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32-digit values of the first 100 recurrence coefficients using the Bose-Einstein weight function: w(x)=[x/(e^x-1)]^4 computed by the SOPQ routine sr_boseeinstein(100,4,32)
2016-10-17 13:19:43 | Datasets | Contributor(s): Walter Gautschi | doi:10.4231/R7000013
https://purr.purdue.edu/publications/1480
32-digit values of the first 100 recurrence coefficients relative to the Bose-Einstein weight function w(x)=[x/(e^x-1)]^3 computed by the SOPQ routine sr_boseeinstein(100,3,32)
2016-10-17 13:17:20 | Datasets | Contributor(s): Walter Gautschi | doi:10.4231/R73R0QRQ
https://purr.purdue.edu/publications/1479
32-digit values of the first 100 recurrence coefficients relative to the Bose-Einstein weight function w(x)=[x/(e^x-1)]^2 computed by the SOPQ routine sr_boseeinstein(100,2,32)
2016-10-13 19:21:14 | Datasets | Contributor(s): Walter Gautschi | doi:10.4231/R77H1GGF
https://purr.purdue.edu/publications/1478
32-digit values of the first 100 recurrence coefficients relative to the Bose-Einstein weight function w(x)=x/(e^x-1) computed by the SOPQ routine sr_boseeinstein(100,1,32)
2016-10-13 16:31:56 | Datasets | Contributor(s): Walter Gautschi | doi:10.4231/R7H12ZX3
https://purr.purdue.edu/publications/1476
32-digit values of the first 100 recurrence coefficients relative to the Theodorus weight function w(x)=x^{1/2}/(e^x-1) on R_{+} computed by the routine sr_theodorus(100,32)
2016-10-12 13:01:51 | Datasets | Contributor(s): Walter Gautschi | doi:10.4231/R71Z4290
https://purr.purdue.edu/publications/1472
SOPQ: Symbolic OPQ
2015-12-30 00:00:00 | Datasets | Contributor(s): Walter Gautschi | doi:10.4231/R7ZG6Q6T
https://purr.purdue.edu/publications/1560
2014-04-22 10:42:19 | Datasets | Contributor(s): Walter Gautschi | doi:10.4231/R7000013
2014-04-22 10:41:38 | Datasets | Contributor(s): Walter Gautschi | doi:10.4231/R73R0QRQ
2014-04-22 10:40:50 | Datasets | Contributor(s): Walter Gautschi | doi:10.4231/R77H1GGF
2014-04-22 09:55:32 | Datasets | Contributor(s): Walter Gautschi | doi:10.4231/R7H12ZX3
2014-04-22 08:12:17 | Datasets | Contributor(s): Walter Gautschi | doi:10.4231/R71Z4290