close

Showing 4 of total 4 results (show query)

cjvanlissa

tidySEM:Tidy Structural Equation Modeling

A tidy workflow for generating, estimating, reporting, and plotting structural equation models using 'lavaan', 'OpenMx', or 'Mplus'. Throughout this workflow, elements of syntax, results, and graphs are represented as 'tidy' data, making them easy to customize. Includes functionality to estimate latent class analyses, and to plot 'dagitty' and 'igraph' objects.

Maintained by Caspar J. van Lissa. Last updated 23 days ago.

58 stars 10.69 score 330 scripts 1 dependents

data-edu

tidyLPA:Easily Carry Out Latent Profile Analysis (LPA) Using Open-Source or Commercial Software

Easily carry out latent profile analysis ("LPA"), determine the correct number of classes based on best practices, and tabulate and plot the results. Provides functionality to estimate commonly-specified models with free means, variances, and covariances for each profile. Follows a tidy approach, in that output is in the form of a data frame that can subsequently be computed on. Models can be estimated using the free open source 'R' packages 'Mclust' and 'OpenMx', or using the commercial program 'MPlus', via the 'MplusAutomation' package.

Maintained by Joshua M Rosenberg. Last updated 1 years ago.

58 stars 8.76 score 121 scripts

shackett

romic:R for High-Dimensional Omic Data

Represents high-dimensional data as tables of features, samples and measurements, and a design list for tracking the meaning of individual variables. Using this format, filtering, normalization, and other transformations of a dataset can be carried out in a flexible manner. 'romic' takes advantage of these transformations to create interactive 'shiny' apps for exploratory data analysis such as an interactive heatmap.

Maintained by Sean Hackett. Last updated 6 months ago.

4.78 score 10 scripts

thomvolker

densityratio:Distribution Comparison Through Density Ratio Estimation

Fast, flexible and user-friendly functionality to directly estimate the ratio of two probability distributions from samples from these distributions without estimating the densities separately. Estimated density ratios can, among other things, be used for prediction, outlier detection, change-point detection in time-series, importance weighting under domain adaptation (i.e., sample selection bias) and evaluation of synthetic data utility. The rationale behind these use-cases is that differences between two data distributions can be captured in the ratio their density ratio, which is estimated over the entire multivariate space of the data. Computationally intensive code is executed in `C++` using `Rcpp` and `RcppArmadillo`. The package provides good default hyperparameters that can be optimized in cross-validation (we do recommend understanding those parameters before using `densityratio` in practice). Multiple density ratio estimation methods are implemented, such as unconstrained least-squares importance fitting (`ulsif()`), Kullback-Leibler importance estimation procedure (`kliep()`), spectral density ratio estimation (`spectral()`), and least-squares heterodistributional subspace search (`lhss()`).

Maintained by Thom Volker. Last updated 2 months ago.

openblascppopenmp

6 stars 4.07 score 18 scripts

: