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predx_classes.md

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Point predictions

Point

A numeric point prediction.

CSV column name: point

Validity:

  • Not NA

PointCat

A character string point prediction, e.g. associated with SampleCat or BinCat.

CSV column name: point

Validity:

  • Not NA

Continuous distributions

Normal: mean, sd

Log-normal: mean, sd

Gamma: shape, rate

Beta: a, b

Discrete distributions

Binary: prob

A numeric probability.

CSV column name: prob

Validity:

  • Not NA
  • 0 <= prob <= 1

Binomial: p, n

Poisson: mean

Negative-Binomial: r, p

Negative-Binomial2: mean, dispersion

Empirical distributions

BinLwr

Binned distribution defined by inclusive lower bounds for each bin.

A data.frame object with two columns:

  • lwr: inclusive numeric lower bounds for sequential bins (equal intervals)
  • prob: probabilities assigned to each bin

CSV column names: lwr, prob

Validity:

  • No NAs in lwr or prob
  • Probabilities are positive
  • Probabilities sum to 1.0
  • Bins are in ascending order
  • Bin sizes are uniform

BinCat

Binned distribution with a category for each bin.

A data.frame object with two columns:

  • cat: character strings representing each possible outcome category
  • prob: probabilities assigned to each bin

CSV column names: cat, prob

Validity:

  • No NAs in lwr or prob
  • Probabilities are positive
  • Probabilities sum to 1.0

Sample

Numeric samples.

CSV column name: sample

Validity:

  • No NAs

SampleCat

Character string samples.

CSV column name: sample

Validity:

  • No NAs