The least-squares regression method of cost estimation mathematically determines the best fit line through a field of points. Therefore, to the extent that a line doesn't best describe cost ...

The least-squares criterion is a method of measuring the accuracy of a line in depicting the data that was used to generate it. That is, the formula determines the line of best fit.

Statisticians typically use the least squares method (sometimes known as ordinary least squares, or OLS) to arrive at the geometric equation for the line, either through manual calculations or by ...

As the wording of Prof. Hall's letter in NATURE for July 25 might imply that he was calling attention to evidence that would change the opinion expressed in my letter, it seems to me worth while ...

Seemingly unrelated regression (SUR), also called joint generalized least squares (JGLS) or Zellner estimation, is a generalization of OLS for multi-equation systems. Like OLS, the SUR method assumes ...

The following example estimates this model using two-stage least squares: ... The 2SLS option on the PROC SYSLIN statement specifies the two-stage least-squares method. The ENDOGENOUS statement ...

We adopt the least squares Monte Carlo (LSMC) method to price time-capped American options. The cap can be an independent random variable or dependent on the asset price at a random time. We ...

Log-linear least-squares method. A statistical technique for fitting a curve to a set of data points. One of the variables is transformed by taking its logarithm, and then a straight line is ...

THE method of least squares has an extensive literature of its own. Our author, in a sketch appended to his work, gives the titles of forty-seven of the most important memoirs and books which ...