mean.LCL

mean.UCL

mean.geometric

mean.stderr

mean.utils

a vector, matrix, data frame, or time series to calculate the
modified mean statistic over


<table><tr><td> <code><a rd-options="" href="/link/mean.geometric?package=PerformanceAnalytics&version=1.4.3541" data-mini-rdoc="PerformanceAnalytics::mean.geometric">mean.geometric</a></code> </td>
</tr><tr><td> geometric mean </td>
</tr><tr><td>
<code><a rd-options="" href="/link/mean.stderr?package=PerformanceAnalytics&version=1.4.3541" data-mini-rdoc="PerformanceAnalytics::mean.stderr">mean.stderr</a></code> </td>
</tr><tr><td> standard error of the mean (S.E. mean) </td>
</tr><tr><td>
<code><a rd-options="" href="/link/mean.LCL?package=PerformanceAnalytics&version=1.4.3541" data-mini-rdoc="PerformanceAnalytics::mean.LCL">mean.LCL</a></code> </td>
</tr><tr><td> lower confidence level (LCL) of the mean </td>
</tr><tr><td>
<code><a rd-options="" href="/link/mean.UCL?package=PerformanceAnalytics&version=1.4.3541" data-mini-rdoc="PerformanceAnalytics::mean.UCL">mean.UCL</a></code> </td>
</tr><tr><td> upper confidence level (UCL) of the mean </td>
</tr></table>


Collection of econometric functions for
performance and risk analysis. This package aims to aid
practitioners and researchers in utilizing the latest
research in analysis of non-normal return streams.  In
general, it is most tested on return (rather than
price) data on a regular scale, but most functions will
work with irregular return data as well, and increasing
numbers of functions will work with P&L or price data
where possible.

mean.geometric: calculate attributes relative to the mean of the observation series given, including geometric, stderr, LCL and UCL

Description

Usage

Arguments

See Also

Examples