Learn R Programming

gaussquad (version 1.0-3)

slegendre.quadrature.rules: Create list of shifted Legendre quadrature rules

Description

This function returns a list with \(n\) elements containing the order \(k\) quadrature rule data frame for the shifted Legendre polynomials for orders \(k = 1,\;2,\; \ldots ,\;n\).

Usage

slegendre.quadrature.rules(n,normalized=FALSE)

Arguments

n

integer value for the highest order

normalized

boolean value. if TRUE rules are for orthonormal polynomials, otherwise they are for orthgonal polynomials

Value

A list with \(n\) elements each of which is a data frame

1

Quadrature rule data frame for the order 1 shifted Legendre polynomial

2

Quadrature rule data frame for the order 2 shifted Legendre polynomial

...
n

Quadrature rule data frame for the order \(n\) shifted Legendre polynomial

Details

An order \(k\) quadrature data frame is a named data frame that contains the roots and abscissa values of the corresponding order \(k\) orthogonal polynomial. The column with name x contains the roots or zeros and the column with name w contains the weights.

References

Abramowitz, M. and I. A. Stegun, 1968. Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables, Dover Publications, Inc., New York.

Press, W. H., S. A. Teukolsky, W. T. Vetterling, and B. P. Flannery, 1992. Numerical Recipes in C, Cambridge University Press, Cambridge, U.K.

Stroud, A. H., and D. Secrest, 1966. Gaussian Quadrature Formulas, Prentice-Hall, Englewood Cliffs, NJ.

See Also

quadrature.rules, slegendre.quadrature

Examples

Run this code
# NOT RUN {
###
### generate the list of shifted Legendre quadrature rules
### for orders 1 to 5 for the orthogonal polynomials
###
orthogonal.rules <- slegendre.quadrature.rules( 5 )
print( orthogonal.rules )
###
### generate the list of shifted Legendre quadrature rules
### for orders 1 to 5 for the orthonormal polynomials
###
orthonormal.rules <- slegendre.quadrature.rules( 5, TRUE )
print( orthonormal.rules )
# }

Run the code above in your browser using DataLab