extRC {extRC}

Extended RC model

Description

Main function that fits extended RC models based on different types of aggregation (continuation, local, global) and different divergence functions defined by a suitable value of lambda.

Usage

extRC(N, mod, k, la, marg.cons = c("free","equal","shift"))

Arguments

N

observed contingency table

mod

vector indicating the types of aggregation for row and column variables ("c" for continuation, "l" for local, "g" for global)

k

rank required for the matrix of interaction parameters

la

value of lambda parameter

marg.cons

type of constraint on the marginal distributions

Value

la

vector of lambda values (when a vector is in input)

dev

deviance of the fitted model (when only one lambda value is in input) or vector of deviances (when a vector of lambda values is in input)

df

degrees of freedom (when only one lambda value is in input)

it

number of iterations (when only one lambda value is in input)

dis

final discrepancy (when only one lambda value is in input)

pj

vector of joint probabilities under the fitted model (when only one lambda value is in input)

eta

full vector of marginal parameters (when only one lambda value is in input)

etaX

vector of row marginal parameters (when only one lambda value is in input)

etaY

vector of column marginal parameters (whenonly one lambda value is in input)

Eta

matrix of association parameters (when only one lambda value is in input)

la

vector of lambda values (when more lambda values are in input)

dev

vector of deviance values (when more lambda values are in input)

Author(s)

Francesco Bartolucci, Antonio Forcina

Examples

# load data
data(mobility)

# for a single value of lambda, fit model with constraints of rank 1 on
# local-local logits and without constraints on the marginal distributions
out = extRC(mobility,mod=c("l","l"),k=1,la=0.6)
summary(out)

# for a single value of lambda, fit model with constraints of rank 1 on
# local-local logits and under constrain of equal marginal distributions
out = extRC(mobility,mod=c("l","l"),k=1,la=0.6,marg.cons="equal")
summary(out)

# for a single value of lambda, fit model with constraints of rank 2 on
# global-global logits and under constraint that marginal distributions
# are equal up to a constant shift
out = extRC(mobility,mod=c("g","g"),k=2,la=0.6,marg.cons="shift")
summary(out)

# fit model for a vector of lambdas
la = seq(-1.8,0.6,length.out=10)
out1 = extRC(mobility,mod=c("l","l"),k=1,la=la)
plot(out1)