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

The Distributed EM Algorithms in Multivariate Gaussian Mixture
Models
c(person("Qian", "Wang", role = c("aut", "cre"),
email = "waqian0715@163.com",
comment = c(ORCID = " ")),
person("Guangbao", "Guo", role="aut"),
person("Guoqi", "Qian", role="aut"))
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>.
Qian Wang [aut, cre],
Guangbao Guo [aut],
Guoqi Qian [aut]

Evaluating the genetic differentiation between populations based
on Gst and D values.
Alexander Jueterbock, Philipp Kraemer, Gabriele Gerlach and
Jana Deppermann
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
comparison from one data set.

Alexander Jueterbock, Philipp Kraemer, Gabriele Gerlach and Jana Deppermann
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 comparison from one data set.