Description Usage Arguments Details Author(s) References Examples
This function computes the local linear estimation of the regression function using the local linear estimation of the conditional distribution function.
1 2 | df.linkfunction.estim(x, data.X, data.Y, bandwidth,
kernel.function = kernel.function.epan)
|
x |
a numeric vector. |
data.X |
a numeric data vector used to obtain the nonparametric estimator of the conditional distribution function. |
data.Y |
a numeric data vector used to obtain the nonparametric estimator of the conditional distribution function. |
bandwidth |
bandwidth used to obtain the nonparametric estimator of the conditional distribution function. |
kernel.function |
kernel function used to obtain the nonparametric estimator of the conditional distribution function. Default option is "kernel.function.epan" which corresponds to the Epanechnikov kernel function. |
Inappropriate bandwidth or x choices can produce "NaN" values in link function estimates.
Romain Azais, Sandie Ferrigno and Marie-Jose Martinez
G. R. Ducharme and S. Ferrigno. An omnibus test of goodness-of-fit for conditional distributions with applications to regression models. Journal of Statistical Planning and Inference, 142, 2748:2761, 2012.
R. Azais, S. Ferrigno and M-J Martinez. cvmgof: An R package for Cramer-von Mises goodness-of-fit tests in regression models. Submitted. January 2021.hal-03101612
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | # Uncomment the following code block
#
# set.seed(1)
#
# # Data simulation
# n = 25 # Dataset size
# data.X = runif(n,min=0,max=5) # X
# data.Y = 0.2*data.X^2-data.X+2+rnorm(n,mean=0,sd=0.3) # Y
#
# ########################################################################
#
# # Estimation of the link function
#
# bandwidth = 0.75 # Here, the bandwidth is arbitrarily fixed
#
# xgrid = seq(0,5,by=0.1)
# ygrid_df = df.linkfunction.estim(xgrid,data.X,data.Y,bandwidth)
#
# plot(xgrid,ygrid_df,type='l',lty=1,lwd=2,xlab='X',ylab='Y',ylim=c(0.25,2.5))
# lines(xgrid,0.2*xgrid^2-xgrid+2,lwd=0.5,col='gray')
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