carMaxBound

vector of the same length as <code>adj</code>, giving the normalized weights associated with each pair of neighboring locations.

vector of indices of the adjacent locations (neighbors) of each spatial location. This is a sparse representation of the full adjacency matrix.

vector giving the number of neighboring locations of each spatial location, with length equal to the number of locations.

vector giving the diagonal elements of the conditional variance matrix, with length equal to the number of locations.

Calculate the upper bound for the <code>gamma</code> parameter of the <code>dcar_proper</code> distribution

A system for writing hierarchical statistical models largely compatible with 'BUGS' and 'JAGS', writing nimbleFunctions to operate models and do basic R-style math, and compiling both models and nimbleFunctions via custom-generated C++. 'NIMBLE' includes default methods for MCMC, particle filtering, Monte Carlo Expectation Maximization, and some other tools. The nimbleFunction system makes it easy to do things like implement new MCMC samplers from R, customize the assignment of samplers to different parts of a model from R, and compile the new samplers automatically via C++ alongside the samplers 'NIMBLE' provides. 'NIMBLE' extends the 'BUGS'/'JAGS' language by making it extensible: New distributions and functions can be added, including as calls to external compiled code. Although most people think of MCMC as the main goal of the 'BUGS'/'JAGS' language for writing models, one can use 'NIMBLE' for writing arbitrary other kinds of model-generic algorithms as well. A full User Manual is available at <https://r-nimble.org>.

carMaxBound: Calculate the upper bound for the autocorrelation parameter of the `dcar_proper` distribution

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