predx_classes.md

In cdcepi/predx: Tools for working with predictions

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

cdcepi/predx documentation built on Dec. 29, 2019, 4:58 p.m.