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

1 |

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`

.

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

1 2 3 | ```
data(mcneall)
showmap(mcneall_temps[,1], pc=FALSE)
``` |

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