linLIR (version 1.1)

kl.ku: Finding k.l and k.u

Description

Internal function to determine the quantities k.l and k.u on the basis of n, p, bet. This function is used within the (internal) functions gen.lms, undom.a and undom.para.

Usage

kl.ku(n, p = 0.5, bet, epsilon = 0)

Arguments

n

Number of observations.

p

Quantile of the abolute residuals' distribution to be used as loss function in the LIR analysis. (0.5 corresponds to the median.)

bet

Cutoff-point for the normalized profile likelihood function.

epsilon

Fraction of coarsening errors considered.

Value

A vector with 2 elements, k.l and k.u.

References

M. Cattaneo, A. Wiencierz (2012c). On the implementation of LIR: the case of simple linear regression with interval data. Technical Report No. 127. Department of Statistics. LMU Munich.

A. Wiencierz, M. Cattaneo (2012b). An exact algorithm for Likelihood-based Imprecise Regression in the case of simple linear regression with interval data. In: R. Kruse et al. (Eds.). Advances in Intelligent Systems and Computing. Vol. 190. Springer. pp. 293-301.

M. Cattaneo, A. Wiencierz (2012a). Likelihood-based Imprecise Regression. International Journal of Approximate Reasoning. Vol. 53. pp. 1137-1154.

See Also

s.linlir, gen.lms, undom.para