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Hi all
Are there inverse probability distribution functions in MKL? For example, x = poissinv(p,lambda), this function generate a number x at the probability p using poisson distribution.
Are there inverse probability distribution functions in MKL? For example, x = poissinv(p,lambda), this function generate a number x at the probability p using poisson distribution.
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See as an example, Exponential (vsrngexponential), Laplace(vsrnglaplace) and many others VSL functions support inverse cumulative distribution..
--Gennady
--Gennady
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That is not my point. I looking for inverse functions that provide rands at a given probability. For example, norminv(p,mu,sigma), in which p is specified by user.
By the way, I could not find spectial functions gamma() in MKL for Linux. But I found this link mention it
http://www.intel.com/software/products/compilers/docs/clin/main_cls/cref_cls/common/cppref_math_special.htm
By the way, I could not find spectial functions gamma() in MKL for Linux. But I found this link mention it
http://www.intel.com/software/products/compilers/docs/clin/main_cls/cref_cls/common/cppref_math_special.htm
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Quoting - yjyincj
That is not my point. I looking for inverse functions that provide rands at a given probability. For example, norminv(p,mu,sigma), in which p is specified by user.
By the way, I could not find spectial functions gamma() in MKL for Linux. But I found this link mention it
http://www.intel.com/software/products/compilers/docs/clin/main_cls/cref_cls/common/cppref_math_special.htm
By the way, I could not find spectial functions gamma() in MKL for Linux. But I found this link mention it
http://www.intel.com/software/products/compilers/docs/clin/main_cls/cref_cls/common/cppref_math_special.htm
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Quoting - yjyincj
Any idea on this? Thanks.
Hello,
Could you please specify exactly what do you mean when you saying 'provide rands at a given probability'?
Because, for instance probability, mean and dispersion values for continuous normal distribution doesn't specify interval of random values unambiguously.
Thanks,
Art
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