| tau-utils {LambertW} | R Documentation |
All functions here are for the transformation parameter vector τ = (μ_x, σ_x, γ, δ, α).
check_tau checks if τ is correctly specified (correct names, non-negativity
constraints, etc.)
complete_tau completes missing values so users don't have to specify
every element of τ explicitly. 'mu_x' and
'sigma_x' must be specified, but alpha = 1, gamma =
0, and delta = 0 will be set automatically if missing.
get_initial_tau provides starting estimates for τ.
normalize_by_tau shifts and scales data given the tau vector as
(data - μ_x) / σ_x.
Parameters μ_x and σ_x are not necessarily mean and
standard deviation in the τ vector; that depends on the family
type and use.mean.variance (for location families they usually are
mean and standard deviation if use.mean.variance = TRUE; for scale
and non-location non-scale families they are just location/scale
parameters for the transformation).
tau2theta converts τ to the parameter list θ
(inverse of theta2tau).
tau2type guesses the type ('s', 'h', 'hh') from the names
of tau vector; thus make sure tau is named correctly.
check_tau(tau)
complete_tau(tau, type = tau2type(tau))
get_initial_tau(y, type = c("h", "hh", "s"), location.family = TRUE)
normalize_by_tau(data, tau, inverse = FALSE)
tau2theta(tau, beta)
tau2type(tau)
tau |
named vector τ which defines the variable transformation.
Must have at least |
type |
type of Lambert W \times F distribution: skewed |
y |
a numeric vector of real values (the observed data). |
location.family |
logical; if |
data |
numeric; a numeric object in R. Usually this is either
|
inverse |
logical; if |
beta |
numeric vector (deprecated); parameter \boldsymbol β of
the input distribution. See |
check_tau throws an error if τ does not define a proper
transformation.
complete_tau returns a named numeric vector.
get_initial_tau returns a named numeric vector.
tau2theta returns a list with entries alpha, beta,
gamma, and delta.
tau2type returns a string: either "s", "h", or
"hh".