Description: Designed for association studies in nested association mapping
(NAM) panels, also handling biparental and random panels. It includes functions
for genome-wide associations mapping of multiple populations, marker quality
control, population genetics analysis, solving mixed models and finding variance
components through REML and Gibbs sampling.

Description: Designed for association studies in nested association mapping (NAM) panels, also handling experimental and random panels. It includes tools for genome-wide associations of multiple populations, marker quality control, population genetics analysis, genome-wide prediction, solving mixed models and finding variance components through likelihood and Bayesian methods.

Description: Designed for association studies in nested association mapping (NAM) panels, experimental and random panels. It includes tools for genome-wide associations of multiple populations, marker quality control, population genetics analysis, genome-wide prediction, solving mixed models and finding variance components through likelihood and Bayesian methods.

Description: Designed for association studies in nested association mapping (NAM) panels, experimental and random panels. The method is described by Xavier et al. (2015) <doi:10.1093/bioinformatics/btv448>. It includes tools for genome-wide associations of multiple populations, marker quality control, population genetics analysis, genome-wide prediction, solving mixed models and finding variance components through likelihood and Bayesian methods.

Package: NAP
Type: Package
Title: Non-Local Alternative Priors in Psychology
Version: 1.0
Date: 2021-11-2
Authors@R: c(person("Sandipan", "Pramanik", email = "sandy@stat.tamu.edu",
role = c("aut", "cre")),
person("Valen E.", "Johnson", role = "aut"))
Author: Sandipan Pramanik [aut, cre],
Valen E. Johnson [aut]
Maintainer: Sandipan Pramanik <sandy@stat.tamu.edu>
Description: Conducts Bayesian Hypothesis tests of a point null hypothesis against a two-sided alternative
using Non-local Alternative Prior (NAP) for one- and two-sample z- and t-tests (Johnson, V. and Rossell, R. (2010) <doi:10.1111/j.1467-9868.2009.00730.x>).
Under the alternative, the NAP is assumed on the standardized effects size in one-sample tests and
on their differences in two-sample tests. The package considers two types of NAP densities:
(1) the normal moment prior, and (2) the composite alternative. In fixed design tests,
the functions calculate the Bayes factors and the expected weight of evidence for varied
effect size and sample size. The package also provides a sequential testing framework using the
Sequential Bayes Factor (SBF) design. The functions calculate the operating characteristics (OC)
and the average sample number (ASN), and also conducts sequential tests for a sequentially
observed data.
Imports: foreach, stats, utils, parallel, doParallel, graphics
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2021-11-02 22:26:01 UTC; sandipanpramanik
Repository: CRAN
Date/Publication: 2021-11-04 07:10:02 UTC