mcneall: Dataset due to McNeall

In multivator: A Multivariate Emulator

Dataset due to McNeall

Description

Data, due to McNeall, from 92 runs of a climate model

Usage

data(mcneall)

Details

McNeall used a numerical climate model and ran it 92 times, on a design matrix specified on 16 independent variables as detailed in McNeall 2008.

The model output is a temperature distribution over the surface of the Earth. The model gives 2048 temperatures, corresponding to 2048 grid squares distributed over the Earth. A vector of 2048 temperatures may be displayed on a global map using the showmap() function.

The 92 model runs are presented in the form of a 2048 by 92 matrix mcneall_temps, each column of which corresponds to a run. A row of 92 temperatures corresponds to the temperature at a particular place on the earth as predicted by each of the 92 model runs.

Following McNeall, a principal component analysis on the maps was performed. The first four were used. Matrix eigenmaps is a 2048 by 4 matrix, with columns corresponding to the four principal components.

Matrix mcneall_pc is a 92-by-20 matrix. The first 16 columns correspond to the independent variables (ie the design matrix); columns 17-20 correspond to the first four principal components of the model output. The 92 rows correspond to the 92 model runs.

The package can be used on the mcneall_temps matrix; use apart() to generate a mdm object. A reasonably optimized hyperparameters object of class mhp is given as opt_mcneall.

References

D. McNeall 2008. "Dimension Reduction in the Bayesian analysis of a numerical climate model". PhD thesis, University of Southampton.

See Also

showmap

Examples

data(mcneall)

showmap(mcneall_temps[,1], pc=FALSE,landmask=landmask)

multivator documentation built on Aug. 22, 2023, 9:10 a.m.