View source: R/combine.chains.r
combine.chains | R Documentation |
Combines two lists of chains from ifm.naive.MCMC, ifm.missing.MCMC, or ifm.robust.MCMC into one list where each element is the concatenated chains.
combine.chains(x1, x2, nburnin, nthin = 1, z.thin = TRUE)
x1 |
First list of chains. |
x2 |
Second list of chains. |
nburnin |
Number of initial iterations to discard. |
nthin |
If nthin>1, subsets to every nthin^th sample |
z.thin |
logical; defaults to TRUE. Thinning for the posterior sample of the occupancy states. If true, uses thinning equal to 5. The posterior sample of occupancy states is a large nsite x nyear x niter array, and this option reduces memory usage. Ignored if the chain is from the ifm.naive.MCMC (where occupancy states are fixed). |
Named list with the same names as the inputs x1 and x2
Benjamin Risk
data(simulatedifm) init1=list(alpha=runif(1,1,30), b=runif(1,0,5),y=runif(1,0,20),e=runif(1,0,1),x=runif(1,0,5)) inm1 <- ifm.naive.MCMC(niter=500,init=init1,z.data = z.sim,site.distance=sim.distance,site.area=sim.area, sd.prop.alpha=4,sd.prop.b=0.6,sd.prop.y=40,sd.prop.e=0.05,sd.prop.x=0.4,nthin=1,print.by=100) init1=list(alpha=runif(1,1,30), b=runif(1,0,5),y=runif(1,0,20),e=runif(1,0,1),x=runif(1,0,5)) inm2 <- ifm.naive.MCMC(niter=500,init=init1,z.data = z.sim,site.distance=sim.distance,site.area=sim.area, sd.prop.alpha=4,sd.prop.b=0.6,sd.prop.y=40,sd.prop.e=0.05,sd.prop.x=0.4,nthin=1,print.by=100) sim.inm=combine.chains(inm1,inm2,nburnin=0,nthin=1)
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