README.md

In poissonconsulting/ml: Maximum Likelihood Analysis using R Expressions

ml

ml is an R package to fit R expression based Maximum Likelihood models.

It is designed to be simple but flexible.

Demonstration

Flexible Analyses

library(ml)
library(tibble)

# the R expression is currently passed as unparsed text
# it should evaluate to the log likelihood
expr <- "sum(dnorm(len, mu, b[1,1] + b[1,2], log = TRUE))"

# the list of starting can include arrays and matrices
# the values are the initial values (NAs are fixed at 0)
start <- list(mu = 20, b = matrix(c(8, NA), ncol = 2))

# data can be a data.frame or list of numeric atomic objects
data <- datasets::ToothGrowth

# perform the analysis
analysis <- ml_fit(expr, start = start, data = data)

# glance at the analysis
glance(analysis)
#> # A tibble: 1 x 4
#>      df logLik   AIC converged
#>   <int>  <dbl> <dbl> <lgl>    
#> 1     2  -207.  417. TRUE

# the coefficient table includes svalues (in place of pvalues)
tidy(analysis)
#> # A tibble: 2 x 6
#>   term   estimate    sd lower upper svalue
#>   <term>    <dbl> <dbl> <dbl> <dbl>  <dbl>
#> 1 mu        18.8  0.979 16.9  20.7   271. 
#> 2 b[1,1]     7.59 0.692  6.23  8.94   90.4

Installation

To install the developmental version from GitHub

# install.packages("remotes")
remotes::install_github("poissonconsulting/ml")

To install the latest developmental release from the Poisson drat repository

# install.packages("drat")
drat::addRepo("poissonconsulting")
install.packages("ml")

Contribution

Please report any issues.

Pull requests are always welcome.

Please note that the ml project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

poissonconsulting/ml documentation built on Feb. 13, 2021, 5:18 p.m.