climate.factor.effect: climate.factor.effect

In RSAlgaeR: Builds Empirical Remote Sensing Models of Water Quality Variables and Analyzes Long-Term Trends

Description

Evaluates difference in values based on climate conditions

Usage

climate.factor.effect(wqrecord, imagedatecol, valuecol, climaterecord,
  climatevarcol, climatedatecol, maxlag, noevent, alternative = "two.sided",
  overall = TRUE, months = NULL, locationcol = "",
  ylabel = "Average Value")

Arguments

wqrecord	dataframe with estimated historical record of water quality parameter
imagedatecol	string, name of column with the date of the estimate (date of remotely sensed imagery)
valuecol	string, name of column with estimated or field-sampled water quality parameter
climaterecord	dataframe with climate variables
climatevarcol	character, name of climate variable (column) of interest
climatedatecol	string, name of column with the date of the climate observation
maxlag	numeric, number of days to lag the climate effect
noevent	numeric, threshold for whether an event occurred
alternative	character string specifying alternative hypothesis ("two.sided","greater","less")
overall	boolean, TRUE: all locations, FALSE: by each location. Default is TRUE
months	months an optional character string for if the t-test should be month specific
locationcol	string, name of column with unique location identifier, used if overall is FALSE
ylabel	string, optional label for plot

Value

results of wilcox test for differences in mean values (and, if overall, boxplots of water quality data)

Examples

data(estimatedrecord)
data(climatedata)
effectresults <- climate.factor.effect(wqrecord=estimatedrecord,imagedatecol="ImageDate",
valuecol="EstChlValue",climaterecord=climatedata,climatevarcol="TMAX",climatedatecol="DATE",
maxlag=7,noevent=16,months=c("July"))

RSAlgaeR documentation built on May 2, 2019, 3:48 p.m.