The aim of the paper is to study the nature of normalization in Structural VAR models. Noting that normalization is the … integral part of identification of a model, we provide a general characterization of the normalization. In consequence some the …

activation policy as well as principles and objectives of social policy in a holistic paradigm of normalization. This summary …

amounts and types of such variations are observed in different arrays. Although various normalization methods have been … for different arrays and data sets. To address this issue, we present a novel normalization technique, STEPNORM, for data …-dependent and adaptive normalization of two-channel spotted microarrays. STEPNORM performs a stepwise interrogation of a range of …

for the normalization of two-color spotted microarrays for various sources of variation including printtip variation …. Normalization with linear mixed models provides a parametric model of which results compare favorably to intensity dependent … normalization LOWESS methods. We illustrate the use of this technique on two datasets. The first dataset contains 24 arrays, each …

Vaughan assert that raw cocitation data should be analyzed directly, without first applying a normalization like the Pearson …

-sensitive axioms in group differential measures. In addition, Mishra (2007) imposes an axiom of normalization. At a basic level it …-sensitivity axioms but failed the normalization axiom at a fundamental level. Further, the comparison between two situations under this …

augmented through factor-specific R&D. The considered model yields a number of interesting results. First, normalization of the …