VGAM (version 0.7-1)

qtplot.lmscreg: Quantile Plot for LMS Quantile Regression

Description

Plots quantiles associated with a LMS quantile regression.

Usage

qtplot.lmscreg(object, newdata = NULL, 
               percentiles = object@misc$percentiles, 
               plot.it = TRUE, ...)

Value

• A list with the following components.
• fitted.values
  A vector of fitted percentile values.
• percentiles
  The percentiles used.

Details

The `primary' variable is defined as the main covariate upon which the regression or smoothing is performed. For example, in medical studies, it is often the age. In VGAM, it is possible to handle more than one covariate, however, the primary variable must be the first term after the intercept.

References

Yee, T. W. (2004) Quantile regression via vector generalized additive models. Statistics in Medicine, 23, 2295--2315.

Documentation accompanying the VGAM package at http://www.stat.auckland.ac.nz/~yee contains further information and examples.

See Also

plotqtplot.lmscreg, deplot.lmscreg, lms.bcn, lms.bcg, lms.yjn.

Examples

fit = vgam(BMI ~ s(age, df=c(4,2)), fam=lms.bcn(zero=1), data=bminz)
qtplot(fit)
qtplot(fit, perc=c(25,50,75,95), lcol="blue", tcol="blue", llwd=2)