Description Usage Arguments Details Value See also Examples
prepare_em_cm
takes a two-column matrix whose rows form
iid samples from a bivariate chi-bar-squared distribution and
prepares the data used in maximum likelihood estimation.
1 | prepare_em_cm(d, low, upp, m_samp)
|
d |
the dimension of the bivariate chi-bar squared distribution. |
low |
lower bound for |
upp |
upper bound for |
m_samp |
two-column matrix whose rows from iid samples from a bivariate chi-bar-squared distribution. |
This function works pretty much exactly as prepare_em
from the
conivol
package, the only difference being that the "boundary
cases" k==0,n
do not have to be considered/are ignored.
In the general case this is not needed, but for the curvature
measures this is a useful feature.
The output of prepare_em_cm
is (low-upp+1)
row matrix whose
k
th row contains the products of the density values of the chi_k^2
and chi_(d-k)^2 distributions evaluated in the sample points;
the row-form of the matrix is more convenient for the computations.
prepare_em
,
constr_eigval
,
constr_eigval_to_bcbsq
,
estim_em_cm
Package: symconivol
1 2 3 4 5 6 | CM <- curv_meas_exact(4,3)$A[,2]
CM <- CM/sum(CM)
m_samp <- conivol::rbichibarsq(1e5,CM)
str( prepare_em_cm( 15, 1, 9, m_samp ))
|
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