...

R/coef.R

@@ -100,6 +100,7 @@ coef.mnhmm <- function(object, probs = c(0.025, 0.5, 0.975), ...) {
   D <- object$n_clusters
   gamma_pi_raw <- unlist(object$coefficients$gamma_pi_raw)
   K_i <- length(object$coef_names_initial)
+  object$state_names <- unname(object$state_names)
   gamma_pi <- data.frame(
     state = unlist(lapply(object$state_names, function(x) x[-1])),
     parameter = rep(object$coef_names_initial, each = (S - 1)),

R/get_probs.R

@@ -340,7 +340,7 @@ get_emission_probs.mnhmm <- function(model, ...) {
               state = model$state_names[[j]],
               channel = model$channel_names[i],
               observation = rep(symbol_names[[i]], each = S),
-              estimate = c(
+              estimate = unlist(
                 get_B_all(
                   model$coefficients$gamma_B_raw[[j]][[i]], model$X_emission, 
                   FALSE, FALSE,attr(model, "tv_B")

tests/testthat/test-forward_backward.R

@@ -64,7 +64,7 @@ test_that("'forward_backward' works for single-channel 'nhmm'", {
   set.seed(1)
   expect_error(
     fit <- estimate_nhmm(
-      hmm_biofam$observations[[1]], n_states = 3,
+      hmm_biofam$observations[[1]][1:10,], n_states = 3,
       restarts = 2, threads = 1, maxeval = 2
     ),
     NA