Delay Distribution Options

Returns delay distributions formatted for usage by downstream functions.

Usage

delay_opts(
  dist = Fixed(0),
  ...,
  fixed = FALSE,
  tolerance = 0.001,
  weight_prior = TRUE
)

Arguments

dist

A delay distribution or series of delay distributions. Default is a fixed distribution with all mass at 0, i.e. no delay.

...

deprecated; use dist instead

fixed

deprecated; use dist instead

tolerance

Numeric; the desired tolerance level.

weight_prior

Logical; if TRUE (default), any priors given in dist will be weighted by the number of observation data points, in doing so approximately placing an independent prior at each time step and usually preventing the posteriors from shifting. If FALSE, no weight will be applied, i.e. any parameters in dist will be treated as a single parameters.

Value

A <delay_opts> object summarising the input delay distributions.

See also

convert_to_logmean() convert_to_logsd() bootstrapped_dist_fit() dist_spec()

Examples

# no delays
delay_opts()
#> - fixed value:
#>   0

# A single delay that has uncertainty
delay <- LogNormal(mean = Normal(1, 0.2), sd = Normal(0.5, 0.1), max = 14)
#> Warning: Uncertain lognormal distribution specified in terms of parameters that are not the "natural" parameters of the distribution (meanlog, sdlog). Converting using a crude and very approximate method that is likely to produce biased results. If possible, it is preferable to specify the distribution directly in terms of the natural parameters.
delay_opts(delay)
#> - lognormal distribution (max: 14):
#>   meanlog:
#>     - normal distribution:
#>       mean:
#>         -0.11
#>       sd:
#>         0.058
#>   sdlog:
#>     - normal distribution:
#>       mean:
#>         0.47
#>       sd:
#>         0.12

# A single delay without uncertainty
delay <- LogNormal(meanlog = 1, sdlog = 0.5, max = 14)
delay_opts(delay)
#> - lognormal distribution (max: 14):
#>   meanlog:
#>     1
#>   sdlog:
#>     0.5

# Multiple delays (in this case twice the same)
delay_opts(delay + delay)
#> Composite distribution:
#> - lognormal distribution (max: 14):
#>   meanlog:
#>     1
#>   sdlog:
#>     0.5
#> - lognormal distribution (max: 14):
#>   meanlog:
#>     1
#>   sdlog:
#>     0.5