Imports: MASS, nlme, Rcpp, methods, rstan, rstantools

Title: Functional Linear Mixed Models for Densely Sampled Data
Description: Estimation of functional linear mixed models for densely sampled data based on functional principal component analysis.
Imports: methods, parallel, MASS, Matrix, mvtnorm

Title: Analysing Density Profiles from Resistance Drilling of Trees
Description: Provides various tools for analysing density profiles
obtained by resistance drilling. It can load individual or
multiple files and trim the starting and ending part of each
density profile. Tools are also provided to trim profiles
manually, to remove the trend from measurements using several
methods, to plot the profiles and to detect tree rings
automatically. Written with a focus on forestry use of resistance
Imports: stats, utils, changepoint (>= 2.2.2)
Suggests: pbapply, mgcv, knitr, rmarkdown, testthat
Packaged: 2020-04-06 09:11:18 UTC; lukak@gozdis.si
Author: Luka Krajnc [aut, cre] (<https://orcid.org/0000-0002-3120-559X>),

Title: Clustering by fast search and find of density peaks
Description: An implementation of the clustering algorithm described by Alex
Rodriguez and Alessandro Laio (Science, 2014 vol. 344), along with tools to

Title: Clustering by Fast Search and Find of Density Peaks
person("Thomas Lin", "Pedersen", , "thomasp85@gmail.com", c("aut", "cre")),

person("Thomas Lin", "Pedersen", email = "thomasp85@gmail.com", role = c("aut", "cre")),
person("Sean", "Hughes", email = "", role = c("aut")),
person("Xiaojie", "Qiu", email = "xqiu@uw.edu", role = c("aut")))
Description: An improved implementation (based on k-nearest neighbors) of the
density peak clustering algorithm, originally described by Alex Rodriguez
and Alessandro Laio (Science, 2014 vol. 344) <DOI: 10.1126/science.1242072>.
It can handle large datasets (> 100, 000 samples) very efficiently. It was
initially implemented by Thomas Lin Pedersen, with inputs from Sean Hughes
and later improved by Xiaojie Qiu to handle large datasets with kNNs.
Imports: Rcpp, FNN, Rtsne, ggplot2, ggrepel, grDevices, gridExtra,