Electrical properties of resistor networks using matrix methods.

A 'shiny' module to facilitate page layouts with resizable panes for page content based on 'split.js' 'JavaScript' library (<https://split.js.org>).

A pair of functions for calculating mean residual life (MRL)
    , median residual life, and percentile residual life using the outputs of 
    either the 'flexsurv' package or parameters
    provided by the user. Input information about the distribution, the given
    'life' value, the percentile, and the type of residual life, 
    and the function will return your desired values. For the 'flexsurv' option,
    the function allows the user to input their own data for making predictions. 
    This function is based on Jackson (2016) <doi:10.18637/jss.v070.i08>.

Implements the Representation-Level Control Surfaces (RLCS) paradigm for ensuring the reliability of autonomous systems and AI models. It provides three deterministic sensors: Residual Likelihood (ResLik) for population-level anomaly detection, Temporal Consistency Sensor (TCS) for drift and shock detection, and Agreement Sensor for multi-modal redundancy checks. These sensors feed into a standardized control surface that issues 'PROCEED', 'DEFER', or 'ABSTAIN' signals based on strict safety invariants, allowing systems to detect and react to out-of-distribution states, sensor failures, and environmental shifts before they propagate to decision-making layers.

The Bayesian modelling of relative sea-level data
    using a comprehensive approach that incorporates
    various statistical models within a unifying framework. 
    Details regarding each statistical models; 
    linear regression (Ashe et al 2019) <doi:10.1016/j.quascirev.2018.10.032>, 
    change point models (Cahill et al 2015) <doi:10.1088/1748-9326/10/8/084002>, 
    integrated Gaussian process models (Cahill et al 2015) <doi:10.1214/15-AOAS824>, 
    temporal splines (Upton et al 2023) <arXiv:2301.09556>, 
    spatio-temporal splines (Upton et al 2023) <arXiv:2301.09556> and
    generalised additive models (Upton et al 2023) <arXiv:2301.09556>.
    This package facilitates data loading, 
    model fitting and result summarisation.
    Notably, it accommodates the inherent measurement errors
    found in relative sea-level data across multiple dimensions,
    allowing for their inclusion in the statistical models.