link {INLA} | R Documentation |
Define link-functions and its inverse
inla.link.log(x, inverse=FALSE) inla.link.invlog(x, inverse=FALSE) inla.link.neglog(x, inverse=FALSE) inla.link.invneglog(x, inverse=FALSE) inla.link.logit(x, inverse=FALSE) inla.link.invlogit(x, inverse=FALSE) inla.link.probit(x, inverse=FALSE) inla.link.invprobit(x, inverse=FALSE) inla.link.cloglog(x, inverse=FALSE) inla.link.invcloglog(x, inverse=FALSE) inla.link.loglog(x, inverse=FALSE) inla.link.invloglog(x, inverse=FALSE) inla.link.tan(x, inverse=FALSE) inla.link.invtan(x, inverse=FALSE) inla.link.cauchit(x, inverse=FALSE) inla.link.invcauchit(x, inverse=FALSE) inla.link.identity(x, inverse=FALSE) inla.link.invidentity(x, inverse=FALSE) inla.link.inverse(x, inverse=FALSE) inla.link.invinverse(x, inverse=FALSE) inla.link.robit(x, df=7, inverse=FALSE) inla.link.invrobit(x, df=7, inverse=FALSE) inla.link.sn(x, intercept=0.5, skew=0, a=0, inverse=FALSE) inla.link.invsn(x, intercept=0.5, skew=0, a=0, inverse=FALSE) inla.link.invalid(x, inverse=FALSE) inla.link.invinvalid(x, inverse=FALSE) inla.link.invqpoisson(x, inverse = FALSE, quantile = 0.5)
x |
The argument. A numeric vector. |
df |
The degrees of freedom for the Student-t |
inverse |
Logical. Use the link ( |
intercept |
The quantile level for the intercept in the Skew-Normal link |
skew |
The skewness in the Skew-Normal.
Not both of |
a |
The |
quantile |
The quantile level for quantile links |
Return the values of the link-function or its inverse.
The inv
-functions are redundant, as
inla.link.invlog(x) = inla.link.log(x, inverse=TRUE)
and so on, but they are simpler to use a arguments
to other functions.
Havard Rue hrue@r-inla.org