This is toolkit/library bridges advanced regression approaches not natively supported in Pinescript, to Pinescript. Advanced regression frameworks that can be critical to ticker data, such as Ridge, Lasso, ElasticNET, and Logistic (normalized) regression, colinarity measuring and quantile regression. As well as approaches to linear based feature selection and importance assessments.
I hope you find it helpful!
Library "Regression_Toolkit"
multipleRegression(y, x1, x2, length)
Parameters:
y (float)
x1 (float)
x2 (float)
length (simple int)
ridgeRegression(y, x1, x2, x3, x4, nVars, length, lambda)
Parameters:
y (float)
x1 (float)
x2 (float)
x3 (float)
x4 (float)
nVars (simple int)
length (simple int)
lambda (simple float)
lassoRegression(y, x1, x2, x3, x4, nVars, length, lambda, iterations)
Parameters:
y (float)
x1 (float)
x2 (float)
x3 (float)
x4 (float)
nVars (simple int)
length (simple int)
lambda (simple float)
iterations (simple int)
logisticRegression(y, x1, x2, x3, x4, nVars, length, learningRate, iterations)
Parameters:
y (float)
x1 (float)
x2 (float)
x3 (float)
x4 (float)
nVars (simple int)
length (simple int)
learningRate (simple float)
iterations (simple int)
featureSelection(y, x1, x2, x3, x4, nVars, length)
Parameters:
y (float)
x1 (float)
x2 (float)
x3 (float)
x4 (float)
nVars (simple int)
length (simple int)
regressionStats(y, x1, x2, x3, x4, nVars, length, b0, b1, b2, b3, b4)
Parameters:
y (float)
x1 (float)
x2 (float)
x3 (float)
x4 (float)
nVars (simple int)
length (simple int)
b0 (float)
b1 (float)
b2 (float)
b3 (float)
b4 (float)
elasticNetRegression(y, x1, x2, x3, x4, nVars, length, lambda, alpha, iterations)
Parameters:
y (float)
x1 (float)
x2 (float)
x3 (float)
x4 (float)
nVars (simple int)
length (simple int)
lambda (simple float)
alpha (simple float)
iterations (simple int)
huberRegression(y, x1, x2, x3, x4, nVars, length, huberK, iterations)
Parameters:
y (float)
x1 (float)
x2 (float)
x3 (float)
x4 (float)
nVars (simple int)
length (simple int)
huberK (simple float)
iterations (simple int)
quantileRegression(y, x1, x2, x3, x4, nVars, length, tau, learningRate, iterations)
Parameters:
y (float)
x1 (float)
x2 (float)
x3 (float)
x4 (float)
nVars (simple int)
length (simple int)
tau (simple float)
learningRate (simple float)
iterations (simple int)
I hope you find it helpful!
Library "Regression_Toolkit"
multipleRegression(y, x1, x2, length)
Parameters:
y (float)
x1 (float)
x2 (float)
length (simple int)
ridgeRegression(y, x1, x2, x3, x4, nVars, length, lambda)
Parameters:
y (float)
x1 (float)
x2 (float)
x3 (float)
x4 (float)
nVars (simple int)
length (simple int)
lambda (simple float)
lassoRegression(y, x1, x2, x3, x4, nVars, length, lambda, iterations)
Parameters:
y (float)
x1 (float)
x2 (float)
x3 (float)
x4 (float)
nVars (simple int)
length (simple int)
lambda (simple float)
iterations (simple int)
logisticRegression(y, x1, x2, x3, x4, nVars, length, learningRate, iterations)
Parameters:
y (float)
x1 (float)
x2 (float)
x3 (float)
x4 (float)
nVars (simple int)
length (simple int)
learningRate (simple float)
iterations (simple int)
featureSelection(y, x1, x2, x3, x4, nVars, length)
Parameters:
y (float)
x1 (float)
x2 (float)
x3 (float)
x4 (float)
nVars (simple int)
length (simple int)
regressionStats(y, x1, x2, x3, x4, nVars, length, b0, b1, b2, b3, b4)
Parameters:
y (float)
x1 (float)
x2 (float)
x3 (float)
x4 (float)
nVars (simple int)
length (simple int)
b0 (float)
b1 (float)
b2 (float)
b3 (float)
b4 (float)
elasticNetRegression(y, x1, x2, x3, x4, nVars, length, lambda, alpha, iterations)
Parameters:
y (float)
x1 (float)
x2 (float)
x3 (float)
x4 (float)
nVars (simple int)
length (simple int)
lambda (simple float)
alpha (simple float)
iterations (simple int)
huberRegression(y, x1, x2, x3, x4, nVars, length, huberK, iterations)
Parameters:
y (float)
x1 (float)
x2 (float)
x3 (float)
x4 (float)
nVars (simple int)
length (simple int)
huberK (simple float)
iterations (simple int)
quantileRegression(y, x1, x2, x3, x4, nVars, length, tau, learningRate, iterations)
Parameters:
y (float)
x1 (float)
x2 (float)
x3 (float)
x4 (float)
nVars (simple int)
length (simple int)
tau (simple float)
learningRate (simple float)
iterations (simple int)
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merlintrades.net
Get access to:
- Indicators
- Merlin Trading Software
- Discord
- Documentation
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As informações e publicações não se destinam a ser, e não constituem, conselhos ou recomendações financeiras, de investimento, comerciais ou de outro tipo fornecidos ou endossados pela TradingView. Leia mais nos Termos de Uso.
Check out the new Website!
merlintrades.net
Get access to:
- Indicators
- Merlin Trading Software
- Discord
- Documentation
merlintrades.net
Get access to:
- Indicators
- Merlin Trading Software
- Discord
- Documentation
Aviso legal
As informações e publicações não se destinam a ser, e não constituem, conselhos ou recomendações financeiras, de investimento, comerciais ou de outro tipo fornecidos ou endossados pela TradingView. Leia mais nos Termos de Uso.