VVm are generic methods that can (and should) be
used to compute the variance of the vocabulary size and the variances
of spectrum elements according to an LNRE model (i.e. an object of
lnre). These methods are also used to access variance
information stored in some objects of class
an object of class
positive integer value determining the frequency class m for which variances are returned (or a vector of such values).
sample size N for which variances are calculated
additional arguments passed on to the method implementation (see respective manpages for details)
vgc objects must represent an expected or
interpolated frequency spectrum or VGC, and must include variance
vgc objects, the
VVm method allows only a single
m to be specified.
N is only allowed for LNRE models and will trigger
an error message otherwise.
For a LNRE model (class
VV computes the variance
of the random variable V(N) (vocabulary size), and
computes the variance of the random variables V_m(N) (spectrum
elements), for a sample of specified size N.
For an observed or interpolated frequency spectrum (class
VV returns the variance of the expected vocabulary size, and
VVm returns variances of the spectrum elements. These methods
are only applicable if the
spc object includes variance
For an expected or interpolated vocabulary growth curve (class
VV returns the variance vector of the expected
vocabulary sizes V, and
VVm the corresponding vector for
V_m. These methods are only applicable if the
includes variance information.
Expected vocabulary size and frequency spectrum for a sample of size
N according to a LNRE model can be computed with the analogous
vgc objects, V and V_m are always accessed with the
Vm, even if they represent
expected or interpolated values.
## see lnre documentation for examples