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VGAM (version 1.1-8)

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, ...)

Value

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

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 "lms.".

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.

Author

Thomas W. Yee

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.

See Also

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

Examples

Run this code
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)))

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