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Compute to the smallest fraction, reduce to the least number

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Q: What does least squares mean?

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least mean squares line

Yes, it does exist.

Formally, the standard deviation is the square root of the variance. The variance is the mean of the squares of the difference between each observation and their mean value. An easier to remember form for variance is: the mean of the squares minus the square of the mean.

Yes.

It means nine squares in tic tac toe

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least mean squares line

PLS can stand for a variety of things depending on the context. It can mean "Please," "Partial Least Squares" in statistics, or "Public Land Survey."

T. A. Doerr has written: 'Linear weighted least-squares estimation' -- subject(s): Least squares, Kalman filtering

the residual.

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Yes, it does exist.

The Recursive least squares RLS adaptive filter is an algorithm which recursively finds the filter coefficients that minimize a weighted linear least squares cost function relating to the input signals. This is in contrast to other algorithms such as the least mean squares LMS that aim to reduce the mean square error. In the derivation of the RLS, the input signals are considered deterministic, while for the LMS and similar algorithm they are considered stochastic. Compared to most of its competitors, the RLS exhibits extremely fast convergence. However, this benefit comes at the cost of high computational complexity.

The Recursive least squares RLS adaptive filter is an algorithm which recursively finds the filter coefficients that minimize a weighted linear least squares cost function relating to the input signals. This is in contrast to other algorithms such as the least mean squares LMS that aim to reduce the mean square error. In the derivation of the RLS, the input signals are considered deterministic, while for the LMS and similar algorithm they are considered stochastic. Compared to most of its competitors, the RLS exhibits extremely fast convergence. However, this benefit comes at the cost of high computational complexity.

R. L. Schwiesow has written: 'Nonlinear least squares fitting on a minicomputer' -- subject(s): Minicomputers, Least squares, Computer programs

Phillip R. Wilcox has written: 'A least squares method for the reduction of free-oscillation data' -- subject(s): Least squares, Oscillations

M. M Hafez has written: 'A modified least squares formulation for a system of first-order equations' -- subject(s): Least squares

IUrii Vladimirovich Linnik has written: 'Method of least squares and principles of the theory of observations' -- subject(s): Least squares, Mathematical statistics