Detecting and measuring lag-dependencies is very important in time-series analysis. This study is commonly carried out by focusing on the linear lag-dependencies via the well-known autocorrelogram. However, in practice, there are many situations in which the autocorrelogram fails because of the nonlinear structure of the serial dependence. To cope with this problem, in this paper the R package SDD is introduced. Among the available approaches to analyze the lag-dependencies in an omnibus way, the SDD package considers the autodependogram and some of its variants. The autodependogram, defined by computing the classical Pearson 2-statistic at various lags, is a graphical device recently proposed in the literature to analyze lag-dependencies. The concept of reproducibility probability, and several density-based measures of divergence, are considered to de ne the variants of the autodependogram. An application to daily returns of the Swiss Market Index is also presented to exemplify the use of the package.