Simulating and estimating peer effect models including the quantile-based specification (Houndetoungan, 2025 <doi:10.48550/arXiv.2506.12920>), and the models with Constant Elasticity of Substitution (CES)-based social norm (Boucher et al., 2024 <doi:10.3982/ECTA21048>).

Estimation and inference methods for the cross-quantilogram.
    The cross-quantilogram is a measure of nonlinear dependence between
    two variables, based on either unconditional or conditional quantile
    functions.  It can be considered an extension of the correlogram,
    which is a correlation function over multiple lag periods that mainly
    focuses on linear dependency.  One can use the cross-quantilogram to
    detect the presence of directional predictability from one time series
    to another.  This package provides a statistical inference method
    based on the stationary bootstrap.  For detailed theoretical and
    empirical explanations, see Linton and Whang (2007) for univariate
    time series analysis and Han, Linton, Oka and Whang (2016) for
    multivariate time series analysis.  The full references for these key
    publications are as follows: (1) Linton, O., and Whang, Y. J. (2007).
    The quantilogram: with an application to evaluating directional
    predictability.  Journal of Econometrics, 141(1), 250-282
    <doi:10.1016/j.jeconom.2007.01.004>; (2) Han, H., Linton, O., Oka, T.,
    and Whang, Y. J. (2016).  The cross-quantilogram: measuring quantile
    dependence and testing directional predictability between time series.
    Journal of Econometrics, 193(1), 251-270
    <doi:10.1016/j.jeconom.2016.03.001>.

Integration of the 'units' and 'errors' packages for a complete
    quantity calculus system for R vectors, matrices and arrays, with automatic
    propagation, conversion, derivation and simplification of magnitudes and
    uncertainties. Documentation about 'units' and 'errors' is provided in the
    papers by Pebesma, Mailund & Hiebert (2016, <doi:10.32614/RJ-2016-061>) and
    by Ucar, Pebesma & Azcorra (2018, <doi:10.32614/RJ-2018-075>), included in
    those packages as vignettes; see 'citation("quantities")' for details.