Create and work with parameter objects

See numericlist for methods to deal with parameter_list objects.

Usage

param(.x, ...)

# S4 method for mrgmod
param(.x, .y = NULL, ..., .pat = "*", .strict = FALSE)

# S4 method for mrgsims
param(.x, ...)

# S4 method for missing
param(..., .strict = TRUE)

# S4 method for list
param(.x, ...)

# S4 method for ANY
param(.x, ...)

allparam(.x)

Arguments

.x

the model object.

...

passed along or name/value pairs to update the parameters in a model object; when passing new values this way, all values must be numeric and all all names must exist in the parameter list for .x.

.y

an object to be merged into parameter list; non-NULL values must be named list, data.frame, numeric vector, or parameter_list object; named items that do not exist in the parameter list are allowed and will be silently ignored; use the .strict argument to require that all names in .y exist already in the parameter list.

.pat

a regular expression (character) to be applied as a filter for which parameters to show when printing.

.strict

if TRUE, all names to be updated must be found in the parameter list.

Value

An object of class parameter_list (see numericlist).

Details

Can be used to either get a parameter list object from a mrgmod model object or to update the parameters in a model object. For both uses, the return value is a parameter_list object. For the former use, param() is usually called to print the parameters to the screen, but the parameter_list object can also be coerced to a list or numeric R object.

Use allparam() to get a parameter_list object including both model parameters and data items listed in $FIXED.

The update to parameters can be permissive (candidates with names that don't exist in the parameter list are silently ignored) or strict (all candidates must already exist in the parameter list). When passing candidate values via ..., the update is strict and an error is generated if you pass a name that isn't found in the parameter list. When candidate values are passed as a named object via .y, then the update is permissive. Any permissive update can be made strict (error if foreign names are found in the candidates) by passing .strict = TRUE.

An alternative is to assess the incoming names using inventory().

See also

inventory()

Examples

## example("param")

mod <- house()

param(mod)
#> 
#>  Model parameters (N=14):
#>  name value . name  value
#>  CL   1     | SEX   0    
#>  D1   2     | SEXCL 0.7  
#>  F1   1     | SEXVC 0.85 
#>  IC50 10    | VC    20   
#>  KA   1.2   | WT    70   
#>  KIN  100   | WTCL  0.75 
#>  KOUT 2     | WTVC  1    

param(mod, .pat="^(C|F)") ## may be useful when large number of parameters
#> 
#>  Model parameters (N=14):
#>  name value . name value
#>  CL   1     | F1   1    

class(param(mod))
#> [1] "parameter_list"
#> attr(,"package")
#> [1] "mrgsolve"

param(mod)$KA
#> [1] 1.2

param(mod)[["KA"]]
#> [1] 1.2

as.list(param(mod))
#> $CL
#> [1] 1
#> 
#> $VC
#> [1] 20
#> 
#> $KA
#> [1] 1.2
#> 
#> $F1
#> [1] 1
#> 
#> $D1
#> [1] 2
#> 
#> $WTCL
#> [1] 0.75
#> 
#> $WTVC
#> [1] 1
#> 
#> $SEXCL
#> [1] 0.7
#> 
#> $SEXVC
#> [1] 0.85
#> 
#> $KIN
#> [1] 100
#> 
#> $KOUT
#> [1] 2
#> 
#> $IC50
#> [1] 10
#> 
#> $WT
#> [1] 70
#> 
#> $SEX
#> [1] 0
#> 

as.data.frame(param(mod))
#>   CL VC  KA F1 D1 WTCL WTVC SEXCL SEXVC KIN KOUT IC50 WT SEX
#> 1  1 20 1.2  1  2 0.75    1   0.7  0.85 100    2   10 70   0

mod <- param(mod, CL = 1.2)

new_values <- list(CL = 1.3, VC = 20.5)

mod <- param(mod, new_values)