Package 'jlme'

Set up Julia connection for jlme

Description

Set up Julia connection for jlme

Usage

check_julia_ok()

stop_julia()

jlme_status()

jlme_setup(
  ...,
  add = NULL,
  restart = FALSE,
  threads = NULL,
  verbose = interactive()
)

Arguments

...	Unused
add	A character vector of additional Julia packages to add and load.
restart	Whether to run stop_julia() first, before attempting setup
threads	Number of threads to start Julia with. Defaults to 1
verbose	Whether to alert setup progress. Defaults to interactive()

Value

Invisibly returns TRUE on success

Examples

# Check whether Julia installation meets requirements
check_julia_ok()

# Connect to a Julia runtime for use with `{jlme}`
jlme_setup()

# Show information about the Julia runtime
jlme_status()

# Stop Julia runtime
stop_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()

---

Re-exported functions for interacting with Julia model objects

Description

Re-exported functions for interacting with Julia model objects

Usage

propertynames(x)

issingular(x)

likelihoodratiotest(x, ...)

Arguments

x	Julia model object
...	Additional arguments passed to the Julia function

Value

An appropriate R or Julia object

Examples

jlme_setup(restart = TRUE)

x <- jlmer(r2 ~ Anger + (1 | id), lme4::VerbAgg, family = "binomial")

# `propertynames()` lists properties accessible via `$`
propertynames(x)

# `issingular()` reports whether model has singular fit
issingular(x)

# `likelihoodratiotest()` conducts a likelihood-ratio test between nested models
likelihoodratiotest(
  x,
  jlmer(r2 ~ 1 + (1 | id), lme4::VerbAgg, family = "binomial")
)

stop_julia()

---

Parametric bootstrap for Julia mixed effects models

Description

Parametric bootstrap for Julia mixed effects models

Usage

parametricbootstrap(
  x,
  nsim,
  seed,
  ...,
  optsum_overrides = list(ftol_rel = 1e-08)
)

Arguments

x	A Julia MixedModel of class jlme
nsim	Number of simulations
seed	Seed for the random number generator (Random.MersenneTwister)
...	Not implemented
optsum_overrides	Values to override in the OptSummary.

Value

MixedModels.parametricboostrap() output as object of class jlmeboot

Examples

jlme_setup(restart = TRUE)

jmod <- jlmer(Reaction ~ Days + (Days | Subject), lme4::sleepstudy)
tidy(jmod)

samp <- parametricbootstrap(jmod, nsim = 100L, seed = 42L)
samp

tidy(samp)

stop_julia()

---

Profile the likelihood surface of Julia mixed effects models

Description

Profile the likelihood surface of Julia mixed effects models

Usage

profilelikelihood(x, ...)

Arguments

x	A Julia MixedModel of class jlme
...	Not implemented

Value

MixedModels.profile() output as object of class jlmeprof

Examples

jlme_setup(restart = TRUE)

jmod <- jlmer(Reaction ~ Days + (Days | Subject), lme4::sleepstudy)
tidy(jmod)

prof <- profilelikelihood(jmod)
prof

tidy(prof)

stop_julia()

---

Tidier methods for Julia regression models

Description

Tidier methods for Julia regression models

Usage

## S3 method for class 'jlmeboot'
tidy(x, effects = c("var_model", "ran_pars", "fixed"), ...)

## S3 method for class 'jlmeprof'
tidy(x, effects = c("var_model", "ran_pars", "fixed"), ...)

## S3 method for class 'jlme'
tidy(x, effects = c("var_model", "ran_pars", "fixed"), ...)

## S3 method for class 'jlme'
glance(x, ...)

Arguments

x	An object of class jlme
effects	One of "var_model", "ran_pars", or "fixed"
...	Unused

Value

A data frame

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