lognorm_rp: A function to fit Log-Normal renewal model

In marp: Model-Averaged Renewal Process

A function to fit Log-Normal renewal model

Description

A function to fit Log-Normal renewal model

Usage

lognorm_rp(data, t, y)

Arguments

data	as input inter-event times
t	as user-specified time intervals (used to compute hazard rate)
y	as user-specified time point (used to compute time-to-event probability)

Value

returns list of estimates after fitting Log-Normal renewal model

par1

Estimated mean (on the log scale) of the Log-Normal model

par2

Estimated standard deviation (on the log scale)of the Log-Normal model

logL

Negative log-likelihood

AIC

Akaike information criterion (AIC)

BIC

Bayesian information criterion (BIC)

mu_hat

Estimated mean

pr_hat

Estimated (logit) probabilities

haz_hat

Estimated (log) hazard rates

Examples

set.seed(42)
data <-  rgamma(100,3,0.01)

# set some parameters
t = seq(100, 200, by=10)  # time intervals
y = 304  # cut-off year for estimating probablity

# fit Log-Normal renewal model
result <- marp::lognorm_rp(data, t, 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")

marp documentation built on Aug. 11, 2022, 5:10 p.m.