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The numerical solutions of the model enable us to locate the pricing variations and the parameters affecting the stock market.
On the other hand, the discrete model enable us to give a Markovian analysis and get some interesting closed-form analytical solution.
The properties of the presented model enable us to design a meta-heuristic based on ant colony system algorithm for solving the shortest loop design problem.
Flexible modelling, via nonparametric or semiparametric model enable us establish a better epidemiological relationship existing between the response and continuous explanatory variables.
The CpG site rate category predictions from our model enable us to identify genomic regions with frequent methylation state changes across hematopoietic differentiation.
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These models enable us to use more powerful parametric statistical techniques for both estimating isoform and processing event frequencies and detecting DP genes between samples.
The use of such a model enables us to simulate the entire pullout process.
GWAS using the appropriate analysis model enabled us to identify several SNP markers significantly associated with QTL.
The use of a multilevel model enabled us to further account for unexplained variation and clustering across hospital trust sites.
The use of this neuronal model enabled us to assess endogenous DOP receptor trafficking in a non-transfected, non-immortalized model.
This analysis using dynamic logistic regression model enabled us to assess the full effect of adherence on mortality without confounding from factors on the causal pathway.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com