positive-continuous-class | R Documentation |

The positive-continuous class inherits from the `continuous-class`

and is the parent of the proportion class.
In both cases, no observations can be zero, and in the case of the proportion class, no observations can be one. The
`nonnegative-continuous-class`

and the `SC_proportion-class`

are appropriate for those situations.
Aside from these facts, the rest of the
documentation here is primarily directed toward developeRs.

Objects can be created that are of positive-continuous or proportion class via the
`missing_variable`

generic function by specifying `type = "positive-continuous"`

or
`type = "proportion"`

The default transformation for the positive-continuous class is the `log`

function. The proportion class inherits
from the positive-continuous class and has the identity transformation and the `binomial`

family as defaults, in
which case the `fit_model-methods`

call the `betareg`

function in the betareg package.
Alternatively, the transformation could be an inverse CDF like the `qnorm`

function and the family could be `gaussian`

,
in which case the `fit_model-methods`

call the `bayesglm`

function in the arm package.

Ben Goodrich and Jonathan Kropko, for this version, based on earlier versions written by Yu-Sung Su, Masanao Yajima, Maria Grazia Pittau, Jennifer Hill, and Andrew Gelman.

`missing_variable`

, `continuous-class`

, `positive-continuous-class`

,
`proportion-class`

# STEP 0: GET DATA data(CHAIN, package = "mi") # STEP 0.5 CREATE A missing_variable (you never need to actually do this) healthy <- missing_variable(CHAIN$healthy / 100, type = "proportion") show(healthy)

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