Perform first- and second-order multi-scale analyses derived from Ripley K-function (Ripley B. D. (1977) <doi:10.1111/j.2517-6161.1977.tb01615.x>), for univariate,
 multivariate and marked mapped data in rectangular, circular or irregular shaped sampling windows, with tests of 
 statistical significance based on Monte Carlo simulations.

A simulations-first sample size determination package that aims at making sample size formulae obsolete for most easily computable statistical experiments ; the main envisioned use case is clinical trials. The proposed clinical trial must be written by the user in the form of a function that takes as argument a sample size and returns a boolean (for whether or not the trial is a success). The 'adsasi' functions will then use it to find the correct sample size empirically. The unavoidable mis-specification is obviated by trying sample size values close to the right value, the latter being understood as the value that gives the probability of success the user wants (usually 80 or 90% in biostatistics, corresponding to 20 or 10% type II error).

Interact with Google Ads Data Hub API <https://developers.google.com/ads-data-hub/reference/rest>. The functionality allows to fetch customer details, submit queries to ADH.

Solving high-dimensional double sparse linear regression via an iterative hard thresholding algorithm. Furthermore, the method is extended to jointly estimate multiple graphical models.  For more details, please see <https://www.jmlr.org/papers/v25/23-0653.html> and <doi:10.48550/arXiv.2503.18722>.

Model adsorption behavior using classical isotherms, including Langmuir,
    Freundlich, Brunauer–Emmett–Teller (BET), and Temkin models. The package supports
    parameter estimation through both linearized and non-linear fitting techniques and
    generates high-quality plots for model diagnostics. It is intended for environmental
    scientists, chemists, and researchers working on adsorption phenomena in soils,
    water treatment, and material sciences. Functions are compatible with base 'R' and
    'ggplot2' for visualization.