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词汇 hypergeometric
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Examples of hypergeometric


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The equation admits exact solutions in terms of confluent hypergeometric functions.
The moving interfaces are parameterized by conformal maps given in terms of hypergeometric functions.
These solutions again express the free boundary in terms of a conformal mapping from a known auxiliary domain, but the conformal mapping is here given in terms of hypergeometric functions.
The fact that this 0.d. e. is the wellknown confluent hypergeometric equation is not critical ; the methods of saddlepoint approximation and turning-point analysis used are quite general.
As in the previous subsection, there are 3 strong regular singularities, so we can represent the solution as a linear combination of solutions of hypergeometric functions.
The statement (3) can be proved by using hypergeometric function.
Rather, one should use the exact distribution, which is hypergeometric.
A useful framework for working with these functions is the class of generalized hypergeometric functions.
The most sophisticated is to calculate the selection response assuming a discrete hypergeometric distribution, with variance derived from (15).
The advantage of this is that solutions to the hypergeometric equation are well-known.
The second linearly independent solution can also be obtained and is also a linear combination of hypergeometric functions.
In this case, the exact weights of different groups are given by a hypergeometric distribution.
This enables us, for = 0, to express its solutions in terms of hypergeometric functions.
So, there are actually 6 auxiliary spaces associated with 6 hypergeometric equations of which the spaces (4.4)-(4.7) are only two of them.
The response is found to be given as the difference between two summed series, where each term in the series involves the confluent hypergeometric function.
The solution for this case (which satisfies the appropriate free-stream boundary condition) is given by a confluent hypergeometric function.
The most basic example for the martingale inequalities involves the binomial distribution: here we include the hypergeometric distribution naturally in the same inequalities.
His method uses a sequential sampling scheme involving a hypergeometric probability distribution to determine the required sample size for this verification.
The second is the distribution of magnitudes of complexity cascades, which occur as hypergeometric runs.
Instead, we use explicit relations for the hypergeometric and confluent hypergeometric functions, which, as we shall see below, have themselves the form of the isomonodromy mappings.


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