New Monte Carlo method is computationally more effective for quantifying uncertainty

September 26, 2017, National University of Singapore
New Monte Carlo method is computationally more effective for quantifying uncertainty
Uncertainty quantification can be used in the positioning of new oil wells and determining how deep to drill for oil and gas. The information provides decision makers with a better understanding of the possible outcomes. Credit: Pixabay

Uncertainty quantification (UQ) is a statistical technique to predict many complex phenomena such as weather conditions and tsunami risks. It involves the combination of real-life data (e.g. weather measurements) together with mathematical equations to model physical systems that are well-understood. These complex models are usually associated with either high-dimensional objects, large datasets or possibly both. In such scenarios, it is important that the required computational methodology to estimate such models is resource-efficient. Prof Ajay JASRA from the Department of Statistics and Applied Probability, NUS and his collaborators have proposed a more efficient approach to perform UQ calculations.

For UQ problems, the Monte Carlo method allows the user to numerically approximate quantities of interest in an efficient manner. Although there is an enhanced version, known as the Multilevel Monte Carlo (MLMC) method, it is challenging to use it for UQ problems. MLMC methods, for UQ problems associated to data is non-trivial to apply. This is because approximating the associated probability distribution, which is needed for the MLMC method to work is not always possible using independent simulation. In their recent paper, Prof Jasra and his collaborators have developed a new approach which allows MLMC to tackle UQ problems without compromising a high level accuracy while using less computational resources.

In future, the researchers plan to expand their statistical methods to tackle a greater range of problems. The will also incorporate the multi-index Monte Carlo method which is a less computationally demanding with similar accuracy to MLMC.

Prof Jasra said, "The ideas in this work can help to broaden the class of models used for uncertainty quantification , such as for weather prediction."

Explore further: Going to extremes to predict natural disasters

More information: Alexandros Beskos et al. Multilevel sequential Monte Carlo samplers, Stochastic Processes and their Applications (2016). DOI: 10.1016/

Related Stories

Going to extremes to predict natural disasters

July 10, 2017

Predicting natural disasters remains one of the most challenging problems in simulation science because not only are they rare but also because only few of the millions of entries in datasets relate to extreme events. A systematic ...

New computing applications expedite animal breeding

December 2, 2014

A doctoral thesis studied new statistical methods for animal breeding, based on which extensive livestock data samples can be analysed, and complex models used, more efficiently. Computing times lasting months can be reduced ...

A new method to generate ensemble initial perturbations

September 1, 2017

The atmosphere is a chaotic system, and even negligible initial errors will give rise to gradual deviation of the forecast state from the true path, eventually resulting in chaos. This means that the weather has a predictability ...

Recommended for you

Study casts new light on fishing throughout history

November 12, 2018

A new study from The Australian National University (ANU) has revealed new insights into ancient fishing throughout history, including what type of fish people were regularly eating as part of their diet.

A toast to the proteins in dinosaur bones

November 9, 2018

Burnt toast and dinosaur bones have a common trait, according to a new, Yale-led study. They both contain chemicals that, under the right conditions, transform original proteins into something new. It's a process that may ...


Please sign in to add a comment. Registration is free, and takes less than a minute. Read more

Click here to reset your password.
Sign in to get notified via email when new comments are made.