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Nonlinear Regression

Definition

Nonlinear regression is a statistical method used to model and analyze relationships between variables when the relationship cannot be adequately described by a linear equation. It involves fitting a curve or function to the data points in order to make predictions or understand the underlying pattern.

Analogy

Imagine you have a scatterplot of people's ages and their heights, but instead of a straight line, you notice that there is a curved relationship. Nonlinear regression helps you find the best-fitting curve that captures this relationship accurately.

Related terms

Exponential Growth/Decay: Exponential growth or decay refers to situations where one variable changes at an increasing (growth) or decreasing (decay) rate proportional to its current value. Nonlinear regression can be used to model such relationships.

Polynomial Regression: Polynomial regression involves fitting a polynomial function (e.g., quadratic, cubic) to the data points. It allows for capturing more complex nonlinear patterns than simple curves.

Sigmoidal Curve: A sigmoidal curve is an S-shaped curve commonly seen in logistic growth models or cumulative probability distributions. Nonlinear regression can help estimate parameters for sigmoidal curves and predict future values.