sirt (version 3.9-4)

qmc.nodes: Calculation of Quasi Monte Carlo Integration Points

Description

This function calculates integration nodes based on the multivariate normal distribution with zero mean vector and identity covariance matrix. See Pan and Thompson (2007) and Gonzales et al. (2006) for details.

Usage

qmc.nodes(snodes, ndim)

Arguments

snodes

Number of integration nodes

ndim

Number of dimensions

Value

theta

A matrix of integration points

References

Gonzalez, J., Tuerlinckx, F., De Boeck, P., & Cools, R. (2006). Numerical integration in logistic-normal models. Computational Statistics & Data Analysis, 51, 1535-1548.

Pan, J., & Thompson, R. (2007). Quasi-Monte Carlo estimation in generalized linear mixed models. Computational Statistics & Data Analysis, 51, 5765-5775.

Examples

# NOT RUN {
## some toy examples

# 5 nodes on one dimension
qmc.nodes( snodes=5, ndim=1 )
  ##            [,1]
  ## [1,]  0.0000000
  ## [2,] -0.3863753
  ## [3,]  0.8409238
  ## [4,] -0.8426682
  ## [5,]  0.3850568

# 7 nodes on two dimensions
qmc.nodes( snodes=7, ndim=2 )
  ##             [,1]        [,2]
  ## [1,]  0.00000000 -0.43072730
  ## [2,] -0.38637529  0.79736332
  ## [3,]  0.84092380 -1.73230641
  ## [4,] -0.84266815 -0.03840544
  ## [5,]  0.38505683  1.51466109
  ## [6,] -0.00122394 -0.86704605
  ## [7,]  1.35539115  0.33491073
# }