LinearRegValueFC (Function)

Disclaimer

Linear Regression is a concept also known as the "least squares method" or "best fit." Linear Regression attempts to fit a straight line between several data points in such a way that distance between each data point and the line is minimized.

The LinearRegValue function projects, based on the current regression line, the regression values for x number of bars out into the future or x number of bars back in the past.

Function

LinearRegValueFC(Price, Length, TgtBar)

Parameters

Name	Type	Description
Price	Numeric	Specifies the value of interest is to be used.
Length	Numeric	Specifies the number of bars to consider in the regression calculation.
TgtBar	Numeric	Represents the number of bars into the future or back into the past, zero for the current bar.  Use a negative integer for a future bar, a positive integer for a previous bar, and zero for the current bar.

Returns

A numeric value containing the current value of the specified regression line at TgtBar.

Usage

The input Price can be hard coded with a bar attribute such as Close, Open, High, Low, and Volume or a numeric series type input. It can also be replaced with a valid EasyLanguage expression. For example: Close + Open, or Average(RSI(Close,14),14).

The input Length can be hard coded replaced with a numeric simple type input.

TgtBar represents the number of bars into the future or back into the past. If TgtBar is a positive number, LinearRegValue will be for a bar in the past. If TgtBar is negative, the LinearRegValue will be for a bar in the future. TgtBar can be replaced with a numeric simple input.

  This function uses a fast calculation method that uses more memory than the traditional method.