Description Usage Format Details Methods Active Bindings
This R6 class Class for defining, fitting and predicting the probability model
P(A|W)
under g_star
or under g_0
for variables
(A,W
). Defines and manages the factorization of the multivariate conditional
probability model P(A=a|...)
into univariate regression models
A[j] ~ A[j-1] + ... + A[1] + W
. The class self$new
method automatically
figures out the correct joint probability factorization into univariate conditional
probabilities based on name ordering provided by (A_nms
, W_nms
).
When the outcome variable A[j]
is binary, this class will automatically call
a new instance of BinaryOutcomeModel
class.
Provide self$fit()
function argument data
as a DataStorageClass
class object.
This data will be used for fitting the model P(A|W)
.
Provide self$fit()
function argument newdata
(also as DataStorageClass
class) for predictions of the type
P(A=1|W=w)
, where w
values are coming from newdata
object.
Finally, provide self$predictAeqa
function newdata
argument
(also DataStorageClass
class object) for getting the likelihood predictions P(A=sa|W=w)
, where
both, sa
and sw
values are coming from newdata
object.
1 |
An R6Class
generator object
n_regs
- .
new(reg, ...)
...
length
...
getPsAsW.models
...
getcumprodAeqa
...
copy.fit(GenericModel)
...
fit(data)
...
predict(newdata)
...
predictAeqa(newdata, ...)
...
wipe.alldat
...
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