standard

<p>2000 U.S. standard million population</p>

datasets

Fits time trend models for routine disease surveillance tasks and returns probability distributions for a variety of quantities of interest, including age-standardized rates, period and cumulative percent change, and measures of health inequality. The models are appropriate for count data such as disease incidence and mortality data, employing a Poisson or binomial likelihood and the first-difference (random-walk) prior for unknown risk. Optionally add a covariance matrix for multiple, correlated time series models. Inference is completed using Markov chain Monte Carlo via the Stan modeling language. References: Donegan, Hughes, and Lee (2022) <doi:10.2196/34589>; Stan Development Team (2021) <https://mc-stan.org>; Theil (1972, ISBN:0-444-10378-3).

Connor Donegan

surveil

Time Series Models for Disease Surveillance

standard function

<p>An object of class <code>data.frame</code> with 19 rows and 3 columns.</p>

standard: 2000 U.S. standard million population

Description

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Examples