LPsmooth - LP Smoothed Inference and Graphics
Classical tests of goodness-of-fit aim to validate the
conformity of a postulated model to the data under study. In
their standard formulation, however, they do not allow
exploring how the hypothesized model deviates from the truth
nor do they provide any insight into how the rejected model
could be improved to better fit the data. To overcome these
shortcomings, we establish a comprehensive framework for
goodness-of-fit which naturally integrates modeling,
estimation, inference and graphics. In this package, the
deviance tests and comparison density plots are performed to
conduct the LP smoothed inference, where the letter L denotes
nonparametric methods based on quantiles and P stands for
polynomials. Simulations methods are used to perform variance
estimation, inference and post-selection adjustments. Algeri S.
and Zhang X. (2020) <arXiv:2005.13011>.