Learn R Programming

⚠️There's a newer version (0.4.8) of this package.Take me there.

wq (version 0.4.4)

Exploring Water Quality Monitoring Data

Description

Functions to assist in the processing and exploration of data from environmental monitoring programs. The package name stands for "water quality" and reflects the original focus on time series data for physical and chemical properties of water, as well as the plankton. Intended for programs that sample approximately monthly at discrete stations, a feature of many legacy data sets. Most of the functions should be useful for analysis of similar-frequency time series regardless of the subject matter.

Copy Link

Version

Install

install.packages('wq')

Monthly Downloads

1

Version

0.4.4

License

GPL-2

Maintainer

Alan Jassby

Last Published

July 30th, 2015

Functions in wq (0.4.4)

plotSeason

Plots seasonal patterns for a time series
tsMake

Create time series from water quality data
mannKen

Mann-Kendall test and the Sen slope
ts2df

Convert time series to data frame
oxySol

Dissolved oxygen at saturation
eofNum

Assess significance of eigenvalues
eof

Empirical orthogonal functions
interpTs

Interpolate or substitute missing time series values
wqData

Construct an object of class "WqData"
phenoPhase-methods

Methods for Function phenoPhase
mts2ts

Converts matrix to vector time series for various analyses
seaKen

Seasonal and Regional Kendall test
plotTsTile

Image plot of monthly time series
trendHomog

Trend homogeneity test
WqData-class

Class "WqData"
sfbay

San Francisco Bay water quality data
phenoAmp-methods

Methods for Function phenoAmp
eofPlot

Plot results of an EOF analysis
utilities

Miscellaneous utility functions
phenoAmp

Phenological amplitude
tsMake-methods

Methods for Function tsMake
zoo-class

Class "zoo"
phenoPhase

Phenological phase
plotTsAnom

Anomaly plot of time series
DateTime-class

Class "DateTime"
ec2pss

Convert conductivity to salinity
wq-package

Exploring water quality monitoring data
plotTs

Time series plot
seasonTrend

Determine seasonal trends
decompTs

Decompose a time series