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- W4386427273 abstract "The weighted median plays a central role in the least absolute deviations (LAD). We propose a nonlinear regression using (LAD). Our objective function $f(a, l, s)$ is non-convex with respect to the parameters a, l, s, and is such that for each fixed l, s the minimizer of $ato f (a, l, s)$ is the weighted median $med(x(l, s), w(l, s))$ of a sequence $x(l, s)$ endowed with the weights $w(l, s)$ (all depend on $l$, $s$). We analyse and compare theoretically the minimizers of the function $(a, l, s)to f (a, l, s)$ and the surface $(l, s) to f (med(x(l, s), w(l, s)), l, s)$. As a numerical application we propose to fit the daily infections of COVID 19 in China using Gaussian model. We derive confident interval for the daily infections from each local minimum." @default.
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- W4386427273 date "2023-07-08" @default.
- W4386427273 modified "2023-09-30" @default.
- W4386427273 title "Confidence intervals from local minimums of objective function" @default.
- W4386427273 doi "https://doi.org/10.19139/soic-2310-5070-1738" @default.
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