Library "FunctionLinearRegression" Method for Linear Regression using array sample points.
linreg(sample_x, sample_y) Performs Linear Regression over the provided sample points. Parameters: sample_x: float array, sample points X value. sample_y: float array, sample points Y value. Returns: tuple with: _predictions: Array with adjusted Y values. _max_dev: Max deviation from the mean. _min_dev: Min deviation from the mean. _stdev/_sizeX: Average deviation from the mean.
draw(sample_x, sample_y, extend, mid_color, mid_style, mid_width, std_color, std_style, std_width, max_color, max_style, max_width) Method for drawing the Linear Regression into chart. Parameters: sample_x: float array, sample point X value. sample_y: float array, sample point Y value. extend: string, default=extend.none, extend lines. mid_color: color, default=color.blue, middle line color. mid_style: string, default=line.style_solid, middle line style. mid_width: int, default=2, middle line width. std_color: color, default=color.aqua, standard deviation line color. std_style: string, default=line.style_dashed, standard deviation line style. std_width: int, default=1, standard deviation line width. max_color: color, default=color.purple, max range line color. max_style: string, default=line.style_dotted, max line style. max_width: int, default=1, max line width. Returns: line array.
A noob question but still taking a shot at this one... How can I make turn the rsi values into a float array to be compatible with the function? Been scratching my head at this for hours, thought it'd be more efficient to ask you.
import RicardoSantos/FunctionLinearRegression/1 as linear
linear.draw(array.from(bar_index, bar_index+10, bar_index+20), array.from(open, open*1.1, open*0.9))