This function extracts distribution families from R-packages along with their parameters and characteristics, and scans specific packages if desired.
getFamilies(all.packages)
character vector or missing or logical; package names in which to scan:
the distribution families given
TRUE
all installed packages
FALSE
base packages of R
If missing, a list of recognized families is returned.
A list of lists. Each sublist pertains to exactly one distribution family (such as ‘norm’ from ‘stats’) and contains:
character; name of the package containing the family
character; name of the family, as defined under “Details”
lower
:
named numeric vector; lower bounds for distribution parameters
upper
:
named numeric vector; upper bounds for distribution parameters
accepts_float
:
named logical vector; whether each parameter can be any real
number (TRUE
) or only integers are valid inputs (FALSE
)
defaults
:
names numeric vector; set of default parameters that jointly constitute valid
input. Used for optimisation.
log
:
logical; whether log values are provided by the density function
discrete
:
logical; whether the distribution itself (not the parameters) takes on
discrete values only
support_min
:
numeric; lower bound of the support, i.e. lowest value of \(x\)
where \(f(x) > 0\) numerically for any valid parameter set, \(f\) the density function
support_max
:
numeric; upper bound of the support
support_max_depends_on
:
named logical vector; whether support_max
depends on the value of each
parameter
support_min_depends_on
:
named logical vector; whether support_min
depends on the value of each
parameter
This function retrieves distribution families from R-packages as specified
in ‘arguments’. A distribution family is defined as follows:
Take the functions dnorm
, pnorm
, qnorm
and rnorm
from the package ‘stats’. These functions are related to sampling,
density etc. of the normal distribution. The family name is the part of
the function name without the prefixes ‘d’, ‘p’, ‘q’, or
‘r’ , in this case: ‘norm’.
# NOT RUN {
str(getFamilies())
# }
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