Dive Analysis and Calibration

Utilities to represent, visualize, filter, analyse, and summarize time-depth recorder (TDR) data. Miscellaneous functions for handling location data are also provided.


diveMove

R build and check CRAN_Status_Badge CRAN_Downloads

diveMove is a GNU R package with tools to represent, visualize, filter, analyse, and summarize time-depth recorder (TDR) data. It also provides miscellaneous functions for handling location data.

Read ?diveMove for a quick overview of the major functionality. A vignette is also available by doing vignette("diveMove").

Dive analysis usually involves handling of large amounts of data, as new instruments allow for frequent sampling of variables over long periods of time. The aim of this package is to make this process more efficient for summarizing and extracting information gathered by time-depth recorders (TDRs, hereafter). The principal motivation for developing diveMove was to provide more flexibility during the various stages of analysis than is available in popular commercial software. This is achieved by making the results from intermediate calculations easily accessible, allowing the user to make his/her own summaries beyond the default choices the package provides.

Installation

Get the released version from CRAN:

install.packages("diveMove")

Or the development version from GitHub:

# install.packages("devtools")
devtools::install_github("spluque/diveMove")

Python users can access the package's functionality via scikit-diveMove.

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("diveMove")

1.6.4 by Sebastian P. Luque, 2 years ago


https://github.com/spluque/diveMove


Report a bug at https://github.com/spluque/diveMove/issues


Browse source code at https://github.com/cran/diveMove


Authors: Sebastian P. Luque [aut, cre]


Documentation:   PDF Manual  


GPL-3 license


Imports geosphere, KernSmooth, plotly, quantreg, uniReg

Depends on methods, stats4

Suggests knitr, lattice, pander, rmarkdown, tinytest


See at CRAN