data_simul_Estim

This function simulates data based on parameter estimates from a specified parametric distribution.
It fits a chosen distribution to the original dataset and samples new values from this fitted distribution.
Supported distributions include "inverse_gamma", "llogis" (log-logistic), "gumbel". "log-normal", "gamma", "exp", "cauchy".

Provides tools for simulating synthetic survival data using a variety of
methods, including kernel density estimation, parametric distribution fitting,
and bootstrap resampling techniques for a desired sample size.

Maria Thurow

RealSurvSim

Simulate Survival Data

Manasi Butee

Ina Dormuth

Christina Sauer

Marc Ditzhaus

Markus Pauly

data_simul_Estim function

<dl><dt>orig_vals</dt>
<dd>Numeric vector of values from the original dataset.</dd>
<dt>n</dt>
<dd>Integer specifying the number of observations to simulate. If <code>NULL</code>, the function simulates
the same number of observations as in the original dataset. Defaults to <code>NULL</code>.</dd>
<dt>distrib</dt>
<dd>Character; one of "inverse_gamma", "llogis", "gumbel",
"exp", "gamma", "normal", or "cauchy".</dd></dl>

Arguments

Simulate Data Based on Parametric Distribution Estimates — data_simul_Estim

<dl>

<dt>orig_vals</dt>
<dd>Numeric vector of values from the original dataset.</dd>


<dt>n</dt>
<dd>Integer specifying the number of observations to simulate. If <code>NULL</code>, the function simulates
the same number of observations as in the original dataset. Defaults to <code>NULL</code>.</dd>


<dt>distrib</dt>
<dd>Character; one of "inverse_gamma", "llogis", "gumbel",
"exp", "gamma", "normal", or "cauchy".</dd>

</dl>

data_simul_Estim: Simulate Data Based on Parametric Distribution Estimates

Description

Usage

Value

Arguments

Examples