FitLogNormal {Temporal}

Log-Normal Distribution Parameter Estimation

Description

Estimates parameters for log-normal event times subject to non-informative right censoring. The log-normal distribution is parameterized in terms of the location \mu and scale \sigma:

f(t) = \phi\left(\frac{\ln t-\mu}{\sigma}\right)\frac{1}{t\sigma}, t>0

Usage

FitLogNormal(
  data,
  eps = 1e-06,
  init = list(),
  maxit = 10,
  report = FALSE,
  sig = 0.05,
  status_name = "status",
  tau = NULL,
  time_name = "time"
)

Arguments

data

Data.frame.

eps

Tolerance for Newton-Raphson iterations.

init

List with initial values for the location ('loc') \mu and 'scale' \sigma.

maxit

Maximum number of NR iterations.

report

Report fitting progress?

sig

Significance level, for CIs.

status_name

Name of the status indicator, 1 if observed, 0 if censored.

tau

Optional truncation times for calculating RMSTs.

time_name

Name of column containing the time to event.

Value

An object of class fit containing the following:

Parameters

The estimated location \mu and scale \sigma.

Information

The observed information matrix.

Outcome

The fitted mean, median, and variance.

RMST

The estimated RMSTs, if tau was specified.

Examples

# Generate log-normal data with 20% censoring.
data <- GenData(n = 1e3, dist = "log-normal", theta = c(0, 2), p = 0.2)

# Estimate parameters.
fit <- FitParaSurv(data, dist = "log-normal")