objective {metabCombiner} | R Documentation

## Weight Parameter Objective Function

### Description

This function evaluates the A, B, C weight parameters in terms of score separability of matching versus mismatching compound alignments. Higher objective function value imply a superior weight parameter selection.

### Usage

    objective(
      cTable,
      idtable,
      A,
      B,
      C,
      minScore,
      mzdiff,
      rtdiff,
      qdiff,
      rtrange,
      adductdiff,
      penalty,
      matches,
      mismatches
    )

### Arguments

`cTable` | data frame. Abridged `metabCombiner` report table.
`idtable` | data frame containing all evaluated identities
`A` | Numeric weight for penalizing m/z differences.
`B` | Numeric weight for penalizing differences between fitted & observed retention times
`C` | Numeric weight for differences in Q (abundance quantiles).
`minScore` | numeric. Minimum score to count towards objective value.
`mzdiff` | numeric differences between feature m/z values
`rtdiff` | Differences between model-projected retention time value & observed retention time
`qdiff` | Difference between feature quantile Q values.
`rtrange` | range of dataset Y retention times
`adductdiff` | Numeric divisors of computed score when non-empty adduct labels do not match
`penalty` | positive numeric penalty wherever S(i,j) > S(i,i), i =/= j
`matches` | integer row indices of identity matches
`mismatches` | list of integer identity row mismatches for each identity

### Details

First, the similarity scores between all grouped features are calculated as described in `scorePairs`

Then, the objective value for a similarity S is evaluated as:

OBJ(S) = ∑ h(S(i,i)) - h(S(i, j)) - p(S(i,i) > S(i,j))

-S(i,i) represents the similarity between correct identity alignments
-S(i,j), represents the maximum similarity of i to grouped feature j, i =/= j (the highest-scoring misalignment)
-h(x) = x if x > `minScore`, 0 otherwise
-p(COND) = 0 if the condition is true, and a `penalty` value otherwise

This is summed over all labeled compound identities (e.g. idx = idy) shared between input datasets.

### Value

A numeric value quantifying total separability of compound match similarity scores from mismatch scores, given A,B,C values

[Package metabCombiner version 1.4.0 Index]