Towards this goal, we selected the best multivariate sets of candidate genes for prognosis, by means of exhaustive feature selection (all possible combinations) of single, pairs and triplets of genes out of the pre-filtered set of 1981 genes, using Linear Discrimination Analysis as the classification rule, and bolstered resubstitution as the error estimator (see the Methods section).
The first objective is to examine the dynamic volatility and volatility transmission in a multivariate setting using the VAR(1)–GARCH(1,1) model for three major sectors, namely, Service, Banking and Industrial/or Insurance, in four Gulf Cooperation Council (GCC)'s economies (Kuwait, Qatar, Saudi Arabia and UAE).
This analysis focused on identifying risk factors for hip fracture in the univariate and multivariate setting.
The multivariate analysis was performed using multinomial logistic regression, a model which is most appropriate for a polytomous-dependent variable 24 in a multivariate setting.
For a reliable analysis and accurate results, these assumptions should also be checked prior to modeling in the multivariate setting.
Levels of ECFC frequency for patient's characteristics were estimated by using logistic regression in univariate and multivariate setting.
For predicting increased level of ECFCs we performed logistic regression analysis in a univariate and multivariate setting that included each characteristic and all interaction terms.
When assessing group differences in a multivariate setting, MANOVA can avoid misleading conclusions associated with the use of univariate t- or F-tests for individual responses.
Since the signal intensities of the amino acids fragments define a multivariate data set (for a detailed peak list, see Table SI-2 in Supporting Information), principal component analysis was applied to reduce data dimensionality and complexity.
However unlike psRNAtarget, which measures the miRNA-RNA interaction and gross secondary structure of the mRNA using RNAup program [ 17] at its back-end, p-TAREF prefers to apply dinucleotide density variation profile around the target site as the multivariate feature set for discrimination through statistical machine learning approach, Support Vector Regression.
