upperLinearReg(), middleLinearReg(), lowerLinearReg() Built-in Study Functions
Linear Regression is a statistical tool used to predict future values from past values. In the case of security prices, it is commonly used to determine when prices are overextended. A linear regression trend line uses the least squares method to plot a straight line through prices so as to minimize the distances between the prices and resulting trend line.
Syntax
upperLinearReg( nLength , nStdev [, Series | sym() | inv() ][, nBarIndex ] )
middleLinearReg( nLength , nStdev [, Series | sym() | inv() ][, nBarIndex ] )
lowerLinearReg ( nLength , nStdev [, Series | sym() | inv() ][, nBarIndex ] )
Parameters
Parameter: | Description: | Default: |
nLength | Required. Number of periods to use for calculation. | n/a |
nStdev | Required. Number of standard deviations to use for calculation. | n/a |
Series or sym() or inv() |
[Optional] Series Object or function of sym() or inv() to determine symbol/interval source for the study. | Chart's sym/inv |
nBarIndex | [Optional] Bar index of series to retrieve . | n/a |
Return Value(s)
Returns a Series Object when nBarIndex is not specified.
Returns a single value when nBarIndex is specified.
Notes
Only available in versions 7.9 or later.
Code Examples
function main() { return new Array( upperLinearReg(20, 1), middleLinearReg(20, 1), lowerLinearReg(20, 1) ); }
function main() { return new Array( upperLinearReg(20, 1, hl2()), middleLinearReg(20, 1, hl2()), lowerLinearReg(20, 1, hl2()) ); }
Retrieve single values:
function main() { var nValue_0 = middleLinearReg(20, 1, 0); // Current Bar Index var nValue_1 = middleLinearReg(20, 1, -1); // Prior Bar Index return new Array(nValue_0, nValue_1); }
//global Series Object variables var xStudy1 = null; var xStudy2 = null; var xStudy3 = null; function main() { if (xStudy1 == null) xStudy1 = upperLinearReg(20, 1); if (xStudy2 == null) xStudy2 = middleLinearReg(20, 1); if (xStudy3 == null) xStudy3 = lowerLinearReg(20, 1); // retrieve single values for conditional statements var nValue1_0 = xStudy1.getValue(0); // Current Bar Index value var nValue2_0 = xStudy2.getValue(0); // Current Bar Index value var nValue3_0 = xStudy3.getValue(0); // Current Bar Index value var nValue1_1 = xStudy1.getValue(-1); // Prior Bar Index value // Plot Current Bar Index Value return new Array(nValue1_0, nValue2_0, nValue3_0); }
// global Series Object variables var xStudy1 = null; var xStudy2 = null; var xStudy3 = null; var bInit = false; // Initialization flag function main() { if (bInit == false) { xStudy1 = upperLinearReg(20, 1, inv(20)); // 20-min interval xStudy2 = middleLinearReg(20, 1, inv(20)); // 20-min interval xStudy3 = lowerLinearReg(20, 1, inv(20)); // 20-min interval bInit = true; } // retrieve single values for conditional statements var nValue1_0 = xStudy1.getValue(0); // Current Bar Index value var nValue1_1 = xStudy1.getValue(-1); // Prior Bar Index value // Synchronized Series plot return new Array(getSeries(xStudy1), getSeries(xStudy2), getSeries(xStudy3)); }
// global Series Object variables var xStudy1 = null; var xStudy2 = null; var xStudy3 = null; var bInit = false; // Initialization flag function main() { if (bInit == false) { xStudy1 = upperLinearReg(20, 1, sym("IBM,20")); // IBM 20-min interval xStudy2 = middleLinearReg(20, 1, sym("IBM,20")); // IBM 20-min interval xStudy3 = lowerLinearReg(20, 1, sym("IBM,20")); // IBM 20-min interval bInit = true; } // retrieve single values for conditional statements var nValue1_0 = xStudy1.getValue(0); // Current Bar Index value var nValue1_1 = xStudy1.getValue(-1); // Prior Bar Index value // Synchronized Series plot return new Array(getSeries(xStudy1), getSeries(xStudy2), getSeries(xStudy3)); }
See Also
Series Object
getSeries()
Built-in Study Functions
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