locNormLinData: Centile curves using local linear polynomial compared to...

In quantCurves: Estimate Quantiles Curves

Centile curves using local linear polynomial compared to noise data

Description

Centile curves using local linear polynomial compared to noise data

Usage

locNormLinData(
  x,
  y,
  bandwidth.method,
  cents = c(0.03, 0.25, 0.5, 0.75, 0.97),
  data,
  leg = FALSE
)

Arguments

x	the explanatory variable - numeric
y	the response variable - numeric
bandwidth.method	the method chosen to calculate bandwidth. Could be cross validation or Plug-in. Default is set to CV.
cents	A numeric vector that represents the centiles calculated. Default is set to cents=c(0.03,0.25,0.5,0.75,0.97))
data	the noise data we want to compare
leg	Boolean. Should the legend be desplayed (TRUE) or not (FALSE).

Value

Plots centile curves with local linear polynomial using a Gaussian kernel and displays them on the same figure as the noise data to be compared

Examples

#create a sample data frame
sample<-data.frame(sample(30:42,50,rep=TRUE),sample(800:5000,50,rep=TRUE))
colnames(sample)<-c("Gestational Age in weeks","Weight in gramms")
x<-sample$`Gestational Age in weeks`
y<-sample$`Weight in gramms`
abnormal<-data.frame(sample(30:42,10,rep=TRUE),sample(800:5000,10,rep=TRUE))
colnames(abnormal)<-c("Gestational Age in weeks","Weight in gramms")
locNormLinData(x,y,bandwidth.method="Plug-in",cents=c(0.03,0.25,0.50,0.75,0.97),data=abnormal)

quantCurves documentation built on March 18, 2022, 5:11 p.m.