Easily use 'Bootstrap' icons inside 'Shiny' apps and 'R
    Markdown' documents. More generally, icons can be inserted in any
    'htmltools' document through inline 'SVG'.

A highly scientific and utterly addictive 
  bird point count simulator
  to test statistical assumptions, aid survey design,
  and have fun while doing it (Solymos 2024 <doi:10.1007/s42977-023-00183-2>).
  The simulations follow time-removal and distance sampling models 
  based on Matsuoka et al. (2012) <doi:10.1525/auk.2012.11190>,
  Solymos et al. (2013) <doi:10.1111/2041-210X.12106>,
  and Solymos et al. (2018) <doi:10.1650/CONDOR-18-32.1>,
  and sound attenuation experiments by 
  Yip et al. (2017) <doi:10.1650/CONDOR-16-93.1>.

The Super Imposition by Translation and Rotation (SITAR) model 
    is a shape-invariant nonlinear mixed effect model that fits a natural cubic 
    spline mean curve to the growth data and aligns individual-specific growth 
    curves to the underlying mean curve via a set of random effects (see Cole, 
    2010 <doi:10.1093/ije/dyq115> for details). The non-Bayesian version of the 
    SITAR model can be fit by using the already available R package 'sitar'. While 
    the 'sitar' package allows modelling of a single outcome only, the 'bsitar' 
    package offers great flexibility in fitting models of varying complexities, 
    including joint modelling of multiple outcomes such as height and weight 
    (multivariate model). Additionally, the 'bsitar' package allows for the simultaneous  
    analysis of an outcome separately for subgroups defined by a factor variable such 
    as gender. This is achieved by fitting separate models for each subgroup 
    (for example males and females for gender variable). An advantage of this approach 
    is that posterior draws for each subgroup are part of a single model object, 
    making it possible to compare coefficients across subgroups and test hypotheses. 
    Since the 'bsitar' package is a front-end to the R package 'brms', it offers excellent 
    support for post-processing of posterior draws via various functions that are 
    directly available from the 'brms' package. In addition, the 'bsitar' package 
    includes various customized functions that allow for the visualization of distance 
    (increase in size with age) and velocity (change in growth rate as a function of age), 
    as well as the estimation of growth spurt parameters such as age at peak growth velocity  
    and peak growth velocity.