least_squares_regression

2022年3月22日

Library "least_squares_regression"
least_squares_regression: Least squares regression algorithm to find the optimal price interval for a given time period

basic_lsr(series, series, series) basic_lsr: Basic least squares regression algorithm
  Parameters:
    series: int[] t: time scale value array corresponding to price
    series: float[] p: price scale value array corresponding to time
    series: int array_size: the length of regression array
  Returns: reg_slop, reg_intercept, reg_level, reg_stdev

trend_line_lsr(series, series, series, string, series, series) top_trend_line_lsr: Trend line fitting based on least square algorithm
  Parameters:
    series: int[] t: time scale value array corresponding to price
    series: float[] p: price scale value array corresponding to time
    series: int array_size: the length of regression array
    string: reg_type: regression type in 'top' and 'bottom'
    series: int max_iter: maximum fitting iterations
    series: int min_points: the threshold of regression point numbers
  Returns: reg_slop, reg_intercept, reg_level, reg_stdev, reg_point_num

2022年3月29日

發行說明

v2 modify some discriptions