midq2q: Recover Ordinary Quantiles from Mid-Quantiles

In Qtools: Utilities for Quantiles

Recover Ordinary Quantiles from Mid-Quantiles

Description

This function recovers ordinary quantiles from fitted mid-quantile objects.

Usage

## S3 method for class 'midquantile'
midq2q(object, observed = FALSE, ...)
## S3 method for class 'midrq'
midq2q(object, observed = FALSE, ..., newdata, offset, na.action = na.pass)

Arguments

object	an object of class midquantile or midrq.
observed	logical flag. If TRUE, ordinary quantiles are recovered from observed sample values. Otherwise, they are calcuated as rounded mid-quantiles. See details.
newdata	optionally, a data frame in which to look for variables with which to predict. If omitted, the fitted values are used.
offset	an optional offset to be included in the model frame (when newdata is provided).
na.action	function determining what should be done with missing values in newdata. The default is to predict NA.
...	not used.

Details

If the values of the support of the random variable are equally spaced integers, then observed should ideally be set to FALSE so that the ordinary quantile is obtained by rounding the predicted mid-quantile. Otherwise, the function returns an integer observed in the sample. See Geraci and Farcomeni for more details.

Value

a vector or a matrix of estimated ordinary quantiles. The attribute Fhat provides the corresponding estimated cumulative distribution.

Author(s)

Marco Geraci

References

Geraci, M. and A. Farcomeni. Mid-quantile regression for discrete responses. arXiv:1907.01945 [stat.ME]. URL: https://arxiv.org/abs/1907.01945.

See Also

plot.midq2q, predict.midrq

Examples

## Not run: 
# Esterase data
data(esterase)

# Fit conditional mid-quantiles 0.1, 0.15, ..., 0.85
fit <- midquantile(esterase$Count, probs = 2:17/20)

# Recover ordinary quantile function
print(Qhat <- midq2q(fit))

# Plot
plot(Qhat)

# Fit conditional mid-quantiles 0.1, 0.15, ..., 0.85
fit <- midrq(Count ~ Esterase, tau = 2:17/20, data = esterase, type = 3, lambda = 0)

# Recover ordinary quantile function
xx <- seq(min(esterase$Esterase), max(esterase$Esterase), length = 5)
print(Qhat <- midq2q(fit, newdata = data.frame(Esterase = xx)))

# Plot
plot(Qhat, sub = TRUE)


## End(Not run)

Qtools documentation built on Aug. 8, 2025, 7:19 p.m.