VGAM (version 0.9-1)

cdf.lmscreg: Cumulative Distribution Function for LMS Quantile Regression

Description

Computes the cumulative distribution function (CDF) for observations, based on a LMS quantile regression.

Usage

cdf.lmscreg(object, newdata = NULL, ...)

Arguments

object

A VGAM quantile regression model, i.e., an object produced by modelling functions such as vglm and vgam with a family function beginning with

newdata

Data frame where the predictions are to be made. If missing, the original data is used.

...

Parameters which are passed into functions such as cdf.lms.yjn.

Value

• A vector of CDF values lying in [0,1].

Details

The CDFs returned here are values lying in [0,1] giving the relative probabilities associated with the quantiles newdata. For example, a value near 0.75 means it is close to the upper quartile of the distribution.

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

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

Examples

fit <- vgam(BMI ~ s(age, df=c(4, 2)), lms.bcn(zero = 1), data = bmi.nz)
head(fit@post$cdf)
head(cdf(fit)) # Same 
head(depvar(fit))
head(fitted(fit))

cdf(fit, data.frame(age = c(31.5, 39), BMI = c(28.4, 24)))