Dirichlet average Contents Notable Dirichlet averages References Navigation...


Calculus


Dirichlet densityhypergeometric functionsorthogonal polynomialselliptic integralsCarlson symmetric formBayesian analysis




Dirichlet averages are averages of functions under the Dirichlet density. An important one are dirichlet averages that have a certain argument structure, namely


F(b;z)=∫f(u⋅z)dμb(u),{displaystyle F(mathbf {b} ;mathbf {z} )=int f(mathbf {u} cdot mathbf {z} ),dmu _{b}(mathbf {u} ),}

where u⋅z=∑iNui⋅zi{displaystyle mathbf {u} cdot mathbf {z} =sum _{i}^{N}u_{i}cdot z_{i}} and b(u)=u1b1−1⋯uNbN−1du{displaystyle dmu _{b}(mathbf {u} )=u_{1}^{b_{1}-1}cdots u_{N}^{b_{N}-1}dmathbf {u} } is the Dirichlet measure with dimension N. They were introduced by the mathematician Bille C. Carlson in the '70s who noticed that the simple notion of this type of averaging generalizes and unifies many special functions, among them generalized hypergeometric functions or various orthogonal polynomials:[1]. They also play an important role for the solution of elliptic integrals (see Carlson symmetric form) and are connected to statistical applications in various ways, for example in Bayesian analysis [2].




Contents






  • 1 Notable Dirichlet averages


    • 1.1 R-function


    • 1.2 S-function




  • 2 References





Notable Dirichlet averages


Some Dirichlet averages are so fundamental that they are named. A few are listed below.



R-function


The (Carlson) R-function is the Dirichlet average of xn{displaystyle x^{n}},


Rn(b,z)=∫(u⋅z)ndμb(u){displaystyle R_{n}(mathbf {b} ,mathbf {z} )=int (mathbf {u} cdot mathbf {z} )^{n},dmu _{b}(mathbf {u} )}

with n{displaystyle n}. Sometimes Rn(b,z){displaystyle R_{n}(mathbf {b} ,mathbf {z} )} is also denoted by R(−n;b,z){displaystyle R(-n;mathbf {b} ,mathbf {z} )}.


Exact solutions:


For n≥0,n∈N{displaystyle ngeq 0,nin mathbb {N} } it is possible to write an exact solution in the form of an iterative sum[3]


Rn(b,z)=Γ(n+1)Γ(b)Γ(b+n)⋅Dn with Dn=1n∑k=1n(∑i=1Nbi⋅zik)⋅Dn−k{displaystyle R_{n}(mathbf {b} ,mathbf {z} )={frac {Gamma (n+1)Gamma (b)}{Gamma (b+n)}}cdot D_{n}{text{ with }}D_{n}={frac {1}{n}}sum _{k=1}^{n}left(sum _{i=1}^{N}b_{i}cdot z_{i}^{k}right)cdot D_{n-k}}

where D0=1{displaystyle D_{0}=1}, N{displaystyle N} is the dimension of b{displaystyle mathbf {b} } or z{displaystyle mathbf {z} } and b=∑bi{displaystyle b=sum b_{i}}.



S-function


The (Carlson) S-function is the Dirichlet average of ex{displaystyle e^{x}},


S(b,z)=∫exp⁡(u⋅z)dμb(u).{displaystyle S(mathbf {b} ,mathbf {z} )=int exp(mathbf {u} cdot mathbf {z} ),dmu _{b}(mathbf {u} ).}


References





  1. ^ Carlson, B.C. (1977). Special functions of applied mathematics..mw-parser-output cite.citation{font-style:inherit}.mw-parser-output .citation q{quotes:"""""""'""'"}.mw-parser-output .citation .cs1-lock-free a{background:url("//upload.wikimedia.org/wikipedia/commons/thumb/6/65/Lock-green.svg/9px-Lock-green.svg.png")no-repeat;background-position:right .1em center}.mw-parser-output .citation .cs1-lock-limited a,.mw-parser-output .citation .cs1-lock-registration a{background:url("//upload.wikimedia.org/wikipedia/commons/thumb/d/d6/Lock-gray-alt-2.svg/9px-Lock-gray-alt-2.svg.png")no-repeat;background-position:right .1em center}.mw-parser-output .citation .cs1-lock-subscription a{background:url("//upload.wikimedia.org/wikipedia/commons/thumb/a/aa/Lock-red-alt-2.svg/9px-Lock-red-alt-2.svg.png")no-repeat;background-position:right .1em center}.mw-parser-output .cs1-subscription,.mw-parser-output .cs1-registration{color:#555}.mw-parser-output .cs1-subscription span,.mw-parser-output .cs1-registration span{border-bottom:1px dotted;cursor:help}.mw-parser-output .cs1-ws-icon a{background:url("//upload.wikimedia.org/wikipedia/commons/thumb/4/4c/Wikisource-logo.svg/12px-Wikisource-logo.svg.png")no-repeat;background-position:right .1em center}.mw-parser-output code.cs1-code{color:inherit;background:inherit;border:inherit;padding:inherit}.mw-parser-output .cs1-hidden-error{display:none;font-size:100%}.mw-parser-output .cs1-visible-error{font-size:100%}.mw-parser-output .cs1-maint{display:none;color:#33aa33;margin-left:0.3em}.mw-parser-output .cs1-subscription,.mw-parser-output .cs1-registration,.mw-parser-output .cs1-format{font-size:95%}.mw-parser-output .cs1-kern-left,.mw-parser-output .cs1-kern-wl-left{padding-left:0.2em}.mw-parser-output .cs1-kern-right,.mw-parser-output .cs1-kern-wl-right{padding-right:0.2em}


  2. ^ Dickey, J.M. (1983). "Multiple hypergeometric functions: Probabilistic interpretations and statistical uses". Journal of the American Statistical Association. 78 (383): 628.


  3. ^ Glüsenkamp, T. (2018). "Probabilistic treatment of the uncertainty from the finite size of weighted Monte Carlo data". EPJ Plus. 133 (6): 218. arXiv:1712.01293. doi:10.1140/epjp/i2018-12042-x.








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