Chapter16
... data set that could be created by observing the value of a random variable many, many, many times (an infinite number of times). This is denoted m x , m ( x ), or E ( x ) . The standard deviation of a random variable represents the standard deviation of the numerical data set described above. This ...
... data set that could be created by observing the value of a random variable many, many, many times (an infinite number of times). This is denoted m x , m ( x ), or E ( x ) . The standard deviation of a random variable represents the standard deviation of the numerical data set described above. This ...
Simplex algorithm
In mathematical optimization, Dantzig's simplex algorithm (or simplex method) is a popular algorithm for linear programming. The journal Computing in Science and Engineering listed it as one of the top 10 algorithms of the twentieth century.The name of the algorithm is derived from the concept of a simplex and was suggested by T. S. Motzkin. Simplices are not actually used in the method, but one interpretation of it is that it operates on simplicial cones, and these become proper simplices with an additional constraint. The simplicial cones in question are the corners (i.e., the neighborhoods of the vertices) of a geometric object called a polytope. The shape of this polytope is defined by the constraints applied to the objective function.