dmulti.RdFunction combines different dose-response functions together to create an object containing parameters for multiple dose-response functions.
dmulti(funs = list())A list of objects of class("dosefun"), each element of which corresponds to
an agent in the dataset to be modelled. The list length must be equal to the number of
agents in network$agents used in mbnma.run(), and the order of the dose-response
functions in the list is assumed to correspond to the same order of agents in network$agents.
An object of class("dosefun")
funs <- c(rep(list(demax()),3),
rep(list(dloglin()),2),
rep(list(demax(ed50="common")),3),
rep(list(dexp()),2))
dmulti(funs)
#> $name
#> [1] "emax" "loglin" "emax" "exp"
#>
#> $params
#> [1] "emax" "ed50" "rate" "emax.4" "ed50.5" "emax.6"
#>
#> $nparam
#> [1] 6
#>
#> $jags
#> [1] "(s.beta.1[agent[i,k]] * dose[i,k]) / (s.beta.2[agent[i,k]] + dose[i,k])"
#> [2] "s.beta.3[agent[i,k]] * log(dose[i,k] + 1)"
#> [3] "(s.beta.4[agent[i,k]] * dose[i,k]) / (s.beta.5[agent[i,k]] + dose[i,k])"
#> [4] "s.beta.6[agent[i,k]] * (1 - exp(- dose[i,k]))"
#>
#> $apool
#> emax ed50 rate emax.4 ed50.5 emax.6
#> "rel" "rel" "rel" "rel" "common" "rel"
#>
#> $paramlist
#> $paramlist[[1]]
#> emax ed50
#> "rel" "rel"
#>
#> $paramlist[[2]]
#> rate
#> "rel"
#>
#> $paramlist[[3]]
#> emax.4 ed50.5
#> "rel" "common"
#>
#> $paramlist[[4]]
#> emax.6
#> "rel"
#>
#>
#> $bname
#> emax ed50 rate emax.4 ed50.5 emax.6
#> "beta.1" "beta.2" "beta.3" "beta.4" "beta.5" "beta.6"
#>
#> $posvec
#> [1] 1 1 1 2 2 3 3 3 4 4
#>
#> $knots
#> $knots[[1]]
#> [1] NA
#>
#> $knots[[2]]
#> [1] NA
#>
#> $knots[[3]]
#> [1] NA
#>
#> $knots[[4]]
#> [1] NA
#>
#>
#> $degree
#> [1] NA NA NA NA
#>
#> $p.expon
#> [1] FALSE
#>
#> $agents
#> NULL
#>
#> attr(,"class")
#> [1] "dosefun"