[R] pls package - validation

[Ladislav Rozkošný]

Hi,




I'm trying to fit PLSR model in R with 'pls' package with 22 samples (16 
train, 6 test). I know that basic for considering of number of component is 
cross-validation (in my case 'LOO') and then I should choose number of 
component with minimum of RMSEP (or first minimum). But problem is that 
values of RMSEP is increasing (not the opposite). Should I choose only 1 
component?




And then I tried compute R2 with my test-dataset (6 samples) and I received 
nonsensical values (below 0, bigger then 1).

Do you have any idea what may be caused? If it's my problem with fitting or 
problem with datasets.




Below, you can see my results:




>pH.spec<-plsr(pH ~ spec, data=soil.train, validation="LOO")

>summary(pH.spec)

Data:     X dimension: 16 501 
    Y dimension: 16 1
Fit method: kernelpls
Number of components considered: 14

VALIDATION: RMSEP
Cross-validated using 16 leave-one-out segments.
       (Intercept)  1 comps  2 comps  3 comps  4 comps  5 comps  6 comps  7 
comps  8 comps  9 comps  10 comps  11 comps
CV          0.5343   0.5435   0.5506    1.629    1.617    1.742    1.921    
1.979    1.977    1.971     1.972     1.972
adjCV       0.5343   0.5419   0.5486    1.587    1.570    1.688    1.860    
1.916    1.914    1.908     1.910     1.909
       12 comps  13 comps  14 comps
CV        1.972     1.972     1.972
adjCV     1.909     1.909     1.909

TRAINING: % variance explained
    1 comps  2 comps  3 comps  4 comps  5 comps  6 comps  7 comps  8 comps  
9 comps  10 comps  11 comps  12 comps
X    96.410   99.655    99.87    99.90    99.93    99.94    99.95    99.96  
  99.96     99.97     99.98     99.99
pH    3.649    8.342    19.41    67.48    88.96    97.19    99.69    99.94  
  99.99    100.00    100.00    100.00
    13 comps  14 comps
X      99.99       100
pH    100.00       100




> R2(pH.spec, newdata = soil.test)
(Intercept)      1 comps      2 comps      3 comps      4 comps      5 comps
      6 comps      7 comps      8 comps  
   -1.65763     -0.60849     -0.05253     -0.72870     -2.84718     -2.34102
     -3.28201     -3.68611     -3.69817  
    9 comps     10 comps     11 comps     12 comps     13 comps     14 comps
  
   -3.77271     -3.74585     -3.76342     -3.76074     -3.76110     -3.76115
  





Thank you in advance for your help






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