create.grid: Create a grid for kernel estimation
In gplm: Generalized Partial Linear Models (GPLM)

Description Usage Arguments Details Value Author(s) See Also Examples

Helps to define a grid for kernel denity or regression estimates (univariate or multivariate).

1	create.grid(grid.list, sort=TRUE)

`grid.list`	list of 1-dimensional vectors containing the grid values for each dimension
`sort`	sort the vectors (can be set to FALSE if vectors are already sorted in ascending order)

This function allows easily to define grids for the "gplm" package. If the data are d-dimensional and the grid vector lengths are n1, ... nd, then the output is a (n1*...*nd) x d matrix with each row corresponding to one d-dimensional data point at which the function estimate is to be calculated.

m x d grid matrix

Marlene Mueller

expand.grid, kde, kreg

  v1 <- 1:5
  v2 <- 3:1
  grid <- create.grid(list(v1,v2))

  x <- matrix(rnorm(60),30,2)
  v1 <- seq(min(x[,1]),max(x[,1]),length=10)
  v2 <- seq(min(x[,2]),max(x[,2]),length=5)
  grid <- create.grid(list(v1,v2))