The main purpose of wq is to explore seasonal time series through plots and 
nonparametric trend tests. It was created originally to examine water quality 
data sets (hence, "wq") but is suitable as a more general purpose set of tools 
for looking at annual or seasonal time series. One of the more tedious tasks in
exploring environmental data sets is creating usable time series from the 
original complex data sets, especially when you want many series at will that 
group data in different ways. So wq also provides a way of transforming data 
sets to a common format that then allows a diversity of time series to be 
created quickly. Finally, a few functions that are specific to the fields of 
limnology and oceanography are a reminder of the package's original intent.

Some of the time series functions include:

* a variety of plots to examine changes in seasonal patterns
* nonparametric trend tests
* time series interpolation and related manipulations
* a simple decomposition of a series into different time scales
* phenological analyses
* the use of empirical orthogonal functions to detect multiple independent 
mechanisms underlying temporal change

Two functions are used mainly for preparing the times series:

* a function that transforms incoming data to a common data structure in the 
form of the "WqData" class
* a function that easily prepares time series objects from this class

The WqData class can be easily adapted to non-aquatic data. Obviously, the 
"depth" field can be used for elevation in atmospheric studies. But more
generally, the "site" and "depth" fields can be used for many two-way 
classifications and don't need to refer to spatial location.

A few functions are specialized for the aquatic sciences:

* converting oxygen concentrations to percent saturation
* finding salinity from conductivity
* estimating the un-ionized fraction of total ammonia

The capabilities of wq are more fully explained in the accompanying vignette:
wq: Some tools for exploring water quality monitoring data.
