This function fits a growth rate model to time series cases and provides parameter estimates along with confidence intervals.
Usage
fit_growth_rate(
cases,
population = NULL,
level = 0.95,
family = c("quasipoisson", "poisson")
)Arguments
- cases
An integer vector containing the time series cases.
- population
An integer vector containing the time series background population.
- level
The confidence level for parameter estimates, a numeric value between 0 and 1.
- family
A character string specifying the family for modeling. Choose between 'poisson', or 'quasipoisson'. Must be one of: character, family-generator, or family object.
Value
A list containing:
'fit': The fitted growth rate model.
'estimate': A numeric vector with parameter estimates, including the growth rate and its confidence interval.
'level': The confidence level used for estimating parameter confidence intervals.
Examples
# Fit a growth rate model to a time series of counts
# (e.g., population growth)
data <- c(100, 120, 150, 180, 220, 270)
fit_growth_rate(
cases = data,
level = 0.95,
family = "poisson"
)
#> $fit
#>
#> Call: stats::glm(formula = stats::reformulate(response = "cases", termlabels = terms),
#> family = fam_obj, data = growth_data)
#>
#> Coefficients:
#> (Intercept) growth_rate
#> 4.4008 0.1992
#>
#> Degrees of Freedom: 5 Total (i.e. Null); 4 Residual
#> Null Deviance: 116.2
#> Residual Deviance: 0.04923 AIC: 45.67
#>
#> $estimate
#> growth_rate 2.5 % 97.5 %
#> 0.1992211 0.1624836 0.2362807
#>
#> $level
#> [1] 0.95
#>