Sentence examples for error structures from inspiring English sources

Robust designs are developed for some correlated error structures.

Our proposed work asks: what are the implications for analysis and inference when using high-resolution data with different error structures?

Then, different error structures are used to investigate the effects of flood data errors on design flood estimation.

The text covers different modeling-related topics for continuous dependent variables, including: mapping data on spatial units, exploratory spatial data analysis, working with regression models that have spatially dependent regressors, and estimating regression models with spatially correlated error structures.

This requires a consistent characterization of the error structures in the individual data sets, which vary due to changes in instrument configuration and calibration, and retrieval algorithm design.

Noticeable similarities between the error structures of the satellite products derived from same retrieval algorithm and same measuring frequency however suggest transferability of error parameters between them.

The results obtained by both methods are compared with the results obtained by MLPARAFAC, which is a method designed to optimally accomodate a variety of measurement error structures.

The multi-scale error structures are found to be non-trivial and vary between the products, giving cause for conducting multi-scale merging with awareness of these differences.

This parameterized approach utilizes Generalized Linear Models (GLMs), based on heteroscedastic Poisson (non-additive) error structures, and using an orthonormal polynomial design matrix.

This study simulates and examines the estimation efficiency of RP/SP models based on the D-error considering both error structures and attribute differences.

Underestimating the phenomenon of correlated measurement error will result in the suggestion of biologically meaningful results that in reality rest solely on complicated error structures.