Sentence examples for transformation for estimating from inspiring English sources

The reasons why we do not use the likelihood given by the Girsanov transformation for estimating the unknown parameters (Cialenco et al. [14]) are twofold.

The Box-Cox power transformation requires all predictor variables to be included in the model for estimating transformation parameter in order to put a skewed response onto the correct scale for the classic ANOVA model [ 27].

Since in our case always more than four point correspondences are known, one can again use the norm as an additional condition and use the basic direct linear transformation (DLT) algorithm [20] for estimating or the set of equations in (12) has to be turned into an inhomogeneous set of linear equations.

The real case examples with Patient Falls and Patient Injury Falls from the NDNQI database showed Box-Cox power transformations both with and without structural effects for teaching and Magnet status included in the models for estimating the transformation parameters were equally effective in normalizing the residual distributions.

Our method adopts a forward selection algorithm to determine feature correspondences needed for estimating the transformation model.

We set the feature searching radius r to 50 pixels, the similarity threshold for the aspect ratio to 0.5 and the number of feature correspondences m for estimating a transformation model to four.

Instead of measuring the similarity of the two edge maps, edge line segments are grouped to form triangle features for estimating the transformation model in Coiras et al. (2000).

The key point underlying the proposed approach is the employment of local frequency representations of CAD models images to efficiently determine sets of matching points from the images to be registered, which in turn enables obtaining correspondence between these sets for estimating the transformation parameters.

Following the observation that windows are typically ubiquitous elements on a façade (Friedman and Stamos 2013; Mesolongitis and Stamos 2012), we propose quadrilateral features which are derived from rectangular façade elements and a hypothesis-evaluation framework for estimating the transformation model.

Nonparametric approaches for estimating optimal transformations of data were used to obtain the maximum correlation between observed variables.

After log transformation, linear regression models were computed for estimating the association between FMR and HOMA score, fasting and 2 hours glucose and A1C levels.