CItran.fun: Confidence intervals for lambda(t) based on transformation

In NHPoisson: Modelling and Validation of Non Homogeneous Poisson Processes

Description

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

Usage

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

Arguments

VARbeta	(Estimated) Coariance matrix of the \hat β parameter vector.
lambdafit	Numeric vector of fitted values of the PP intensity \hat λ(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)

NHPoisson documentation built on Feb. 19, 2020, 5:07 p.m.