tests/xtests.R

In spatPomp: Inference for Spatiotemporal Partially Observed Markov Processes

## extra tests of correctness requiring addition Monte Carlo intensity

XTEST <- FALSE
set.seed(42)
library(spatPomp)

if(XTEST){

  print("Test PF/KF consistency for bm")
  bb <- bm(U=4,N=10)
  bb_pf_loglik <- round(logLik(pfilter(bb,1000)),10)
  print(paste("bm pfilter loglik: ",bb_pf_loglik))
  print(paste("bm kalman filter loglik: ",round(bm_kalman_logLik(bb),10)))

  print("Test PF/KF consistency for bm2")
  bb2 <- bm2(U=4,N=10)
  bb2_pf_loglik <- round(logLik(pfilter(bb2,1000)),10)
  print(paste("bm2 pfilter loglik: ",bb2_pf_loglik))
  print(paste("bm2 kalman filter loglik: ",round(bm2_kalman_logLik(bb2),10)))

  print("Test PF/KF consistency for bm2 with unequal parameters")
  U <- 4
  bb3 <- bm2(U=U,N=10,unit_specific_names=c("rho","sigma","tau","X_0"))
  coef(bb3)[paste("rho",1:U)]=seq(from=0.2,to=0.8,length=U)
  coef(bb3)[paste("sigma",1:U)]=seq(from=0.8,to=1.2,length=U)
  coef(bb3)[paste("tau",1:U)]=seq(from=0.5,to=1.5,length=U)
  coef(bb3)[paste("X_0",1:U)]=seq(from=-1,to=1,length=U)
  bb3 <- simulate(bb3)
  bb3_pf_loglik <- round(logLik(pfilter(bb3,1000)),10)
  print(paste("bm3 pfilter loglik: ",bb3_pf_loglik))
  print(paste("bm3 kalman filter loglik: ",round(bm2_kalman_logLik(bb3),10)))

  print("Test he10 with towns_selected argument")
  h4 <- he10(U=4,towns_selected=c(1,2,11,12),
  basic_params = c(
    alpha =0.99,      iota=0,          R0=30,
    cohort=0.5,  amplitude=0.3,     gamma=52,
    sigma=52,           mu=0.02,  sigmaSE=0.05,
    rho=0.5,           psi=0.1,         g=800,
    S_0=0.036,         E_0=0.00007,   I_0=0.00006
  ))
  s4 <- simulate(h4,seed=27)
  obs(s4)[,1:2]
 
}