1.8 Simulating multiple populations

We can use the simulate_population() function to generate multiple datasets (populations) form the same set of parameters (world). To do this we can specify the n_pop argument in simulate_population(). This defaults to 1.

squid_data <- simulate_population(
  n=2000,
  response_name = "body_mass",
  parameters=list(
    intercept=10,
    observation=list(
      names=c("temperature","rainfall", "wind"),
      beta =c(0.5,-0.3,0.4)
    ),
    residual=list(
      vcov=0.8
    )
  ),
  n_pop=5
)

By default get_population_data returns a data.frame, where the squid_pop column indicates the population

data <- get_population_data(squid_data)
head(data)

##   body_mass temperature    rainfall        wind    residual squid_pop
## 1  9.963488 -0.87042429  0.08123816 -1.46160423  1.00771338         1
## 2 11.679887  0.54596251 -1.35020676  0.44824010  0.82254729         1
## 3 10.205083  0.05409334 -0.59114054  0.30053533 -0.11952024         1
## 4  9.957851 -1.73773422 -0.62630133 -0.38115588  0.79129050         1
## 5 10.547339  1.61947126  0.76155388 -0.05519906 -0.01185064         1
## 6 10.196599  0.68431346  0.65455707 -2.19404168  0.92842638         1

tail(data)

##       body_mass temperature   rainfall        wind      residual squid_pop
## 9995   8.086665  -0.6214712 -0.8064454 -0.54186069 -1.6277892272         5
## 9996  11.521081   0.2075812 -2.0356218 -0.01890323  0.8141651756         5
## 9997  11.384367  -0.2871820 -1.1694008  0.59354828  0.9397186387         5
## 9998  11.682527  -0.1509205 -0.9174626 -0.46858243  1.6701819257         5
## 9999   9.570990  -1.4052158 -1.7697390 -0.97793190  0.1338485092         5
## 10000  9.421060  -1.1131408 -1.4915844 -1.17264236 -0.0007877935         5

It can also be output as a list, which might be more useful for processing many iterations of a simulation.

data <- get_population_data(squid_data, list=TRUE)
length(data)

## [1] 5