qdegross: Quantile function based on an object resulting from the...
In degross: Density Estimation from GROuped Summary Statistics

Description Usage Arguments Value Author(s) References See Also Examples

Quantile function based on an object resulting from the estimation procedure in degross.

1	qdegross(p, degross.fit, phi, get.se=FALSE, cred.level=.95, eps=1e-4)

`p`	Scalar or vector of probabilities in (0,1) indicating the requested fitted quantiles Q(p) based on the density estimation results in `degross.fit`.
`degross.fit`	A `degross.object` generated using degross and containing the density estimation results.
`phi`	(Optional) vector of spline parameters for the log density (default: `degross.fit$phi` if missing).
`get.se`	Logical indicating if standard errors for Q(p) are requested (default: FALSE).
`cred.level`	Level of credible intervals for Q(p).
`eps`	Precision with which each quantile should be computed (default: 1e-4).

A scalar or vector x of the same length as p containing the values Q(p) at which the cdf pdegross(x,degross.fit) is equal to p. When get.se is TRUE, a vector or a matrix containing the quantile estimate(s), standard errors and credible interval limits for Q(p) is provided.

Philippe Lambert p.lambert@uliege.be

Lambert, P. (2021) Moment-based density and risk estimation from grouped summary statistics. arXiv:2107.03883.

degross.object, ddegross, pdegross, degross.

## Generate grouped data
sim = simDegrossData(n=3500, plotting=TRUE, choice=2)

## Create a degrossData object
obj.data = degrossData(Big.bins=sim$Big.bins, freq.j=sim$freq.j, m.j=sim$m.j)
print(obj.data)

## Estimate the density
obj.fit = degross(obj.data)

## Corresponding fitted quantiles
p = c(.01,.05,seq(.1,.9,by=.1),.95,.99) ## Desired probabilities
Q.p = qdegross(p,obj.fit) ## Compute the desired quantiles
print(Q.p) ## Estimated quantiles

## Compute the standard error and a 90% credible interval for the 60% quantile
Q.60 = qdegross(.60,obj.fit,get.se=TRUE,cred.level=.90) ## Compute the desired quantile
print(Q.60) ## Estimated quantile, standard error and credible interval