若在Stata中构建这两种模型后发现loglikelihood值相同，可能原因如下：数据集缺乏时间维度或时间跨度较短，导致模型中的滞后项效应不显著，动态杜宾模型则退化为静态杜宾模型。数据存在多重共线性问题或空间权重矩阵选择不当，影响参数估计准确度，进而使得两种模型的对数似然函数值相同。Stata命令输入错误或未安...
stata 命令有误，或者没有安装正确的空间计量经济模型的程序包，导致模型的计算结果有误。
Fitting target model: Iteration 0:loglikelihood = -2098.5822 Iteration 1:loglikelihood = -2098.5822 Structural equation model Number of obs = 200 Estimation method: ml Log likelihood = -2098.5822 --- | OIM | Coefficient std. err. z P>|z| [95% conf. interval] ---+--- ...
Iteration 0: Log= -32496.539 Iteration 1: Log likelihood = -31055.932 Iteration 2: Log likelihood = -31039.614 Iteration 3: Log likelihood = -31039.595 Iteration 4: Log likelihood = -31039.595 Ordered logistic regression Number of obs = 24,037 LR chi2(18) = 2913.89 Prob > chi2 = 0.0000 ...
Iteration 0: log likelihood = -49251.544 (not concave) Iteration 1: log likelihood = -48594.032 (not concave) Iteration 2: log likelihood = -48387.836 (not concave) Iteration 3: log likelihood = -48199.213 Iteration 4: log likelihood = -47919.729 ...
对300多个数据做回归,十几个变量,log likelihood是负的一百多 3用stata做logit回归,Log likelihood 值为多少比较正常?说明什么问题?对300多个数据做回归,十几个变量,log likelihood是负的一百多 4 用stata做logit回归,Log likelihood 值为多少比较正常? 对300多个数据做回归,十几个变量,log likelihood是负的一百...
除了拟合优度R2检验以外,常用的检验准则还有:自然对数似然函数值(Log likelihood,LogL)、似然比率(Likelihood Ratio,LR)、赤池信息准则(Akaike information criterion,AIC)、施瓦茨准则(Schwartz criterion,SC)。对数似然值越大,AIC和SC值越小,模型拟合效果越好。这几个指标也用来比较OLS估计的经典线性回归模型和SLM、SEM...
Iteration 5:loglikelihood = -12.889633 Logistic regression Number of obs = 32 LR chi2(3) = 15.40 Prob > chi2 = 0.0015 Log likelihood = -12.889633 Pseudo R2 = 0.3740 --- grade | Coef. Std. Err. z P>|z| [95% Conf. Interval] ---+--- ...
(weight_file)[ model(sar|sdm) run(xtabond|xtdhp|xtdpd|xtdpdsys) be fe relmspac lmhet lmnorm diag tests stand inv inv2 mfx(lin, log) noconstantpredict(new_var) resid(new_var) inst(vars) diff(vars) endog(vars) pre(vars)dgmmiv(varlist) coll zero tolog twostep level(#) vce(vce...
stata做probit回归中的Log likelihood 表示 对数似然值 其值一般为负数,但是有时候也是可以为正数的 解释:The likelihood is the product of the density evaluated at the observations. Usually, the density takes values that are smaller than one, so its logarithm will be negative. However, this is not ...