fourCurv: Centile curves based on each of the four different methods

In quantCurves: Estimate Quantiles Curves

Centile curves based on each of the four different methods

Description

Centile curves based on each of the four different methods

Usage

fourCurv(x, y, bandwidth.method = "CV", lambdas)

Arguments

x	the explanatory variable - numeric
y	the response variable - numeric
bandwidth.method	the bandwidth method choice: CV or plug-in. Default is CV (for Local Linear and Local Constant estimators)
lambdas	tunes the tradeoff between the goodness of fit and the regularity of the spline - numeric value or numeric vector (for penalized B-spline estimator).

Value

Four graphs, one for each of the following methods : Local Linear, Local Constant, Cubic Splines and penalized B-splines.

Examples

#create a sample data frame
weights=c(500,600,1000,1150,1200,1260,1240,1300,1370,1500,2000,2100,2150,2500,
2800,2900,3050,3200,2980,3000,3300,3100,3200,3600,3500,3700,3900,3900,4000,
4200,3000,4500,4300,4900,4350,3700,4000,5000,4300)
age<-c(30,30,30,31,31,31,32,32,32,33,33,33,34,34,34,35,35,35,36,36,36,
37,37,37,38,38,38,39,39,39,40,40,40,41,41,41,42,42,42)
sample<-data.frame(weights,age)
colnames(sample)<-c("Weight in gramms","Gestational Age in weeks")
x<-sample$`Gestational Age in weeks`
y<-sample$`Weight in gramms`
fourCurv(x,y, lambdas=seq(1,10))

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