Maple Professional
Maple Academic
Maple Student Edition
Maple Personal Edition
Maple Player
Maple Player for iPad
MapleSim Professional
MapleSim Academic
Maple T.A. - Testing & Assessment
Maple T.A. MAA Placement Test Suite
Möbius - Online Courseware
Machine Design / Industrial Automation
Aerospace
Vehicle Engineering
Robotics
Power Industries
System Simulation and Analysis
Model development for HIL
Plant Modeling for Control Design
Robotics/Motion Control/Mechatronics
Other Application Areas
Mathematics Education
Engineering Education
High Schools & Two-Year Colleges
Testing & Assessment
Students
Financial Modeling
Operations Research
High Performance Computing
Physics
Live Webinars
Recorded Webinars
Upcoming Events
MaplePrimes
Maplesoft Blog
Maplesoft Membership
Maple Ambassador Program
MapleCloud
Technical Whitepapers
E-Mail Newsletters
Maple Books
Math Matters
Application Center
MapleSim Model Gallery
User Case Studies
Exploring Engineering Fundamentals
Teaching Concepts with Maple
Maplesoft Welcome Center
Teacher Resource Center
Student Help Center
Efficient Computation in the Statistics Package
This help page provides details about how numeric computation is performed by commands in the Statistics package. Included are suggestions on how to get the most efficient performance from the solvers.
The Floating-Point Environment
Most of the Statistics package commands rely on external libraries that perform their computation in floating-point. These libraries include statistics and optimization routines provided by the Numerical Algorithms Group (NAG).
The solvers used by the Statistics package will choose either the hardware floating-point environment or the arbitrary-precision software floating-point environment to perform the computations. To maximize efficiency, the solvers attempt to use hardware floats whenever possible. Software floats are used only when the environment variable UseHardwareFloats is set to 'false', or when UseHardwareFloats is 'deduced' and Digits is greater than the value of evalhf(Digits).
Data Sets
A data set is generally provided as a Vector or Matrix. Most Statistics commands will accept an Array or a list in the place of a Vector or Matrix. For greatest efficiency, it is recommended that data sets be provided as Vectors and Matrices having datatype float.
Solving Regression Problems
To ensure maximum efficiency, special care must be taken when specifying regression problems. The regression commands, described in the Statistics/Regression help page, allow problems to be specified in one of three forms: algebraic form, operator form, and Matrix form. The algebraic and operator forms are easier to use. However, the Matrix form is most similar to the internal representation used by the solvers and leads to greatest efficiency. The Statistics/Regression/InputForms help page provides a summary of all three forms and links to more information.
When using operator or Matrix form with the regression commands, a procedure must be provided. If possible, the procedure should be written so that it can be evaluated by the evalhf command. Procedures that contain any Maple constructs not supported by evalhf are evaluated using the slower evalf command. For more information on evalhf construct support, see the evalhf and evalhf/procedure help pages.
See Also
Digits, evalhf, evalhf/procedure, Matrix, Statistics, Statistics/Regression, Statistics/Regression/InputForms, Vector
Download Help Document