Set parameters for one model.
set_sim_par(
mean_fun = NULL,
err_dist = NULL,
Dat = NULL,
thetaM = NULL,
thetaE = NULL,
thetaC = NULL
)Mean function of model.
Error distribution of model.
Data frame containg x and y to estimate tail-adjusted beta "delta" parameter.
Vector of parameters values for mean function.
Vector of parameters values for error distribution.
Vector of parameters values for constants.
List containing parameters to simulated data set.
## Sim simulation parameters for gaussian-negbin model
set_sim_par(mean_fun="gaussian", err_dist="negbin",
thetaM=c(H=60,m=50,s=10), thetaE=c(phi=1.5))
#> $model_name
#> [1] "gaussian_negbin"
#>
#> $mean_fun
#> [1] "gaussian"
#>
#> $err_dist
#> [1] "negbin"
#>
#> $err_class
#> [1] "count"
#>
#> $thetaM
#> H m s
#> 60 50 10
#>
#> $thetaE
#> phi
#> 1.5
#>
#> $theta
#> H m s phi
#> 60.0 50.0 10.0 1.5
#>
#> attr(,"class")
#> [1] "senlm_par"
## Sim simulation parameters for binomial model
set_sim_par(mean_fun="gaussian", err_dist="binomial.count",
thetaM=c(H=60,m=50,s=10), thetaC=c(binomial_n=100))
#> $model_name
#> [1] "gaussian_binomial.count"
#>
#> $mean_fun
#> [1] "gaussian"
#>
#> $err_dist
#> [1] "binomial.count"
#>
#> $err_class
#> [1] "binomial"
#>
#> $thetaM
#> H m s
#> 60 50 10
#>
#> $thetaC
#> binomial_n
#> 100
#>
#> $theta
#> H m s binomial_n
#> 60 50 10 100
#>
#> attr(,"class")
#> [1] "senlm_par"