Approximation methods are widely used in many fields and many techniques have been published already. This comparative study presents a comparison of LOWESS (Locally weighted scatterplot smoothing) and RBF (Radial Basis Functions) approximation methods on noisy data as they use different approaches. The RBF approach is generally convenient for high dimensional scattered data sets. The LOWESS me...

Locally weighted regression combines the advantages of polynomial regression and kernel smoothing. We present three ideas for appropriate and effective use of LOcally WEighted Scatterplot Smoothing (LOWESS) models for surrogate optimization. First, a method is proposed to reduce the computational cost of LOWESS models. Second, a local scaling coefficient is introduced to adapt LOWESS models to ...

background: reference charts are widely used in healthcare as a screening tool. this study aimed to produce reference growth charts for school children from west malaysia in comparison with the united states centers for disease control and prevention (cdc) chart. methods: a total of 14,360 school children ranging from 7 to 17 years old from six states in west malaysia were collected. a two-stag...

This package contains an implementation of the CGHnormaliter strategy for normalization of two-channel array Comparative Genomic Hybridization (aCGH) data displaying many copy number imbalances. The key idea of our method is that temporary exclusion of aberrations from the aCGH data allows for a more appropriate calculation of the LOWESS regression curve. As a result, after normalization, the l...

This package contains an implementation of the CGHnormaliter strategy for normalization of two-channel array Comparative Genomic Hybridization (aCGH) data displaying many copy number imbalances. The key idea of our method is that temporary exclusion of aberrations from the aCGH data allows for a more appropriate calculation of the LOWESS regression curve. As a result, after normalization, the l...

This package contains an implementation of the CGHnormaliter strategy for normalization of two-channel array Comparative Genomic Hybridization (aCGH) data displaying many copy number imbalances. The key idea of our method is that temporary exclusion of aberrations from the aCGH data allows for a more appropriate calculation of the LOWESS regression curve. As a result, after normalization, the l...

This package contains an implementation of the CGHnormaliter strategy for normalization of two-channel array Comparative Genomic Hybridization (aCGH) data displaying many copy number imbalances. The key idea of our method is that temporary exclusion of aberrations from the aCGH data allows for a more appropriate calculation of the LOWESS regression curve. As a result, after normalization, the l...

This package contains an implementation of the CGHnormaliter strategy for normalization of two-channel array Comparative Genomic Hybridization (aCGH) data displaying many copy number imbalances. The key idea of our method is that temporary exclusion of aberrations from the aCGH data allows for a more appropriate calculation of the LOWESS regression curve. As a result, after normalization, the l...

This package contains an implementation of the CGHnormaliter strategy for normalization of two-channel array Comparative Genomic Hybridization (aCGH) data displaying many copy number imbalances. The key idea of our method is that temporary exclusion of aberrations from the aCGH data allows for a more appropriate calculation of the LOWESS regression curve. As a result, after normalization, the l...

This package contains an implementation of the CGHnormaliter strategy for improved normalization of dual-channel array Comparative Genomic Hybridization (aCGH) data displaying many copy number imbalances. The key idea of our method is that temporary exclusion of aberrations from the data allows for a more appropriate calculation of the LOWESS regression curve. As a result, after normalization, ...