New PDF release: Algorithms for Computer Algebra

By Keith O. Geddes, Stephen R. Czapor, George Labahn

ISBN-10: 0792392590

ISBN-13: 9780792392590

Algorithms for laptop Algebra is the 1st entire textbook to be released relating to computational symbolic arithmetic. The ebook first develops the foundational fabric from glossy algebra that's required for next subject matters. It then offers an intensive improvement of recent computational algorithms for such difficulties as multivariate polynomial mathematics and maximum universal divisor calculations, factorization of multivariate polynomials, symbolic resolution of linear and polynomial structures of equations, and analytic integration of hassle-free capabilities. a variety of examples are built-in into the textual content as an relief to figuring out the mathematical improvement. The algorithms built for every subject are provided in a Pascal-like computing device language. an intensive set of workouts is gifted on the finish of every bankruptcy.
Algorithms for machine Algebra is acceptable to be used as a textbook for a path on algebraic algorithms on the third-year, fourth-year, or graduate point. even though the mathematical improvement makes use of recommendations from glossy algebra, the publication is self-contained within the feel one-term undergraduate direction introducing scholars to jewelry and fields is the one prerequisite assumed. The publication additionally serves good as a supplementary textbook for a normal sleek algebra path, through providing concrete functions to encourage the figuring out of the idea of jewelry and fields.

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Additional info for Algorithms for Computer Algebra

Example text

For more information, see the section “Effect Selection Methods” on page 4611. SEQUENTIAL forces variables to be added to the model in the order specified in the MODEL statement or to be eliminated from the model in the reverse order of that specified in the MODEL statement. MODEL Statement ✦ 4565 SINGULAR=value specifies the singularity criterion for determining linear dependencies in the set of explanatory variables. The default value is 10 12 . SLENTRY=value SLE=value specifies the significance level (a value between 0 and 1) for entering an explanatory variable into the model in the FORWARD or STEPWISE method.

1998), the correlation time, and the efficiency of the chain for each parameter. See the section “Effective Sample Size” on page 169 for details. MCSE MCERROR computes the Monte Carlo standard error for each parameter. The Monte Caro standard error, which measures the simulation accuracy, is the standard error of the posterior mean estimate and is calculated as the posterior standard deviation divided by the square root of the effective sample size. See the section “Standard Error of the Mean Estimate” on page 170 for details.

If the NOFIT option is specified along with other MODEL statement options, NOFIT takes precedence, and all other options are ignored except the TIES= option. OFFSET=name specifies the name of an offset variable, which is an explanatory variable with a regression coefficient fixed as one. This option can be used to incorporate risk weights for the likelihood function. PLCONV=value controls the convergence criterion for confidence intervals based on the profile-likelihood function. The quantity value must be a positive number, with a default value of 1E 4.

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Algorithms for Computer Algebra by Keith O. Geddes, Stephen R. Czapor, George Labahn


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