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