True Random Numbers using (random)
The true random number service provided by the website created by Mads Haahr samples atmospheric noise via radio tuned to an unused broadcasting frequency together with a skew correction algorithm due to John von Neumann. More background is available in the included vignette based on an essay by Mads Haahr. In its current form, the package offers functions to retrieve random integers, randomized sequences and random strings.

Quantile Regression for Linear Mixed-Effects Models (qrLMM)
Quantile regression (QR) for Linear Mixed-Effects Models via the asymmetric Laplace distribution (ALD). It uses the Stochastic Approximation of the EM (SAEM) algorithm for deriving exact maximum likelihood estimates and full inference results for the fixed-effects and variance components. It also provides graphical summaries for assessing the algorithm convergence and fitting results.

An htmlwidget interface to the MetricsGraphics.js D3 chart library (metricsgraphics)
metricsgraphics is an ‘htmlwidget’ interface to the MetricsGraphics.js D3 chart library. The current htmlwidget wrapper for it is minimaly functional and does not provide support for metricsgraphics histograms and provides nascent support for metricsgraphics’ best feature – time series charts.

Create diagrams and flowcharts using R (DiagrammeR)
Create diagrams and flowcharts using R.

Multivariate Normality Tests (MVN)
Assessing the assumption of multivariate normality is required by many parametric multivariate statistical methods, such as discriminant analysis, principal component analysis, MANOVA, etc. Here, we present an R package to asses multivariate normality. The MVN package contains three widely used multivariate normality tests, including Mardia’s, Henze-Zirkler’s, Royston’s, graphical approaches, including chi-square Q-Q plot, perspective plot and contour plot and two outlier detection methods based on Mahalanobis distance. We have also developed web-tool version of the package which is available at

Farewell’s Linear Increments Model (FLIM)
FLIM fits linear models for the observed increments in a longitudinal dataset, and imputes missing values according to the models.