View source: R/logdetPaceBarry.R
logdetPaceBarry | R Documentation |
Bayesian estimates of parameters of SAR and SDM type spatial models require the computation of the log-determinant of positive-definite spatial projection matrices of the form (I_n - ρ W), where W is a n by n spatial weight matrix. However, direct computation of the log-determinant is computationally expensive.
logdetPaceBarry(W, length.out = 200, rmin = -1, rmax = 1)
W |
numeric n by n non-negative spatial weights matrix, with zeros on the main diagonal. |
length.out |
single, integer number, has to be at least 51 (due to order of approximation). Sets how fine the grid approximation is. Default value is 200. |
rmin |
single number between -1 and 1. Sets the minimum value of the
spatial autoregressive parameter ρ. Has to be lower than
|
rmax |
single number between -1 and 1. Sets the maximum value of the
spatial autoregressive parameter ρ. Has to be higher than
|
This function wraps the log-determinant approximation by Barry and Pace (1999), which can be used to precompute the log-determinants over a grid of ρ values.
numeric length.out
by 2
matrix; the first column
contains the approximated log-determinants the second column the ρ values
ranging between rmin
and rmax
.
Barry, R. P., and Pace, R. K. (1999) Monte Carlo estimates of the log determinant of large sparse matrices. Linear Algebra and its applications, 289(1-3), 41-54.
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