MLE: A maximum likelihood calibrator using the bbmle package

In junlingm/REpiSim: Mathematical Epidemiological Model Simulations in R

A maximum likelihood calibrator using the bbmle package

Description

A maximum likelihood calibrator using the bbmle package

A maximum likelihood calibrator using the bbmle package

Super classes

REpiSim::Calibrator -> REpiSim::Optimizer -> MLE

Public fields

the

names of all parameters

Active bindings

the

names of all parameters

Methods

Public methods

• MLE$new()

• MLE$clone()

Inherited methods

• REpiSim::Optimizer$calibrate()

---

Method new()

initializer

Usage

MLE$new(
  model,
  time,
  data,
  likelihood,
  ...,
  cumulative = FALSE,
  mapping = character()
)

Arguments

model

the model to calibrate

time

either a numeric vector containing the times (including the initial time) of the ODE solution that corresponds to the data, or a character value giving the name of the column in data that corresponds to time.

data

a data.frame object containign the data for the calibration

likelihood

a Lieklihood object specify the type of likelihood

...

each argument is a formula defining the maps between the data columns and the model variables. Please see the details section.

cumulative

whether the data is cumulative

Details

A mapping is a named argument, where name is the data colummn name, and value corresponds to the model variables (or an expression to calculate from the model variables.)

---

Method clone()

The objects of this class are cloneable with this method.

Usage

MLE$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

junlingm/REpiSim documentation built on Nov. 28, 2023, 2:35 a.m.