Symbolic Expectation of a Matrix-valued Function of an Inverse beta-Wishart Distribution
Symbolic Expectation of a Matrix-valued Function of an Inverse beta-Wishart Distribution
When iw = 0, the function returns an analytical expression of E[∏j=1r\mboxtr(W−j)fj], where W∼Wmβ(n,S). When iw != 0, the function returns an analytical expression of E[∏j=1r\mboxtr(W−j)fjW−iw]. For a given f, iw, and alpha, this function provides the aforementioned expectations in terms of the variables n~ and Σ.
iwishmom_sym(f, iw =0, alpha =2, latex =FALSE)
Arguments
f: A vector of nonnegative integers fj that represents the power of \mboxtr(W−j), where j=1,…,r
iw: The power of the inverse beta-Wishart matrix W−1 (0 by default)
alpha: The type of Wishart distribution (α=2/β):
1/2: Quaternion Wishart
1: Complex Wishart
2: Real Wishart (default)
latex: A Boolean indicating whether the output will be a LaTeX string or dataframe (FALSE by default)
Returns
When iw = 0, it returns an analytical expression of E[∏j=1r\mboxtr(W−j)fj]. When iw != 0, it returns an analytical expression of E[∏j=1r\mboxtr(W−j)fjW−iw]. If latex = FALSE, the output is a data frame that stores the coefficients for calculating the result. If latex = TRUE, the output is a LaTeX formatted string of the result in terms of n~ and Σ.
Examples
# Example 1: For E[tr(W^{-1})^4] with W ~ W_m^1(n,Sigma), represented as a dataframe:iwishmom_sym(4)# iw = 0, for real Wishart distribution# Example 2: For E[tr(W^{-1})*tr(W^{-2})W^{-1}] with W ~ W_m^1(n,S), represented as a dataframe:iwishmom_sym(c(1,1),1)# iw = 1, for real Wishart distribution# Example 3: For E[tr(W^{-1})^4] with W ~ W_m^2(n,S), represented as a LaTeX string:# Using writeLines() to formatwriteLines(iwishmom_sym(4,0,1, latex=TRUE))# iw = 0, for complex Wishart distribution# Example 4: For E[tr(W^{-1})*tr(W^{-2})W^{-1}] with W ~ W_m^2(n,S), represented as a LaTeX string:# Using writeLines() to formatwriteLines(iwishmom_sym(c(1,1),1,1, latex=TRUE))# iw = 1, for real Wishart distribution