Observation Model Options — obs

Defines a list specifying the structure of the observation model. Custom settings can be supplied which override the defaults.

Usage

obs_opts(
  family = c("negbin", "poisson"),
  phi = Normal(mean = 0, sd = 0.25),
  weight = 1,
  week_effect = TRUE,
  week_length = 7,
  scale = Fixed(1),
  na = c("missing", "accumulate"),
  likelihood = TRUE,
  return_likelihood = FALSE
)

Arguments

family: Character string defining the observation model. Options are Negative binomial ("negbin"), the default, and Poisson.
phi: A <dist_spec> specifying a prior on the overdispersion parameter of the reporting process, used only if familiy is "negbin". Internally parameterised such that the overdispersion is one over the square of this prior overdispersion phi. Defaults to a half-normal distribution with mean of 0 and standard deviation of 0.25: Normal(mean = 0, sd = 0.25). A lower limit of zero will be enforced automatically.
weight: Numeric, defaults to 1. Weight to give the observed data in the log density.
week_effect: Logical defaulting to TRUE. Should a day of the week effect be used in the observation model.
week_length: Numeric assumed length of the week in days, defaulting to 7 days. This can be modified if data aggregated over a period other than a week or if data has a non-weekly periodicity.
scale: A <dist_spec> specifying a prior on the scaling factor to be applied to map latent infections (convolved to date of report). Defaults to a fixed value of 1, i.e. no scaling: Fixed(1). A lower limit of zero will be enforced automatically. If setting to a prior distribution and no overreporting is expected, it might be sensible to set a maximum of 1 via the max option when declaring the distribution.
na: Deprecated; use the fill_missing() function instead
likelihood: Logical, defaults to TRUE. Should the likelihood be included in the model.
return_likelihood: Logical, defaults to FALSE. Should the likelihood be returned by the model.

Value

An <obs_opts> object of observation model settings.

Examples

# default settings
obs_opts()
#> $family
#> [1] "negbin"
#> 
#> $phi
#> - normal distribution:
#>   mean:
#>     0
#>   sd:
#>     0.25
#> 
#> $weight
#> [1] 1
#> 
#> $week_effect
#> [1] TRUE
#> 
#> $week_length
#> [1] 7
#> 
#> $scale
#> - fixed value:
#>   1
#> 
#> $accumulate
#> [1] 0
#> 
#> $likelihood
#> [1] TRUE
#> 
#> $return_likelihood
#> [1] FALSE
#> 
#> $na_as_missing_default_used
#> [1] TRUE
#> 
#> attr(,"class")
#> [1] "obs_opts" "list"    

# Turn off day of the week effect
obs_opts(week_effect = TRUE)
#> $family
#> [1] "negbin"
#> 
#> $phi
#> - normal distribution:
#>   mean:
#>     0
#>   sd:
#>     0.25
#> 
#> $weight
#> [1] 1
#> 
#> $week_effect
#> [1] TRUE
#> 
#> $week_length
#> [1] 7
#> 
#> $scale
#> - fixed value:
#>   1
#> 
#> $accumulate
#> [1] 0
#> 
#> $likelihood
#> [1] TRUE
#> 
#> $return_likelihood
#> [1] FALSE
#> 
#> $na_as_missing_default_used
#> [1] TRUE
#> 
#> attr(,"class")
#> [1] "obs_opts" "list"    

# Scale reported data
obs_opts(scale = Normal(mean = 0.2, sd = 0.02))
#> $family
#> [1] "negbin"
#> 
#> $phi
#> - normal distribution:
#>   mean:
#>     0
#>   sd:
#>     0.25
#> 
#> $weight
#> [1] 1
#> 
#> $week_effect
#> [1] TRUE
#> 
#> $week_length
#> [1] 7
#> 
#> $scale
#> - normal distribution:
#>   mean:
#>     0.2
#>   sd:
#>     0.02
#> 
#> $accumulate
#> [1] 0
#> 
#> $likelihood
#> [1] TRUE
#> 
#> $return_likelihood
#> [1] FALSE
#> 
#> $na_as_missing_default_used
#> [1] TRUE
#> 
#> attr(,"class")
#> [1] "obs_opts" "list"