# installation
library(devtools)
install_github('bkellman/WeightedMeanCompletion')
library(WeightedMeanCompletion)
# interpolation in mtcars
X = data.matrix(mtcars)
X[sample(prod(dim(X)),20)] = NA
# default correlation based interpolation for rows (i) and columns (j)
X_out1 = interp_weightedMean(X,t=5)
# default correlation-based interpolation for columns (j), integer distance informed interpolation with exponential spreading function in rows (i)
X_out2 = interp_weightedMean(X,t=10,D_i=dist_integer(X),sim_func_i=sim_exp_func)
# integer distance informed interpolation with exponential spreading function in rows (i) and columns (j)
X_ou32 = interp_weightedMean(X,t=10,
D_i=dist_integer(X),sim_func_i=sim_exp_func,
D_j=dist_integer(X),sim_func_j=sim_exp_func)
For more information on parameter optimization, see the notes at the end of each function in R/benchmarking.R
https://www.overleaf.com/6466536zjchwf#/21826208/
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