wishmom_sym | R Documentation |
When iw = 0
, the function returns an analytical expression of
E[\prod_{j=1}^r \mbox{tr}(W^j)^{f_j}]
, where W \sim W_m^{\beta}(n, S)
.
When iw != 0
, the function returns an analytical expression of
E[\prod_{j=1}^r \mbox{tr}(W^j)^{f_j}W^{iw}]
.
For a given f
, iw
, and alpha
, this function provides the aforementioned
expectations in terms of the variables n
and \Sigma
.
wishmom_sym(f, iw = 0, alpha = 2, latex = FALSE)
f |
A vector of nonnegative integers |
iw |
The power of the beta-Wishart matrix |
alpha |
The type of Wishart distribution
|
latex |
A Boolean indicating whether the output will be a LaTeX string or a dataframe (FALSE by default) |
When iw = 0
, it returns an analytical expression of
E[\prod_{j=1}^r \mbox{tr}(W^j)^{f_j}]
.
When iw != 0
, it returns an analytical expression of
E[\prod_{j=1}^r \mbox{tr}(W^j)^{f_j}W^{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 \Sigma
.
# Example 1: For E[tr(W)^4] with W ~ W_m^1(n,Sigma), represented as a dataframe:
wishmom_sym(4) # iw = 0, for real Wishart distribution
# Example 2: For E[tr(W)*tr(W^2)W] with W ~ W_m^1(n,S), represented as a dataframe:
wishmom_sym(c(1, 1), 1) # iw = 1, for real Wishart distribution
# Example 3: For E[tr(W)^4] with W ~ W_m^2(n,S), represented as a LaTeX string:
# Using writeLines() to format
writeLines(wishmom_sym(4, 0, 1, latex=TRUE)) # iw = 0, for complex Wishart distribution
# Example 4: For E[tr(W)*tr(W^2)W] with W ~ W_m^2(n,S), represented as a LaTeX string:
# Using writeLines() to format
writeLines(wishmom_sym(c(1, 1), 1, 1, latex=TRUE)) # iw = 1, for real Wishart distribution
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