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