posterior function

Posterior probabilities based on a group-based multivariate trajectory model

Posterior probabilities based on a group-based multivariate trajectory model

Computation of posterior probabilities for new units.

posterior(x, newdata=NULL)

Arguments

  • x: Object of class gbmt.
  • newdata: Object of class data.frame containing the multivariate time series of the indicators for the new units. If NULL (the default), posterior probabilities of the sample units are returned. If newdata is not NULL, it must include the variable identifying the time points. If newdata does not include the variable identifying the units, it is assumed that all observations refer to the same unit.

Returns

An object of class data.frame with one entry for each unit, containing the posterior probability of each group for that unit.

Note

Data in newdata must be expressed on the original scale of the indicators. Normalisation is applied internally.

See Also

gbmt .

Examples

data(agrisus2) # names of indicators (just a subset for illustration) varNames <- c("TFP_2005", "NetCapital_GVA", "Income_rur", "Unempl_rur", "GHG_UAA", "GNB_N_UAA") # model with 2 polynomial degrees and 3 groups m3_2 <- gbmt(x.names=varNames, unit="Country", time="Year", d=2, ng=3, data=agrisus2, scaling=4) # pretend that 'Italy' is a new unit posterior(m3_2, newdata=agrisus2[which(agrisus2$Country=="Italy"),]) # consider only the last 3 years posterior(m3_2, newdata= agrisus2[which(agrisus2$Country=="Italy"&agrisus2$Year>=2016),] ) # provide more than one new unit posterior(m3_2, newdata= agrisus2[which(agrisus2$Country%in%c("Italy","Austria","Greece")),] )
  • Maintainer: Alessandro Magrini
  • License: GPL-2
  • Last published: 2024-12-02

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