Bump the version to 0.3.0.3

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: modelbpp
 Title: Model BIC Posterior Probability
-Version: 0.3.0.2
+Version: 0.3.0.3
 Authors@R:
     c(person(given = "Shu Fai",
              family = "Cheung",

NEWS.md

@@ -1,4 +1,4 @@
-# modelbpp 0.3.0.2
+# modelbpp 0.3.0.3
 
 ## Miscellaneous
 
@@ -8,13 +8,17 @@
   (0.3.0.1)
 
 - If the option `modelbpp.do_fit` is set
-  to `FALSE`, a parameter table will not
+  to `FALSE` or not set, a parameter table will not
   be fitted to get the model *df*, leading
   to faster search. If this options is
-  set to `TRUE` or is not set, then the
+  set to `TRUE`, then the
   parameter table will be fitted as
   in 0.3.0.2 or older version.
-  (0.3.0.2)
+  (0.3.0.2, 0.3.0.3)
+
+- Disabled more options to make the search
+  faster.
+  (0.3.0.3)
 
 - Depends on R 4.1.0 or later now.
   (0.3.0.2)

R/get_add.R

@@ -426,7 +426,7 @@ gen_pt_add <- function(x, pt, sem_out, from = NA) {
         x_constr_out <- NULL
       }
     # Add free parameters
-    do_fit <- getOption("modelbpp.do_fit", TRUE)
+    do_fit <- getOption("modelbpp.do_fit", FALSE)
     if (length(x_free) > 0) {
         x_free_str <- par_names(pars_list = x_free)
         p_to_add <- sapply(x_free, paste0, collapse = "")
@@ -436,6 +436,15 @@ gen_pt_add <- function(x, pt, sem_out, from = NA) {
           model = pt,
           add = x_free_str,
           do.fit = do_fit,
+          baseline = FALSE,
+          h1 = FALSE,
+          implied = FALSE,
+          check.vcov = FALSE,
+          check.start = FALSE,
+          check.sigma.pd = FALSE,
+          check.gradient = FALSE,
+          check.post = FALSE,
+          samplestats = do_fit,
           optim.force.converged = TRUE,
           control = list(max.iter = 1)
         )
@@ -455,6 +464,15 @@ gen_pt_add <- function(x, pt, sem_out, from = NA) {
           object = sem_out,
           model = pt,
           do.fit = do_fit,
+          baseline = FALSE,
+          h1 = FALSE,
+          implied = FALSE,
+          check.vcov = FALSE,
+          check.start = FALSE,
+          check.sigma.pd = FALSE,
+          check.gradient = FALSE,
+          check.post = FALSE,
+          samplestats = do_fit,
           optim.force.converged = TRUE,
           control = list(max.iter = 1)
         )

R/get_drop.R

@@ -232,7 +232,7 @@ gen_pt_drop <- function(x, pt, to, source_df = NA, sem_out) {
     p_to_drop_out <- lapply(x, function(x) {
         c(lhs = pt[x, "lhs"], op = pt[x, "op"], rhs = pt[x, "rhs"])
       })
-    do_fit <- getOption("modelbpp.do_fit", TRUE)
+    do_fit <- getOption("modelbpp.do_fit", FALSE)
     suppressWarnings(sem_out_update <- auto_ram(
       FUN = lavaan::update,
       object = sem_out,
@@ -245,6 +245,11 @@ gen_pt_drop <- function(x, pt, to, source_df = NA, sem_out) {
       check.start = FALSE,
       check.post = FALSE,
       check.vcov = FALSE,
+      h1 = FALSE,
+      implied = FALSE,
+      check.sigma.pd = FALSE,
+      check.gradient = FALSE,
+      samplestats = do_fit,
       control = list(max.iter = 1))
     )
     pt_update <- lavaan::parameterTable(sem_out_update)

README.md

@@ -11,7 +11,7 @@
 
 # modelbpp: Model BIC Posterior Probability <img src="man/figures/logo.png" align="right" />
 
-(Version 0.3.0.2 updated on 2026-05-30, [release history](https://sfcheung.github.io/modelbpp/news/index.html))
+(Version 0.3.0.3 updated on 2026-06-03, [release history](https://sfcheung.github.io/modelbpp/news/index.html))
 
 This package is for assessing model uncertainty in structural
 equation modeling (SEM) by the BIC posterior