Conditional Predictive Ordinate (CPO) Statistic
Makes the CPO Plot and calculates the logarithm of the Pseudomarginal likelihood (LPML).
cpo(res)
res |
tibble. The output from the *Res functions, where * could either be BeM, GaM, CGaM, CuM, CCuM |
Computes de CPO as a goodness of fit measure
LPML |
The value of the logarithm of the Pseudomarginal likelihood |
plot |
CPO Plot |
See Geisser (1993); Gelfand, Dey, and Chang (1992); Dey, Chen, and Chang (1997); and Sinha and Dey (1997)
## Example 1 # data(gehan) # timesG <- gehan$time[gehan$treat == "6-MP"] # deltaG <- gehan$cens[gehan$treat == "6-MP"] # GEX1 <- GaMRes(timesG, deltaG, K = 8, iterations = 3000) # cpo(GEX1)
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