http://202.127.29.3/~shen/wiki/index.php?action=history&feed=atom&title=Lowess 2026-05-13T05:41:42Z 本wiki上该页面的版本历史 MediaWiki 1.38.1 http://202.127.29.3/~shen/wiki/index.php?title=Lowess&diff=3832&oldid=prev 2022-08-17T12:58:08Z

<p></p> <table style="background-color: #fff; color: #202122;" data-mw="interface"> <col class="diff-marker" /> <col class="diff-content" /> <col class="diff-marker" /> <col class="diff-content" /> <tr class="diff-title" lang="zh-Hans-CN"> <td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">←上一版本</td> <td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">2022年8月17日 (三) 12:58的版本</td> </tr><tr> <td colspan="2" class="diff-lineno">第1行：</td> <td colspan="2" class="diff-lineno">第1行：</td> </tr> <tr> <td colspan="2" class="diff-empty diff-side-deleted"></td> <td class="diff-marker" data-marker="+"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>*One of Michele Cappellari Python Programs [https://www-astro.physics.ox.ac.uk/~cappellari/software/#loess]</div></td> </tr> <tr> <td class="diff-marker" data-marker="−"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>Locally Weighted Scatterplot Smoothing</div></td> <td colspan="2" class="diff-empty diff-side-added"></td> </tr> <tr> <td colspan="2" class="diff-empty diff-side-deleted"></td> <td class="diff-marker" data-marker="+"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>*Locally Weighted Scatterplot Smoothing：在局域回归方法基础上重新给数据点分配权重之后再smooth</div></td> </tr> <tr> <td class="diff-marker" data-marker="−"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>*局域的回归方法</div></td> <td colspan="2" class="diff-empty diff-side-added"></td> </tr> <tr> <td colspan="2" class="diff-empty diff-side-deleted"></td> <td class="diff-marker"><a class="mw-diff-movedpara-right" title="段落已移动。点击跳到旧位置。" href="#movedpara_6_0_lhs">&#x26AB;</a></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><a name="movedpara_4_0_rhs"></a><ins style="font-weight: bold; text-decoration: none;">*</ins>参见 [https://sites.stat.washington.edu/courses/stat527/s14/readings/Cleveland_JASA_1979.pdf] [https://people.stat.sc.edu/grego/courses/stat540/ScatterplotSmoothing.pdf]</div></td> </tr> <tr> <td class="diff-marker" data-marker="−"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>*散点图smooth的方法</div></td> <td colspan="2" class="diff-empty diff-side-added"></td> </tr> <tr> <td class="diff-marker"><a class="mw-diff-movedpara-left" title="段落已移动。点击跳到新位置。" href="#movedpara_4_0_rhs">&#x26AB;</a></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><a name="movedpara_6_0_lhs"></a>参见 [https://sites.stat.washington.edu/courses/stat527/s14/readings/Cleveland_JASA_1979.pdf] [https://people.stat.sc.edu/grego/courses/stat540/ScatterplotSmoothing.pdf]</div></td> <td colspan="2" class="diff-empty diff-side-added"></td> </tr> <tr> <td class="diff-marker" data-marker="−"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>*Python package [https://pypi.org/project/loess/#:~:text=Smoothing%20via%20robust%20locally-weighted%20regression%20in%20one%20or,%26%20Devlin%20%281988%29%20for%20the%20two-dimensional%20case.%20Contents]</div></td> <td colspan="2" class="diff-empty diff-side-added"></td> </tr> </table>

Shen http://202.127.29.3/~shen/wiki/index.php?title=Lowess&diff=3831&oldid=prev 2022-08-17T12:53:58Z

<p></p> <table style="background-color: #fff; color: #202122;" data-mw="interface"> <col class="diff-marker" /> <col class="diff-content" /> <col class="diff-marker" /> <col class="diff-content" /> <tr class="diff-title" lang="zh-Hans-CN"> <td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">←上一版本</td> <td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">2022年8月17日 (三) 12:53的版本</td> </tr><tr> <td colspan="2" class="diff-lineno">第2行：</td> <td colspan="2" class="diff-lineno">第2行：</td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>*局域的回归方法</div></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>*局域的回归方法</div></td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>*散点图smooth的方法</div></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>*散点图smooth的方法</div></td> </tr> <tr> <td class="diff-marker" data-marker="−"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>参见 [https://sites.stat.washington.edu/courses/stat527/s14/readings/Cleveland_JASA_1979.pdf]</div></td> <td class="diff-marker" data-marker="+"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>参见 [https://sites.stat.washington.edu/courses/stat527/s14/readings/Cleveland_JASA_1979<ins style="font-weight: bold; text-decoration: none;">.pdf] [https://people.stat.sc.edu/grego/courses/stat540/ScatterplotSmoothing</ins>.pdf]</div></td> </tr> <tr> <td colspan="2" class="diff-empty diff-side-deleted"></td> <td class="diff-marker" data-marker="+"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>*Python package [https://pypi.org/project/loess/#:~:text=Smoothing%20via%20robust%20locally-weighted%20regression%20in%20one%20or,%26%20Devlin%20%281988%29%20for%20the%20two-dimensional%20case.%20Contents]</div></td> </tr> </table>

Shen http://202.127.29.3/~shen/wiki/index.php?title=Lowess&diff=3830&oldid=prev 2022-08-17T12:50:22Z

<p>创建页面，内容为“Locally Weighted Scatterplot Smoothing *局域的回归方法 *散点图smooth的方法 参见 [https://sites.stat.washington.edu/courses/stat527/s14/readings/Clevel…”</p> <p><b>新页面</b></p><div>Locally Weighted Scatterplot Smoothing<br /> *局域的回归方法<br /> *散点图smooth的方法<br /> 参见 [https://sites.stat.washington.edu/courses/stat527/s14/readings/Cleveland_JASA_1979.pdf]</div>

Shen