Multiple Non Linear Regression

Multiple Non-Linear Regression

This indicator is designed to perform multiple non-linear regression analysis using four independent variables: close, open, high, and low prices.

Here's a components and functionalities:

• Normalization Data Length: Length of data used for normalization.
• Learning Rate: Rate at which the algorithm learns from errors.
• Show data points: Show plotting of normalized input data(close, open, high, low)
• Smooth?: Option to smooth the output.
• Smooth Length: Length of smoothing if enabled.
• Define start coefficients: Initial coefficients for the regression equation.

Gradient Descent:

The coefficients are updated iteratively using gradient descent to minimize the error.

• Plotting of normalized input data (close, open, high, low).
• The indicator provides visualization of normalized data values (close, open, high, low) in the form of circular markers on the chart, allowing users to easily observe the relative positions of these values in relation to each other and the regression line.
• Plotting of the regression line.
• Color gradient on the regression line based on its value and bar colors.
• Display of normalized input data and predicted value in a table.
• Signals for crossovers with a midline (0.5).