When type.cens is different from mixed, this variable can be equal to 1 if the event occurredĪnd 0 otherwise. Here margin can be 'PH' (generalised proportional hazards), 'PO' (generalised proportional odds), Is used for binary responses and is more stable and faster than the R package bgeva). Poisson ('ZTP'), negative binomial - type I ('NBI'), negativeīinomial - type II ('NBII'), Poisson inverse Gaussian ('PIG'), generalised extreme value link function ('GEVlink', this Singh-Maddala ('SM'), beta ('BE'), Fisk ('FISK', also known as log-logistic distribution), Poisson ('PO'), zero truncated Under the scenario in which shape = 0 ('DGP0'), logistic ('LO'), Weibull ('WEI'), inverse Gaussian ('iG'), gamma ('GA'), Dagum ('DAGUM'), Generelised Pareto (with orthogonal parametrisation) ('GPo') where the shape parameter is forced to be > -0.5,ĭiscrete generelised Pareto II ('DGPII') where the shape parameter is forced to be positive, discrete generelised Pareto derived Generelised Pareto II ('GPII') where the shape parameter is forced to be > -0.5, Log-normal ('LN'), Gumbel ('GU'), reverse Gumbel ('rGU'), generelised Pareto ('GP'), Optional vector specifying a subset of observations to be used in the fitting process. Optional vector of prior weights to be used in fitting. Variables are taken from environment(formula), typically the environment from which gamlss is called. This should contain one or more equations.Īn optional data frame, list or environment containing the variables in the model.

Sp.method = 'perf', hrate = NULL, d.lchrate = NULL, d.rchrate = NULL,ĭ.lchrate.td = NULL, d.rchrate.td = NULL, truncation.time = NULL, Informative = 'no', v = NULL, margin2 = 'PH',ĭ = TRUE, siginit = NULL, shinit = NULL, Robust = FALSE, rc = 3, lB = NULL, uB = NULL, infl.fac = 1, Margin = 'N', surv = FALSE, cens = NULL, type.cens = 'R', upperB = NULL, Gamlss(formula, data = list(), weights = NULL, subset = NULL, Have been parametrised according to Rigby and Stasinopoulos (2005). Univariate models using the general estimation approach of this package. The purpose of this function was only to provide, in some cases, starting valuesįor the simultaneous models in the package, but it has now been made available in the form of a proper function should the user wish to fit Gamlss fits flexible univariate regression models with several continuous and discrete distributions, and types of covariateĮffects.

Generalised Additive Models for Location, Scale and Shape Description

Show z1 u z2 is a null set