method of least squares การใช้

• Polynomial regression models are usually fit using the method of least squares.
• Alignment measurement method of least squares; 2-1.
• The method of least squares was first described by Adrien-Marie Legendre in 1805.
• By the method of least squares.
• He is chiefly remembered for his formulation of the method of least squares, published in 1808.
• Because of the nature of the method of least squares, the whole vector of residuals, with
• The first clear and concise exposition of the method of least squares was published by Legendre in 1805.
• In that work he claimed to have been in possession of the method of least squares since 1795.
• The mathematical forms arising from quantile regression are distinct from those arising in the method of least squares.
• In practice multiple arc measurements are used to determine the ellipsoid parameters by the method of least squares.
• This makes it possible to find optimal coefficients through the method of least squares using simple matrix operations.
• In evaluating the SiTF curve, the signal input and signal output are measured the method of least squares.
• If it is important to give greater weight to outliers, the method of least squares is a better choice.
• The value of Legendre's method of least squares was immediately recognized by leading astronomers and geodesists of the time.
• In the history of statistics, this disagreement is called the " priority dispute over the discovery of the method of least squares ."
• However, once there, he began studying mathematics under Carl Friedrich Gauss ( specifically his lectures on the method of least squares ).
• The values of a and b, obtained by the method of least squares, are 3.60 and 0.0624 respectively.
• The doses z are transformed to logarithms x = \ log ( z ) and the method of least squares is used to fit two parallel lines to the data.
• The following is a table contrasting some properties of the method of least absolute deviations with those of the method of least squares ( for non-singular problems ).
• However, to Gauss's credit, he went beyond Legendre and succeeded in connecting the method of least squares with the principles of probability and to the normal distribution.