Statistical Analysis for Random Objects and Non-Euclidean Data

Provides implementation of statistical methods for random objects lying in various metric spaces, which are not necessarily linear spaces. The core of this package is Fréchet regression for random objects with Euclidean predictors, which allows one to perform regression analysis for non-Euclidean responses under some mild conditions. Examples include distributions in 2-Wasserstein space, covariance matrices endowed with power metric (with Frobenius metric as a special case), Cholesky and log-Cholesky metrics, spherical data. References: Petersen, A., & Müller, H.-G. (2019) .

Longitudinal Targeted Maximum Likelihood Estimation

Targeted Maximum Likelihood Estimation ('TMLE') of treatment/censoring specific mean outcome or marginal structural model for point-treatment and longitudinal data.

Compare the Goodness of Fit of Benford's and Blondeau Da Silva's Digit Distributions to a Given Dataset

Allows to compare the goodness of fit of Benford's and Blondeau Da Silva's digit distributions in a dataset. It is used to check whether the data distribution is consistent with theoretical distributions highlighted by Blondeau Da Silva or not (through the dat.distr() function): this ideal theoretical distribution must be at least approximately followed by the data for the use of Blondeau Da Silva's model to be well-founded. It also enables to plot histograms of digit distributions, both observed in the dataset and given by the two theoretical approaches (with the digit.ditr() function). Finally, it proposes to quantify the goodness of fit via Pearson's chi-squared test (with the chi2() function).

Tools for Linear Dimension Reduction

Linear dimension reduction subspaces can be uniquely defined using orthogonal projection matrices. This package provides tools to compute distances between such subspaces and to compute the average subspace. For details see Liski, E.Nordhausen K., Oja H., Ruiz-Gazen A. (2016) Combining Linear Dimension Reduction Subspaces .

Spatio-Temporal Autologistic Regression Model

Estimates the coefficients of the two-time centered autologistic regression model based on Gegout-Petit A., Guerin-Dubrana L., Li S. "A new centered spatio-temporal autologistic regression model. Application to local spread of plant diseases." 2019. , using a grid of binary variables to estimate the spread of a disease on the grid over the years.

AI-Driven Code Generation, Explanation and Execution for Data Analysis

Employing artificial intelligence to convert data analysis questions into executable code, explanations, and algorithms. The self-correction feature ensures the generated code is optimized for performance and accuracy. 'mergen' features a user-friendly chat interface, enabling users to interact with the AI agent and extract valuable insights from their data effortlessly.

Longitudinal Graphical Lasso

For high-dimensional correlated observations, this package carries out the L_1 penalized maximum likelihood estimation of the precision matrix (network) and the correlation parameters. The correlated data can be longitudinal data (may be irregularly spaced) with dampening correlation or clustered data with uniform correlation. For the details of the algorithms, please see the paper Jie Zhou et al. Identifying Microbial Interaction Networks Based on Irregularly Spaced Longitudinal 16S rRNA sequence data .

Find Related Items and Lexical Dimensions in a Lexicon

Implements code to identify lexical competitors in a given list of words. We include many of the standard competitor types used in spoken word recognition research, such as functions to find cohorts, neighbors, and rhymes, amongst many others. The package includes documentation for using a variety of lexicon files, including those with form codes made up of multiple letters (i.e., phoneme codes) and also basic orthographies. Importantly, the code makes use of multiple CPU cores and vectorization when possible, making it extremely fast and able to handle large lexicons. Additionally, the package contains documentation for users to easily write new functions, allowing researchers to examine other relationships within a lexicon. Preprint: < https://osf.io/preprints/psyarxiv/8dyru/>. Open access: . Citation: Li, Z., Crinnion, A.M. & Magnuson, J.S. (2021). .

Functions Related to ICES Advice

A collection of functions that facilitate computational steps related to advice for fisheries management, according to ICES guidelines. These include methods for calculating reference points and model diagnostics.

Yeast-Proteome Secondary-Structure Calculator

An extension for 'NetSurfP-2.0' (Klausen et al. (2019) ) which is specifically designed to analyze the results of bottom-up-proteomics that is primarily analyzed with 'MaxQuant' (Cox, J., Mann, M. (2008) ). This tool is designed to process a large number of yeast peptides that produced as a results of whole yeast cell-proteome digestion and provide a coherent picture of secondary structure of proteins.