Use of the samples so collected raised a question of how the allele frequency parameters, p and q, can be calculated and used to estimate the disequilibrium parameter, D. We proposed to calculate p, the marker allele frequency, from the control sub-samples, and explored two alternative ways to obtain the value of q, the disease allele frequency.
A question of interest is whether the precision of parameter estimates is lessened by the reduced information for non-cases.
This question of parameter uncertainty and sensitivity analysis has been addressed in many different applications, including biological, chemical and risk assessment [ 10- 16].
The question of parameter overfitting has already been answered in the neighbor jack-knife test when whole homologous groups of sequences have been taken out of the learning set.
For questions of parameter dependence, see the discussion above on positive-definiteness.
However, making quantitative predictions with such models often requires parameter estimation from data, raising questions of parameter identifiability and estimability.
Thus, gene regulatory network identifying becomes to an question to optimize a set of parameters w ji, and to maximize the SRC between SPM and the gene expression data.
Let P ij represent the true probability of a correct answer on a test question, the parameters of interest are the person's latent score θ i and item difficulty b j such that P Y ij = 1 | η ij = exp η ij 1 + exp η ij, (1).
We explored the question of " What parameters need to be considered to engineer an endoglucanase with suitable thermodynamics, stability, and higher activity?" Any mutant or engineered endoglucanase that preserves the thermostability in terms of the dynamics is a potential industrial candidate.
Thus the question of which parameters are consistent or inconsistent with the data arises naturally.
Aston et al. 11 mathematically analyzed this model to answer the question of which parameters affect the potency of the drug.
