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Simulate One-Hot Encoded Sequence Data

Source: R/simulate_onehot_data.R
simulate_onehot_data.Rd

Generate simulated sequence data in one-hot encoded format. Creates the same hierarchical structure as simulate_long_data (Actor, Achiever, Group, Course, Time) but with binary 0/1 columns for each state instead of a categorical Action column.

Usage

simulate_onehot_data(
  n_groups = 5,
  n_actors = 10,
  n_courses = 3,
  n_states = 9,
  states = NULL,
  use_learning_states = TRUE,
  categories = "group_regulation",
  seq_length_range = c(10, 30),
  achiever_levels = c("High", "Low"),
  achiever_probs = c(0.5, 0.5),
  start_time = "2025-01-01 10:00:00",
  time_interval_range = c(60, 600),
  trans_matrix = NULL,
  init_probs = NULL,
  sort_states = FALSE,
  state_prefix = "",
  seed = NULL,
  actors_per_group = NULL,
  actions = NULL,
  action_categories = NULL,
  n_actions = NULL,
  transition_probs = NULL,
  initial_probs = NULL
)

Arguments

n_groups

Integer. Number of groups. Default: 5.

n_actors

Integer or integer vector of length 2. If single integer, exact number of actors per group. If vector c(min, max), random sizes in that range. Default: 10.

n_courses

Integer or character vector. Number of courses or specific course names (e.g., c("A", "B", "C")). Groups are distributed evenly across courses. Default: 3.

n_states

Integer. Number of actions to sample when using categories. Ignored if states is provided. Default: 9.

states

Character vector. The action/state names to use. If NULL, uses learning states based on categories. Default: NULL.

use_learning_states

Logical. If TRUE and states is NULL, uses learning state verbs from the specified categories. Default: TRUE.

categories

Character vector. Categories of learning states to use when states = NULL. Options: "metacognitive", "cognitive", "behavioral", "social", "motivational", "affective", "group_regulation", or "all". Default: "group_regulation".

seq_length_range

Integer vector of length 2. Range for sequence lengths per actor (min, max). Default: c(10, 30).

achiever_levels

Character vector. Levels for the Achiever variable. Default: c("High", "Low").

achiever_probs

Numeric vector. Probabilities for each achiever level. Must sum to 1. Default: c(0.5, 0.5).

start_time

POSIXct or character. Start time for timestamps. Default: "2025-01-01 10:00:00".

time_interval_range

Numeric vector of length 2. Range for time intervals between actions in seconds (min, max). Default: c(60, 600).

trans_matrix

Matrix or NULL. Custom transition probability matrix. If NULL, generates random probabilities. Default: NULL.

init_probs

Numeric vector or NULL. Custom initial probabilities. If NULL, generates random probabilities. Default: NULL.

sort_states

Logical. Sort state columns alphabetically. Default: FALSE.

state_prefix

Character. Prefix for state column names. Default: "".

seed

Integer or NULL. Random seed for reproducibility. Default: NULL.

actors_per_group

Deprecated. Use n_actors instead.

actions

Deprecated. Use states instead.

action_categories

Deprecated. Use categories instead.

n_actions

Deprecated. Use n_states instead.

transition_probs

Deprecated. Use trans_matrix instead.

initial_probs

Deprecated. Use init_probs instead.

Value

A tibble (data frame) with columns:

Actor

Integer. Actor identifier (1 to n_actors).

Achiever

Character. Achievement level (e.g., "High", "Low").

Group

Numeric. Group identifier (1 to n_groups).

Course

Character. Course identifier.

Time

POSIXct. Timestamp of the action.

Integer (0/1). One column per state, with 1 indicating the active state for that row.

Details

This function internally calls simulate_long_data to generate the base data, then applies an internal one-hot helper to convert the Action column to one-hot encoded columns.

Each row will have exactly one state column with value 1, and all others with value 0, representing the action performed at that time point.

See also

simulate_long_data for categorical Action format, Nestimate::action_to_onehot() for converting existing long data, simulate_sequences for generating wide-format sequences.

Examples

if (FALSE) { # \dontrun{
# Basic usage with new standardized params
data <- simulate_onehot_data(n_groups = 5, n_actors = 3, seed = 42)
head(data)

# Custom states with prefix
data <- simulate_onehot_data(
  n_groups = 3,
  states = c("Read", "Write", "Think"),
  state_prefix = "state_",
  seed = 123
)
names(data)

# Verify one-hot encoding (each row sums to 1)
state_cols <- setdiff(names(data), c("Actor", "Achiever", "Group", "Course", "Time"))
all(rowSums(data[, state_cols]) == 1)  # TRUE

# Old parameter names still work (backward compatible)
data <- simulate_onehot_data(
  actors_per_group = 5,
  actions = c("A", "B", "C"),
  seed = 42
)
} # }