CuPloth {BGPhazard}  R Documentation 
Plots for the Hazard and Survival Funcion Estimates
Description
Plots the hazard function and the survival function estimates defined by the bayesian semiparametric cure rate model with an unknown threshold (NietoBarajas & Yin, 2008).
Usage
CuPloth(
M,
type.h = "segment",
intervals = T,
confidence = 0.95,
qn = 0.5,
summary = FALSE,
position_label = "right"
)
Arguments
M 
tibble. Contains the output generated by 
type.h 
character. "segment"= use segments to plot hazard rates, "line" = link hazard rates by a line 
intervals 
logical. If TRUE, plots credible intervals. 
confidence 
Numeric. Confidence level. 
qn 
Numeric. Quantile for Tao that should be visualized on the plot. 
summary 
Logical. If 
position_label 
character. Labels on the right or left side of the plot. 
Details
This function return estimators plots for the resulting hazard rate as it is computed by CuMRes and the cure time (quantile of Tao specified by the user), together with credible intervals. Additionally, it plots the survival function and the cure proportion estimates with their corresponding credible intervals.
Value
SUM.h 
Numeric tibble. Summary for the mean, median, and a

SUM.S 
Numeric tibble. Summary for
the mean, median, and a 
References
 NietoBarajas, L. E. (2003). Discrete time Markov gamma processes and time dependent covariates in survival analysis. Bulletin of the International Statistical Institute 54th Session. Berlin. (CDROM).
NietoBarajas, L. E., & Yin, G. (2008). Bayesian semiparametric cure rate model with an unknown threshold. Scandinavian Journal of Statistics, 35(3), 540556. https://doi.org/10.1111/j.14679469.2007.00589.x
See Also
Examples
## Simulations may be time intensive. Be patient.
## Example 1
# data(crm3)
# times<crm3$times
# delta<crm3$delta
# res < CuMRes(times, delta, type.t = 2, length = .1,
# K = 100, alpha = rep(1, 100 ),
# beta = rep(1, 100),c.r = rep(50, 99),
# iterations = 100, burn.in = 10, thinning = 1, type.c = 2)
# CuPloth(res, type.h = "segment",qn=.5, summary = T)
# CuPloth(res, type.h = "line",qn=.5)