Examples of 'nonlinear regression' in a sentence
Meaning of "nonlinear regression"
This phrase refers to a statistical method used to analyze the relationship between variables when the data does not follow a linear pattern. It is a technique employed in data analysis and predictive modeling to identify and understand nonlinear relationships between variables
How to use "nonlinear regression" in a sentence
Basic
Advanced
nonlinear regression
The results are analysed by nonlinear regression analysis.
Nonlinear regression analysis was used to examine the data fit.
The results are analyzed by nonlinear regression analysis.
A nonlinear regression approach is proposed to estimate the parameters of the Johnson SB distribution.
One common type of application is nonlinear regression.
Both linear and nonlinear regression methods were explored.
Kinetic binding parameters were determined by nonlinear regression.
One of the advantages of the nonlinear regression models is to have interpretable parameters.
The treatment of experimental data was performed by nonlinear regression.
Data was analyzed using a nonlinear regression computer program.
We discuss the detection of influential observations in symmetrical linear and nonlinear regression models.
Data were analyzed by nonlinear regression analysis.
Furthermore, it was proposed a generalized mathematical model adjusted by nonlinear regression.
Data analysis by nonlinear regression.
The curves represent the fits of the data to a sigmoidal dose-response model using nonlinear regression.
See also
The determination by nonlinear regression can be obtained by an artificial neural networks model.
It is used in some forms of nonlinear regression.
This program uses a nonlinear regression with sigmoidal curve on a semilogarithmic scale.
Metabolic constants were determined by nonlinear regression.
Among those formulas are the nonlinear regression methods determining the minimal sum of deviations.
Fit a line to the graph using nonlinear regression.
The Logit model is a nonlinear regression model specifically designed to assess dependent binary variables.
The values were determined by nonlinear regression analysis.
I forgot my notebook… including standard T-ratios for the perimeter estimates for logarithmic nonlinear regression.
Radioligand binding data were analyzed by nonlinear regression analysis equipped with a statistical package.
Data was fit to a one site binding model using nonlinear regression.
The standard curve is determined by nonlinear regression analysis using the logistic equation.
Eight transport parameters were calculated from the conductivity results by a nonlinear regression computation.
Curve fitting was carried out by nonlinear regression with the computer program PHAKOK.
Curves were fitted to the measurement points ( glucose versus time ) using weighed nonlinear regression analysis.
Data were analyzed using nonlinear regression least squares curve fit in Prizm statistical analysis software.
This equation was derived by using nonlinear regression analysis.
A general-purpose nonlinear regression subroutine was used to fit the model.
The function was fit to experimental data using standard nonlinear regression techniques.
Options for nonlinear regression in XLSTAT.
Km and Vmax values were determined from nonlinear regression.
We considered linear and nonlinear regression models with logistic-ii and student-t errors.
The new class of models is called generalized log-gamma nonlinear regression models glgnlm.
Nonlinear regression with many options remove outliers, compare models, compare curves, interpolate standard curves, etc.
The KD values were calculated using a nonlinear regression curve fit.
Data were analyzed by nonlinear regression using the data analysis program Enzfitter ( Elsevier-Biosoft ).
The standard curve was fit using a four-parameter nonlinear regression curve-fitting program.
Nonlinear regression is used to fit the competitive binding curve to determine the log ( IC50 ).
An improvement was suggested in the form of nonlinear regression using a feed-forward neural network model.
The ED80 values are obtained by fitting the data to a sigmoidal curve using nonlinear regression.
IC50 values were determined by nonlinear regression fitting of the competition curves.
The IC50 values were determined from the concentration curves by nonlinear regression analysis.
Experimental data were fitted by nonlinear regression using the following equation, EPMATHMARKEREP.
Evaluation, The binding parameters were calculated by nonlinear regression in SAS.
The results were analyzed by nonlinear regression using graphpad prism 5.0 software.
You'll also be interested in:
Examples of using Regression
Show more
Your regression models are the stuff of legend
Inhibition results in the regression of prostatic tumours
Regression analysis was used to estimate this effect
Examples of using Nonlinear
Show more
The regression is nonlinear in the unknown parameters
A nonlinear function can be defined by linear features
Analysis of linear and nonlinear dynamical systems
