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partial least squares regression (pls-r)  (Aspen Technology Inc)

 
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    Aspen Technology Inc partial least squares regression (pls-r)
    Partial Least Squares Regression (Pls R), supplied by Aspen Technology Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/partial+least+squares+regression+%28pls-r%29/10__1155_slash_2023_slash_3537294-145-11-18?v=Aspen+Technology+Inc
    Average 90 stars, based on 1 article reviews
    partial least squares regression (pls-r) - by Bioz Stars, 2026-07
    90/100 stars

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    MVDA of the historical data set. ( A ) removal of outliers prior to analysis; ( B <t>)</t> <t>PLS-R</t> model fit using two Principal Components, here Comp 1 and 2. R2Y(cum) indicates the explained variance, while Q2(cum) explains the predictive quality using one resp. two principal components; ( C ) VIP plot of the most important variables in the analysis sorted by relevance; ( D ) Loading scatter plot of data relationship between predictors (X) and predicted (Y) variable discriminated by VIP size.
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    MVDA of the historical data set. ( A ) removal of outliers prior to analysis; ( B ) PLS-R model fit using two Principal Components, here Comp 1 and 2. R2Y(cum) indicates the explained variance, while Q2(cum) explains the predictive quality using one resp. two principal components; ( C ) VIP plot of the most important variables in the analysis sorted by relevance; ( D ) Loading scatter plot of data relationship between predictors (X) and predicted (Y) variable discriminated by VIP size.

    Journal: Bioengineering

    Article Title: Metabolic Control in Mammalian Fed-Batch Cell Cultures for Reduced Lactic Acid Accumulation and Improved Process Robustness

    doi: 10.3390/bioengineering3010005

    Figure Lengend Snippet: MVDA of the historical data set. ( A ) removal of outliers prior to analysis; ( B ) PLS-R model fit using two Principal Components, here Comp 1 and 2. R2Y(cum) indicates the explained variance, while Q2(cum) explains the predictive quality using one resp. two principal components; ( C ) VIP plot of the most important variables in the analysis sorted by relevance; ( D ) Loading scatter plot of data relationship between predictors (X) and predicted (Y) variable discriminated by VIP size.

    Article Snippet: In order to gather process understanding of how and by which importance the process parameters relate to each other, we used PLS-R (partial least squares regression) in Simca 13.0.3 (Umetrics, Sweden) to analyze the historical dataset.

    Techniques: