Description Usage Arguments References See Also Examples
'Vuongtest' suggests the better of two (not necessarily nested) models according to Vuong's statistic for the parameters in each of the iterations.
1 2 |
LogLike1, LogLike2 |
the output of two model fits obtained by using 'LogLike'. |
alpha |
significance level, defaults to 0.05. |
p, q |
the number of estimated coefficients in models LogLike1 and Loglike2, respectively. |
correction |
boolean, if TRUE (default), the Schwarz correction will be used on the differences of log-likelihoods. |
Vuong, Q.H. (1989). Likelihood Ratio tests for model selection and nonnested hypotheses. Econometrica 57(2), 307-333.
Schwarz, G. (1978). Estimating the Dimension of a Model. Annals of Statistics 6, 461-464.
Clarketest
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | data(sim.Yin)
data(sim.fm.X)
data(sim.region)
data(sim.gmat)
data(sim.nmat)
poi <- est.sc(sim.Yin, ~1+sim.fm.X[,1]+sim.fm.X[,2], sim.region,
model="Poi", sim.gmat, sim.nmat, 3)
nb <- est.sc(sim.Yin, ~1+sim.fm.X[,1]+sim.fm.X[,2], sim.region,
model="NB", sim.gmat, sim.nmat, 3)
DIC.poi <- DIC(sim.Yin, ~1+sim.fm.X[,1]+sim.fm.X[,2], sim.region, poi)
DIC.nb <- DIC(sim.Yin, ~1+sim.fm.X[,1]+sim.fm.X[,2], sim.region, nb)
ll.poi <- LogLike(sim.Yin, ~1+sim.fm.X[,1]+sim.fm.X[,2], sim.region, poi)
ll.nb <- LogLike(sim.Yin, ~1+sim.fm.X[,1]+sim.fm.X[,2], sim.region, nb)
Vuong.poi.nb <- Vuongtest(ll.poi, ll.nb, alpha = 0.05, p = DIC.poi$p.D,
q = DIC.nb$p.D, correction = TRUE)
|
acceptb/(i+1) 0.8 0.8 0.8
acceptga1/i acceptga2/(i+1) 0.6 0.8
acceptpsi/(i+1) 0.2
acceptb/(i+1) 0.6 0.8 0.6
acceptga1/i acceptga2/(i+1) 0.4 0.8
acceptr/(i+1) 0.2
acceptpsi/(i+1) 0.6
DIC 9456.907
mean deviance 9035.386
p.D 421.5213
DIC 9381.389
mean deviance 9126.81
p.D 254.5798
Favour model 1 0
No decision 0
Favour model 2 1
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