Estimation and inference for conditional linear quantile regression models using a convolution smoothed approach. In the low-dimensional setting, efficient gradient-based methods are employed for fitting both a single model and a regression process over a quantile range. Normal-based and (multiplier) bootstrap confidence intervals for all slope coefficients are constructed. In high dimensions, the conquer method is complemented with flexible types of penalties (Lasso, elastic-net, group lasso, sparse group lasso, scad and mcp) to deal with complex low-dimensional structures.

Extends 'ACER ConQuest' through a family of functions
    designed to improve graphical outputs and help with advanced analysis
    (e.g., differential item functioning).  Allows R users to call 
    'ACER ConQuest' from within R and read 'ACER ConQuest' System Files
    (generated by the command `put` <https://conquestmanual.acer.org/s4-00.html#put>).
    Requires 'ACER ConQuest' version 5.40 or later. 
    A demonstration version can be downloaded from <https://shop.acer.org/acer-conquest-5.html>.

Convert text into synthesized speech and get a list of supported voices for a region. 
    Microsoft's 'Cognitive Services Text to Speech REST' API <https://learn.microsoft.com/en-us/azure/cognitive-services/speech-service/rest-text-to-speech?tabs=streaming>  
    supports neural text to speech voices, which support specific languages and dialects that are identified by locale.

Provides data science tools for conservation science, including
    methods for environmental data analysis, humidity calculations,
    sustainability metrics, engineering calculations, and data
    visualisation. Supports conservators, scientists, and engineers
    working with cultural heritage preventive conservation data.
    The package is motivated by the framework outlined 
    in Cosaert and Beltran et al. (2022) 
    "Tools for the Analysis of Collection Environments" 
    <https://www.getty.edu/conservation/publications_resources/pdf_publications/tools_for_the_analysis_of_collection_environments.html>.