R/data.R

In randomForestVIP: Tune Random Forests Based on Variable Importance & Plot Results

#' Lichen data from the Current Vegetation Survey
#'
#' @name lichen
#' @keywords lichen
#' @docType data
#' @description
#' Data were collected between 1993 and 1999 as part of the Lichen Air
#'   Quality surveys on public lands in Oregon and southern Washington.
#'   Observations were obtained from 1-acre (0.4 ha) plots at Current
#'   Vegetation Survey (CVS) sites. Indicator variables denote the presences
#'   and absences of 7 lichen species. Data for each sampled plot include
#'   the topographic variables elevation, aspect, and slope; bioclimatic
#'   predictors including maximum, minimum, daily, and average temperatures,
#'   relative humidity precipitation, evapotranspiration, and vapor
#'   pressure; and vegetation variables including the average age of
#'   the dominant conifer and percent conifer cover. The data in lichenTest
#'   were collected from half-acre plots at CVS sites in the same
#'   geographical region and contains many of the same variables,
#'   including presences and absences for the 7 lichen species. As such,
#'   it is a good test dataset for predictive methods applied to the Lichen
#'   Air Quality data.
#' @usage lichen
#' @format
#' A data frame with 840 observations and 40 variables. One variable is
#'   a location identifier, 7 (coded as 0 and 1) identify the presence or
#'   absence of a type of lichen species, and 32 are characteristics of
#'   the survey site where the data were collected.
#'
#'   There were 12 monthly values in the original data for each of the
#'   bioclimatic predictors. Principal components analyses suggested
#'   that for each of these predictors 2 principal components explained
#'   the vast majority (95.0\%-99.5\%) of the total variability. Based on
#'   these analyses, indices were created for each set of bioclimatic
#'   predictors. The variables with the suffix Ave in the variable name
#'   are the average of 12 monthly variables. The variables with the
#'   suffix Diff are contrasts between the sum of the April-September
#'   monthly values and the sum of the October-December and January-March
#'   monthly values, divided by 12. Roughly speaking, these are
#'   summer-to-winter contrasts.
#'
#'   The variables are summarized as follows:
#'
#'   \describe{
#'   \item{LobaOreg}{Lobaria oregana (Absent = 0, Present = 1)}
#'   \item{EvapoTransAve}{Average monthly potential evapotranspiration in mm}
#'   \item{EvapoTransDiff}{Summer-to-winter difference in monthly potential
#'   evapotranspiration in mm}
#'   \item{MoistIndexAve}{Average monthly moisture index in cm}
#'   \item{MoistIndexDiff}{Summer-to-winter difference in monthly monthly
#'   moisture index in cm}
#'   \item{PrecipAve}{Average monthly precipitation in cm}
#'   \item{PrecipDiff}{Summer-to-winter difference in monthly precipitation
#'   in cm}
#'   \item{RelHumidAve}{Average monthly relative humidity in percent}
#'   \item{RelHumidDiff}{Summer-to-winter difference in monthly relative
#'   humidity in percent}
#'   \item{PotGlobRadAve}{Average monthly potential global radiation in kJ}
#'   \item{PotGlobRadDiff}{Summer-to-winter difference in monthly potential
#'   global radiation in kJ}
#'   \item{AveTempAve}{Average monthly average temperature in degrees Celsius}
#'   \item{AveTempDiff}{Summer-to-winter difference in monthly average
#'   temperature in degrees Celsius}
#'   \item{MaxTempAve}{Average monthly maximum temperature in degrees Celsius}
#'   \item{MaxTempDiff}{Summer-to-winter difference in monthly maximum
#'   temperature in degrees Celsius}
#'   \item{MinTempAve}{Average monthly minimum temperature in degrees Celsius}
#'   \item{MinTempDiff}{Summer-to-winter difference in monthly minimum
#'   temperature in degrees Celsius}
#'   \item{DayTempAve}{Mean average daytime temperature in degrees Celsius}
#'   \item{DayTempDiff}{Summer-to-winter difference in average daytime
#'   temperature in degrees Celsius}
#'   \item{AmbVapPressAve}{Average monthly average ambient vapor pressure in Pa}
#'   \item{AmbVapPressDiff}{Summer-to-winter difference in monthly average
#'   ambient vapor pressure in Pa}
#'   \item{SatVapPressAve}{Average monthly average saturated vapor pressure
#'   in Pa}
#'   \item{SatVapPressDiff}{Summer-to-winter difference in monthly average
#'   saturated vapor pressure in Pa}
#'   \item{Aspect}{Aspect in degrees}
#'   \item{TransAspect}{Transformed Aspect: TransAspect=(1-cos(Aspect))/2}
#'   \item{Elevation}{Elevation in meters}
#'   \item{Slope}{Percent slope}
#'   \item{ReserveStatus}{Reserve Status (Reserve, Matrix)}
#'   \item{StandAgeClass}{Stand Age Class (< 80 years, 80+ years)}
#'   \item{ACONIF}{Average age of the dominant conifer in years}
#'   \item{PctVegCov}{Percent vegetation cover}
#'   \item{PctConifCov}{Percent conifer cover}
#'   \item{PctBroadLeafCov}{Percent broadleaf cover}
#'   \item{TreeBiomass}{Live tree (> 1inch DBH) biomass, above ground,
#'   dry weight}
#'   }
#' @source
#' Cutler, D. Richard., Thomas C. Edwards Jr., Karen H. Beard, Adele Cutler,
#'   Kyle T. Hess, Jacob Gibson, and Joshua J. Lawler. 2007. Random Forests
#'   for Classification in Ecology. Ecology 88(11): 2783-2792.
#'
#'   https://CRAN.R-project.org/package=EZtune/
"lichen"


#' Housing Values in Suburbs of Boston
#'
#' @name boston
#' @keywords boston
#' @docType data
#' @description
#' The Boston data frame has 506 rows and 14 columns.
#' @usage boston
#' @format
#' This data frame contains the following columns:
#'
#'   \describe{
#'   \item{crim}{per capita crime rate by town.}
#'   \item{zn}{proportion of residential land zoned for lots over 25,000 sq.ft.}
#'   \item{indus}{proportion of non-retail business acres per town.}
#'   \item{chas}{Charles River dummy variable (= 1 if tract bounds river;
#'   0 otherwise).}
#'   \item{nox}{nitrogen oxides concentration (parts per 10 million).}
#'   \item{rm}{average number of rooms per dwelling.}
#'   \item{age}{proportion of owner-occupied units built prior to 1940.}
#'   \item{dis}{weighted mean of distances to five Boston employment centres.}
#'   \item{rad}{index of accessibility to radial highways.}
#'   \item{tax}{full-value property-tax rate per $10,000.}
#'   \item{ptratio}{pupil-teacher ratio by town.}
#'   \item{black}{\eqn{1000(Bk-0.63)^2} where \eqn{Bk} is the
#'   proportion of blacks by town.}
#'   \item{lstat}{lower status of the population (percent).}
#'   \item{medv}{median value of owner-occupied homes in $1000s.}
#'   }
#'
#' @source
#' https://www.stats.ox.ac.uk/pub/MASS4/
"boston"