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"Frontmatter" Monte Carlo Methods and Applications, vol. 26, no. 4, 2020, pp. i-iv. https://doi.org/10.1515/mcma-2020-frontmatter4

(2020). Frontmatter. Monte Carlo Methods and Applications, 26(4), i-iv. https://doi.org/10.1515/mcma-2020-frontmatter4

(2020) Frontmatter. Monte Carlo Methods and Applications, Vol. 26 (Issue 4), pp. i-iv. https://doi.org/10.1515/mcma-2020-frontmatter4

"Frontmatter" Monte Carlo Methods and Applications 26, no. 4 (2020): i-iv. https://doi.org/10.1515/mcma-2020-frontmatter4

Frontmatter. Monte Carlo Methods and Applications. 2020;26(4): i-iv. https://doi.org/10.1515/mcma-2020-frontmatter4

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Frontmatter
Drift velocity in GaN semiconductors: Monte Carlo simulation and comparison with experimental measurements
Gaussian variant of Freivalds’ algorithm for efficient and reliable matrix product verification
An approximate formula for calculating the expectations of functionals from random processes based on using the Wiener chaos expansion
Implementing de-biased estimators using mixed sequences
Hidden Markov Model with Markovian emission
On the density of lines and Santalo’s formula for computing geometric size measures
Constructing a confidence interval for the ratio of normal distribution quantiles
Random walk on ellipsoids method for solving elliptic and parabolic equations

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Frontmatter
Drift velocity in GaN semiconductors: Monte Carlo simulation and comparison with experimental measurements
Gaussian variant of Freivalds’ algorithm for efficient and reliable matrix product verification
An approximate formula for calculating the expectations of functionals from random processes based on using the Wiener chaos expansion
Implementing de-biased estimators using mixed sequences
Hidden Markov Model with Markovian emission
On the density of lines and Santalo’s formula for computing geometric size measures
Constructing a confidence interval for the ratio of normal distribution quantiles
Random walk on ellipsoids method for solving elliptic and parabolic equations