Examples of 'stochastic models' in a sentence

Meaning of "stochastic models"

Stochastic models: Mathematical tools used to describe random events and their probability of occurrence. They are commonly used in fields such as statistics, economics, and science to model uncertain and unpredictable systems

How to use "stochastic models" in a sentence

Basic
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stochastic models
Stochastic models of membrane voltage and spike timing.
Uncertainty is quantified by means of stochastic models.
Introduction to stochastic models in operations research.
A crucial distinction is between deterministic and stochastic models.
Stochastic models in biological systems.
Probability and stochastic models.
Stochastic models for learning.
Another relevant distinction is between deterministic and stochastic models.
Stochastic models are needed in order to assess the variability of the claims reserve.
Renewable energy sources are represented by stochastic models with multiple states.
Stochastic models can be simulated to assess the percentiles of the aggregated distributions.
Truncating and censoring of data can also be estimated using stochastic models.
We work with stochastic models in order to model the movement of transport motor proteins.
The influence of random fluctuations on the stability is studied using three stochastic models.
It is thus convenient to construct stochastic models that may describe the dynamics of systems.

See also

The phenology of this insect and its host were described using stochastic models.
Create the basic classes of stochastic models applied by listing the deformations of the patterns.
Researchers from Mephysto team study quantitative methods for stochastic models.
Our model follows the basic principles of stochastic models presented for stratified data.
The stochastic models proved sufficiently complex to describe the biochemical and cellular processes involved.
The methods used involve a mathematical analysis of several stochastic models associated to these networks.
Stochastic models of code and phase GPS measurements for navigation.
All the above features of TS breaking work for both deterministic and stochastic models.
Tying CSC and stochastic models together.
Davis as a general class of non-diffusive stochastic models.
Rojas, stochastic models and statistical properties in high frequency markets.
For example, probabilities for stochastic models are largely subjective.
Finally, we discuss on the extension of the classical stochastic models.
In stochastic models a piece of music is composed as a result of non-deterministic methods.
Then, these properties can be used to produce various other stochastic models.
Stochastic models tend to be more realistic, especially for small samples.
These two sources of " error " have different implications for predictions from stochastic models.
Traditionally, stochastic models use time series to reproduce the behavior of a given phenomenon.
Energizing . Highlighting the urgent need for the kind of quantum stochastic models.
Optimization of portfolios in stochastic models in continuous time with utility functions range-dependent.
Abstract, This thesis examines some quantitative questions in the framework of two different stochastic models.
Some more common stochastic models are queueing models, markov chains, and most simulations.
Abstract, The thesis is devoted to limit theorems for stochastic models with long-range dependence.
Fractional and stochastic models for the sub-diffusion has been the subject of numerous studies.
Tosca - TO Simulate and CAlibrate stochastic models.
For the kind of quantum stochastic models of salvo analysis… Pause. Highlighting the urgent need.
However, there are other models, such as non-deterministic or stochastic models.
Grejo, c. b . evolution of species, stochastic models for natural selection through competition and mutation.
PLASMA LAB, is a platform for statistical model-checking of stochastic models.

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Examples of using Models
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