are.parsmd.valid {lmomco}

Are the Distribution Parameters Consistent with the Singh–Maddala Distribution

Description

Is the distribution parameter object consistent with the corresponding distribution? The distribution functions (cdfsmd, pdfsmd, quasmd, and lmomsmd) require consistent parameters to return the cumulative probability (nonexceedance), density, quantile, and L-moments of the distribution, respectively. These functions internally use the are.parsmd.valid function. The parameter constraints are simple a > 0 (scale), b > 0 (shape), and q > 0 (shape).

Usage

are.parsmd.valid(para, nowarn=FALSE)

Arguments

para

A distribution parameter list returned by parsmd or vec2par.

nowarn

A logical switch on warning suppression. If TRUE then options(warn=-1) is made and restored on return. This switch is to permit calls in which warnings are not desired as the user knows how to handle the returned value—say in an optimization algorithm.

Value

TRUE

If the parameters are smd consistent.

FALSE

If the parameters are not smd consistent.

Note

This function calls is.smd to verify consistency between the distribution parameter object and the intent of the user.

Author(s)

W.H. Asquith

References

Shahzad, M.N., and Zahid, A., 2013, Parameter estimation of Singh Maddala distribution by moments: International Journal of Advanced Statistics and Probability, v. 1, no. 3, pp. 121–131, doi:10.14419/ijasp.v1i3.1206.

See Also

is.smd, parsmd

Examples

#para <- parsmd(lmoms(c(123, 34, 4, 654, 37, 78)))
#if(are.parsmd.valid(para)) Q <- quasmd(0.5, para)