Sentence examples for by a polynomial regression from inspiring English sources

The segmental features are represented as a trajectory of observed vector sequences by a polynomial regression function.

The assay linearity was evaluated by performing a polynomial regression (least-squares regression using polynomials with various orders) to determine the degree of non-linearity of the set.

Growth was significantly improved by dietary hyp addition in a polynomial regression, indicating maximum growth at 2.9 g kg− 1 added hyp in which weight gain was improved by 14%.

Furthermore, we fitted a polynomial regression by including a quadratic term for exposure and compared these models with the linear model using the likelihood ratio test.

A unified dataset was generated for both the proteome and the transcriptome by fitting the replicate datasets with a polynomial regression, only retaining highly reproducible expression profiles (∼85% of genes, Figure 2 figure supplement 6), and resampling the fit at the actual time points of the experiment.

For each contig, the proportion of nsSNPs was plotted against SNP density and a polynomial regression fitted, weighting by the total number of SNPs the contig contained.

It is worth noting that the response data were fit by a quadratic polynomial regression equation with a significance level of α ≤ 0.05.

Figure 3 shows the number of recaptured Ae. camptorhynchus per trap per night versus distance from the release point overlaid by a cubic polynomial regression line, which shows a rapid decline in recaptures out to 3 km and a very low likelihood of Ae. camptorhynchus being recaptured beyond this distance.

The response (the percentage of adsorbed lead II), i.e. zinc II) ions) was fitted by a quadratic polynomial regression model using least square analysis in a five-level-three-factor CCD.

Non-linear regression of the YF IgG and YF PRNT indices as a function of time post-vaccination in days was performed by a locally weighted polynomial regression (lowess) implemented by the R function plot.smooth.line.line

Each response had been described by a second-order polynomial regression model developed by ANOVA, which could properly determine the experimental data.