person(given = "Marco Antonio", family = "Grivet Mattoso Maia", role = "aut", comment = c(ORCID = "0000-0001-5130-095X")),
person(given = "Ana Tereza", family = "Ribeiro de Vasconcelos", role = "aut", comment = c(ORCID = "0000-0002-4632-2086")))

Title: Density Estimation by Life Time Distributions
Description: It plots densities by using asymmetrical kernels which belong to
life time distributions and calculate its related MSE. For details see Chen (2000),

Title: Kernel Density Estimation using Lifetime Distributions
Description: A collection of asymmetrical kernels belong to lifetime distributions for kernel density estimation is presented.
Mean Squared Errors (MSE) are calculated for estimated curves. For this purpose, R functions allow the distribution to be Gamma, Exponential or Weibull.
For details see Chen (2000), Jin and Kawczak (2003) and Salha et al. (2014) <doi:10.12988/pms.2014.4616>.

For details see Chen (2000a, b), Jin and Kawczak (2003) and Salha et al. (2014) <doi:10.12988/pms.2014.4616>.

For details see Chen (2000a,b), Jin and Kawczak (2003) and Salha et al. (2014) <doi:10.12988/pms.2014.4616>.
Packaged: 2022-09-20 14:28:28 UTC; Javaria Ahamd Khan

Title: The Distributed EM Algorithms in Multivariate Gaussian Mixture
c(person("Qian", "Wang", role = c("aut", "cre"),
Description: The distributed expectation maximization algorithms are used to solve parameters of multivariate Gaussian mixture models. The philosophy of the package is described in Guo, G. (2022) <doi:10.1080/02664763.2022.2053949>.

Title: Evaluating the genetic differentiation between populations based
Author: Alexander Jueterbock, Philipp Kraemer, Gabriele Gerlach and
Description: This package allows to calculate the fixation index Gst
(Nei, 1973) and the differentiation index D (Jost, 2008)
pairwise between or averaged over several populations.
P-values, stating the significance of differentiation, and 95
percent confidence intervals can be estimated using bootstrap
resamplings. In the case that more than two populations are
compared pairwise, the p-values are adjusted by bonferroni
correction and in several other ways due to the multiple