International Journal of Applied Mathematics and Machine Learning[1] N. A. Nechval and E. K. Vasermanis, Improved Decisions in
Statistics, Riga: Izglitibas Soli, 2004.
[2] N. A. Nechval, G. Berzins, M. Purgailis and K. N. Nechval,
Improved estimation of state of stochastic systems via invariant
embedding technique, WSEAS Transactions on Mathematics 7(4) (2008),
141-159.
[3] N. A. Nechval, K. N. Nechval, V. Danovich and T. Liepins,
Optimization of new-sample and within-sample prediction intervals for
order statistics, in Proceedings of the 2011 World Congress in
Computer Science, Computer Engineering, and Applied Computing,
WORLDCOMP'11, Las Vegas Nevada, USA, CSREA Press, July 18-21 (2011),
91-97.
[4] N. A. Nechval, K. N. Nechval and G. Berzins, A new technique for
intelligent constructing exact 
content tolerance limits with expected
confidence on future outcomes in the Weibull
case using complete or Type II censored data, Automatic Control and
Computer Sciences 52(6) (2018), 476-488.
DOI: https://doi.org/10.3103/S0146411618060081
[5] N. A. Nechval, G. Berzins, K. N. Nechval and J. Krasts, A new
technique of intelligent constructing unbiased prediction limits on
future order statistics coming from an inverse Gaussian distribution
under parametric uncertainty, Automatic Control and Computer Sciences
53(3) (2019), 223-235.
DOI: https://doi.org/10.3103/S0146411619030088
[6] N. A. Nechval, G. Berzins and K. N. Nechval, A novel intelligent
technique for product acceptance process optimization on the basis of
misclassification probability in the case of log-location-scale
distributions, in: F. Wotawa et al. (Editors) Advances and Trends in
Artificial Intelligence, From Theory to Practice, IEA/AIE 2019,
Lecture Notes in Computer Science, 11606 (2019), pp. 801-818, Springer
Nature Switzerland AG.
DOI: https://doi.org/10.1007/978-3-030-22999-3_68
[7] N. A. Nechval, G. Berzins and K. N. Nechval, A novel intelligent
technique of invariant statistical embedding and averaging via pivotal
quantities for optimization or improvement of statistical decision
rules under parametric uncertainty, WSEAS Transactions on Mathematics
19 (2020), 17-38.
DOI: https://doi.org/10.37394/23206.2020.19.3
[8] N. A. Nechval, G. Berzins and K. N. Nechval, A new technique of
invariant statistical embedding and averaging via pivotal quantities
for intelligent constructing efficient statistical decisions under
parametric uncertainty, Automatic Control and Computer Sciences 54(3)
(2020), 191-206.
DOI: https://doi.org/10.3103/S0146411620030049
[9] N. A. Nechval, G. Berzins and K. N. Nechval, Cost-effective
planning reliability-based inspections of fatigued structures in the
case of log-location-scale distributions of lifetime under parametric
uncertainty, in Proceedings of the 30th European Safety and
Reliability Conference and the 15th Probabilistic Safety Assessment
and Management Conference, Edited by Piero Baraldi, Francesco Di Maio
and Enrico Zio, ESREL2020-PSAM15, 1-6 November, 2020, Venice, Italy,
pp. 455-462.
DOI: https://doi.org/10.3850/978-981-14-8593-0_3664-cd
[10] N. A. Nechval, G. Berzins and K. N. Nechval, A new technique of
invariant statistical embedding and averaging in terms of pivots for
improvement of statistical decisions under parametric uncertainty,
CSCE'20 - The 2020 World Congress in Computer Science, Computer
Engineering, & Applied Computing, July 27-30, 2020, Las Vegas, USA,
in: H. R. Arabnia et al. (Editors), Advances in Parallel & Distributed
Processing, and Applications, Transactions on Computational Science
and Computational Intelligence, pp. 257-274. Springer Nature
Switzerland AG 2021.
DOI: https://doi.org/10.1007/978-3-030-69984-0_20
[11] N. A. Nechval, G. Berzins and K. N. Nechval, A new simple
computational method of simultaneous constructing and comparing
confidence intervals of shortest length and equal tails for making
efficient decisions under parametric uncertainty. Proceedings of Sixth
International Congress on Information and Communication Technology
– ICICT 2021, Lecture Notes in Network and Systems (LNNS,
Volume 235), X.-S. Yang, S. Sherratt, N. Dey and A. Joshi (Editors),
25-26 February 2021, London, United Kingdom, pp. 473-482. Springer
Nature Singapore 2022.
DOI: https://doi.org/10.1007/978-981-16-2377-6_44
