multinomial_impute: Impute Values for missing multinomial values

In alexWhitworth/imputeMulti: Imputation Methods for Multivariate Multinomial Data

Impute Values for missing multinomial values

Description

Impute values for multivariate multinomial data using either EM or Data Augmentation.

Usage

multinomial_impute(
  dat,
  method = c("EM", "DA"),
  conj_prior = c("none", "data.dep", "flat.prior", "non.informative"),
  alpha = NULL,
  verbose = FALSE,
  ...
)

Arguments

dat	A data.frame. All variables must be factors.
method	c("EM", "DA") A string specifying EM or Data Augmentation (DA)
conj_prior	A string specifying the conjugate prior. One of c("none", "data.dep", "flat.prior", "non.informative").
alpha	The vector of counts α for a Dir(α) prior. Must be specified if conj_prior is either c("data.dep", "flat.prior"). If flat.prior, specify as a scalar. If data.dep, specify as a vector with key matching enum_comp.
verbose	Logical. If TRUE, provide verbose output on each iteration.
...	Arguments to be passed to other methods

Value

An object of class imputeMulti-class

References

Schafer, Joseph L. Analysis of incomplete multivariate data. Chapter 7. CRC press, 1997.

See Also

data_dep_prior_multi, multinomial_em

Examples

## Not run: 
 data(tract2221)
 imputeEM <- multinomial_impute(tract2221[,1:4], method= "EM",
                   conj_prior = "none", verbose= TRUE)
 imputeDA <- multinomial_impute(tract2221[,1:4], method= "DA",
                   conj_prior = "non.informative", verbose= TRUE)

## End(Not run)

alexWhitworth/imputeMulti documentation built on July 15, 2022, 7:02 p.m.