mcEst: Compute the Monte Carlo estimate

Usage Arguments

Usage

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mcEst(fit, start = 1, node = "W", t, Anode, intervention = NULL,
  lag = 0, MC = 100, returnMC = FALSE, returnMC_full = FALSE,
  clevCov = FALSE, set = NULL, full = FALSE, update = FALSE)

Arguments

fit

fit object obtained by initEst.

start

Start generating Monte Carlo estimates from this point earliest time point is 1. For the clever covariate, this is also our s.

node

Start generating Monte Carlo estimates from O_i node W, A or Y.

t

Outcome time point of interest. It must be greater than the intervention node A.

Anode

Intervention node.

intervention

Specify

\item

lagThis is an user impossed dependency lag necessary for the calculation of the clever covariate in the targeting step. It refers to past. Default is 0, meaning that it starts right after the node in question. Also, note that lag should be equal or smaller than start.

\item

MCHow many Monte Carlo samples should be generated.

\item

returnMCIf TRUE, returns all MC draws up until outcome time.

\item

returnMC_fullIf TRUE, returns all full MC draws.

\item

clevCovIf TRUE, this MC is used for the calculation of the clever covariate. Instead of observed data, it used intervened

\item

setSet the s node to either 1 or 0. Used for the clever covariate calculation.

\item

fullTRUE if full time-series should be used.

\item

updateTRUE, use updated fits to get Monte Carlo draws. An object of class tstmle01.

estimate

Mean of the outcome at time t under specified intervention, or no intervention.

outcome

Outcome at time t for each MC interation.

intervention

Intervention specified.

MC

How many Monte Carlo samples should be generated.

Anode

Intervention node as a function of O_i.

MCdata

If returnMC is TRUE, returns a data.frame with MC time-series.

set

Returns what the s node was set to.

This function computes the Monte Carlo estimate of the expected value of the parameter of interest under specified intervention and under the estimated mechanism.


podTockom/tstmle01 documentation built on May 14, 2019, 2:03 a.m.