  Normality is the main assumption for analyzing dependent data in several time
series models, and tests of normality have been widely studied in the
literature, however, the implementations of these tests are limited. The
\textbf{nortsTest} package performs the tests of \textit{Lobato and Velasco,
Epps, Psaradakis and Vavra} and \textit{random projection} for normality of
stationary processes. In addition, the package offers visual diagnostics for
checking stationarity and normality assumptions for the most used time series
models in several \R packages. The aim of this work is to show the
functionality of the package, presenting each test performance with simulated
examples, and the package utility for model diagnostic in time series analysis.
