f_test_unpaired

Computes the unpaired tests on difference in weight per catch category

f_test_unpaired(weight_species, sp, cat)

Arguments

weight_species

data.frame. A dataframe containing the weights of catch per category for TEST and STD device

sp

character. The species to use in test

cat

character. The category to use in test

Value

data.frame. The summary table of the statistical tests

Examples

# Setup OTB input data
OTB_data_folder <-
  system.file("script_origin", "Data", "Example_OTB_alternate", package = "inser")

TR <- readr::read_delim(
  file = file.path(OTB_data_folder, "TR.csv"),
  delim = ";",
  escape_double = FALSE,
  locale = readr::locale(encoding = "WINDOWS-1252"),
  trim_ws = TRUE
)
#> Rows: 2 Columns: 31
#> ── Column specification ────────────────────────────────────────────────────────
#> Delimiter: ";"
#> chr (12): sampling_type, landing_country, vessel_flag_country, project, harb...
#> dbl (11): trip_code, year, vessel_length, vessel_power, vessel_size, vessel_...
#> lgl  (8): number_of_sets, days_at_sea, departure_date_time, return_date_time...
#> 
#> ℹ Use `spec()` to retrieve the full column specification for this data.
#> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
HH <-
  read.table(
    file.path(OTB_data_folder, "HH.csv"),
    sep = ";",
    header = TRUE,
    encoding = "WINDOWS-1252"
  )#,colClasses = colClasses)
SL <-
  read.table(
    file.path(OTB_data_folder, "SL.csv"),
    sep = ";",
    header = TRUE,
    encoding = "WINDOWS-1252"
  )
HL <-
  read.table(
    file.path(OTB_data_folder, "HL.csv"),
    sep = ";",
    header = TRUE,
    encoding = "WINDOWS-1252"
  )

colClasses <- rep(NA, ncol(HH))
colClasses[which(names(HH) == "statistical_rectangle")] <-
  "character"

HH <-
  read.table(
    file.path(OTB_data_folder, "HH.csv"),
    sep = ";",
    header = TRUE,
    colClasses = colClasses,
    encoding = "WINDOWS-1252"
  )

# create TAB output
data <- prep_sel_data(data = list(TR, HH, SL, HL))

# weight for each species
weight_species <-
  data %>% dplyr::group_by(
    project,
    vessel_identifier,
    trip_code,
    station_number,
    gear_label,
    catch_category,
    species
  ) %>%
  dplyr::summarize(weight = sum(weight) * 10 ^ (-3)) %>% as.data.frame()
#> `summarise()` has grouped output by 'project', 'vessel_identifier',
#> 'trip_code', 'station_number', 'gear_label', 'catch_category'. You can override
#> using the `.groups` argument.

weight_species <-
  as.data.frame(
    tidyr::complete(
      weight_species,
      tidyr::nesting(project, vessel_identifier, trip_code, station_number),
      gear_label,
      catch_category,
      species,
      fill = list(weight = 0)
    )
  )

# run f_test_unpaired
f_test_unpaired(weight_species = weight_species,
                sp = "Solea solea",
                cat = "LAN")
#>   pvalue   moyenne mediane       test Taux_Var_Tot
#> 1 0.7052 -50.55715       0 Kolmogorov       -82.21