Let K_{min} and K_{max} be the minimum and maximum for the number of joinpoints, respectively. First the program goes through each of the k-joinpoint models, K_{min} ≤ k ≤ K_{max}. For each of the models, the program estimates the regression parameters with the smallest sum of squared error (SSE, or smallest weighted SSE). Statistics related to each of the k-joinpoint models are discussed in the selections under** Related Content**. The sequential permutation test procedure to choose the best joinpoint model is discussed in detail in Kim et al. (2000), and only briefly described here.