Package: amei
Type: Package
Title: Adaptive Management of Epidemiological Interventions
Version: 1.0
Date: 2008-12-04
Author: Daniel Merl <dan@stat.duke.edu>, Leah R. Johnson <leah@statslab.cam.ac.uk>, Robert B. Gramacy <bobby@statslab.cam.ac.uk>, and Marc S. Mangel <msmangel@ams.ucsc.edu>
Maintainer: Robert B. Gramacy <bobby@statslab.cam.ac.uk>
Description:
This package provides a flexible statistical framework for generating optimal
epidemiological interventions that are designed to minimize the total expected
cost of an emerging epidemic while simultaneously propagating uncertainty regarding
underlying disease parameters through to the decision process via Bayesian posterior
inference.  The strategies produced through this framework are adaptive: vaccination
schedules are iteratively adjusted to reflect the anticipated trajectory of the
epidemic given the current population state and updated parameter estimates.
License: GPL
LazyLoad: yes
Packaged: Thu Dec  4 21:55:07 2008; bobby

Title: Anomaly Detection with Normal Probability Functions
Authors@R: c(person("Dmitriy", "Bolotov", email = "dbolotov@live.com", role = c("aut", "cre")))
Description: Implements anomaly detection as binary classification for cross-sectional data. Uses maximum likelihood estimates and normal probability functions to classify observations as anomalous. The method is presented in the following lecture from the Machine Learning course by Andrew Ng: <https://www.coursera.org/learn/machine-learning/lecture/C8IJp/algorithm/>, and is also described in: Aleksandar Lazarevic, Levent Ertoz, Vipin Kumar, Aysel Ozgur, Jaideep Srivastava (2003) <doi:10.1137/1.9781611972733.3>.

Package: amen
Type: Package
Title: Additive and multiplicative effects modeling of networks and
relational data
Version: 0.75
Date: 2012-06-12
Author: Peter Hoff, Bailey Fosdick, Alex Volfovsky, Kate Stovel
Maintainer: Peter D. Hoff <pdhoff@uw.edu>
Suggests: coda
Description: This package computes Bayesian estimates for additive and
multiplicative effects (AME) models for networks and relational
data. The basic model includes regression terms, the covariance
structure of the social relations model (Warner, Kenny and
Stoto (1979), Wong (1982)), and multiplicative factor effects
(Hoff(2009)). Four different link functions accomodate
different relational data structures, including binary/network
data (bin), normal relational data (nrm), ordinal relational
data (ord) and data from fixed-rank nomination schemes (frn).
Development of this software was supported in part by NICHD
grant 1R01HD067509-01A1.
License: GPL-3
Packaged: 2012-06-16 19:57:01 UTC; hoff
Repository: CRAN
Date/Publication: 2012-06-17 00:06:28