| ZIPLN {PLNmodels} | R Documentation | 
Zero Inflated Poisson lognormal model
Description
Fit the multivariate Zero Inflated Poisson lognormal model with a variational algorithm. Use the (g)lm syntax for model specification (covariates, offsets, subset).
Usage
ZIPLN(
  formula,
  data,
  subset,
  zi = c("single", "row", "col"),
  control = ZIPLN_param()
)
Arguments
| formula | an object of class "formula": a symbolic description of the model to be fitted. | 
| data | an optional data frame, list or environment (or object coercible by as.data.frame to a data frame) containing the variables in the model. If not found in data, the variables are taken from environment(formula), typically the environment from which PLN is called. | 
| subset | an optional vector specifying a subset of observations to be used in the fitting process. | 
| zi | a character describing the model used for zero inflation, either of 
 | 
| control | a list-like structure for controlling the optimization, with default generated by  | 
Details
Covariates for the Zero-Inflation parameter (using a logistic regression model) can be specified in the formula RHS using the pipe
(~ PLN effect | ZI effect) to separate covariates for the PLN part of the model from those for the Zero-Inflation part.
Note that different covariates can be used for each part.
Value
an R6 object with class ZIPLNfit
See Also
The class ZIPLNfit
Examples
data(trichoptera)
trichoptera <- prepare_data(trichoptera$Abundance, trichoptera$Covariate)
## Use different models for zero-inflation...
myZIPLN_single <- ZIPLN(Abundance ~ 1, data = trichoptera, zi = "single")
## Not run: 
myZIPLN_row    <- ZIPLN(Abundance ~ 1, data = trichoptera, zi = "row")
myZIPLN_col    <- ZIPLN(Abundance ~ 1, data = trichoptera, zi = "col")
## ...including logistic regression on covariates
myZIPLN_covar  <- ZIPLN(Abundance ~ 1 | 1 + Wind, data = trichoptera)
## End(Not run)