pLC: Probability estimates from a log concave fit
In logconPH: CoxPH Model with Log Concave Baseline Distribution

Description Usage Arguments Author(s) Examples

View source: R/LogConcave.R

Returns the the estimated probability from a log concave fit

1	pLC(x, fit, covars)

`x`	A vector of numeric values for which the estimated probabilities will be calculated
`fit`	Log concave fit (from the logconcave() function)
`covars`	A matrix of covariate values. Number of columns must match number in original fit

Clifford Anderson-Bergman

  fit = logconcave(rnorm(500) )
  # Fits a log concave estimator to an uncensored sample
    
  pLC(0, fit)  						
  # Estimates the cdf at the true mode

  simData <- simPH_Censored()
  # Simulates current status data from a CoxPH model
  
  fit <- logconcave(simData$times, simData$x)
  # Fits coxPH model
  
  pLC(1, fit, covars = c(0,0))
  # Estimates the baseline probability at t = 1