https://wiki.statsape.com/index.php?action=history&feed=atom&title=%E5%B9%BF%E4%B9%89%E7%BA%BF%E6%80%A7%E5%9B%9E%E5%BD%92_%E9%80%86%E6%A6%82%E7%8E%87%E5%8A%A0%E6%9D%83%E8%81%94%E5%90%88%E6%A0%87%E5%87%86%E5%B7%AE 2026-05-15T15:18:17Z 本wiki上该页面的版本历史 MediaWiki 1.39.6 https://wiki.statsape.com/index.php?title=%E5%B9%BF%E4%B9%89%E7%BA%BF%E6%80%A7%E5%9B%9E%E5%BD%92_%E9%80%86%E6%A6%82%E7%8E%87%E5%8A%A0%E6%9D%83%E8%81%94%E5%90%88%E6%A0%87%E5%87%86%E5%B7%AE&diff=6076&oldid=prev 2024-01-19T11:09:05Z

<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;">2024年1月19日 (五) 19:09的版本</td> </tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l7">第7行：</td> <td colspan="2" class="diff-lineno">第7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>|productionstate={{图标文件|Win}} / {{图标文件|W10}} Win10及以上可用</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; 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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>|nodeoutputports=WorkFlow-Control ➤;Transfer-Table ■</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>|statsapewikiurl=https://wiki.statsape.com/广义线性回归_逆概率加权联合标准差</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>|statsapewikiurl=https://wiki.statsape.com/广义线性回归_逆概率加权联合标准差</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; 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Zeroclanzhang https://wiki.statsape.com/index.php?title=%E5%B9%BF%E4%B9%89%E7%BA%BF%E6%80%A7%E5%9B%9E%E5%BD%92_%E9%80%86%E6%A6%82%E7%8E%87%E5%8A%A0%E6%9D%83%E8%81%94%E5%90%88%E6%A0%87%E5%87%86%E5%B7%AE&diff=5315&oldid=prev 2024-01-18T14:11:37Z

<p>创建页面，内容为“{{Infobox nodebasic |nodename=广义线性回归_逆概率加权联合标准差 |nodeimage=GLM_Inverse Probability Weighted with Standard Deviation.png |icon=GLM_Inverse Probability Weighted with Standard Deviation.svg |simpleicon=GLM_Inverse Probability Weighted with Standard Deviation_Pure.svg |developer=Dev.Team-DPS |productionstate={{图标文件|Win}} / {{图标文件|W10}} Win10及以上可用 |productionstatedesc=在Update:DecisionLinnc 1.0.2.0|V1.0.2…”</p> <p><b>新页面</b></p><div>{{Infobox nodebasic <br /> |nodename=广义线性回归_逆概率加权联合标准差<br /> |nodeimage=GLM_Inverse Probability Weighted with Standard Deviation.png<br /> |icon=GLM_Inverse Probability Weighted with Standard Deviation.svg<br /> |simpleicon=GLM_Inverse Probability Weighted with Standard Deviation_Pure.svg<br /> |developer=Dev.Team-DPS<br /> |productionstate={{图标文件|Win}} / {{图标文件|W10}} Win10及以上可用<br /> |productionstatedesc=在[[Update:DecisionLinnc 1.0.2.0|V1.0.2]]部署<br /> |nodeenglishname=[[Has english name::GLM_Inverse Probability Weighted with Standard Deviation]]<br /> |abbreviation=[[Has abbreviation::GLMIPWSD]]<br /> |funcmaincategory=数据分析<br /> |funcsubcategory=[[DataAGM Lv1 Cat::回归分析]]<br /> |nodecategory=数据挖掘<br /> |nodeinterpretor=R<br /> |nodeshortdescription=&lt;p&gt;广义线性回归-逆概率加权联合标准差是利用反概率加权和基于设计的标准误差，对来自复杂调查设计的数据拟合广义线性模型。&lt;/p&gt;&lt;p&gt;用途：用于拟合设计调查数据的广义线性模型。这个函数可以处理复杂的调查设计，包括加权、层次和聚类抽样等设计。&lt;/p&gt;&lt;p&gt;参数：选择因变量，和自变量。&lt;/p&gt;<br /> |nodeinputnumber=7<br /> |nodeoutputnumber=2<br /> |nodeloopsupport=是<br /> |nodeifswitchsupport=否<br /> |nodeavailableplotlist=FR_Curve_Plot;RegressionCoefficientPlot<br /> |nodeavailabletablelist=Coeff-Value;SE;t-Value;P-Value;CI;OR;AIC<br /> |nodeconfiguration=VariableList;DropMenu;RadioButton<br /> |nodeinputports=WorkFlow-Control ➤;Transfer-Variable ◆;Transfer-Table ■<br /> |nodeoutputports=WorkFlow-Control ➤;Transfer-Table ■<br /> |statsapewikiurl=https://wiki.statsape.com/广义线性回归_逆概率加权联合标准差<br /> |previousnode=[[PLS回归]]<br /> |nextnode=[[广义相加模型_伽玛]]<br /> }}<br /> <br /> <br /> {{Navplate AlgorithmNodeList}}<br /> <br /> [[Category:回归分析]]</div>

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