Least squares

Least squares regression analysis calculates best-fit alignments. Cant Design Tools Integrated cant and horizontal design ensures compliance with design standards. Vertical Lift Diagram Validate design visually with curvature, lift, and slew diagrams.

least squares A mathematical method for fitting a line or curve to a set of data points. Least squares minimizes the sum of the squares of the error term at each point.

Least squares - A statistical method of fitting a mathematical model. It is based on computing the minimum sum of the squared deviation between measured data and their estimates (i.e. the mean value).

The method of least squares, which was used to minimize errors in data measurement, was published independently by Adrien-Marie Legendre (1805), Robert Adrain (1808), and Carl Friedrich Gauss (1809).

The Franklin algorithm then says compute the "best" solution using a least squares approach. The LSQR algorithm, which is a well-known iterative least squares solver developed by Dr. Saunders and Dr. Paige at Stamford University is used to do this.

Use the survey (least squares) adjustment feature to accurately and incrementally update your fabric with each new survey plan. In parallel, you can also adjust related GIS layers such as building footprints, roads, and easements.

DA Form 1925. Quadrilateral Adjustment (Least Squares Method). 1 February 1957. DA Form 1927. Latitude and Longitude Adjustment. 1 February 1957. DA Form 1930. Special Angle Computation. 1 February 1957.

When there are more control points, than actually needed for the estimation of the coefficients (transformation parameters), the Root Mean Squares Error (RMSE) can be calculated using the Least Squares Adjustment.

It calculates band locations (indexed to the wavelength at the bottom of the trough) and depths, using a continuum base as reference. The weighted fit leads to correlation coefficients that a least squares routine numerically fixes.

See also: Surface, Survey, Information, Feature, Analysis