Wald_trans.Wald_nr {cta}R Documentation

Wald-Type CIs (Non-Robust)

Description

Constructs non-transformed and transformed (if the transformation gg is specified) Wald confidence intervals (CIs) for estimands in contingency tables subject to equality constraints.

The program may stop because of a non-convergence issue.

Usage

Wald_trans.Wald_nr(y, strata, fixed.strata, h0.fct, h0.fct.deriv,
                   S0.fct, S0.fct.deriv, max.mph.iter, step,
                   change.step.after, y.eps, iter.orig, norm.diff.conv,
                   norm.score.conv, max.score.diff.iter, cut.off,
                   S.space.H0, trans.g, trans.g.deriv, trans.g.inv)

Arguments

y

Observed table counts in the contingency table(s), in vector form.

strata

Vector of the same length as y that gives the stratum membership identifier.

fixed.strata

The object that gives information on which stratum (strata) has (have) fixed sample sizes.

h0.fct

The constraint function h0()h_{0}(\cdot) with respect to mm, where m=E(Y)m = E(Y), the vector of expected table counts.

h0.fct.deriv

The R function object that computes analytic derivative of the transpose of the constraint function h0()h_{0}(\cdot) with respect to mm. If h0.fct.deriv is not specified or h0.fct.deriv = NULL, numerical derivatives will be used.

S0.fct

The estimand function S0()S_{0}(\cdot) with respect to mm.

S0.fct.deriv

The R function object that computes analytic derivative of the estimand function S0()S_{0}(\cdot) with respect to mm. If S0.fct.deriv is not specified or S0.fct.deriv = NULL, numerical derivatives will be used.

max.mph.iter, step, change.step.after, y.eps, iter.orig, norm.diff.conv, norm.score.conv, max.score.diff.iter

The parameters used in mph.fit.

cut.off

qchisq(cc, 1). i.e. The chi-square cutoff, with 11 df, based on the significance level 1-cc.

S.space.H0

Restricted estimand space of S()S(\cdot) under H0H_{0}, i.e. subject to the imposed equality constraints along with sampling constraints.

trans.g

The transformation gg used in the transformed Wald confidence interval.

trans.g.deriv

The derivative function of the transformation gg, i.e. dg(w)/dwd g(w) / d w. If it is specified, it should be an R function, even if the derivative function is a constant function.

trans.g.inv

g1g^{-1} function used in back-transformation step in construction of the transformed Wald confidence interval.

Value

Provided that Wald_trans.Wald_nr does not stop,

Author(s)

Qiansheng Zhu

References

Zhu, Q. (2020) "On improved confidence intervals for parameters of discrete distributions." PhD dissertation, University of Iowa.

See Also

Wald_trans.Wald_robust, f.psi, ci.table


[Package cta version 1.3.0 Index]