DDPGP_meansurvival: Posterior mean survival estimation using Gibbs MCMC Outputs

In DDPGPSurv: DDP-GP Survival Analysis

Description

Posterior mean survival estimation using Gibbs MCMC Outputs

Usage

DDPGP_meansurvival(mcmc, new_pat, if_plot = 0, quantiles = c(0.025, 0.975),
  cov_col = 1)

Arguments

mcmc	A list-The MCMC output from mcmc_Gibbs.
new_pat	A matrix consisting of the covariates of new sample points. Each row represents one sample point. It can also be vector consisting of the covariates of a new sample point.
if_plot	A logical variable indicating whether the mean survival estimation should be plotted. 1 means estimation should be plotted; 0 means otherwise. Defualt value is 0, i.e. not plotted.
quantiles	A two-dimensional vector determining the quantiles for the confidence bounds to be plotted. The first value is the lower quantile and the second value is the upper quantile. Default is (0.025,0.975)
cov_col	An integer defining which covariate column in new_pat to plot on the x-axis for the mean survival figure.

Value

A list composed of the estimation for the mean survival across the values for the covariate specified. The mean_survival is the average of the mean survival calculuation for all iterations, and lower_quant and upper_quant is that for the quantiles specified. optimal is the optimal covariate value (which is specified in cov_col). meansurvival_all is the mean survival for all iterations.

Examples

########################################
#Source dependent packages
library(MASS)
library(mc2d)
library(mvnfast)
library(survival)
#Simulate Data using built-in data generation
##
seed=1
set.seed(seed)
Npat=5
data <- simulate_data(Npat)

########################################
#Run MCMC 
########################################
#Inputs for mcmc 
response <- log(data$OS)
covariate <- cbind(scale(data$Age),data$AUC,data$CR)
censor_status <- data$death
mcmc_settings<-NULL
mcmc_settings$nskip<-10
mcmc_settings$nburn<-50
mcmc_settings$ndisplay<-100
mcmc_settings$nsave<-20
mcmc_settings$sigma_jump<-c(0,4,2.5,4,2.6)
###################
#Run MCMC function
mcmc_Gibbs<-mcmc_DDPGP(response,covariate,censor_status,mcmc_settings)
########################################
#Plotting Mean Survival Estimation 
########################################
#Parameters in Plotting Mean Survival Estimation 
example_CR <- 1
example_Age <- 1
range_AUC <- seq(2.6, 7, 0.1)
new_pat_1<-cbind(example_Age,range_AUC,example_CR)
if_plot=1
DPGP_mean<-DDPGP_meansurvival(mcmc_Gibbs,new_pat_1,if_plot,cov_col=2)

DDPGPSurv documentation built on May 2, 2019, 2:51 p.m.