Description: We develop three procedures for estimation in a two-groups model with covariates. One of them is a nonparametric maximum likelihood estimation based approach when the signal distribution is an infinite Gaussian location mixture and the signal proportion is a logistic function of the available covariates. Two other functions - marg1() and marg2() have also been implemented for inference in the above framework. All these methods can be used for inference in multiple hypotheses testing. For more information, see the paper: Deb, Saha, Guntuboyina and Sen (2019), ''Two-component Mixture Model in the Presence of Covariates'' <arXiv:1810.07897v2>.
Packaged: 2020-12-05 23:47:37 UTC; Nabarun Deb

Author: Juan Pablo Paulino-Arce, Nery Sofia Huerta-Pacheco, Victor Manuel Aguirre-Torres
Description: Non-Parametric Module (NPMOD) is a graphical interface dedicated to the testing of non-parametric data for educational purposes.
Imports: readxl, nortest, BSDA, RVAideMemoire, clinfun, pspearman,
Packaged: 2017-05-20 14:48:17 UTC; sofia.huerta.p

Package: NPMPM
Type: Package
Title: tertiary probabilistic model in predictive microbiology for use
in food manufacture
Version: 1.0
Date: 2011-03-18
Author: Nadine Schoene
Maintainer: Nadine Schoene <nadine.schoene@fu-berlin.de>
Description: The main method npmpm calculates bacterial concentrations
during food manufacture after a contamination. Variability and
uncertainty are included by use of probability distributions
and Monte Carlo Simulation. The model aims at predicting
possible bacterial concentrations at one certain point in time
s, e.g. at the end of a process chain. The process steps of
this process chain are run through in linear order.
Experimental data that match current process step conditions
are gathered, and one deterministic primary model is fitted to
every series of measured values. From every fitted curve one
concentration of bacteria at time s is computed, yielding a set
of concentrations. This sample of possible contamination sizes
is assumed to follow a certain probability distribution. After
calculation of distribution parameters, one value is randomly
drawn from this probability distribution. This value may be
modified, and then serves as contamination for the next process
step.
License: GPL (>= 2)
Depends: R (>= 2.11.0)
Suggests: SweaveListingUtils, graphics
LazyLoad: yes
Packaged: 2012-10-29 08:57:20 UTC; ripley
Repository: CRAN
Date/Publication: 2012-10-29 08:57:20