We present global and local algorithms for evaluating minimal xed points of dependency graphs, a general problem in xed-point computation and model checking. Our algorithms run in linear-time, matching the complexity of the best existing algorithms for similar problems, and are simple to understand. The main novelty of our global algorithm is that it does not use the counter and \reverse list" ...

Rationale Frequently decision-making situations require modeling of relationships among business variables. For instance, the amount of sale of a product may be related to its advertising expenditures for marketing, the health of the economy as measured by the stock market performance, and the number of sales people etc? The regression analysis provides tools for modeling a "response" variable ...

One of the most widely used statistical techniques is simple linear regression. This technique is used to relate a measured response variable, Y, to a single measured predictor (explanatory) variable, X, by means of a straight line. It uses the principle of least squares to come up with values of the “best” slope and intercept for a straight line that approximates the relationship. By means of ...

In the first part of the paper we survey some far reaching applications of the basis facts of linear programming to the combinatorial theory of simple polytopes. In the second part we discuss some recent developments concurring the simplex algorithm. We describe sub-exponential randomized pivot roles and upper bounds on the diameter of graphs of polytopes. 

In some applications of statistical process monitoring, a quality characteristic can be characterized by linear regression relationships between several response variables and one explanatory variable, which is referred to as a “multivariate simple linear profile.” It is usually assumed that the process parameters are known in Phase II. However, in most applications, this assumption is viola...

in the first part of the paper we survey some far reaching applications of the basis facts of linear programming to the combinatorial theory of simple polytopes. in the second part we discuss some recent developments concurring the simplex algorithm. we describe sub-exponential randomized pivot roles and upper bounds on the diameter of graphs of polytopes.