摘要：The bayesTFR package for R provides a set of functions to produce probabilistic projections of the total fertility rate (TFR) for all countries. In the model, a random walk with drift is used to project the TFR during the fertility transition, using a Bayesian hierarchical model to estimate the parameters of the drift term. The TFR is modeled with a first order autoregressive process during the post-transition phase. The computationally intensive part of the projection model is a Markov chain Monte Carlo algorithm for estimating the parameters of the drift term. This article summarizes the projection model and describes the basic steps to generate probabilistic projections, as well as other functionalities such as projecting aggregate outcomes and dealing with missing values.
