Free time & chunking modeling
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  1. Function reference
  2. Plot Linear RV Recovery
  • Version 0.1
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  • About
  • Development notes
    • Notes
    • 2024-05-16 Meeting Notes
    • Extra primacy parameter
  • Notebooks
    • Data
      • View the data structure
      • Exploratory data analysis
      • Subject-level data
    • Model 1: Original model
      • Main results
      • Parameter identifiability
      • Sensitivity to tau
      • Experiment 3
      • Exploring model predictions
    • Model 2: Include encoding time
      • Main results
    • Model 3: Non-linear recovery
      • Explore model predictions
      • Basic fits
      • Bootstrapping data and fits for parameter uncertainty estimation
      • Extra primacy parameter
      • Linear recovery as a random variable
  • Function reference
    • Aggregate Data
    • Perform bootstrapped estimation
    • Calculate the deviance of a model
    • Get data object from a file
    • Generate a bootstrapped dataset
    • get_data function
    • Inverse Logit Transformation
    • Logit Transformation
    • Calculate the overall deviance
    • Plot Bootstrap Results
    • Plot Linear RV Recovery
    • Preprocesses the data
    • Execute an expression and save the result to a file or load the result from a file if it already exists.
    • Serial Recall Model

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  • Plot Linear RV Recovery
    • Description
    • Usage
    • Arguments
    • Details
    • Value
    • Examples

Plot Linear RV Recovery

Description

This function plots the recovery of a linear random variable (RV) over time.

Usage

plot_linear_rv_recovery(r, t, title = "Uniform distribution")

Arguments

  • r: A vector representing the recovery rates sampled from some distribution.
  • t: A vector representing the time values.
  • title: The title of the plot (default is “Uniform distribution”).

Details

Average recovery is given as a red line, while individual trajectories are given as black lines.

Value

A ggplot object representing the plot of linear RV recovery over time.

Examples

r <- runif(1000, 0, 1)
t <- seq(0, 5, by = 0.01)
plot_linear_rv_recovery(r, t, title = "Uniform distribution")
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Plot Bootstrap Results
Preprocesses the data