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stepwise linear regression glmselect procedure  (SAS institute)


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    SAS institute stepwise linear regression glmselect procedure
    Stepwise Linear Regression Glmselect Procedure, supplied by SAS institute, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    Models selected by PROC  GLMSELECT procedure.

    Journal: Animals : an Open Access Journal from MDPI

    Article Title: Predictions of Daily Milk and Fat Yields, Major Groups of Fatty Acids, and C18:1 cis -9 from Single Milking Data without a Milking Interval

    doi: 10.3390/ani5030377

    Figure Lengend Snippet: Models selected by PROC GLMSELECT procedure.

    Article Snippet: Considering that not all of these influential factors may have statistically significant effects on all of the traits examined, an appropriate subset of variables for each model was determined using the stepwise GLMSELECT procedure in the SAS/STAT software package [ ].

    Techniques:

    Calibration and validation statistics (correlation values between true and estimate daily yield (Ry,ŷ), root mean square errors (RMSE) and standard deviation for each studied predicted trait (σŷ)) for the best model selected by PROC  GLMSELECT.  Ry,ŷ were expressed in % and RMSE and σŷ were expressed in kg/day for milk and g/day for the remaining studied traits.

    Journal: Animals : an Open Access Journal from MDPI

    Article Title: Predictions of Daily Milk and Fat Yields, Major Groups of Fatty Acids, and C18:1 cis -9 from Single Milking Data without a Milking Interval

    doi: 10.3390/ani5030377

    Figure Lengend Snippet: Calibration and validation statistics (correlation values between true and estimate daily yield (Ry,ŷ), root mean square errors (RMSE) and standard deviation for each studied predicted trait (σŷ)) for the best model selected by PROC GLMSELECT. Ry,ŷ were expressed in % and RMSE and σŷ were expressed in kg/day for milk and g/day for the remaining studied traits.

    Article Snippet: Considering that not all of these influential factors may have statistically significant effects on all of the traits examined, an appropriate subset of variables for each model was determined using the stepwise GLMSELECT procedure in the SAS/STAT software package [ ].

    Techniques: Biomarker Discovery, Standard Deviation