step.model: step.model

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

Description

Use stepwise regression to parameterize model

Usage

step.model(data, imagerydate, value, modelvariables, timewindow, season,
  stepdirection, print.on = TRUE)

Arguments

data	dataframe, formatted calibration data (model variables: field data and surface reflectance values)
imagerydate	string, name of column with dates of imagery
value	string, name of column with water quality values
modelvariables	vector of strings with the names of columns for bands to consider
timewindow	numeric, number of days to allow for near coincidence
season	vector, months to include in model
stepdirection	string, direction for stepwise regression ("backward","both","forward")
print.on	boolean, option to print the results of the model (default is TRUE)

Value

list with the stepwise model and the modeled values

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