GenericModel: Generic R6 class for modeling (fitting and predicting)...

In stremr: Streamlined Estimation of Survival for Static, Dynamic and Stochastic Treatment and Monitoring Regimes

Description

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.

Usage

GenericModel

Format

An R6Class generator object

Details

• n_regs - .

Methods

new(reg, ...)

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length

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getPsAsW.models

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getcumprodAeqa

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copy.fit(GenericModel)

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fit(data)

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predict(newdata)

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predictAeqa(newdata, ...)

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Active Bindings

wipe.alldat

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stremr documentation built on May 30, 2017, 6:35 a.m.