fit_disc_gamma.Rd
These functions performs maximumlikelihood (ML) fitting of a discretised
distribution. This is typically useful for describing delays between
epidemiological events, such as incubation period (infection to onset) or
serial intervals (primary to secondary onsets). The function
optim
is used internally for fitting.
fit_disc_gamma(x, mu_ini = 1, cv_ini = 1, interval = 1, w = 0, ...)
x  A vector of numeric data to fit; NAs will be removed with a warning. 

mu_ini  The initial value for the mean 'mu', defaulting to 1. 
cv_ini  The initial value for the coefficient of variation 'cv', defaulting to 1. 
interval  The interval used for discretisation; see 
w  The centering of the interval used for discretisation; see

...  Further arguments passed to 
The function returns a list with humanreadable parametrisation of
the discretised Gamma distibution (mean, sd, cv), convergence indicators,
and the discretised Gamma distribution itself as a distcrete
object
(from the distcrete
package).
The distcrete
package for discretising distributions, and
optim
for details on available optimisation procedures.
## generate data mu < 15.3 # days sigma < 9.3 # days cv < mu / sigma cv#> [1] 1.645161param < gamma_mucv2shapescale(mu, cv) if (require(distcrete)) { w < distcrete("gamma", interval = 1, shape = param$shape, scale = param$scale, w = 0) x < w$r(100) x fit_disc_gamma(x) }#>#> $mu #> [1] 16.32518 #> #> $cv #> [1] 1.489823 #> #> $sd #> [1] 24.32163 #> #> $ll #> [1] 359.4442 #> #> $converged #> [1] TRUE #> #> $distribution #> A discrete distribution #> name: gamma #> parameters: #> shape: 0.450537383210182 #> scale: 36.2349175631082 #>