addressed PR comments, cleaned up some R CMD warnings

Author: Paul-Carvalho

R/check_exp.R

@@ -2,12 +2,12 @@ check_exp <- function(ec, ec_names) {
 #' Prepare expected catch matrix
 #' 
 #' Checks that specified expected catch matrices exists and is formatted correctly
-#' when \code{\link{make_model_design}} is called.
+#' when \code{make_model_design} is called.
 #' 
 #' @param ec Expected catch list created by \code{\link{create_expectations}}.
 #' @param ec_names The names of the expected catch matrices to include in the
 #'   model and how they are used (i.e. used together or separately). See the
-#'   \code{expectcatchmodels} argument in \code{\link{make_model_design}}.
+#'   \code{expectcatchmodels} argument in \code{make_model_design}.
 #' @returns Returns a list containing the filtered expected catch list and specified
 #'   matrices to include in model.
 #' @details Checks that \code{ec_names} is specified properly by identifying 

R/create_alternative_choice.R

@@ -81,25 +81,25 @@
 #' @details Defines the alternative fishing choices. These choices are used to develop
 #'  the matrix of distances between observed and alternative fishing choices (where
 #'  they could have fished but did not). The distance matrix is calculated by the
-#'  [make_model_design()] function. `occasion` defines the observed fishing
+#'  [format_model_data()] function. `occasion` defines the observed fishing
 #'  location and `alt_var` the alternative fishing location. `occasion_var`
 #'  identifies an ID column or set of lon-lat variables needed to create the
 #'  distance matrix.
 #'
 #'  Parts of the alternative choice list are pulled by [create_expectations()],
-#'  [make_model_design()], and the model run [discretefish_subroutine()])
+#'  [format_model_data()], and the model run [fishset_fit()])
 #'  functions. These output include choices of which variable to use for catch and
 #'  which zones to include in analyses based on a minimum number of hauls per trip
 #'  within a zone. Note that if the alternative choice list is modified, the
-#'  [create_expectations()] and [make_model_design()] functions
+#'  [create_expectations()] and [format_model_data()] functions
 #'  should also be updated before rerunning models.
 #' 
 #' @return Function saves a list of alternative choice matrices to the FishSET
 #'  database as `projectAlternativeChoice`. The list includes
 #'  the alternative choice list from the user-defined choices. Multiple alternative
 #'  choice cases can be added to the list by specifying unique names. The list is
 #'  automatically saved to the FishSET database and is called in
-#'  `make_model_design`.
+#'  `format_model_data`.
 
 create_alternative_choice <- function(dat,
                                       project,

R/create_dist_matrix.R

@@ -28,7 +28,7 @@
 #' @importFrom stats setNames
 #' @export 
 #' @keywords internal
-#' @details Function is called by \code{\link{make_model_design}} to generate the
+#' @details Function is called by \code{\link{format_model_data}} to generate the
 #'   distance matrix. Alternative fishing options come from the Alternative Choice
 #'   list, generated from the \code{\link{create_alternative_choice}} function.
 #' @return

R/create_expectations.R

@@ -1,7 +1,7 @@
 #' Create expected catch/expected revenue matrix
 #'
 #' Create expected catch or expected revenue matrix. The matrix is required for 
-#' the \code{\link{logit_c}} model. Multiple matrices (with unique names) can be saved in a 
+#' the conditional logit model. Multiple matrices (with unique names) can be saved in a 
 #' project.
 #' 
 #' @param dat Primary data containing information on hauls or trips. Table in FishSET 
@@ -55,11 +55,11 @@
 #'   as \code{projectExpectedCatch}. The list includes 
 #'   the expected catch matrix from the user-defined choices. Multiple expected catch cases 
 #'   can be added to the list by specifying unique names. The list is automatically saved to 
-#'   the FishSET database and is called in \code{\link{make_model_design}}. The expected catch 
+#'   the FishSET database and is called in \code{\link{format_model_data}}. The expected catch 
 #'   output does not need to be loaded when defining or running the model.
 #' @details Function creates an expectation of catch or revenue for alternative 
 #'   fishing zones (zones where they could have fished but did not). The output is 
-#'   saved to the FishSET database and called by the \code{\link{make_model_design}} 
+#'   saved to the FishSET database and called by the \code{\link{format_model_data}} 
 #'   function. \code{\link{create_alternative_choice}} must be called first as observed 
 #'   catch and zone inclusion requirements are defined there.\cr 
 #'   The primary choices are whether to treat data as a fleet or to group the data 

R/epm_lognormal.R

@@ -30,7 +30,7 @@ epm_lognormal <- function(starts3, dat, otherdat, alts, project, expname, mod.na
   #' @param expname Expected catch table (optional)
   #' @param mod.name Name of model run for model result output table
   #' @return ld: negative log likelihood
-  #' @details This function is called in \code{\link{discretefish_subroutine}} when running an EPM model with
+  #' @details This function is called in \code{discretefish_subroutine} when running an EPM model with
   #'     a log-normal catch function.
   #' @export
 

R/epm_normal.R

@@ -29,7 +29,7 @@ epm_normal <- function(starts3, dat, otherdat, alts, project, expname, mod.name)
   #' @param expname Expected catch table (optional)
   #' @param mod.name Name of model run for model result output table
   #' @return ld: negative log likelihood
-  #' @details This function is called in \code{\link{discretefish_subroutine}} when running an EPM model with
+  #' @details This function is called in \code{discretefish_subroutine} when running an EPM model with
   #'     a normal catch function.
   #' @export
 

R/epm_weibull.R

@@ -30,7 +30,7 @@ epm_weibull <- function(starts3, dat, otherdat, alts, project, expname, mod.name
   #' @param expname Expected catch table (optional)
   #' @param mod.name Name of model run for model result output table
   #' @return ld: negative log likelihood
-  #' @details This function is called in \code{\link{discretefish_subroutine}} when running an EPM model with
+  #' @details This function is called in \code{discretefish_subroutine} when running an EPM model with
   #'     a Weibull catch function.
   #' @export
 

R/fishset_fit.R

@@ -36,6 +36,30 @@
 #'   \item{diagnostics}{A list containing the Hessian, gradients, eigenvalues, and 
 #'     condition number.}
 #' }
+#' 
+#' @examples
+#' \dontrun{
+#'   # 1. Standard fit using default settings
+#'   # This uses the design object named "clogit_design" saved in "MyProject"
+#'   fit_result <- fishset_fit(
+#'     project = "MyProject",
+#'     model_name = "clogit_design"
+#'   )
+#'   
+#'   # 2. Advanced fit with custom optimization settings and start values
+#'   # 'control' and 'start_values' are passed via the '...' argument
+#'   fit_custom <- fishset_fit(
+#'     project = "MyProject",
+#'     model_name = "clogit_design",
+#'     fit_name = "clogit_custom_fit",
+#'     
+#'     # Pass control list to nlminb (e.g., increase max iterations, turn on tracing)
+#'     control = list(eval.max = 5000, iter.max = 5000, trace = 1),
+#'     
+#'     # Pass initial start values for the parameters (e.g., for 2 predictors)
+#'     start_values = c(0.5, -0.2)
+#'   )
+#' }
 #'
 #' @seealso \code{\link{fishset_design}} for creating the input design object.
 #'
@@ -62,7 +86,16 @@ fishset_fit <- function(project,
 
   design <- full_design_list[[model_name]]
 
-  if (is_empty(fit_name)) fit_name <- paste0(model_name, "_fit")
+  # Load model fit list and check fit_name input
+  full_fit_list <- unserialize_table(paste0(project, "ModelFit"), project)
+
+  if (is_empty(fit_name)) {
+    fit_name <- paste0(model_name, "_fit")
+  }
+  
+  if (fit_name %in% names(full_fit_list)) {
+    stop(paste0("Model fit '", fit_name, "' already exists. Enter a new fit_name."))
+  }
 
   # Extract "..." arguments -----------------------------------------------------------------------
   dots <- list(...)
@@ -298,6 +331,7 @@ fishset_fit <- function(project,
   class(result) <- "fishset_fit"
 
   # Save to database ------------------------------------------------------------------------------
+  # Check if fit_name exists
   fishset_db <- DBI::dbConnect(RSQLite::SQLite(), locdatabase(project = project))
   on.exit(DBI::dbDisconnect(fishset_db), add = TRUE)
 
@@ -389,6 +423,6 @@ print.fishset_fit <- function(x, digits = 4, ...) {
     p_val_str <- format.pval(x$LR_p_value, eps = 0.001)
     cat("LR Test:        Chi2 =", fmt(x$LR_stat, 2), ", p =", p_val_str, sig_star, "\n")
   }
-
+  
   invisible(x)
 }

R/format_grid.R

@@ -2,7 +2,7 @@
 #' 
 #' Change the format of a gridded dataset from wide to long (or vice versa) 
 #' and remove any unmatched area/zones from `grid`. This is a necessary step
-#' for including gridded variables in the conditional logit ([logit_c()]) model.
+#' for including gridded variables in the conditional logit model.
 #' 
 #' @param grid Gridded dataset to format.
 #' @param dat Primary data containing information on hauls or trips. Table in 

R/model_prediction.R

@@ -18,7 +18,7 @@
 #' @importFrom yaml read_yaml
 #' @importFrom DBI dbConnect dbDisconnect dbGetQuery
 #' @importFrom RSQLite SQLite
-#' @details Calls \code{\link{logit_predict}}, \code{\link{epm_predict}}, and 
+#' @details Calls \code{logit_predict}, \code{epm_predict}, and 
 #'    \code{\link{predict_probability}}. Closure scenarios and TAC must be define using 
 #'    \code{\link{zone_closure}} function before function can be run. 
 #' @export