Description Usage Arguments Value Author(s) References See Also Examples
Estimate the CUDIA model parameters, then output cross-level imputed values. The default algorithm is set to the Bregman deterministic clustering algorithm in the referenced paper. Currently, only Gaussian-type data are supported.
1 |
formula |
a symbolic description of the model to be fit. e.g. x~y+z means that the aggregate-level summary x is cross-level imputed using individual-level data y and z. |
data |
a data frame object in the model. |
K |
a number of intrinsic clusters. |
... |
other algorithm operational parameters |
An object of class cudia
, basically a list including elements
indiv |
original individual-level data |
fitted.values |
cross-level imputed aggregated data |
theta |
parameter vectors for individual-level clusters |
eta |
a parameter vector for aggregate-level clusters |
Nk |
estimated cluster sizes |
xlab |
variable names of individual-level data |
Yubin Park
Y. Park and J. Ghosh, CUDIA: Probabilistic Cross-level Imputation using Individual Auxiliary Information, ACM Trans-IST, 2012.
1 2 3 | data(cudia_simul,package="cudia")
mod.sim <- cudia(aggr~indiv,cudia_simul,K=3)
summary(mod.sim)
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