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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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
免責聲明
這些資訊和出版物並非旨在提供，也不構成TradingView提供或認可的任何形式的財務、投資、交易或其他類型的建議或推薦。請閱讀使用條款以了解更多資訊。