gamma_rp {marp} | R Documentation |
A function to fit Gamma renewal model
gamma_rp(data, t, m, y)
data |
input inter-event times |
t |
user-specified time intervals (used to compute hazard rate) |
m |
the number of iterations in nlm |
y |
user-specified time point (used to compute time-to-event probability) |
returns list of estimates after fitting Gamma renewal model
Estimated shape parameter of the Gamma model
Estimated scale parameter of the Gamma model
Negative log-likelihood
Akaike information criterion (AIC)
Bayesian information criterion (BIC)
Estimated mean
Estimated (logit) probabilities
Estimated (log) hazard rates
set.seed(42)
data <- rgamma(100,3,0.01)
# set some parameters
m = 10 # number of iterations for MLE optimization
t = seq(100, 200, by=10) # time intervals
y = 304 # cut-off year for estimating probablity
# fit Gamma renewal model
result <- marp::gamma_rp(data, t, m, y)
# print result
cat("par1 = ", result$par1, "\n")
cat("par2 = ", result$par2, "\n")
cat("logL = ", result$logL, "\n")
cat("AIC = ", result$AIC, "\n")
cat("BIC = ", result$BIC, "\n")
cat("mu_hat = ", result$mu_hat, "\n")
cat("pr_hat = ", result$pr_hat, "\n")