BGPhazard (version 1.2.3)

CGaPred: Predictive hazard function

Description

Estimates the hazard function for a given vector of covariates.

Usage

CGaPred(M, xf = "median", confidence = 0.95)

Arguments

M

List. Contains the information given for lambda and u by CGaMRes.

xf

Vector. Varying covariates that are used to generate the predictive hazard function estimate.

confidence

Numeric. Confidence band width.

Value

theta.summary

Numeric matrix. Summary for the regression coefficients.

h.xf

Numeric vector. Estimate for the hazard function given covariates vector xf.

S.xf

Numeric vector. Estimate for the survival function given covariates vector xf.

Details

If no vector of varying covariates is specified, a vector of medians of each covariate will be taken.

References

- Nieto-Barajas, L. E. (2003). Discrete time Markov gamma processes and time dependent covariates in survival analysis. Bulletin of the International Statistical Institute 54th Session. Berlin. (CD-ROM).

- Nieto-Barajas, L. E. & Walker, S. G. (2002). Markov beta and gamma processes for modelling hazard rates. Scandinavian Journal of Statistics 29: 413-424.

See Also

CGaMRes, CLambdaSumm

Examples

# NOT RUN {
## Simulations may be time intensive. Be patient.

## Example 1
#  data(leukemiaFZ)
#  leukemia1 <- leukemiaFZ
#  leukemia1$wbc <- log(leukemiaFZ$wbc)
#  CGEX1 <- CGaMRes(data = leukemia1, K = 10, iterations = 10000, thpar = 10)
#  CGaPred(CGEX1)
# }