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A regression line is simply a single line that best fits the data.

In the pinescript you can plot a linear regression line using the

*linreg*function.

Here i share the entire calculation of the linear regression line, you are free to take the code and modify the functions in the script for creating your own kind of filter.

Hope you enjoy :)

Ask me a question https://curiouscat.me/alexgrover

I'm just trying to get the exact function ported from pine to python,

do you have any idea how the "correlation" function works internally, or in other words could you mokup your formula without using any build in pine functions?

Thanks

I am trying to us the homodyne discriminator from ehlers ideal rsi, to set a variable length based on the price cycle for some of my indicators. this does work but the pinescript standard functions do not like dealing with a variable length, so i normally have to code out the functions... i am having such a problem with linreg, so finding your formula is very useful but it has the stock function 'sma' stdev' and 'correlation' which stops the code dead...

I wondered if you might be able to write out the stdev and the correlation functions in pinescript, if you have time.

Let me know what you think

Cheers

H

Cheers

H

I'm trying to code a Linear Regression Band indicator that has the same standard deviations as the built in Linear Regression indicator/drawing tool.

The mean of my indicator (code below) is correct but the standard deviation bands are always in the wrong place when I compare them to the same length LR indicator or drawing tool.

Does anyone know how to fix this issue so that the bands match the built in drawing tool/indicator?

Here is my code ...

//@version=3

study(shorttitle="LRB", title="Linear Regression Bands", overlay=true)

source = close

length = input(50, minval=1)

offset = 0

mult = input(2, title="StDev", minval=0.001, maxval=5)

basis = linreg(source, length, offset)

dev = mult * stdev(source, length)

upper = basis + dev

lower = basis - dev

plot(basis, color=red)

plot(upper, color=blue)

plot(lower, color=blue)

Many thanks! Pete