Imports: bib2df, magrittr, dplyr, geosphere, tidyr, stringr, rlang,

Title: Tools and Data for Quantitative Peace Science Research
Imports: magrittr, dplyr, geosphere, tidyr, stringr, rlang, stevemisc

Title: Periodogram Peaks in Correlated Time Series
Description: Calculates the periodogram of a time series, maximum-likelihood fits an Ornstein-Uhlenbeck state space (OUSS) null model and evaluates the statistical significance of periodogram peaks against the OUSS null hypothesis. The OUSS is a parsimonious model for stochastically fluctuating variables with linear stabilizing forces, subject to uncorrelated measurement errors. Contrary to the classical white noise null model for detecting cyclicity, the OUSS model can account for temporal correlations typically occurring in ecological and geological time series.
Packaged: 2014-06-05 04:09:19 UTC; stilianoslouca

Packaged: 2014-10-29 07:15:41 UTC; SteliosLouca

Packaged: 2015-06-13 23:22:20 UTC; SteliosLouca

Packaged: 2016-11-13 21:31:41 UTC; SteliosLouca

Title: Peak Picking and Annotation of High Resolution Experiments
Authors@R: c(person("Arnaud", "Wolfer", email = "adwolfer@gmail.com", role = c("aut", "cre")),
person("Goncalo", "Correia", email = "gscorreia89@gmail.com", role = "ctb"),
person("Jake", "Pearce", email = "jake.pearce@imperial.ac.uk", role = "ctb"))
Description: An automated pipeline for the detection, integration and reporting of predefined features across a large number of mass spectrometry data files.
Imports: foreach (>= 1.4.4), doParallel (>= 1.0.11), ggplot2 (>=
Suggests: testthat, faahKO, knitr, rmarkdown, pander

Title: Peak Picking Methods Inspired by Biological Data
Description: Biologically inspired methods for
detecting peaks in one-dimensional data, such as time series or genomics data.
The algorithms were originally designed by Weber, Ramachandran, and Henikoff,

Title: Monitor the Total and Peak RAM Used by an Expression or Function
Description: When working with big datasets, RAM conservation is critically
important. However, it is not always enough to just monitor the
size of the objects created. So-called "copy-on-modify" behavior,
characteristic of R, means that some expressions or functions may
require an unexpectedly large amount of RAM overhead. For example,
replacing a single value in a matrix duplicates that matrix in the
backend, making this task require twice as much RAM as that used
by the matrix itself. This package makes it easy to monitor the total
and peak RAM used so that developers can quickly identify and