Sentence examples for well developed methods from inspiring English sources

Although statistical analysis of univariate longitudinal data has been well developed, methods for modeling multivariate high-dimensional longitudinal data are still under development.

The skew Toeplitz approach is one of the well developed methods to design H*infin; controllers for infinite dimensional systems.

Besides traditional, already well developed methods – such as first order perturbation theory or Monte Carlo sampling – Polynomial Chaos Expansion (PCE) has been given a growing emphasis in recent years due to its simple application and good performance.

Therefore, it can be estimated efficiently by well developed methods and algorithms.

Modern psychometrics [44] [45] offers statistically and theoretically well developed methods, such as (genetically informed) latent factor models and Item Response Theory, for addressing the phenotypic measurement issues discussed here, and as such has the potential to contribute considerably to the success of genetic studies.

We performed an extensive search for studies and used well developed methods for quality assessment.

Derivative transformation [12], spectrum subtraction [13], amplitude factor [14], advanced absorbance subtraction method (AAS) [15], advanced amplitude modulation method (AAM) [15] and simultaneous derivative ratio (S1DD) [16] are well developed method that were successfully adopted for resolution of overlapped spectra of binary mixtures.

While complete cation exchange is a quite well developed method for the chemical transformation of binary NCs with preservation of their anion lattices via one-step or sequential exchange reactions, a partial exchange is an emerging technique which can yield a wide range of alloyed structures.

Objective: This study is undertaken with the objective to scrutinize and offer a notion of commonly used as well as recently developed methods of causality assessment tools for the diagnosis of adverse drug reactions and discuss their pros and cons.

Transcriptome analysis, such as microarray and RNA-sequencing, has superior power because of its high throughput, cost performance and well developed statistical methods for data interpretation.

One straightforward approach often followed in practice is to dichotomize the test results into two categories and apply the well developed bivariate methods separately for each of the thresholds.