Functions to analyze neuronal spike trains from a single neuron or from several neurons recorded simultaneously.

Functions to analyze neuronal spike trains from a single
neuron or from several neurons recorded simultaneously.

R (>= 2.10), survival, mgcv, R2HTML, gss, codetools

Secondary Trait Association analysis for Rare variants via
SEQuence data
STARSEQ is an R-package for detecting associations with
rare variants using selected samples in sequence-based
association studies. It corrects for the bias in the secondary
trait distribution induced by selective sampling on the primary
trait. The corrected secondary trait can be analyzed by
standard rare variant tests. In the STARSEQ package, several
popular rare variant tests were implemented, which include 1.)
combined multivariate and collapsing 2.) weighted sum
statistics, 3.) kernel based adaptive cluster, 4.) variable
threshold test 5.) sequence kernel association test.

Alexander Robitzsch [aut,cre], Oliver Luedtke [aut]
Contains functions for estimating the STARTS model of
Kenny and Zautra (1995, 2001) <DOI:10.1037/0022-006X.63.1.52>,
<DOI:10.1037/10409-008>.

CDM (>= 6.0), graphics, LAM, sirt (>= 2.3), stats, utils

Contains functions for estimating the STARTS model of
Kenny and Zautra (1995, 2001) <DOI:10.1037/0022-006X.63.1.52>,
<DOI:10.1037/10409-008>. Penalized maximum likelihood
estimation and Markov Chain Monte Carlo estimation are
also provided, see Luedtke, Robitzsch and Wagner (2017)
<DOI:10.1037/met0000155>.
CDM (>= 6.0), graphics, LAM (>= 0.2-4), sirt (>= 2.3), stats,
utils

Contains functions for estimating the STARTS model of
Kenny and Zautra (1995, 2001) <DOI:10.1037/0022-006X.63.1.52>,
<DOI:10.1037/10409-008>. Penalized maximum likelihood
estimation and Markov Chain Monte Carlo estimation are
also provided, see Luedtke, Robitzsch and Wagner (2018)
<DOI:10.1037/met0000155>.
CDM (>= 6.0), graphics, LAM (>= 0.3-27), sirt (>= 2.3), Rcpp,
stats, utils

Alexander Robitzsch [aut,cre] (<https://orcid.org/0000-0002-8226-3132>),
Oliver Luedtke [aut] (<https://orcid.org/0000-0001-9744-3059>)