I'm trying to fit a MultiStraussHardcore interaction to one of the sample datatsets in spatstat (flu). I'm maintaining the same interaction and hardcore radius for all types and point patterns. I'm running the following block:
library(spatstat)
library("optimbase")
flusubset <- flu[1:4]
typelist <- lapply(lapply(flusubset$pattern, marks), levels)
stopifnot(length(unique(typelist))==1)
num_marks <- length(typelist[[1]])
iradii <- 50*ones(num_marks)
hradii <- 3*ones(num_marks)
Int <- anylist()
for (i in 1:dim(flusubset)[1]) {
Int[[i]] <- MultiStraussHard(iradii=iradii, hradii=hradii)
}
Int <- as.hyperframe(Int)
multmodel <- mppm(pattern ~ 1, data=flusubset, interaction=Int)
Each time I run mppm, I get the following error
Error in (function (d, tx, tu, par) : data and model do not have the same possible levels of marks
I've included the traceback, too.
12. stop("data and model do not have the same possible levels of marks")
11. (function (d, tx, tu, par) { r <- par$iradii h <- par$hradii ...
10. do.call(fun, usedargs)
9. do.call.matched(pairpot, list(d = matrix(, 0, 0), tx = marks(X)[integer(0)], tu = marks(P)[integer(0)], par = potpars))
8. evalPairPotential(X, U, EqualPairs, pairpot, potpars, Reach)
7. evaluate(X, P, E, interaction$pot, interaction$par, correction = correction, splitInf = splitInf, ..., Reach = Reach, precomputed = precomputed, savecomputed = savecomputed)
6. evalInterEngine(X = X, P = P, E = E, interaction = interaction, correction = correction, splitInf = splitInf, ..., precomputed = precomputed, savecomputed = savecomputed)
5. evalInteraction(X, P, E, interaction, correction, ..., splitInf = splitInf, precomputed = precomputed, savecomputed = savecomputed)
4. mpl.prepare(Q, X, P, trend, interaction, covariates, want.trend, want.inter, correction, rbord, "quadrature points", callstring, subsetexpr = subsetexpr, allcovar = allcovar, precomputed = precomputed, savecomputed = savecomputed, covfunargs = covfunargs, weightfactor = weightfactor, ...
3. mpl.engine(Q, trend = trend, interaction = interaction, ..., covariates = covariates, correction = correction, rbord = rbord, use.gam = use.gam, allcovar = allcovar, preponly = TRUE, forcefit = TRUE)
2. bt.frame(Yi, ~1, inter, ..., covariates = covariates, allcovar = TRUE, use.gam = use.gam, vnamebase = itags[j], vnameprefix = itags[j])
1. mppm(pattern ~ 1, data = flusubset, interaction = Int)
I've tried fitting a MultiStraussHardcore model with ppm for each individual point pattern, and I have no issues. I've confirmed that the possible levels of each point pattern are identical. I've also verified that the interaction and hardcore radii matrices have the correct dimensions (2x2 for both) and that my hyperframe containing the interact objects is the correct dimensions. Thanks!
