pclm.confidence: Compute Confidence Intervals for PCLM output

In ungroup: Penalized Composite Link Model for Efficient Estimation of Smooth Distributions from Coarsely Binned Data

Compute Confidence Intervals for PCLM output

Description

Compute Confidence Intervals for PCLM output

Usage

pclm.confidence(fit, out.step, y, SE, ci.level, type, offset)

Arguments

fit	Fitted values from pclm.fit
out.step	Length of estimated intervals in output. Values between 0.1 and 1 are accepted. Default: 1.
y	Vector with counts to be ungrouped. It must have the same dimension as x.
SE	Standard Errors
ci.level	Confidence level, as a percentage rather than a proportion, so 95 and not 0.95. Values in [50.1, 99.9] are accepted. It sets the width of both interval pairs in ci: the pointwise conf_lower and conf_upper, and the mass-preserving lower and upper scenarios. Default: 95.
type	Type of PCLM model. Options: "1D", "2D" for univariate and two-dimensional model respectively.
offset	Optional offset term to calculate smooth mortality rates. A vector of the same length as x and y, or one of the same length as the ungrouped output. See \insertCiterizzi2015;textualungroup for further details.

ungroup documentation built on Oct. 3, 2026, 5:06 p.m.