Provides functions to produce advanced ascii graphics, directly to the terminal window. This package utilizes the txtplot() function from the 'txtplot' package, to produce text-based histograms, empirical cumulative distribution function plots, scatterplots with fitted and regression lines, quantile plots, density plots, image plots, and contour plots.

Provides efficient implementation of the Narrowest-Over-Threshold methodology for detecting an unknown number of change-points occurring at unknown locations in one-dimensional data following 'deterministic signal + noise' model. Currently implemented scenarios are: piecewise-constant signal, piecewise-constant signal with a heavy-tailed noise, piecewise-linear signal, piecewise-quadratic signal, piecewise-constant signal and with piecewise-constant variance of the noise. For details, see Baranowski, Chen and Fryzlewicz (2019) <doi:10.1111/rssb.12322>.

This is a pure dummy interfaces package which mirrors 'MsSparkUtils' APIs <https://learn.microsoft.com/en-us/azure/synapse-analytics/spark/microsoft-spark-utilities?pivots=programming-language-r> of 'Azure Synapse Analytics' <https://learn.microsoft.com/en-us/azure/synapse-analytics/> for R users,
    customer of Azure Synapse can download this package from CRAN for local development.

Functions to flash your hue lights, or text yourself, from R. Designed to be used with long running scripts.

Computes the probability density function, the cumulative density function, quantile function, random numbers and measures of inference for the following families exponentiated generalized gull alpha power family, exponentiated gull alpha powerfamily, gull alpha power family.

The raw dataset and model used in Lai et al. (2021) 
    Decoupled responses of native and exotic tree diversities to 
    distance from old-growth forest and soil phosphorous in 
    novel secondary forests. Applied Vegetation Science, 24, e12548.

In semi-structured interviews that use the 'framework' method, it
    is not always clear how refinements to interview questions affect the
    decision of when to stop interviews. The trend of 'novel' and 'duplicate'
    interview codes (novel codes are information that other interviewees have
    not previously mentioned) provides insight into the richness of qualitative
    information. This package provides tools to visualise when refinements occur
    and how that affects the trends of novel and duplicate codes. These
    visualisations, when used progressively as new interviews are finished, can
    help the researcher to decide on a stopping point for their interviews.