A Declarative Interface for Statistical Inference

A declarative interface for statistical inference built on the S7 object system. The layouts of the statistical inference are described using expressive variable mappers, null hypotheses are stated as mathematical expressions over population parameters, and estimation is deferred until explicitly requested. Supports estimation method involving hypothesis testing and model-based inference with an extensible variant system for registering custom estimation methods.

statim

A Declarative Interface for Statistical Inference

Package Overview: Simple Fun Fact

What does {statim} mean?

statim is a Latin word for “immediately, at once”. Its prefix, stat (as in statistics), is where the domain this package lives in. This can be interpreted as: you declare what statistical inference you want to perform, then {statim} immediately delivers how.

Why statim?

R has a dedicated rich ecosystem in statistics. Statistical inference in general is served by an assortment of disconnected functions: the functions you’re looking for may exist but they are scattered across different packages.

R gained a grammar for graphics ({ggplot2}), and one for data manipulation ({dplyr}). And then there’s {statim}, an attempt to re-imagine the “grammar of statistical inference” from the ground up. The core idea of {statim} in general is it’s fully declarative, and that any inferential procedure can be described in three steps.

What makes {statim} composable for statistical workflows is the verbs and the accessibility of the methods you’re looking for. For example, you want to write a t-test pipeline, and you want to use the classical one and then the permutation method. {statim} lets you do that with via("<method_name>"), and while you can use t-test from default (classical), you can access its permutation method through ... |> via("permute") with one line of code only. You won’t need you to do a lot of work (which sometimes require rewriting your code), just a single addition to the syntax.

# Classical t-test
sleep |> 
    define_model(x_by(extra, group)) |> 
    prepare_test(T_TEST) |> 
    conclude()

# Permutation t-test
sleep |> 
    define_model(x_by(extra, group)) |> 
    prepare_test(T_TEST) |> 
    # Here, one line added
    # Nothing else changed
    via("permute", n = 1000L) |>         
    conclude()

For a quick result, a one-liner or an eager form skips the piped syntax entirely:

# Only works for `<stat_fn>` functions
T_TEST(x_by(extra, group), sleep)

The nuanced downside of eager forms is that they are not supported with its main semantics that is, for example, (1) recalibrating / switching off into different methods from the same estimation method with via() and (2) do not support post-execution output manipulation.

Visit vignette("statim") to get started.

Core Semantics

The package is designed around three ideas:

1. Composability: the simplest way to write {statim} has two forms: the eager form and the grammar/piped syntax form. The eager form skips the verbs and cannot be recalibrated, only skips to the output. On the other hand, the grammar/piped syntax form relies on verbs and lazy loading, which comes with the recalibration of the estimation method with a single via() call, and the execution of the lazy-loaded pipeline with conclude().

2. A shared grammar: Only applied on the main {statim} semantics: piped/grammar syntax. define_model() => prepare() => conclude() is the same shape for every inferential procedure. The <var_id> objects (x_by, rel, pairwise, …) describe the statistical structure of the problem; the verbs stay constant.

   Eager forms (T_TEST(), COR_TEST(), …) provide a shortcut when the full pipeline (in a form of piped syntax that reads like a sentence) is not needed.

3. Extensible by design: the {statim} pipeline is extensible. For instance, if you want to write new estimation method, an implementation is through filling up the stat_define() object (then store it within list of defs from STAT_CONSTRUCTOR() functions, saved as <STAT_FN>), then baseline() to write the default form of <STAT_FN> and variant() to extend the current <STAT_FN> form (only be accessed with via() only). With these, you can bring your own engine, your own method, your own implementation, or use them to extend the current ones.

Installation

The package is yet to be submitted into CRAN.

# Stable version (not yet released)
install.packages("statim")

For the time being, you can install the current implementation on GitHub:

# Development version from GitHub
# install.packages("pak")
pak::pak("s7-stats/statim")

License

MIT + file LICENSE

Contributing

We are sincerely grateful for contributions; they are beneficial for the project and for us as maintainers. Please read CONTRIBUTING.md for development setup, pull request guidelines, and workflow notes.

Code of Conduct

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