The phrase "infer model" is grammatically correct and can be used in written English.
It may be used when discussing or describing the process of making educated guesses or conclusions based on available data or evidence. Example: "To better understand the behavior of the market, economists use statistical analysis to infer models that can predict future trends."
A Bayesian approach is applied to infer model parameter distributions.
MCMC-sampling was used to infer model parameters, where α, β k and were sampled with Gibbs steps and δ k and with a Metropolis-Hastings step.
MetaGeneTack uses a heuristic method (Besemer et al., 1999) to infer model parameters suitable for analysis of a short sequence at hand (e.g. 400 nt).
In addition, a multiple-objective optimization approach was developed to infer model parameters in order to realize the three stable steady states representing the three different types of blood cells and genetic switching.
Clinical data is used to infer model parameters using a Bayesian approach, enabling a quantitative estimation of the contributions of specific transport processes and molecular interactions of the drug that cannot be examined in other PK modeling, and insight into the mechanisms of aflibercept's antiangiogenic action.
We also report experimental results highlighting the ability of the methods to infer models on a number of artificial data sets.
The study of such processes, which is pivotal to our understanding of how best to predict and control spatio-temporal systems, has motivated researchers to develop appropriate tools that infer models and their parameters from observed data.
Similarly, supervised learning methods can infer models of pitch combinations seen in the training stage, but they are currently constrained to monotimbral sounds with almost constant spectral profiles [4].
Instead we are forced to infer models from incomplete knowledge.
Here, we used prior information to infer models with higher accuracy and predictive power compared to de novo models.
One other major difference is that they infer models for individual genes while we do it for co-expressed groups of genes.
