Diggle-Rowlingson Raised Incidence Model

Fits the Diggle-Rowlingson Raised Incidence Model.

tribble(ccflag, vars=NULL, alphas=NULL, betas=NULL, rho, 
 which=1:length(alphas), covars=NULL, thetas=NULL, 
 steps=NULL, reqmin=0.001, icount=50, hessian=NULL)

Arguments

ccflag

Case-control flag : a vector of ones and zeroes.

vars

A matrix where vars[i,j] is the distance squared from point i to source j.

alphas

Initial value of the alpha parameters.

betas

Initial value of the beta parameters.

rho

Initial value of the rho parameter.

which

Defines the mapping from sources to parameters.

covars

A matrix of covariates to be modelled as log-linear terms. The element covars[i,j] is the value of covariate j for case/control i.

thetas

Initial values of covariate parameters.

steps

Step sizes for the Nelder-Mead simplex algorithm.

reqmin

Tolerance for simplex algorithm

icount

Iteration count for simplex algorithm

hessian

by default NULL, any other value causes hessian to be computed and returned

Value

The return value is a list with many components, and class ribfit.

alphas

A vector of the alpha parameters at the maximum

betas

A vector of the beta values at the maximum

rho

The value of rho at the maximum

logl

The maximised log-likelihood

null.logl

The null log-likelihood

call

The function call to tribble

For further information see Diggle and Rowlingson (1993).

See also

triblik, dsquare

References

Rowlingson, B. and Diggle, P. 1993 Splancs: spatial point pattern analysis code in S-Plus. Computers and Geosciences, 19, 627-655; the original sources can be accessed at: https://www.maths.lancs.ac.uk/~rowlings/Splancs/. See also Bivand, R. and Gebhardt, A. 2000 Implementing functions for spatial statistical analysis using the R language. Journal of Geographical Systems, 2, 307-317.