Description Usage Arguments Value References Examples
This function takes inferential results from Infer
and computes predictive statistics on a validation data set. These include RMS
, PMCC
, CR1
and CR2
as defined in Sahu and Mardia (2005), and the Mahalanobis distance Mahalanobis
, the eigenvalue errors DE
and the pivoted Cholesky errors DPC
as described in Bastos and O'Hagan (2009).
1 2 3 4 5 6 7 |
Results |
a list generated by the function |
G |
an object of class |
sim_obs |
if set to |
A data frame with the predictive statistics as described above.
Sahu, S. K., & Mardia, K. V. (2005). A Bayesian kriged Kalman model for short-term forecasting of air pollution levels. Journal of the Royal Statistical Society: Series C (Applied Statistics), 54(1), 223-244. Bastos, L. S. and O'Hagan, A. (2008). Diagnostics for Gaussian process emulators. Technometrics 51, 425-438.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 | require(Matrix)
data(icesat)
data(surf_fe)
## First create observation object
icesat_obs <- Obs(df=icesat,
abs_lim = 5,
avr_method = "median",
box_size=100,
name="icesat")
## Now split into a training/validation set
split_data <- split_validation(icesat_obs,sample=500,common=0, t==2)
icesat_validation <- split_data$O_val
icesat_training <- split_data$O_pruned
## Now create GMRF defined over some FE basis
Mesh <- initFEbasis(p=surf_fe$p,
t=surf_fe$t,
M=surf_fe$M,
K=surf_fe$K)
mu <- matrix(0,nrow(Mesh),1)
Q <- sparseMatrix(i=1:nrow(surf_fe$p), j = 1:nrow(surf_fe$p), x = 1)
my_GMRF <- GMRF(mu = mu, Q = Q,name="SURF",t_axis = 0:6)
SURF <-GMRF_basis(G = my_GMRF, Basis = Mesh)
L1 <- link(SURF,icesat_training)
e <- link_list(list(L1))
v <- block_list(list(O = icesat_training, G = SURF))
G <- new("Graph",e=e,v=v)
G_reduced <- compress(G)
Results <- Infer(G_reduced)
## Now we validate the results with icesat
L1 <- link(SURF,icesat_validation)
e <- link_list(list(L1))
v <- block_list(list(G1=SURF,O1=icesat_validation))
G <- Graph(e=e,v=v)
G_reduced <- compress(G)
val_results <- validate(Results,G_reduced,sim_obs=F)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.