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Fit a count distribution by maximum likelihood

Source: R/ct_plot_calendar.R
ct_fit_distribution.Rd

Fits a Poisson, negative binomial, or binomial distribution to a vector of counts and returns the parameter estimates together with the log-likelihood, AIC and BIC.

Usage

ct_fit_distribution(count, distribution)

Arguments

count

Numeric vector of non-negative counts. For distribution = "binomial" it must contain only 0 and 1.

distribution

One of "poisson", "nbinomial" or "binomial".

Value

A one-row tibble with the fitted parameter(s), their standard error(s), the log-likelihood, AIC, BIC and sample size.

See also

ct_plot_calendar()

Examples

set.seed(1)
ct_fit_distribution(stats::rpois(100, 3), "poisson")
#> # A tibble: 1 × 7
#>   lambda lambda_se loglik   aic   bic     n distribution
#>    <dbl>     <dbl>  <dbl> <dbl> <dbl> <int> <chr>       
#> 1   3.05     0.175  -181.  364.  367.   100 poisson     
ct_fit_distribution(stats::rnbinom(100, size = 1, mu = 4), "nbinomial")
#> # A tibble: 1 × 9
#>    size    mu  prob theta_se loglik   aic   bic     n distribution
#>   <dbl> <dbl> <dbl>    <dbl>  <dbl> <dbl> <dbl> <int> <chr>       
#> 1 0.873  3.66 0.193    0.164  -242.  488.  493.   100 nbinomial