Correlative Variation of The Essential Amino Acids (CTBB): Lupine Publishers

Correlative Variation of The Essential Amino Acids By Mazurkin P M in Current Trends on Biostatistics & Biometrics in Lupine Puiblishers

On the example of the table of contents of eight essential amino acids in 22 products, the methodology of factor analysis and determination of the coefficient of correlation variation, calculated as the ratio of the sum of the correlation coefficients of stable laws and laws of binary relations between amino acids to the product of the number of amino acids as influencing variables and as dependent indicators. It is shown that this evaluation criterion depends on the composition of the products and the set of amino acids considered. Therefore, it is proposed to make a more complete table considering the set of objects, which considers the content of all 20 amino acids. The law of binary relations between amino acids is the sum of the exponential law and the biotechnical law of stress excitation in the product. By correlation coefficients of individual binary relations, the ratings of amino acids as influencing variables and as dependent indicators are performed. The correlation matrix of super strong bonds of essential amino acids with correlation coefficients of more than 0.99 is considered, in part of which the graphs are given. By the nature of behavior, it is proposed to classify the binary relationships between amino acids into positive, neutral and negative. Separately, the method of rating products. The equations and graphs of rank distributions of the content of essential amino acids in products are given. The rating of essential amino acids by dispersion of residues from the equations of binary relations and rank distributions is given.

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https://lupinepublishers.com/biostatistics-biometrics-journal/abstracts/correlative-variation-of-the-essential-amino-acids.ID.000105.php
https://lupinepublishers.com/biostatistics-biometrics-journal/pdf/CTBB.MS.ID.000105.pdf

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Model Selection in Regression: Application to Tumours in Childhood: (CTBB)- Lupine publishers

Model Selection in Regression: Application to Tumours in Childhood by Annah Managa in Current Trends on Biostatistics & Biometrics in Lupine publishers

We give a chronological review of the major model selection methods that have been proposed from circa 1960. These model selection procedures include Residual mean square error (MSE), coefficient of multiple determination (R2), adjusted coefficient of multiple determination (Adj R2), Stepwise methods, Mallow’s Cp, Akaike information criterion (AIC),Schwarz criterion (BIC). Some of these methods are applied to a problem of developing a model for predicting tumors in childhood using log-linear models. The theoretical review will discuss the problem of model selection in a general setting. The application will be applied to log-linear models in particular.

https://lupinepublishers.com/biostatistics-biometrics-journal/fulltext/model-selection-in-regression-application-to-tumours-in-childhood.ID.000101.php
https://lupinepublishers.com/biostatistics-biometrics-journal/abstracts/model-selection-in-regression-application-to-tumours-in-childhood.ID.000101.php
https://lupinepublishers.com/biostatistics-biometrics-journal/pdf/CTBB.MS.ID.000101.pdf

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