censored-continuous-class | R Documentation |

The censored-continuous class and the truncated-continuous class are both virtual and both inherit from the `continuous-class`

and each is the parent of four classes that differ depending on whether the lower and upper bounds are numeric vectors or functions. A
censored observation is one whose exact value is not observed. A truncated observation is one whose exact value is not observed and which
implies that values on some *other* variables are not observed for that unit of observation. An example of truncation might be that
some taxation forms are not required when a person's income falls below a certain threshold. The methods for these classes are not
working yet. Aside from these facts, the rest of the documentation here is primarily directed toward developeRs.

Both the censored-continuous class and the truncated-continuous class are virtual, so no objects can be
created with these classes. However, the `missing_variable`

generic function can be used to create an object that inherits
from one of their subclasses by specifying `type = "NNcensored-continuous"`

, `type = "NFcensored-continuous"`

,
`type = "FNcensored-continuous"`

, `type = "FFcensored-continuous"`

, `type = "NNtruncated-continuous"`

, `type = "NFtruncated-continuous"`

,
`type = "FNtruncated-continuous"`

, `type = "FFtruncated-continuous"`

. When doing so, the lower and upper slots need to be
specified appropriately.

The censored-continuous class and the truncated-continuous class are both virtual, both inherit from the continuous class, both use the identity transformation by default, and both have two additional slots:

- upper
The upper bound for each observation

- lower
The lower bound for each observation

Both the censored-continuous class and the truncated-continuous class have four subclasses that differ depending
on whether the upper and / or lower bounds are numeric vectors or functions that output numeric
vectors (scalars are recycled and can be `Inf`

). These subclasses are

- NN_censored-continuous
where both the lower and upper bounds are numeric vectors

- FN_censored-continuous
where the lower bound is a function and the upper bound is a numeric vector

- NF_censored-continuous
where the lower bound is a numeric vector and the upper bound is a function

- FF_censored-continuous
where both the lower and upper bounds are functions

- NN_truncated-continuous
where both the lower and upper bounds are numeric vectors

- FN_truncated-continuous
where the lower bound is a function and the upper bound is a numeric vector

- NF_truncated-continuous
where the lower bound is a numeric vector and the upper bound is a function

- FF_truncated-continuous
where both the lower and upper bounds are functions

Ben Goodrich, 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`

# STEP 0: GET DATA data(CHAIN, package = "mi") # STEP 0.5 CREATE A missing_variable (you never need to actually do this) #log_virus <- missing_variable(CHAIN$log_virus, type = "NN_censored-continuous", # lower = 0, upper = Inf) #show(log_virus)

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