Makes a vector with zeroes, with names and length corresponding to the model parameters of the design.
Arguments
- design
a list of the design made with
design()
.- model
a model list. Defaults to the model specified in the design list.
- doMap
logical. If
TRUE
will also include an attributemap
with the design matrices that perform the mapping back to the design- add_da
Boolean. Whether to include the relevant data columns in the map attribute
- all_cells_dm
Boolean. Whether to include all levels of a factor in the mapping attribute, even when one is dropped in the design
Examples
# First define a design
design_DDMaE <- design(data = forstmann,model=DDM,
formula =list(v~0+S,a~E, t0~1, s~1, Z~1, sv~1, SZ~1),
constants=c(s=log(1)))
#> Parameter(s) st0 not specified in formula and assumed constant.
#>
#> Sampled Parameters:
#> [1] "v_Sleft" "v_Sright" "a" "a_Eneutral" "a_Eaccuracy"
#> [6] "t0" "Z" "sv" "SZ"
#>
#> Design Matrices:
#> $v
#> S v_Sleft v_Sright
#> left 1 0
#> right 0 1
#>
#> $a
#> E a a_Eneutral a_Eaccuracy
#> speed 1 0 0
#> neutral 1 1 0
#> accuracy 1 0 1
#>
#> $t0
#> t0
#> 1
#>
#> $s
#> s
#> 1
#>
#> $Z
#> Z
#> 1
#>
#> $sv
#> sv
#> 1
#>
#> $SZ
#> SZ
#> 1
#>
#> $st0
#> st0
#> 1
#>
# Then for this design get which cognitive model parameters are sampled:
sampled_p_vector(design_DDMaE)
#> v_Sleft v_Sright a a_Eneutral a_Eaccuracy t0
#> 0 0 0 0 0 0
#> Z sv SZ
#> 0 0 0
#> attr(,"map")
#> attr(,"map")$v
#> v_Sleft v_Sright
#> 1 1 0
#> 58 0 1
#>
#> attr(,"map")$a
#> a a_Eneutral a_Eaccuracy
#> 1 1 0 0
#> 20 1 1 0
#> 39 1 0 1
#>
#> attr(,"map")$t0
#> t0
#> 1 1
#>
#> attr(,"map")$s
#> s
#> 1 1
#>
#> attr(,"map")$Z
#> Z
#> 1 1
#>
#> attr(,"map")$sv
#> sv
#> 1 1
#>
#> attr(,"map")$SZ
#> SZ
#> 1 1
#>
#> attr(,"map")$st0
#> st0
#> 1 1
#>