coef() retrieve all coefficients from the output of lifelihood()
coeff() retrieve coefficients of one parameter
from the output of lifelihood()
Arguments
- object
output of
lifelihood()- ...
Ignored
- parameter_name
Name of the parameters to extract the estimate from to extract all parameter estimates). All parameters#' can be found here.
Examples
library(lifelihood)
library(tidyverse)
df <- lifelihood::fakesample |>
mutate(
type = as.factor(type),
geno = as.factor(geno)
)
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_start",
death_end = "death_end",
covariates = c("geno", "type"),
model_specs = c("gam", "lgn", "wei")
)
results <- lifelihood(
lifelihoodData = dataLFH,
path_config = get_config_path("config"),
seeds = c(1, 2, 3, 4),
raise_estimation_warning = FALSE
)
coef(results)
#> int_expt_death eff_expt_death_geno_1
#> -14.95337701 2.27064527
#> eff_expt_death_type_1 eff_expt_death_type_2
#> -9.55371757 0.53315647
#> int_survival_shape eff_survival_shape_geno_1
#> 10.28792377 -1.93963186
#> eff_survival_shape_type_1 eff_survival_shape_type_2
#> 7.57026237 4.74998927
#> eff_survival_shape_type_1:geno_1 eff_survival_shape_type_2:geno_1
#> -0.24718760 3.52427897
#> int_ratio_expt_death eff_ratio_expt_death_geno_1
#> -1.45299283 3.02680049
#> int_prob_death eff_prob_death_geno_1
#> -17.15815657 0.02066385
#> int_expt_maturity eff_expt_maturity_geno_1
#> -0.07781130 -0.34729932
#> eff_expt_maturity_type_1 eff_expt_maturity_type_2
#> -0.76380036 -0.75476253
#> int_maturity_shape eff_maturity_shape_geno_1
#> -10.02261060 -3.30865726
#> int_ratio_expt_maturity eff_ratio_expt_maturity_geno_1
#> 1.74264178 3.36233997
#> eff_ratio_expt_maturity_type_1 eff_ratio_expt_maturity_type_2
#> -2.79189482 -4.87384990
#> int_expt_reproduction eff_expt_reproduction_geno_1
#> -1.79104715 -0.89759305
#> int_pontn eff_pontn_geno_1
#> -2.96400432 -1.03064224
#> int_increase_death_hazard eff_increase_death_hazard_geno_1
#> 3.32326622 2.18470307
#> eff_increase_death_hazard_type_1 eff_increase_death_hazard_type_2
#> -0.38970742 -3.84713473
#> eff_increase_death_hazard_type_1:geno_1 eff_increase_death_hazard_type_2:geno_1
#> -1.13985166 -3.69784224
#> int_tof_reduction_date eff_tof_reduction_date_geno_1
#> -1.27913674 -3.51198283
#> int_increase_tof_n_offspring eff_increase_tof_n_offspring_geno_1
#> 0.24026695 -0.32428130
#> int_lin_decrease_hazard eff_lin_decrease_hazard_geno_1
#> 0.81074061 0.19505972
#> eff_lin_decrease_hazard_type_1 eff_lin_decrease_hazard_type_2
#> 5.50927699 -0.85842716
#> eff_lin_decrease_hazard_type_1:geno_1 eff_lin_decrease_hazard_type_2:geno_1
#> 3.98397092 0.69812447
#> int_quad_senescence eff_quad_senescence_geno_1
#> -0.49711337 0.47173154
#> int_quad_decrease_hazard eff_quad_decrease_hazard_geno_1
#> -0.07370047 -0.14027753
#> int_quad_change_n_offspring eff_quad_change_n_offspring_geno_1
#> 0.07862816 0.00640363
#> int_tof_n_offspring
#> -0.21320110
library(lifelihood)
library(tidyverse)
df <- lifelihood::fakesample |>
mutate(
type = as.factor(type),
geno = as.factor(geno)
)
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_start",
death_end = "death_end",
covariates = c("geno", "type"),
model_specs = c("gam", "lgn", "wei")
)
results <- lifelihood(
lifelihoodData = dataLFH,
path_config = get_config_path("config"),
seeds = c(1, 2, 3, 4),
raise_estimation_warning = FALSE
)
coeff(results, "expt_death")
#> int_expt_death eff_expt_death_geno_1 eff_expt_death_type_1
#> -14.9533770 2.2706453 -9.5537176
#> eff_expt_death_type_2
#> 0.5331565