Depends: forecast (>= 5.3), parallel, RColorBrewer, smooth (>= 1.4.7)

Authors@R: c(person("Nikolaos", "Kourentzes", email = "nikolaos@kourentzes.com",
person("Fotios", "Petropoulos", role = c("aut")))
Description: Functions and wrappers for using the Multiple Aggregation Prediction Algorithm (MAPA) for time series forecasting. MAPA models and forecasts time series at multiple temporal aggregation levels, thus strengthening and attenuating the various time series components for better holistic estimation of its structure. For details see Kourentzes et al. (2014) <doi:10.1016/j.ijforecast.2013.09.006>.
Packaged: 2018-01-05 10:23:02 UTC; Konstantinos

Title: MArginal ePIstasis Test for Regions
Description: A genetic analysis tool and variance component
model for identifying marginal epistasis between pathways
and the rest of the genome. 'MAPITR' uses as input a matrix
of genotypes, a vector of phenotypes, and a list of
pathways, and iteratively tests each pathway for epistasis
between any variants within the pathway versus any
variants remaining in the rest of the genome. 'MAPITR'
returns results in the form of p-values for every pathway
indicating whether the null model of there being no
epistatic interactions between a pathway and the rest of
Imports: utils, stats, doParallel, Rcpp (>= 1.0.5), CompQuadForm
Author: Michael Turchin [aut, cre] (<https://orcid.org/0000-0003-3569-1529>),
Gregory Darnell [aut, ctb] (<https://orcid.org/0000-0003-0425-940X>),
Lorin Crawford [aut, ctb] (<https://orcid.org/0000-0003-0178-8242>),

pathways. 'MAPITR' then iteratively tests each pathway for
epistasis between any variants within the pathway versus
any variants remaining in the rest of the genome. 'MAPITR'
Imports: stats, doParallel, Rcpp (>= 1.0.5), CompQuadForm

Description: MAPLES is a general method for the estimation of age
profiles that uses standard micro-level demographic survey
data. The aim is to estimate smoothed age profiles and relative
risks for time-fixed and time-varying covariates.

Package: MAR1
Type: Package
Title: Multivariate Autoregressive Modeling for Analysis of Community
Time-Series Data
Version: 1.0
Date: 2013-03-01
Author: Lindsay P. Scheef
Maintainer: Lindsay P. Scheef <scheef@utexas.edu>
Description: The MAR1 package provides basic tools for preparing
ecological community time-series data for MAR modeling,
building MAR-1 models via model selection and bootstrapping,
and visualizing and exporting model results. It is intended to
make MAR analysis (sensu Ives et al. (2003) Analysis of
community stability and ecological interactions from
time-series data) a more accessible tool for anyone studying
community dynamics.  The user need not necessarily be familiar
with time-series modeling or command-based statistics programs
such as R.
License: GPL-2
Depends: R (>= 2.15.1), tcltk, leaps, bestglm
Suggests: MARSS (>= 3.2)
Packaged: 2013-03-03 21:05:33 UTC; Lindsay Scheef
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2013-03-04 07:47:36