In martinoandrea92/dpdistance: Inference and Clustering of Functional Data

Introduction

Package gmfd (Generalized Mahalanobis Functional Distance) is an R package which gather statistical methods for both inference and clustering of functional data based on a generalization of Mahalanobis distance. The package supports both univariate and multivariate functional data.

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Styles

The html_vignette template includes a basic CSS theme. To override this theme you can specify your own CSS in the document metadata as follows:

output: 
  rmarkdown::html_vignette:
    css: mystyles.css

Figures

The figure sizes have been customised so that you can easily put two images side-by-side.

plot(1:10)
plot(10:1)

You can enable figure captions by fig_caption: yes in YAML:

output:
  rmarkdown::html_vignette:
    fig_caption: yes

Then you can use the chunk option fig.cap = "Your figure caption." in knitr.

More Examples

You can write math expressions, e.g. $Y = X\beta + \epsilon$, footnotes^[A footnote here.], and tables, e.g. using knitr::kable().

knitr::kable(head(mtcars, 10))

Also a quote using >:

"He who gives up [code] safety for [code] speed deserves neither." (via)

martinoandrea92/dpdistance documentation built on May 29, 2019, 3:44 a.m.