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2. Linear programming - Wikipedia

   en.wikipedia.org/wiki/Linear_programming

   More formally, linear programming is a technique for the optimization of a linear objective function, subject to linear equality and linear inequality constraints. Its feasible region is a convex polytope , which is a set defined as the intersection of finitely many half spaces , each of which is defined by a linear inequality.

3. Jim Williams (analog designer) - Wikipedia

   en.wikipedia.org/wiki/Jim_Williams_(analog_designer)

   James M. Williams (April 14, 1948 – June 12, 2011) was an analog circuit designer and technical author who worked for the Massachusetts Institute of Technology (1968–1979), Philbrick, National Semiconductor (1979–1982) and Linear Technology Corporation (LTC) (1982–2011). [1]

4. Linear model - Wikipedia

   en.wikipedia.org/wiki/Linear_model

   An example of a linear time series model is an autoregressive moving average model.Here the model for values {} in a time series can be written in the form = + + = + =. where again the quantities are random variables representing innovations which are new random effects that appear at a certain time but also affect values of at later times.

5. AOL Mail

   mail.aol.com

   Get AOL Mail for FREE! Manage your email like never before with travel, photo & document views. Personalize your inbox with themes & tabs. You've Got Mail!

6. Regularized least squares - Wikipedia

   en.wikipedia.org/wiki/Regularized_least_squares

   Several methods can be used to solve the above linear system, Cholesky decomposition being probably the method of choice, since the matrix + is symmetric and positive definite. The complexity of this method is O ( n D 2 ) {\displaystyle O(nD^{2})} for training and O ( D ) {\displaystyle O(D)} for testing.

7. Linear algebra - Wikipedia

   en.wikipedia.org/wiki/Linear_algebra

   where v 1, v 2, ..., v k are in S, and a 1, a 2, ..., a k are in F form a linear subspace called the span of S. The span of S is also the intersection of all linear subspaces containing S . In other words, it is the smallest (for the inclusion relation) linear subspace containing S .

8. LISREL - Wikipedia

   en.wikipedia.org/wiki/LISREL

   A Primer of LISREL: Basic Applications and Programming for Confirmatory Factor Analytic Models. New York: Springer. ISBN 0-387-96972-1. Kelderman, Henk (1987). "LISREL models for inequality constraints in factor and regression analysis". In Cuttance, Peter; Ecob, Russell (eds.). Structural Modelling by Example.

9. Linear least squares - Wikipedia

   en.wikipedia.org/wiki/Linear_least_squares

   Linear least squares (LLS) is the least squares approximation of linear functions to data. It is a set of formulations for solving statistical problems involved in linear regression, including variants for ordinary (unweighted), weighted, and generalized (correlated) residuals.