README.Rmd

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output: github_document
---

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```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```

# sparsegl <a href="https://dajmcdon.github.io/sparsegl/"><img src="man/figures/logo.png" align="right" height="139" alt="sparsegl website" /></a>

The goal of sparsegl is to fit regularization paths for sparse group-lasso
penalized learning problems. The model is typically fit for a sequence of 
regularization parameters $\lambda$. Such estimators minimize

$$
-\ell(\beta | y,\ \mathbf{X}) + \lambda(1-\alpha)\sum_{g\in G} \lVert\beta_g\rVert_2 + \lambda\alpha \lVert\beta\rVert_1.
$$

The main focus of this package is for the case where the loglikelihood
corresponds to Gaussian or logistic regression. But we also provide the ability
to fit arbitrary GLMs using `stats::family()` objects. Details may be found in
Liang, Cohen, Sólon Heinsfeld, Pestilli, and McDonald ([2024](#ref-sparsegl)).

## Installation


You can install the released version of sparsegl from [CRAN](https://CRAN.R-project.org) with:

```{r, echo = TRUE, eval = FALSE}
install.packages("sparsegl")
```

You can install
the development version from [GitHub](https://github.com/) with:

```{r, echo = TRUE, eval = FALSE}
# install.packages("remotes")
remotes::install_github("dajmcdon/sparsegl")
```

## Minimal Example

```{r load-library, echo = FALSE}
library(sparsegl)
```

```{r minimal-ex, echo = TRUE, fig.align = 'center', dev="svg"}
set.seed(1010)
n <- 100
p <- 200
X <- matrix(data = rnorm(n * p, mean = 0, sd = 1), nrow = n, ncol = p)
eps <- rnorm(n, mean = 0, sd = 1)
beta_star <- c(
  rep(5, 5), c(5, -5, 2, 0, 0),
  rep(-5, 5), c(2, -3, 8, 0, 0), rep(0, (p - 20))
)
y <- X %*% beta_star + eps
groups <- rep(1:(p / 5), each = 5)
fit1 <- sparsegl(X, y, group = groups)
plot(fit1, y_axis = "coef", x_axis = "penalty", add_legend = FALSE)
```

## References

<div id="refs" class="references">

<div id="ref-sparsegl">
Liang, X., Cohen, A., Sólon Heinsfeld, A., Pestilli, F., and McDonald, D.J. 2024.
"sparsegl: An `R` Package for Estimating Sparse Group Lasso." 
*Journal of Statistical Software* 110(6), 1–23.
<https://doi.org/10.18637/jss.v110.i06>.
</div>

</div>