## New error coefficients for estimating quadrature errors for analytic functions

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- by Philip Rabinowitz and Nira Richter PDF
- Math. Comp.
**24**(1970), 561-570 Request permission

## Abstract:

Since properly normalized Chebyshev polynomials of the first kind ${\tilde T_n}(Z)$ satisfy \[ ({\tilde T_m},{\tilde T_n}) = \int _{ \in \rho } {{{\tilde T}_m}({\text {z}})} \overline {{T_n}({\text {z}})} |1 - {{\text {z}}^2}{|^{ - 1/2}}|d{\text {z}}| = {\delta _{mn}}\] for ellipses $\in \rho$ with foci at $\pm 1$, any function analytic in $\in \rho$ has an expansion, $f({\text {z}}) = \sum {{a_n}{{\tilde T}_n}({\text {z}})}$ with ${a_n} = (f,{\tilde T_n})$. Applying the integration error operator $E$ yields $E(f) = \sum {{a_n}E({{\tilde T}_n})}$. Applying the Cauchy-Schwarz inequality to $E(f)$ leads to the inequality \[ |E(f){|^2} \leqq \sum {|{a_n}{|^2}} \sum {|E({{\tilde T}_n})} {|^2} = ||f|{|^2}||E|{|^2}.\] . $||E||$ can be computed for any integration rule and approximated quite accurately for Gaussian integration rules. The bound for $|E(f)|$ using this norm is compared to that using a previously studied norm based on Chebyshev polynomials of the second kind and is shown to be superior in practical situations. Other results involving the latter norm are carried over to the new norm.## References

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## Additional Information

- © Copyright 1970 American Mathematical Society
- Journal: Math. Comp.
**24**(1970), 561-570 - MSC: Primary 65.55
- DOI: https://doi.org/10.1090/S0025-5718-1970-0275675-X
- MathSciNet review: 0275675