[R-sig-Geo] Problem of vector allocation in GSIF package

[Tomislav Hengl]

You have two options:

1. Run predictions using tiling 
(https://github.com/Envirometrix/BigSpatialDataR#dem-analysis-using-tiling-and-parallelization)

2. Buy more RAM.

I suggest using option 1 since option 2 can propagate to infinity.

PS: I am working on a new package 
(https://github.com/Envirometrix/landmap/) that should give more 
flexibility to users and maybe even incorporate tiling of large objects 
by default.


On 9/13/19 5:38 PM, Manuel Spínola wrote:
> Dear list members,
> 
> I am fitting a model with the GSIF package, but I ran into a problem of
> vector allocation.  Is there any way to solve this problem?  See code and
> error message below.
> 
> I am using:
> R 3.6.1
> GSIF 0.5-5
> Mac with 16 GB of RAM
> 
>> rk_rf_ac <- fit.gstatModel(variables_todos_sp["ac"], ac_formulaString_correlacion, covar_finales_sp, method = "quantregForest")Fitting a Quantile Regression Forest model...Shapiro-Wilk normality test and Anderson-Darling normality test report probability of < .05 indicating lack of normal distribution for residualsFitting a 2D variogram...Saving an object of class 'gstatModel'...> rk_rf_ac_pred <- GSIF::predict(rk_rf_ac, covar_finales_sp, predict.method = "KED")Error: cannot allocate vector of size 19.4 Gb
> 
> Thank you very much,
> 
> Manuel
>