# coxseiInt: Calculate the estimator of the cumulative baseline intensity... In coxsei: Fitting a CoxSEI Model

## Description

It takes the paramter of the parametric part (or its theorized value) and calculate the values of the estimator at the jump times; it also gives the values of the estimator for the variance of the intensity estimator.

## Usage

 ``` 1 2 3 4 5 6 7 8 9 10``` ```coxseiInt(dat, parest, hessian=NULL, vcovmat=solve(hessian), m = 2, gfun = function(x, pa) { ifelse(x <= 0, 0, pa * pa * exp(-pa * x)) }, gfungrd = function(x, pa){ if(length(x)==0)return(matrix(0,2,0)); rbind(pa*exp(-pa*x), pa*exp(-pa*x)*(1-pa*x) ) }) ```

## Arguments

 `dat` a data frame containing the right-censored counting process data `parest` the estimate of parameter of the parametric part of the CoxSEI model `hessian` the hessian matrix returned by the optimization procedure in the estimation of the parametric part based on partial likelihood `vcovmat` the variance-covariance matrix of the estimator of the the parametric components; defaulted to the inverse of the hessian matrix `m` autoregressive order in the excitation part of the intensity `gfun` the excitation function; defaults to the exponential decay function `gfungrd` derivative/gradient function of the excitation function

## Value

a list giving the jump times and values at these of the estimator of the cumulative baseline intensity function.

 `x` the ordered death/event times `y` the value of the estimator of the intensity function at the observed death/event times `varest` the value of the estimator of the variance of the estimator of the intensity function, at the jump times

The step function can be obtained using `stepfun`, and plotted by setting `type="s"` in the `plot` function.

## Note

Currently doesn't compute the standard error or variance estimator of the baseline cumulative intensity estimator.

## Author(s)

Feng Chen <feng.chen@unsw.edu.au>

## Examples

 ```1 2 3 4 5 6``` ```data("dat") est <- coxseiest3(dat,c(0.2,0.4,0.6,log(0.06),log(5))) pe <- est\$par; pe[4:5] <- exp(pe[4:5]); ve <- diag(pe) %*% solve(est\$hessian, diag(pe)); cintest <- coxseiInt(dat,pe,vcovmat=ve) plot(cintest,type="s") ```

coxsei documentation built on Feb. 8, 2020, 9:07 a.m.