Sharma, HemantGlennon, Colin
test cohort patients (linear regression analysisR2=0.862). (d) Magnified view of (c) using decreased x- andyaxis limits to show missense mutation vs predicted neoantigen load in test cohort. (e) Histogram of natural log-transformed predicted neoantigen count (mutant peptide-binding affinity IC50<...
Table 3. Summary of simple regression models results. Simple regression models based on each factor separately resulted in achieving the highest 𝑅2R2 = 0.584 when including only the number of containers. Therefore, multiple regression was used to predict a time spent at WCP by a garbage truc...
The multiple linear regression outcomes showed that there was no problem with collinearity for the sample’s data since the range of VIF values was between 1.030 and 2.783, and the tolerance values were between 0.359 and 0.971. The Mahalanobis distance indicated the presence of 24 outliers. Howeve...
Pant, Mohan DevPant, Mohan. "Does Literacy Predict Economic Growth? A Multiple Regression Analysis" Paper presented at the annual meeting of the MWERA Annual Meeting, Westin Great Southern Hotel, Columbus, Ohio, Oct 15, 2008 . 2010- 06-06 ...
TOP PAPERS: Student Classroom Engagement: A Multiple Linear Regression Analysis of the Variables Predicting Student Silence and ParticipationMeyer, Kevin R
To demonstrate the existence of a clock-like mutational process in MM, we explored the association between SBS5/SBS1 and patient’s age by a linear regression model (lm R function) across a large cohort of newly patients with available whole-exome sequencing data (CoMMpass; NCT01454297) and...
MI learning includes instance classification [4], clustering [5], regression [5], and multi-label learning [6,7], but this article will focus on bag classification. MI learning can also be found as integrated parts of end-to-end methods for image analysis that generate patches, extract ...
Table 6. Factors’ fixed effect regression results to TFEE. From the regression results, the largest coefficient is X3 (−6.18860) which has most influence on the TFEE of thermal power industry. In other words, 1% decline of coal consumption can bring 6.18860% increase on TFEE. It also...
On the other hand, Table 3 shows the results of the analysis of universities of those researchers who achieved greater academic efficiency in the publication of MCDM articles from Taiwan (National Chiao Tung University; CpD = 224), Italy (University of Catania; CpD = 76.07) and Portugal (Unive...