dnestlog {BMAmevt}  R Documentation 
Likelihood function (spectral density) and random generator in the Pairwise Beta and NL models.
dnestlog(
x = rbind(c(0.1, 0.3, 0.6), c(0.3, 0.3, 0.4)),
par = c(0.5, 0.5, 0.2, 0.3),
log = FALSE,
vectorial = TRUE
)
dpairbeta(
x,
par = c(1, rep(2, choose(4, 2) + 1)),
log = FALSE,
vectorial = TRUE
)
rnestlog(
n = 5,
par = c(0.2, 0.3, 0.4, 0.5),
threshold = 1000,
return.points = FALSE
)
rpairbeta(n = 1, dimData = 3, par = c(1, rep(1, 3)))
x 
An angular data set (may be reduced to a single point).
A 
par 
The parameter for the Pairwise Beta or the Nested Logistic density.

log 
Logical. Should the density be returned on the log scale ? 
vectorial 
Logical. Should a vector or a single value be returned ? 
n 
The number of points on the simplex to be generated. 
threshold 
The radial threshold
to hold. 
return.points 
logical: should the censored vectorial dataset corresponding to the angular one be returned ? 
dimData 
the dimension of the sample space, which is 
Applies to angular data sets. The density is given with respect to the Lebesgue measure on R^{p1}
, where p
is the number of columns in x
(or the length of x
, if the latter is a single point).
The value returned by the likelihood function is imposed (see
e.g. posteriorMCMC
.
In contrast, the random variable have unconstrained output format.
dpairbeta
returns the likelihood as a single number if vectorial ==FALSE
, or as a vector of size nrow(x)
containing the likelihood of each angular data point. If log == TRUE
, the loglikelihood is returned instead.
rpairbeta
returns a matrix with n
rows and dimData
columns.
dnestlog
returns the likelihood as a single number if vectorial ==FALSE
, or as a vector of size nrow(x)
containing the likelihood of each angular data point. If log == TRUE
, the loglikelihood is returned instead.
rnestlog
returns a matrix with n
rows and dimData
columns if return.points==FALSE
(the default). Otherwise,
a list is returned, with two elements:
Angles
: The angular data set
Points
: The full trivariate data set above
threshold
(i.e. Angles
multiplied by the radial components)