CItran.fun {NHPoisson}

Confidence intervals for \lambda(t) based on transformation

Description

Given the \hat \beta covariance matrix (or its estimation), an approximate confidence interval for each \lambda(t)=\exp(\nu(t)) is calculated using a transformation of the confidence interval for the linear predictor \nu(t)=\textbf{X(t)} \beta. The transformation is \exp(I_i), where I_i are the confidence limits of \nu(t).

Usage

CItran.fun(VARbeta, lambdafit, covariates, clevel = 0.95)

Arguments

VARbeta

(Estimated) Coariance matrix of the \hat \beta parameter vector.

lambdafit

Numeric vector of fitted values of the PP intensity \hat \lambda(t).

covariates

Matrix of covariates to estimate the PP intensity.

clevel

Confidence level of the confidence intervals. A value in the interval (0,1).

Value

A list with elements

LIlambda

Numeric vector of the lower values of the intervals.

UIlambda

Numeric vector of the upper values of the intervals.

lambdafit

Input argument.

Note

fitPP.fun calls CItran.fun when the argument is CIty='Transf'.

References

Casella, G. and Berger, R.L., (2002). Statistical inference. Brooks/Cole.

Cebrian, A.C., Abaurrea, J. and Asin, J. (2015). NHPoisson: An R Package for Fitting and Validating Nonhomogeneous Poisson Processes. Journal of Statistical Software, 64(6), 1-24.

See Also

CIdelta.fun, fitPP.fun, VARbeta.fun

Examples

aux<-CItran.fun(VARbeta=0.01, lambdafit=exp(rnorm(100)), covariates=matrix(rep(1,100)),
	 clevel=0.95)