Once you have created your lifelihoodData object with
lifelihoodData(), you can call the default_bounds_df()
function to generate (and load) a dataframe with default
parameter bounds.
This is useful when you want to customise these bounds and
then pass this dataframe to the lifelihood() function via
the param_bounds_df argument (if not, it will automatically
generate it and keep the default values).
Arguments
- lifelihoodData
lifelihoodDataobject created withlifelihoodData().
Examples
library(lifelihood)
library(tidyverse)
df <- fakesample |>
mutate(
geno = as.factor(geno),
type = as.factor(type)
)
head(df)
#> type geno sex_start sex_end sex mat_start mat_end clutch_start1 clutch_end1
#> 1 1 0 0 1000 0 0 1000 NA NA
#> 2 2 0 0 1000 0 2 3 4 3
#> 3 0 1 0 1000 0 3 4 2 4
#> 4 0 1 0 1000 0 3 4 2 4
#> 5 0 1 0 1000 0 3 4 2 4
#> 6 1 0 0 1000 0 0 1000 NA NA
#> clutch_size1 clutch_start2 clutch_end2 clutch_size2 death_start death_end
#> 1 NA NA NA NA 0.1 1
#> 2 4 2 4 5 9.0 10
#> 3 5 NA NA NA 5.0 6
#> 4 5 NA NA NA 5.0 6
#> 5 5 NA NA NA 5.0 6
#> 6 NA NA NA NA 0.1 1
clutchs <- c(
"clutch_start1", "clutch_end1", "clutch_size1",
"clutch_start2", "clutch_end2", "clutch_size2"
)
dataLFH <- lifelihoodData(
df = df,
sex = "sex",
sex_start = "sex_start",
sex_end = "sex_end",
maturity_start = "mat_start",
maturity_end = "mat_end",
clutchs = clutchs,
death_start = "death_end",
death_end = "death_end",
covariates = c("geno", "type"),
model_specs = c("gam", "lgn", "wei")
)
bounds_df <- default_bounds_df(dataLFH)
head(bounds_df)
#> param min max
#> 1 expt_death 0.001 40
#> 2 survival_shape 0.05 500
#> 3 ratio_expt_death 0.01 100
#> 4 prob_death 1e-05 0.99999
#> 5 sex_ratio 1e-05 0.99999
#> 6 expt_maturity 0.001 8
# for example, we want to change this value
bounds_df[bounds_df$name == "increase_death_hazard", "max"] <- 80
# then we pass it to lifelihood()
results <- lifelihood(
lifelihoodData = dataLFH,
path_config = get_config_path("config"),
param_bounds_df = bounds_df,
raise_estimation_warning = FALSE
)