lg {lg}

lg: A package for calculating the local Gaussian correlation in multivariate applications.

Description

The lg package provides implementations for the multivariate density estimation and the conditional density estimation methods using local Gaussian correlation as presented in Otneim & Tjøstheim (2017) and Otneim & Tjøstheim (2018).

Details

The main function is called lg_main, and takes as argument a data set (represented by a matrix or data frame) as well as various (optional) configurations that is described in detail in the articles mentioned above, and in the documentation of this package. In particular, this function will calculate the bandwidths used for estimation, using either a plugin estimate (default), or a cross validation estimate. If x is the data set, then the following line of code will create an lg object using the default configuration, that can be used for density estimation afterwards:

lg_object <- lg_main(x)

You can change estimation method, bandwidth selection method and other parameters by using the arguments of the lg_main function.

You can evaluate the multivariate density estimate on a grid as described in Otneim & Tjøstheim (2017) using the dlg-function as follows:

dens_est <- dlg(lg_object, grid = grid).

Assuming that the data set has p variables, you can evaluate the conditional density of the p - q first variables (counting from column 1), given the remaining q variables being equal to condition = c(v1, ..., vq), on a grid, by running

conditional_dens_est <- clg(lg_object, grid = grid, condition = condition).

References

Otneim, Håkon, and Dag Tjøstheim. "The locally gaussian density estimator for multivariate data." Statistics and Computing 27, no. 6 (2017): 1595-1616.

Otneim, Håkon, and Dag Tjøstheim. "Conditional density estimation using the local Gaussian correlation" Statistics and Computing 28, no. 2 (2018): 303-321.