theta {madness} | R Documentation |
Estimate the symmetric second moment array of values.
Description
Given rows of observations of some vector (or multidimensional
data), estimates the second moment by taking a simple mean,
returning a madness
object.
Usage
theta(X, vcov.func=vcov, xtag=NULL)
Arguments
X |
a multidimensional array (or a data frame) of observed values. |
vcov.func |
a function which takes an object of class |
xtag |
an optional string tag giving the name of the input data. defaults to figuring it out from the input expression. |
Details
Given a
n\times k_1 \times k_2 \times ... \times k_l
array whose 'rows' are independent observations of X
, computes the
k_1 \times k_2 \times ... \times k_l \times k_1 \times k_2 ... k_l
array of the mean of \mathrm{outer}(X,X)
based on n
observations,
returned as a madness
object. The variance-covariance
is also estimated, and stored in the object.
One may use the default method for computing covariance,
via the vcov
function, or via a 'fancy' estimator,
like sandwich:vcovHAC
, sandwich:vcovHC
, etc.
Value
A madness
object representing the mean of the outer
product of the tail dimensions of X
.
Author(s)
Steven E. Pav shabbychef@gmail.com
See Also
Examples
set.seed(123)
X <- matrix(rnorm(1000*3),ncol=3)
th <- theta(X)
## Not run:
if (require(sandwich)) {
th2 <- theta(X,vcov.func=vcovHC)
}
## End(Not run)
# works on data frames too:
set.seed(456)
X <- data.frame(a=runif(100),b=rnorm(100),c=1)
th <- theta(X)