论文检索

驻点位置受限的抛物线回归与最小二乘估计AI 解读

It is sometimes desired to fit a second degree polynomial E(y|x) = α + βx + γx 2 to a set of data so that its stationary point will fall in a given region. Methods are shown to calculate a, b, c, the least squares estimates of the regression coefficients α, β, and γ. An example is given in which this theory is applied to fit a parabolic regression to a set of data so that in a given contiguous and finite region of the independent variable, the regression function is strictly…

驻点位置受限的抛物线回归与最小二乘估计AI 解读

It is sometimes desired to fit a second degree polynomial E(y|x) = α + βx + γx 2 to a set of data so that its stationary point will fall in a given region. Methods are shown to calculate a, b, c, the least squares estimates of the regression coefficients α, β, and γ. An example is given in which this theory is applied to fit a parabolic regression to a set of data so that in a given contiguous and finite region of the independent variable, the regression function is strictly…