beta2(mu, phi)
: Beta
distribution reparameterised by mean mu
and precision
phi
bcpe(mu, sigma, nu, tau)
:
Box-Cox power exponential distribution parameterised by location
mu
, scale sigma
, nu
, and
tau
bccg(mu, sigma, nu)
:
Box-Cox Cole and Green distribution parameterised by location
mu
, scale sigma
, and skewness
nu
bct(mu, sigma, nu, tau)
:
Box-Cox t-distribution parameterised by location mu
, scale
sigma
, skewness nu
, and degrees of freedom
tau
exgauss(mu, sigma, lambda)
:
Exponentially modified Gaussian distribution parameterised by location
mu
, scale sigma
and rate
lambda
foldnorm(mu, sigma)
:
Folded normal distribution parameterised by location mu
and
scale sigma
gamma2(mean, sd)
: Gamma
distribution reparameterised by mean and standard deviation
gumbel(location, scale)
:
Gumbel distribution parameterised by location and scale
invgauss(mean, shape)
:
Inverse Gaussian distribution parameterised by mean and shape
laplace(mu, b)
:
Laplace distribution parameterised by location mu
and scale
b
oibeta(shape1, shape2, oneprob)
:
One-inflated beta distribution parameterised by shape parameters
shape1
, shape2
and one-probability
oneprob
oibeta2(mu, phi, oneprob)
:
One-inflated beta distribution reparameterised by mean mu
,
precision phi
, and one-probability
oneprob
pareto(mu)
:
Pareto distribution parameterised by mu
powerexp(mu, sigma, nu)
:
Power exponential distribution parameterised by mean mu
,
standard deviation sigma
and shape nu
powerexp2(mu, sigma, nu)
:
Power exponential distribution reparameterised by location
mu
, scale sigma
and shape
nu
skewnorm(xi, omega, alpha)
:
Skew normal distribution parameterised by location xi
,
scale omega
and skewness alpha
skewnorm2(mean, sd, alpha)
:
Skew normal distribution reparameterised by mean, standard deviation and
skewness alpha
skewt(mu, sigma, skew, df)
:
Skew t-distribution parameterised by location mu
, scale
sigma
, skewness skew
and degrees of freedom
df
truncnorm(mean, sd, min, max)
:
Truncated normal distribution parameterised by mean, standard deviation,
lower bound min
and upper bound max
trunct(df, min, max)
:
Truncated t-distribution parameterised by degrees of freedom
df
, lower bound min
and upper bound
max
trunct2(df, mu, sigma, min, max)
:
Truncated t-distribution parameterised location mu
, scale
sigma
, degrees of freedom df
, lower bound
min
and upper bound max
t2(mu, sigma, df)
:
Non-central and scaled t-distribution parameterised by location
mu
, scale sigma
and degrees of freedom
df
vm(mu, kappa)
:
Von Mises distribution parameterised by mean direction mu
and concentration kappa
wrpcauchy(mu, rho)
:
Wrapped Cauchy distribution parameterised by mean direction
mu
and concentration rho
zibeta(shape1, shape2, zeroprob)
:
Zero-inflated beta distribution parameterised by shape parameters
shape1
, shape2
and zero-probability
zeroprob
zibeta2(mu, phi, zeroprob)
:
Zero-inflated beta distribution reparameterised by mean mu
,
precision phi
, and zero-probability
zeroprob
zigamma(shape, scale, zeroprob)
:
Zero-inflated gamma distribution parameterised by shape and scale, with
a zero-probability zeroprob
zigamma2(mean, sd, zeroprob)
:
Zero-inflated gamma distribution reparameterised by mean, standard
deviation and zero-probability zeroprob
ziinvgauss(mean, shape, zeroprob)
:
Zero-inflated inverse Gaussian distribution parameterised by mean, shape
and zero-probability zeroprob
zoibeta(shape1, shape2, zeroprob, oneprob)
:
Zero- and one-inflated beta distribution parameterised by shape
parameters shape1
, shape2
, zero-probability
zeroprob
and one-probability oneprob
zoibeta2(mu, phi, zeroprob, oneprob)
:
Zero- and one-inflated beta distribution reparameterised by mean
mu
, precision phi
, zero-probability
zeroprob
and one-probability oneprob