capm (version 0.14.0)

GetDataIASA: Get initial values and paramters for IASA model from survey data

Description

Calculates initial values and paramters for the IASA model, from survey data collectected with the questionnaire described by Bquero at al., 2018.

Usage

GetDataIASA(data = NULL, sex.col = "sex", female.label = "female",
  male.label = "male", sterilized.col = "sterilized",
  sterilized.label = "yes", sterilized.ly.col = "sterilized_ly",
  sterilized.ly.label = "yes", births.ly.col = "births_ly",
  species3.col = "species3", species.label = "dog",
  sex3.col = "sex2", fate.col = "fate", died.label = "died",
  lost.label = "lost", acquisition.col = "acquisition",
  acquired.ly.col = "acquired_ly", acquired.ly.label = "yes",
  adopted.label = "adopted", bought.label = "bought",
  acquisition.source.col = "acquisition_city",
  acquired.sterilized.col = "acquired_sterilized",
  destination.label = NULL, total.estimate = NULL, k1.scale = 5,
  h1 = 1, N2.scale = 0.05, f2.scale = 0.9, fs2.scale = 0.1,
  m2.scale = 0.95, ms2.scale = 0.05, b2.scale = 1.5,
  df2.scale = 1.2, dm2.scale = 1.2, sf2.scale = 0.3,
  sm2.scale = 0.3, k2.scale = 2, h2 = 0.5)

Arguments

data

data.frame with survey data.

sex.col

name or index of the column with the *sex* variable.

female.label

string with the *female* category in sex.col.

male.label

string with the *male* category in sex.col.

sterilized.col

name or index of the column with the *sterilized* variable.

sterilized.label

string with the *sterilized* category (ex. yes) in sterilized.col.

sterilized.ly.col

name or index of the column with *sterilized last year* variable.

sterilized.ly.label

string with the *sterilized during the last year* category (ex. yes) in sterilized.ly.col.

births.ly.col

name or index of the column with the *births during the last year* variable.

species3.col

name or index of the column with the *species* variable form the third questionnaire's section (animals that left the household).

species.label

string with the *species* category of interest (ex. dog) in species3.col.

sex3.col

name or index of the column with the *sex* variable form the third questionnaire's section (animals that left the household).

fate.col

name or index of the column with the *fate* variable.

died.label

string with the *died* category in fate.col.

lost.label

string with the *lost* category in fate.col.

acquisition.col

name or index of the column with the *acquisition* variable.

acquired.ly.col

name or index of the column with the *acquisition during the last year* variable.

acquired.ly.label

string with the *acquisition during the last year* category (ex. yes) in acquisition.ly.col.

adopted.label

string with the *adopted* category in acquistion.col.

bought.label

string with the *bought* category in acquisition.col.

acquisition.source.col

name or index of the column with the *source* variable (ex. city).

acquired.sterilized.col

name or index of the column with the *sterilized when acquired* variable.

destination.label

string with the *destination* category (ex. city) in acquisition.source.col.

total.estimate

number representing the estimated total population size.

k1.scale

scale to define the carrying capacity of the owned population as k1 = k.scale * total.estimate.

h1

number representing the mean harem size in the owned population.

N2.scale

scale to define the unowned population size as N2 = N2.sclae * total.estimate.

f2.scale

scale to define the female unowned population size as f2 = f2.scale * f1.

fs2.scale

scale to define the sterilized female unowned population size as fs2 = fs2.scale * fs1.

m2.scale

scale to define the sterimlized male unowned population as m2 = m2.scale * m1.

ms2.scale

scale to define the sterilized male unowned population size as ms2 = ms2.scale * ms1.

b2.scale

scale to define the birth function of the unowned population as b2 = f2 \* b1 / f1 \* b2.scale.

df2.scale

scale to define the death rate of the female unowned population as df2 = df2.scale * df1.

dm2.scale

scale to define the death rate of the male unowned population as dm2 = dm2.scale * dm1.

sf2.scale

scale to define the sterilized female unowned population size as sf2 = sf2 = sf2.scale * sf1.

sm2.scale

scale to define the sterilized male unowned population size as sm2 = sm2.scale * sm1.

k2.scale

scale to define the carrying capacity of the unowned population as k2 = k2.scale * N2.

h2

number representing the mean harem size in the unowned population.

Value

list with two vectors: init (initial values) and pars (parameters).

Details

If column and category names in data match arguments' defaults, the function call is simplified as in the example below.

References

Baquero, O. S., Marconcin, S., Rocha, A., & Garcia, R. D. C. M. (2018). Companion animal demography and population management in Pinhais, Brazil. Preventive Veterinary Medicine.

http://oswaldosantos.github.io/capm

Examples

# NOT RUN {
data(dogs)
GetDataIASA(dogs, destination.label = "Pinhais", total.estimate = 50444)

# }