dec_neg is a frequency that describes the number of individuals in the current population N for which the decision is negative (i.e., cases not called or not predicted).

dec_neg

## Format

An object of class numeric of length 1.

## Details

Key relationships:

1. to probabilities: The frequency of dec_neg individuals depends on the population size N and the decision's proportion of negative decisions (1 - ppod) and is split further into two subsets of cr by the negative predictive value NPV and mi by the false omission rate FOR = 1 - NPV.

Perspectives:

1. by condition:

The frequency dec_neg is determined by the population size N times the proportion of negative decisions (1 - ppod):

dec_neg = N x (1 - ppod)

2. by decision:

a. The frequency cr is determined by dec_neg times the negative predictive value NPV:

cr = dec_neg x NPV

b. The frequency mi is determined by dec_neg times the false omission rate FOR = (1 - NPV):

mi = dec_neg x FOR = dec_neg x (1 - NPV)

2. to other frequencies: In a population of size N the following relationships hold:

• N = cond_true + cond_false (by condition)

• N = dec_pos + dec_neg (by decision)

• N = dec_cor + dec_err (by correspondence of decision to condition)

• N = hi + mi + fa + cr (by condition x decision)

Current frequency information is computed by comp_freq and contained in a list freq.

## References

Consult Wikipedia: Confusion matrix for additional information.

is_freq verifies frequencies; num contains basic numeric parameters; init_num initializes basic numeric parameters; freq contains current frequency information; comp_freq computes current frequency information; prob contains current probability information; comp_prob computes current probability information.
Other frequencies: N, cond_false, cond_true, cr, dec_cor, dec_err, dec_pos, fa, hi, mi
dec_neg <- 1000 * .67   # => sets dec_neg to 67% of 1000 = 670 cases.
is_freq(dec_neg)        # => TRUE#> [1] TRUEis_prob(dec_neg)        # => FALSE, as dec_neg is no probability (but ppod, NPV and FOR are)#> [1] FALSE