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# Libraries.
library(lavaan)
library(ggplot2)
library(patchwork)

# If not installed, then install as follows:
install.packages(c("lavaan", "ggplot2", "patchwork"))

# Model 1.
#

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# Phantom latent variables.

# Load the packages.
library(lavaan)
library(semPlot)

# Load data.
data(HolzingerSwineford1939)

# Store the data.

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# Load libraries.
library(lavaan)


# #region Helpers.

# These functions exist to make it more convenient for you to carry out the
# model specification without dealing with unintuitive `R` syntax and naming
# conventions. You can ignore this section and focus on the steps that follow
# (i.e., the actual model specification and estimation).

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# Please run the code top to bottom and follow the comments.

# Task function with errors or warnings.
naughty_task <- function(error = TRUE, warning = FALSE) {
    # If warning.
    if (warning) {
        warning("Warning thrown.")
    }
        
    # If error.

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# A function to quickly grasp the `CRAN` daily downloads.
plot_cran_downloads_trend <- function(package, x_axis_frequency = "3 months") {
    # Packages required.
    packages <- c("cranlogs", "mgcv", "curl", "ggplot2", "scales")
    
    # Load required packages.
    sapply(packages, function(pkg) {
        # Require the package.
        status <- suppressPackageStartupMessages(require(pkg, character.only = TRUE))

mihaiconstantin

Goal

Install and run the Windows version of LatentGOLD 6.0 on a Mac device (Intel or Apple Silicon).

Steps

1. Install homebrew

• link: https://brew.sh

mihaiconstantin

library(mgcv)
#library(modules) #devtools::install_github(klmr/modules)
#mgcv<-import_package("mgcv")

mspline<-function(x,y,k=10,lower=NA,upper=NA){
  #fits a monotonic spline to data
  #small values of k= more smoothing (flatter curves)
  #large values of k= more flexible (wiggly curves)
  #k is related to effective degrees of freedom and number of knots
  #use unconstrained gam to get rough parameter estimates

mihaiconstantin

# # # Scope of the issue:
# 
# - without the following line `object$parent_env <- environment()` (i.e., line 54 below), it throws an error: 
#     - `Error in { : task 1 failed - "object 'Work' not found"`.
#
# - I would like to know:
#     1. what are some potential pitfalls when assigning the `parent_env` inside `foreach` 
#     2. why does it work in the first place

# Minimal reproducible example: