jlm: Fit a (mixed-effects) regression model in Julia

In jlme: Regression Modelling with 'GLM.jl' and 'MixedModels.jl' in 'Julia'

Fit a (mixed-effects) regression model in Julia

Description

Fit a (mixed-effects) regression model in Julia

Usage

jlm(formula, data, family = "gaussian", contrasts = jl_contrasts(data), ...)

jlmer(
  formula,
  data,
  family = NULL,
  contrasts = jl_contrasts(data),
  ...,
  fit = TRUE,
  optsum = list(),
  progress = interactive()
)

Arguments

formula	A formula written in Julia syntax. Can be a string or a language object.
data	A data frame
family	A distribution family
contrasts	A Julia dictionary of contrasts Inferred from data by default.
...	Additional arguments to the fit() function called in Julia
fit	Whether to fit the model. If FALSE, returns the unfit model object.
optsum	A list of values to set for the optimizer. See ⁠$optsum⁠ of unfit model for possible options.
progress	Whether to print model fitting progress. Defaults to interactive()

Value

A julia model object of class jlme

Examples

jlme_setup(restart = TRUE)

# Fixed effects models
lm(mpg ~ hp, mtcars)
jlm(mpg ~ hp, mtcars)

# Auto-handling of contrasts
x <- mtcars
x$cyl_helm <- factor(x$cyl)
contrasts(x$cyl_helm) <- contr.helmert(3)
colnames(contrasts(x$cyl_helm)) <- c("4vs6", "4&6vs8")
lm(mpg ~ cyl_helm, x)
jlm(mpg ~ cyl_helm, x)

# Mixed effects models
library(lme4)

glmer(r2 ~ Anger + Gender + (1 | id), VerbAgg, family = "binomial")
jlmer(r2 ~ Anger + Gender + (1 | id), VerbAgg, family = "binomial")

# Set optimizer options via `optsum`
jlmer(
  r2 ~ Anger + Gender + (1 | id), VerbAgg, family = "binomial",
  optsum = list(
    optimizer = jl(":LN_NELDERMEAD"),
    maxfeval = 10L
  )
)

stop_julia()

jlme documentation built on April 3, 2025, 10:29 p.m.