Analysis of stock data ups and downs trend, the stock technical analysis indicators function have trend line, reversal pattern and market trend.
Chun-Yu Liu [aut,cph],
Shu-Nung Yao [rev,ths]

Design of experiments for detection of linkage disequilibrium
R package for design of experiments for association
studies for detection of linkage disequilibrium. Uses an existing
deterministic power calculation for detection of linkage
disequilibrium between a bi-allelic QTL and a bi-allelic marker,
together with the Spiegelhalter and Smith Bayes factor to generate
designs with power to detect effects with a given Bayes factor.

R package for design of experiments for association
studies for detection of linkage disequilibrium. Uses an
existing deterministic power calculation for detection of
linkage disequilibrium between a bi-allelic QTL and a
bi-allelic marker, together with the Spiegelhalter and Smith
Bayes factor to generate designs with power to detect effects
with a given Bayes factor.

R package for design of experiments for design of genome-wide
association studies.  Version 2 incorporating quantitative traits and
case-control studies. The Bayes factor should be chosen large enough to
give respectable posterior odds. This requires Bayes factors of the order
of 10^6 in genome-wide association studies where prior odds are low. Sample sizes needed to get this strength of evidence are substantially higher than those from traditional power calculations. The corresponding threshold for p-values is substantially lower than commonly used.
For quantitative traits
ldDesign uses an existing deterministic power calculation for detection
of linkage disequilibrium between a bi-allelic QTL and a bi-allelic marker,
together with the Spiegelhalter and Smith Bayes factor to generate
designs with power to detect effects with a given Bayes factor. For case-
control studies an asymptotic approximate Bayes factor is used to derive
an analytical power calculation in dominant, recessive, additive
and general genetic models.