docs updating documentation

R/02_modeler.R

@@ -1,25 +1,35 @@
-#' Modeler
+#' Modeler: Non-linear Regression for Curve Fitting
 #'
 #' @description
-#' General-purpose optimization techniques for non-linear least squares problems.
-#'
-#' @param data A data.frame in a wide format.
-#' @param x The name of the column in `data` that contains x points.
-#' @param y The name of the column in `data` that contain the variable to be analyzed. Must match a var in the data.
-#' @param grp The names of the columns in `data` that contains a grouping variable. (Optional).
-#' @param keep The names of the columns in `data` to keep across the analysis.
-#' @param fn A string specifying the name of the function to be used for the curve fitting. Default is \code{"fn_linear_sat"}.
-#' @param parameters Can be a named numeric vector specifying the initial values for the parameters to be optimized,
-#' If a data frame it needs to have a column \code{uid}, and the initial parameter values for each group id.
-#' If list it needs to be a named list with the initial parameters and numeric or string values can be used (e.g. list(k = "max(y)", t1 = 40)).
-#' Used for providing specific initial values per group id. Default is \code{NULL}.
-#' @param lower Numeric vector specifying the lower bounds for the parameters. Default is \code{-Inf} for all parameters.
-#' @param upper Numeric vector specifying the upper bounds for the parameters. Default is \code{Inf} for all parameters.
-#' @param fixed_params Can be a list or data frame. If data frame it needs columns \code{uid}, and the fixed parameter values for each group id.
-#' If list it needs to be a named list with the parameters to be fixed and numeric or string values can be used (e.g. list(k = "max(y)", t1 = 40)).
-#' @param method A character vector specifying the optimization methods to be used. Check `optimx::checkallsolvers()` for available methods.
-#' Default is \code{c("subplex", "pracmanm", "anms")}.
-#' @param subset An optional vector with levels of `grp` to filter the data. Default is \code{NULL}, meaning all groups are used.
+#' A versatile function for performing non-linear least squares optimization on grouped data.
+#' It supports customizable optimization methods, flexible initial/fixed parameters, and parallel processing.
+#' @param data A `data.frame` containing the input data for analysis.
+#' @param x The name of the column in `data` representing the independent variable (x points).
+#' @param y The name of the column in `data` containing the dependent variable to analyze (response variable).
+#' @param grp Column(s) in `data` used as grouping variable(s). Defaults to `NULL`. (optional)
+#' @param keep Names of columns to retain in the output. Defaults to `NULL`. (Optional)
+#' @param fn A string. The name of the function used for curve fitting.
+#'   Example: `"fn_linear_sat"`. Defaults to \code{"fn_linear_sat"}.
+#' @param parameters A numeric vector, named list, or `data.frame` providing initial values for parameters:
+#'   \describe{
+#'     \item{Numeric vector}{Named vector specifying initial values (e.g., `c(k = 0.5, t1 = 30)`).}
+#'     \item{Data frame}{Requires a `uid` column with group IDs and parameter values for each group.}
+#'     \item{List}{Named list where parameter values can be numeric or expressions (e.g., `list(k = "max(y)", t1 = 40)`).}
+#'   }
+#'   Defaults to `NULL`.
+#' @param lower A numeric vector specifying lower bounds for parameters. Defaults to `-Inf` for all parameters.
+#' @param upper A numeric vector specifying upper bounds for parameters. Defaults to `Inf` for all parameters.
+#' @param fixed_params A list or `data.frame` for fixing specific parameters:
+#'   \describe{
+#'     \item{List}{Named list where parameter values can be numeric or expressions (e.g., `list(k = "max(y)", t1 = 40)`).}
+#'     \item{Data frame}{Requires a `uid` column for group IDs and fixed parameter values.}
+#'   }
+#'   Defaults to `NULL`.
+#' @param method A character vector specifying optimization methods.
+#'   Check available methods using \code{list_methods()} and their dependencies using
+#'   \code{optimx::checkallsolvers()}. Defaults to \code{c("subplex", "pracmanm", "anms")}.
+#' @param subset A vector (optional) containing levels of `grp` to filter the data for analysis.
+#'   Defaults to `NULL` (all groups are included).
 #' @param options A list of additional options. See `modeler.options()`
 #' \describe{
 #'   \item{\code{add_zero}}{Logical. If \code{TRUE}, adds a zero value to the series at the start. Default is \code{FALSE}.}
@@ -34,16 +44,16 @@
 #' @param control A list of control parameters to be passed to the optimization function. For example: \code{list(maxit = 500)}.
 #' @return An object of class \code{modeler}, which is a list containing the following elements:
 #' \describe{
-#'   \item{\code{param}}{A data frame containing the optimized parameters and related information.}
-#'   \item{\code{dt}}{A data frame with data used and fitted values.}
-#'   \item{\code{fn}}{The call used when fitting models.}
+#'   \item{\code{param}}{Data frame containing optimized parameters and related information.}
+#'   \item{\code{dt}}{Data frame with input data, fitted values, and residuals.}
+#'   \item{\code{fn}}{The function call used for fitting models.}
 #'   \item{\code{metrics}}{Metrics and summary of the models.}
-#'   \item{\code{execution}}{Execution time.}
-#'   \item{\code{response}}{Response variable.}
-#'   \item{\code{keep}}{Metadata to keep across.}
-#'   \item{\code{fun}}{Name of the function.}
-#'   \item{\code{parallel}}{List returning parallel and workers.}
-#'   \item{\code{fit}}{List with the fitted models.}
+#'   \item{\code{execution}}{Total execution time for the analysis.}
+#'   \item{\code{response}}{Name of the response variable analyzed.}
+#'   \item{\code{keep}}{Metadata retained based on the `keep` argument.}
+#'   \item{\code{fun}}{Name of the curve-fitting function used.}
+#'   \item{\code{parallel}}{List containing parallel execution details (if applicable).}
+#'   \item{\code{fit}}{List of fitted models for each group.}
 #' }
 #' @export
 #'

_pkgdown.yml

@@ -53,6 +53,7 @@ reference:
   - goodness_of_fit
   - print.modeler
   - metrics
+  - list_methods
 - title: Data Exploration
 - contents:
   - explorer
@@ -68,9 +69,11 @@ reference:
   - fn_lin
   - fn_quad
   - fn_linear_sat
+  - fn_logistic
   - fn_exp1_lin
   - fn_exp2_lin
   - fn_exp1_exp
   - fn_exp2_exp
   - fn_lin_pl_lin
   - fn_lin_pl_lin2
+  - list_funs