The heatex package calculates heat storage in the body and
        the components of heat exchange (conductive, convective,
        radiative, and evaporative) between the body and the
        environment during physical activity based on the principles of
        partitional calorimetry. The program enables heat exchange
        calculations for a range of environmental conditions when
        wearing various clothing ensembles.

Implements the simpler and faster heat index, which matches the values of the original 1979 heat index and its 2022 extension for air temperatures above 300 K (27 C, 80 F) and with only minor differences at lower temperatures. Also implements an algorithm for calculating the thermodynamic (and psychrometric) wet-bulb (and ice-bulb) temperature.

An improved heatmap package. Completely
    compatible with the original R function 'heatmap',
    and provides more powerful and convenient features.

Generates a fit plot for diagnosing misspecification in models of
    binary dependent variables, and calculates the related heatmap fit
    statistic described in Esarey and Pierce (2012) <DOI:10.1093/pan/mps026>.

A set of tools supporting more flexible heatmaps. The graphics is grid-like using
  the old graphics system. The main function is heatmap.n2(), which is a wrapper around the various functions
  constructing individual parts of the heatmap, like sidebars, picket plots, legends etc. The function supports zooming
  and splitting, i.e., having (unlimited) small heatmaps underneath each other in one plot deriving from the same data set,
  e.g., clustered and ordered by a supervised clustering method.

Create interactive cluster 'heatmaps' that can be saved as a stand-
    alone HTML file, embedded in 'R Markdown' documents or in a 'Shiny' app, and
    available in the 'RStudio' viewer pane. Hover the mouse pointer over a cell to
    show details or drag a rectangle to zoom. A 'heatmap' is a popular graphical
    method for visualizing high-dimensional data, in which a table of numbers
    are encoded as a grid of colored cells. The rows and columns of the matrix
    are ordered to highlight patterns and are often accompanied by 'dendrograms'.
    'Heatmaps' are used in many fields for visualizing observations, correlations,
    missing values patterns, and more. Interactive 'heatmaps' allow the inspection
    of specific value by hovering the mouse over a cell, as well as zooming into
    a region of the 'heatmap' by dragging a rectangle around the relevant area.
    This work is based on the 'ggplot2' and 'plotly.js' engine. It produces
    similar 'heatmaps' to 'heatmap.2' with the advantage of speed
    ('plotly.js' is able to handle larger size matrix), the ability to zoom from
    the 'dendrogram' panes, and the placing of factor variables in the sides of the
    'heatmap'.