atsa-es / marsstmb Goto Github PK

• add tinitx so x0 can be at 0
• estimate_marss2() is slow. Try logging the diagonal and then Q.diagonal() = Q.diagonal().exp(); https://stackoverflow.com/questions/33834873/modify-eigen-matrix-diagonal. vector diag_exp = Q.diagonal().array().exp();` Q.diagonal().array() = diag.exp;
• Not handling convergence messages from nlminb
• add Q estimation (diag or unconstrained)
• nlminb not picking up maxit? check might have been the print issue that I fixed
• check tinitx = 0 and V0 not zero
• allow zeros on diagonal of R and Q
• add D estimation; cutting out all the extraneous stuff to make just like MARSS
• add C estimation
• fix the print out. something is off with metadata
• I bet CRAN will complain re ::: what to do?
• Add in test for marssTMB being installed and loaded if method="TMB"
• Revamp the vignettes
• Add vignette for model comparisons/testing

LATER

• Add G and H to allow zeros on the diagonal of Q and R
• Test time-varying Q and R
• look into how to do equal var cov; the diag splitting didn't work.

MARSS

• add method="TMB"
• fix the error with iterations for optim. should be counts[2]
• need Rd file for MARSS::MARSSfit

Running into numerical problems but not really reporting that.

Should put in the option to compute the chol of the var-cov matrix the way I did for MARSSoptim(). Something is off with the separation method.

library(MARSS)
data(lakeWAplankton, package = "MARSS")
phytoplankton <- c("Cryptomonas", "Diatoms", "Greens", "Unicells", "Other.algae")
dat <- as.data.frame(lakeWAplanktonTrans) |>
  subset(Year >= 1980 & Year <= 1989) |>
  subset(select=phytoplankton) |>
  t() |>
  MARSS::zscore()
modlist = list(U="zero", A="zero", Q="unconstrained")
a = MARSS(dat[,14:22], method="BFGS_TMB", model=modlist, control=list(trace=1))

LL much lower than

a = MARSS(dat[,14:22], method="BFGS_TMB")

also LL doesn't match. The LL output is from the KF but within the opt output is the LL coming from TMB. Should match.

a$iter.record$opt.output$value

@ericward-noaa When I change .hpp files, the .so and .o files don't get rebuild when I hit 'Install' and rebuild the package the .so and .o files don't rebuild. What am I doing wrong? Thanks!!

This is lower with BFGS. Even if. Perhaps has something to do with the NAs in the data. Seems to go away wo the NAs.

library(marssTMB)
U1 <- matrix(0,2,1)
Q1 <- matrix(c("q11","q12","q12","q22"),2,2)
Z1 <- matrix(c(1,0,1,1,1,0),3,2)
A1 <- matrix(list("a1",0,0),3,1)
R1 <- matrix(list("r11",0,0,0,"r",0,0,0,"r"),3,3)
pi1 <- matrix(0,2,1); V1=diag(1,2)
model.list <- list(U=U1, Q=Q1, Z=Z1, A=A1, R=R1, x0=pi1, V0=V1, tinitx=0)
dat <- t(harborSealWA)[2:4, ] # remove the year row
fit1 <- MARSS(dat, model=model.list, method="BFGS")
fit2 <- MARSS(dat, model=model.list, method="TMB", inits=fit1)

dat <- t(harborSealWA); dat <- dat[2:4, ]
modlist = list(U="zero", A="zero", x0="zero", Q="unconstrained")
MARSS(dat[,14:22], method="TMB", silent=TRUE, model=modlist)$logLik
MARSS(dat[,14:22], silent=TRUE, model=modlist)$logLik

maxit not getting set for nlminb

a = MARSS(dat[,14:22], method="TMB", model=modlist, control=list(maxit=20000))

false convergence for nlminb but seems ok

modlist = list(U="zero", A="zero", Q="unconstrained", tinitx=1)
a = MARSS(dat[,14:22], method="TMB", model=modlist)
a = MARSS(dat[,14:22], method="BFGS_TMB", model=modlist)
a = MARSS(dat[,14:22], model=modlist)

false convergence for nlminb and no convergence at 5000+ iter for optim,

modlist = list(U="zero", A="zero", Q="unconstrained", x0="zero", tinitx=1)
a = MARSS(dat[,14:22], method="TMB", model=modlist) # reports false convergence but better LL than EM
a = MARSS(dat[,14:22], method="BFGS_TMB", model=modlist) # not remotely converged
a = MARSS(dat[,14:22], method="BFGS", model=modlist) # bad
a = MARSS(dat[,14:22], model=modlist) 
a = MARSS(dat[,14:22], method="BFGS", model=modlist, inits=a) # good same as TMB

false/no convergence but LL looks ok

modlist = list(U="zero", A="zero", Q="unconstrained")
a = MARSS(dat[,14:22], method="TMB", model=modlist)
a = MARSS(dat[,14:22], method="BFGS_TMB", model=modlist)
a = MARSS(dat[,14:22], model=modlist)

Not handling convergence messages from nlminb

@ericward-noaa

I think one the first tasks is to write a generic TMB function that does:

A %*% x

So rather than writing code for Bx, and Cc, and Dd. We have a function for mult(A, x). Maybe you have something like that already?

Idea is to have maps for all the MARSS parameters and then code to do

x(t) - Bx(t-1) + u + Cc(t) ~ MVN(0, Q)

and

y(t) - Zx(t) + a + Dd(t) = MVN(0, R)

Seems pretty straight forward from Tim's code, but that mult(A, x) function would make the code cleaner.

par should be in marss form

> names(m1.em$par)
 [1] "Z"  "A"  "R"  "B"  "U"  "Q"  "x0" "V0" "G"  "H"  "L" 
> names(m1.tmb2$par)
 [1] "Z"  "A"  "R"  "B"  "U"  "Q"  "x0" "V0" "D"  "C"  "d"  "c"  "G"  "H"  "L" 
>