Generate data for a regular monitoring design. The counts follow a negative binomial distribution with given size parameters and the true mean mu depending on a year, period and site effect. All effects are independent from each other and have, on the log-scale, a normal distribution with zero mean and given standard deviation.
Usage
generate_data(
intercept = 2,
n_year = 24,
n_period = 6,
n_site = 20,
year_factor = FALSE,
period_factor = FALSE,
site_factor = FALSE,
trend = 0.01,
sd_rw_year = 0.1,
amplitude_period = 1,
mean_phase_period = 0,
sd_phase_period = 0.2,
sd_site = 1,
sd_rw_site = 0.02,
sd_noise = 0.01,
size = 2,
n_run = 10,
as_list = FALSE,
details = FALSE
)Arguments
- intercept
The global mean on the log-scale.
- n_year
The number of years.
- n_period
The number of periods.
- n_site
The number of sites.
- year_factor
Convert year to a factor. Defaults to
FALSE.- period_factor
Convert period to a factor. Defaults to
FALSE.- site_factor
Convert site to a factor. Defaults to
FALSE.- trend
The long-term linear trend on the log-scale.
- sd_rw_year
The standard deviation of the year effects on the log-scale.
- amplitude_period
The amplitude of the periodic effect on the log-scale.
- mean_phase_period
The mean of the phase of the periodic effect among years. Defaults to
0.- sd_phase_period
The standard deviation of the phase of the periodic effect among years.
- sd_site
The standard deviation of the site effects on the log-scale.
- sd_rw_site
The standard deviation of the random walk along year per site on the log-scale.
- sd_noise
The standard deviation of the noise effects on the log-scale.
- size
The size parameter of the negative binomial distribution.
- n_run
The number of runs with the same mu.
- as_list
Return the dataset as a list rather than a data.frame. Defaults to
FALSE.- details
Add variables containing the year, period and site effects. Defaults tot
FALSE.