Content-Length: 132030 | pFad | https://dlmf.nist.gov/./.././././././././30.16#i
For small we can use the power-series expansion (30.3.8). Schäfke and Groh (1962) gives corresponding error bounds. If is large we can use the asymptotic expansions in §30.9. Approximations to eigenvalues can be improved by using the continued-fraction equations from §30.3(iii) and §30.8; see Bouwkamp (1947) and Meixner and Schäfke (1954, §3.93).
Another method is as follows. Let be even. For sufficiently large, construct the tridiagonal matrix with nonzero elements
30.16.1 | ||||
and real eigenvalues , , , , arranged in ascending order of magnitude. Then
30.16.2 | |||
and
30.16.3 | |||
. | |||
The eigenvalues of can be computed by methods indicated in §§3.2(vi), 3.2(vii). The error satisfies
30.16.4 | |||
. | |||
If is large, then we can use the asymptotic expansions referred to in §30.9 to approximate .
If is known, then we can compute (not normalized) by solving the differential equation (30.2.1) numerically with initial conditions , if is even, or , if is odd.
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Alternative Proxies: