This function returns a keyed list of priors related to probability of
diagnosis. Called with no arguments, the default values are returned. Custom
hyperpriors can be specified by passing values for the parameters specified
below. The return value of this function must be added to a
`covidestim`

object using the addition operator (see examples).

```
priors_diagnosis(
rr_diag_asy_vs_sym = c(2, 18),
rr_diag_sym_vs_sev = c(2, 2),
p_diag_if_sev = c(20, 5)
)
```

## Arguments

- rr_diag_asy_vs_sym
A two-element numeric vector containing
`c(alpha, beta)`

parameters/hyperpriors of a Beta distribution
modeling the rate ratio of diagnosis among asymptomatic versus symptomatic,
but non-"severe" infections.

Lowering the mean of this prior would reflect a belief that even fewer
asymptomatic indivivduals are diagnosed than currently assumed.

- rr_diag_sym_vs_sev
A two-element numeric vector containing
`c(alpha, beta)`

parameters/hyperpriors of a Beta distribution
modeling the rate ratio of diagnosis at the symptomatic vs severe stage of
infection.

- p_diag_if_sev
A two-element numeric vector containing ```
c(alpha,
beta)
```

parameters/hyperpriors of a Beta distribution modeling the
probability of being diagnosed if severely ill.

## Value

An S3 object of class 'priors'

## Details

Boundary avoiding priors are used by default; a weakly informative prior
is used for the probability of diagnosis if severely ill.

## Examples

```
cfg <- covidestim(ndays = 50, region = 'New York') + priors_diagnosis(p_diag_if_sev = c(2, 2))
#> Error in covidestim(ndays = 50, region = "New York"): unused argument (ndays = 50)
```