heemod (version 0.3.3)

define_parameters: Define Markov Model Parameters

Description

Define parameters called to compute the transition matrix or state values for a Markov model. Parameters can be time dependent by using the markov_cycle parameter.

Usage

define_parameters(...)
define_parameters_(.dots)
"modify"(.OBJECT, ...)

Arguments

...

Name-value pairs of expressions definig parameters.

.dots

Used to work around non-standard evaluation.

.OBJECT

An object of class uneval_parameters.

Value

An object of class uneval_parameters (actually a named list of lazy expressions).

Details

Parameters are defined sequencially, parameters defined earlier can be called in later expressions.

Vector length should not be explicitly set, but should instead be stated relatively to markov_cycle (whose length depends on the number of simulation cycles). Alternatively, dplyr functions such as n() or row_numbers() can be used.

This function relies heavily on the dplyr package. Parameter definitions should thus mimic the use of functions such as mutate.

Variable names are searched first in the parameter definition (only parameters defined earlier are visible) then in the environment where define_parameters was called.

For the modify function, existing parameters are modified, but no new parameter can be added. Parameter order matters since only parameters defined earlier can be referenced in later expressions.

Examples

# parameter 'age' depends on time:
# simulating a cohort starting at 60 yo

define_parameters(
  age_start = 60,
  age = age_start + markov_cycle
)

# other uses of markov_cycle are possible

define_parameters(
  top_time = ifelse(markov_cycle < 10, 1, 0)
)

# more elaborate: risk function

define_parameters(
  rate = 1 - exp(- markov_time * .5)
)

# dont explicitly state lengths
# define_parameters(
#   var = seq(1, 15, 2)
# )


# instead rely on markov_cycle or dplyr 
# functions such as n() or row_number()

define_parameters(
  var = seq(from = 1, length.out = n(), by = 3),
  var2 = seq(1, length(markov_cycle), 2)
)

param <- define_parameters(
  age_start = 60,
  age = age_start + markov_cycle
)

# modify existing parameters

modify(
  param,
  age_start = 40
)

# cannot add new parameters

# modify(
#   param,
#   const = 4.4,
#   age_2 = age ^ 2
# )