[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$f2aGj2csiB2JsUIVxwITQhrSwsxeHfMfjXlaO2K0dww8":3},{"answer":4,"createTime":5,"id":6,"options":7,"origin":12,"question":19,"related":20,"source":24,"type":25},[],"2025-11-04 21:48:05",224514485,[8,9,10,11],"有效性","线性","一致性","无偏性",{"count":13,"courseId":14,"courseImg":15,"courseName":16,"workId":17,"workName":18},50,"6164a168c3366a84bbd3481a65155a6c","https:\u002F\u002Ftihai-oss-cloud.itihey.com\u002Fimg\u002F82ed79d174b5a4977bfbd273169821e9.png","计量经济学","work_47039757","第四章1","当模型存在严重的多重共线性时,OLS估计量将不具备( )D",[21,26,35,44,53,62,71,80,88,97],{"answer":22,"createTime":5,"id":6,"options":23,"question":19,"source":24,"type":25},[],[8,9,10,11],"v1",0,{"answer":27,"createTime":5,"id":28,"options":29,"question":34,"source":24,"type":25},[],224514486,[30,31,32,33],"\u003Cimg src=\"https:\u002F\u002Ftihai-oss-cloud.itihey.com\u002Fimg\u002F2222e06b116fdadfdf2338bd527f0e5e.png\">","\u003Cimg src=\"https:\u002F\u002Ftihai-oss-cloud.itihey.com\u002Fimg\u002Fe1bcb823fa2007abb8d4df75bb534c76.png\">","\u003Cimg src=\"https:\u002F\u002Ftihai-oss-cloud.itihey.com\u002Fimg\u002F517f62b8f6bb56bad57f94160abdebf0.png\">","\u003Cimg src=\"https:\u002F\u002Ftihai-oss-cloud.itihey.com\u002Fimg\u002F74ead73d6d3ec2521951a8180f268241.png\">","设回归模型为\u003Cimg src=\"https:\u002F\u002Ftihai-oss-cloud.itihey.com\u002Fimg\u002F3b011a04d98ecfe215b6444afe7078a7.png\">,其中\u003Cimg src=\"https:\u002F\u002Ftihai-oss-cloud.itihey.com\u002Fimg\u002F7eebac194297e38dfcd00e340731db4a.png\">,则\u003Cimg src=\"https:\u002F\u002Ftihai-oss-cloud.itihey.com\u002Fimg\u002F4720792ac8374ad459a2185a1758380e.png\">的最有效估计量为( )",{"answer":36,"createTime":5,"id":37,"options":38,"question":43,"source":24,"type":25},[],224514487,[39,40,41,42],"加权最小二乘法","对原模型变换的方法","两阶段最小二乘法","对模型的对数变换法","在修正异方差性的方法中,不正确的是( )",{"answer":45,"createTime":5,"id":46,"options":47,"question":52,"source":24,"type":25},[],224514488,[48,49,50,51],"DW检验法","戈德菲尔德一匡特检验方法","怀特检验法","戈里瑟检验法","在检验异方差性的方法中,不正确的是( )",{"answer":54,"createTime":5,"id":55,"options":56,"question":61,"source":24,"type":25},[],224514489,[57,58,59,60],"参数无法估计","模型的拟合程度不能判断","可以计算模型的拟合程度","只能估计参数的线性组合","完全多重共线性时,下列判断不正确的是( )",{"answer":63,"createTime":5,"id":64,"options":65,"question":70,"source":24,"type":25},[],224514490,[66,67,68,69],"无偏、有效估计量","有偏、非有效估计量","有偏、有效估计量","无偏、非有效估计量","如果回归模型中的随机误差项存在异方差性,则模型参数的普通最小二乘估计量是( )",{"answer":72,"createTime":5,"id":73,"options":74,"question":79,"source":24,"type":25},[],224514491,[75,76,77,78],"随机解释变量","自相关性","多重共线性","异方差性","Glejser检验方法主要用于检验( )",{"answer":81,"createTime":5,"id":82,"options":83,"question":87,"source":24,"type":25},[],224514492,[84,77,85,86],"异方差","序列相关","高拟合优度","在多元线性回归模型中,若某个解释变量对其余解释变量的判定系数接近于1,则表明模型中存在( )",{"answer":89,"createTime":5,"id":90,"options":91,"question":96,"source":24,"type":25},[],224514493,[92,93,94,95],"变大","无法估计","变小","无穷大","存在严重的多重共线性时,参数估计的标准差( )",{"answer":98,"createTime":5,"id":99,"options":100,"question":105,"source":24,"type":25},[],224514494,[101,102,103,104],"小于1","大于1","大于5","小于5","经验研究认为,某个解释变量与其他解释变量间多重共线性严重的情况是这个解释变量的VIF( )"]