snapKrig0.0.2 package

Fast Kriging and Geostatistics on Grids with Kronecker Covariance

as.double.sk

Coerce grid values to numeric (double type)

as.integer.sk

Coerce grid values to integer

as.logical.sk

Coerce grid values to logical

as.matrix.sk

convert to matrix

as.vector.sk

Convert grid data to vector of specified mode

dim.sk

Grid dimensions

is.na.sk

Indices of grid points with missing data (NAs)

length.sk

The number of grid-points

Math.sk

Math group generics

mean.sk

Calculate the mean value in a grid

Ops.sk

Operations group generics

plot.sk

Heatmap plots

print.sk

Auto-printing

sk

Make a snapKrig grid list object

anyNA.sk

Check for presence of grid points with missing data (NAs)

sk_add_bins

Add bin labels to a variogram data frame

sk_bds

Set default parameter covariance parameter bounds for a Kronecker cova...

sk_cmean

Compute kriging predictor (or variance) for an sk grid

sk_coords

Return coordinates of a grid of points in column-vectorized order

sk_corr

Stationary 1D correlation kernels

sk_corr_mat

Construct 1D stationary correlation matrices for regularly spaced data

sk_export

Convert "sk" grid to SpatRaster

sk_fit

Fit a covariance model to an sk grid by maximum likelihood

sk_GLS

Generalized least squares (GLS) with Kronecker covariances for sk grid...

sk_kp

Return named vector of Kronecker covariance parameters initialized to ...

sk_LL

Likelihood of covariance model pars given the data in sk grid g

sk_make

Make a sk grid object

sk_mat2vec

Column-vectorization indices

sk_nLL

Negative log-likelihood for parameter vector p

sk_pars

Initialize Kronecker covariance function parameters for a sk grid

sk_pars_make

Build a parameter list defining the 2d spatial Kronecker covariance mo...

sk_pars_update

Convert covariance parameter list to/from vectorized form

sk_plot

Plot grid data

sk_plot_pars

Plot the covariance structure of a snapKrig model

sk_plot_semi

Plot a semi-variogram

sk_rescale

Up or down-scale a sk grid by an integer factor

sk_sample_pt

Sub-grid point sampler for grid data

sk_sample_vg

Sample point pair absolute differences for use in semi-variogram estim...

sk_sim

Random draw from multivariate normal distribution for sk grids

sk_snap

Snap a set of points to a "sk" grid

sk_sub

Return a sub-grid of a sk grid object

sk_sub_find

Find complete regular sub-grids in a sk grid object

sk_sub_idx

Find column-vectorized index of a sub-grid

sk_to_string

Extract Kronecker covariance parameters as plot-friendly strings

sk_toep_mult

Efficiently compute yzx for symmetric Toeplitz matrices y and x

sk_validate

Check compatibility of entries in a sk grid object, and fill in any mi...

sk_var

Generate a covariance matrix or its factorization

sk_var_mult

Multiply a vector by a power of the covariance matrix

sk_vario_fun

Theoretical variogram function

sk_vec2mat

Invert column-vectorization indices

sub-.sk

Extract a sk list element (single-bracket access)

sub-sub-.sk-set

sk_methods.R Dean Koch, 2022 S3 methods for sk grid list objects

subset-.sk

Single-bracket assign

Summary.sk

Grid summary

Geostatistical modeling and kriging with gridded data using spatially separable covariance functions (Kronecker covariances). Kronecker products in these models provide shortcuts for solving large matrix problems in likelihood and conditional mean, making 'snapKrig' computationally efficient with large grids. The package supplies its own S3 grid object class, and a host of methods including plot, print, Ops, square bracket replace/assign, and more. Our computational methods are described in Koch, Lele, Lewis (2020) <doi:10.7939/r3-g6qb-bq70>.

  • Maintainer: Dean Koch
  • License: MIT + file LICENSE
  • Last published: 2023-05-06