistics analysis and earthquakes prediction
Vestnik KazNU/ Physics, Vol. 3, (38) : 53-58
Kussainov, Arman; Pya, Natalya
A note on vector-valued goodness-of-fit tests
Communications in Statistics - Theory and Methods, Taylor & Francis 2010, Vol. 39, (3) : 452-459
Voinov, Vassilly; Pya, Natalya
A comparative study of some modified chi-squared tests
Communications in statistics. Simulation and computation, Taylor & Francis 2009, Vol. 38, (2) : 355-367
Voinov, Vassilly; Pya Arnqvist, Natalya; Alloyarova, Roza
Recent achievements in modified chi-squared goodness-of-fit testing
Statistical models and methods for biomedical and technical systems, Birkhäuser Verlag 2008 : 241-258
Voinov, Vassilly; Alloyarova, Roza; Pya Arnqvist, Natalya
A modified chi-squared goodness-of-fit test for the three-parameter Weibull distribution and its applications in reliability
Mathematical methods in survival analysis, reliability and quality of life, John Wiley & Sons 2008 : 189-202
Voinov, Vassilly; Alloyarova, Roza; Pya, Natalya
The Power-Generalized Weibull probability distribution and its use in survival analysis
Communications in Dependability and Quality Management, Vol. 10, (1) : 5-15
Alloyarova, Roza; Nikulin, Mikhail; Pya, Natalya; et al.
Independent chi-squared one distributed in the limit components of some chi-squared tests
Recent advances in stochastic modelling and data analysis, World Scientific 2007 : 243-250
Voinov, Vassilly; Nikulin, Mikhail; Pya, Natalya
Visa publikationer i DiVA

Jag har undervisar på kandidat- och masterprogram samt executive MBA courses inom områden som sannolikhet, statistik, tillämpade statistiska och kvantitativa metoder, prognoser för tidsserier, regressionsanalys och design av experiment.

För närvarande undervisar jag på följande kurser:

  • Design av experiment och avancerad statistisk modellering
  • Statistik för ingenjörer
  • Analys av fältdata