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(This article was first published on <strong><a href="https://xianblog.wordpress.com/2018/07/05/hitting-a-wall/"> R – Xi'an's Og</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
<p><a rel="nofollow" href="https://i0.wp.com/i.stack.imgur.com/6WAC2m.jpg?ssl=1" target="_blank"><img width="320" src="https://i0.wp.com/i.stack.imgur.com/6WAC2m.jpg?resize=320%2C320&ssl=1" data-recalc-dims="1" height="320"></a><strong>O</strong>nce in a while, or a wee bit more frequently (!), it proves impossible to communicate with a contributor of a <a rel="nofollow" href="https://stats.stackexchange.com/q/349922/7224" target="_blank">question</a> on X validated. A <a rel="nofollow" href="https://stats.stackexchange.com/q/349922/7224" target="_blank">recent instance</a> was about simulating from a multivariate kernel density estimate where the kernel terms at x¹,x²,… are Gaussian kernels applied to the inverses of the norms |x-x¹|, |x-x²|,… rather than to the norms as in the usual formulation. The reason for using this type of kernel is unclear, as it certainly does not converge to an estimate of the density of the sample x¹,x²,…  as the sample size grows, since it excludes a neighbourhood of each point in the sample. Since the kernel term tends to a non-zero constant at infinity, the support of the density estimate is restricted to the hypercube [0,1]x…x[0,1], again with unclear motivations. No mention being made of the bandwidth adopted for this kernel. If one takes this exotic density as a given, the <a rel="nofollow" href="https://stats.stackexchange.com/q/349922/7224" target="_blank">question</a> is rather straightforward as the support is compact, the density bounded and a vanilla accept-reject can be implemented. As illustrated by the massive number of comments on that entry, it did not work as <a rel="nofollow" href="https://stats.stackexchange.com/users/140570/y0da" target="_blank">the contributor</a> adopted a fairly bellicose attitude about suggestions from moderators on that site and could not see the point in our requests for clarification, despite <a rel="nofollow" href="https://i.stack.imgur.com/LeN6g.png" target="_blank">plotting a version</a> of the kernel that had its maximum [and not its minimum] at x¹… After a few attempts, including writing a complete answer, from which the above graph is taken (based on an initial understanding of the support being for (x-x¹), …), I gave up and deleted all my entries.On that question.</p>
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