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  1. 32-digit values of the first 100 recurrence coefficients for the half-range generalized Hermite weight function with exponent 0

    2016-11-29 15:07:32 | Datasets | Contributor(s): Walter Gautschi | doi:10.4231/R7ZP443R

    32-digit values of the first 100 recurrence coefficients for the weight function w(x)=x^(2*mu)*exp(-x^2) on [0,Inf], mu=0

    https://purr.purdue.edu/publications/1490

  2. 32-digit values of the first 100 recurrence coefficients for the Bose-Einstein-type weight function with exponent 4

    2016-11-29 13:20:40 | Datasets | Contributor(s): Walter Gautschi | doi:10.4231/R7765C8X

    32-digit values of the first 100 recurrence coefficients for the weight function w(x)=[x/(exp(x)-1)]^r on [0,Inf], r=4

    https://purr.purdue.edu/publications/1480

  3. 32-digit values of the first 100 recurrence coefficients for the Bose-Einstein-type weight function with exponent 3

    2016-11-29 13:20:09 | Datasets | Contributor(s): Walter Gautschi | doi:10.4231/R7BZ640B

    32-digit values of the first 100 recurrence coefficients for the weight function w(x)=[x/(exp(x)-1)]^r on [0,Inf], r=3

    https://purr.purdue.edu/publications/1479

  4. 32-digit values of the first 100 recurrence coefficients for the Bose-Einstein-type weight function with exponent 2

    2016-11-30 16:49:07 | Datasets | Contributor(s): Walter Gautschi | doi:10.4231/R7GQ6VQ8

    32-digit values of the first 100 recurrence coefficients for the weight function w(x)=[x/(exp(x)-1)]^r on [0,Inf], r=2

    https://purr.purdue.edu/publications/1478

  5. 32-digit values of the first 100 recurrence coefficients for the Bose-Einstein weight function

    2016-11-30 16:48:34 | Datasets | Contributor(s): Walter Gautschi | doi:10.4231/R7MG7MGF

    32-digit values of the first 100 recurrence coefficients for the weight function w(x)=[x/(exp(x)-1)]^r on [0,Inf], r=1

    https://purr.purdue.edu/publications/1476

  6. 32-digit values of the first 100 recurrence coefficients for the Freud weight function with exponent 8

    2016-11-29 13:23:13 | Datasets | Contributor(s): Walter Gautschi | doi:10.4231/R7R78C5Q

    32-digit values of the first 100 recurrence coefficients for the weight function w(x)=x^mu*exp(-x^nu) on [-Inf,Inf], mu=0, nu=8

    https://purr.purdue.edu/publications/1489

  7. 32-digit values of the first 100 recurrence coefficients for the Freud weight function with exponent 4

    2016-11-29 13:21:13 | Datasets | Contributor(s): Walter Gautschi | doi:10.4231/R7VX0DHD

    32-digit values of the first 100 recurrence coefficients for the weight function w(x)=x^mu*exp(-x^nu) on [-Inf,Inf], mu=0, nu=4

    https://purr.purdue.edu/publications/1487

  8. 32-digit values of the first 100 recurrence coefficients for the Freud weight function with exponent 10

    2016-11-29 13:24:20 | Datasets | Contributor(s): Walter Gautschi | doi:10.4231/R74F1NPK

    32-digit values of the first 100 recurrence coefficients for the weight function w(x)=x^mu*exp(-x^nu) on [-Inf,Inf], mu=0, nu=10

    https://purr.purdue.edu/publications/1486

  9. 32-digit values of the first 100 recurrence coefficients for the Fermi-Dirac weight function

    2016-11-29 13:32:22 | Datasets | Contributor(s): Walter Gautschi | doi:10.4231/R7HQ3WW3

    32-digit values of the first 100 recurrence coefficients for the weight function w(x)=[1/(exp(x)+1)]^r on [0,Inf], r=1

    https://purr.purdue.edu/publications/1481

  10. POEXPINT: Polynomials orthogonal with respect to the exponential integral

    2014-04-28 14:27:31 | Datasets | Contributor(s): Walter Gautschi | doi:10.4231/R7X34VD9

    Matlab scripts for computing orthogonal polynomials whose weight function involves an exponential integral

    https://purr.purdue.edu/publications/1587

  11. NEUTRAL: Neutralizing nearby singularities in numerical quadrature

    2014-04-23 08:27:11 | Datasets | Contributor(s): Walter Gautschi | doi:10.4231/R75H7D6P

    Matlab routines for neutralizing nearby singularities in numerical quadrature

    https://purr.purdue.edu/publications/1579

  12. RMOP: Repeated modifications of orthogonal polynomials

    2014-04-23 08:25:49 | Datasets | Contributor(s): Walter Gautschi | doi:10.4231/R7F18WNB

    Matlab routines and data sets that compute repeated modifications of orthogonal polynomials

    https://purr.purdue.edu/publications/1577

  13. SRJAC: Sub-range Jacobi polynomials

    2014-04-23 08:24:06 | Datasets | Contributor(s): Walter Gautschi | doi:10.4231/R7JS9NCR

    Matlab routines for computing sub-range Jacobi polynomials within the sub interval of [-1, 1]

    https://purr.purdue.edu/publications/1576

  14. GQLOG: Matlab routines for computing Gauss Quadrature rules with logarithmic weight functions

    2014-04-23 08:28:47 | Datasets | Contributor(s): Walter Gautschi | doi:10.4231/R72R3PMB

    Matlab routines for computing Gauss Quadrature rules with logarithmic weight functions

    https://purr.purdue.edu/publications/1571

  15. OWF: Matlab programs for computing orthogonal polynomials with respect to densely oscillating and exponentially decaying weight functions

    2014-04-23 08:26:04 | Datasets | Contributor(s): Walter Gautschi | doi:10.4231/R7NK3BZ7

    Software (in Matlab) is developed for computing variable-precision recurrence coefficients for orthogonal polynomials with respect to densely oscillating and exponentially decaying weight functions

    https://purr.purdue.edu/publications/1562

  16. NUMINT: Numerical Integration over the square

    2014-04-23 08:26:33 | Datasets | Contributor(s): Walter Gautschi | doi:10.4231/R7PK0D31

    Matlab routines for computing numerical integration over the square

    https://purr.purdue.edu/publications/1575

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