Data object for lifelihood — lifelihoodData • lifelihood

Creates a lifelihoodData object, which is a list containing all the information needed to run the lifelihood program of a given dataset of individual life history. This function will mainly be used to pass to lifelihood() or for customizing parameter boundaries with default_bounds_df().

Usage

lifelihoodData(
  df,
  sex,
  sex_start,
  sex_end,
  maturity_start,
  maturity_end,
  clutchs,
  death_start,
  death_end,
  model_specs,
  covariates,
  matclutch = FALSE,
  matclutch_size = NULL,
  right_censoring_date = 1000,
  critical_age = 20,
  ratiomax = 10
)

Arguments

df: Dataframe with the data of life history. It should have one row per life history / observation.
sex: Column name containing the sex of the observations.
sex_start: Column name containing the first date of the interval in which the sex was determined.
sex_end: Column name containing the second date of the interval in which the sex was determined.
maturity_start: Column name containing the first date of the interval in which the maturity was determined.
maturity_end: Column name containing the second date of the interval in which the maturity was determined.
clutchs: Vector containing the names of the clutch columns. The order should be: first clutch first date, first clutch second date, first clutch clutch size, second clutch first date, first clutch second date, second clutch clutch size, and so on. If the observation with the most clutches is, for example, 10, then the vector must be of size 10 x 3 = 30 (3 elements per clutch: first date, second date and size).
death_start: Column name containing the first date of the interval in which the death was determined.
death_end: Column name containing the second date of the interval in which the death was determined.
model_specs: Vector of characters with the name of the statistical law to use. Must be of length 3 and each element must be one of "wei" (Weibull law), "exp" (Exponential law), "gam" (Gamma law) or "lgn" (Log-normal law). The first one is used for maturity, the second one is used for clutchs and the third one for death.
covariates: Vector containing the names of the covariates.
matclutch: Whether the maturity event (designated by maturity_start and maturity_end) is a clutch event or not. If TRUE, must specify the matclutch_size argument. Default is FALSE.
matclutch_size: Column name containing the size of the clutch for the maturity event. Only used (and required) if matclutch is TRUE.
right_censoring_date: (CURRENTLY IGNORED) Time (integer) point at which a subject’s data is censored. This means that for subjects who do not experience the event of interest (e.g., death, failure) by this date, their data is considered censored. In practice, choose a value much larger than the maximum longevity seen in the data.
critical_age: (CURRENTLY IGNORED) Critical age (integer) below which life histories are not followed individually.
ratiomax: (CURRENTLY IGNORED) Maximum ratio (integer) between number of offspring of last and first reproduction events. Cannot be greater than ratiomax.

Value

lifelihoodData object

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_start",
  death_end = "death_end",
  covariates = c("geno", "type"),
  model_specs = c("gam", "lgn", "wei")
)

summary(data)
#> Error in object[[i]]: object of type 'closure' is not subsettable