Fitting data with nonlinear regression -- Fitting data with linear regression -- Models -- How nonlinear regression works -- Confidence intervals of the parameters -- Comparing models -- How does a ...

Choosing the right curve fit model is essential for revealing key data features, such as rate of change, asymptotes, and EC 50 /IC 50 values. The best model is the one that most faithfully reflects ...

Linear models, generalized linear models, and nonlinear models are examples of parametric regression models because we know the function that describes the relationship between the response and ...

A fixed-effects formulation of repeated-measures and growth-curve problems usually leads to an unwieldy linear model, so mixed models are widely used for inference ...

Fluorescence curves are useful for monitoring changes in photosynthesis activity. Various summary measures have been used to quantify differences among fluorescence curves corresponding to different ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using JavaScript. Linear regression is the simplest machine learning technique to predict a single numeric value, ...

During the course of operation, businesses accumulate all kinds of data such as numbers related to sales performance and profit, and information about clients. Companies often seek out employees with ...