Robust and efficient estimation in ordinal response models using the density power divergence
IF 1.2
4区 数学
Q2 STATISTICS & PROBABILITY
引用次数: 0
Abstract
In real life, we frequently encounter ordinal variables depending upon independent covariates. The latent linear regression model is useful for modelling such data. One can find the model's parame...利用密度幂发散对序数响应模型进行稳健高效的估计
在现实生活中，我们经常会遇到取决于独立协变量的序变量。潜在线性回归模型对此类数据建模非常有用。我们可以发现该模型的参数...
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来源期刊
Statistics
数学-统计学与概率论
CiteScore
1.00
自引率
0.00%
发文量
59
审稿时长
12 months
期刊介绍：
Statistics publishes papers developing and analysing new methods for any active field of statistics, motivated by real-life problems. Papers submitted for consideration should provide interesting and novel contributions to statistical theory and its applications with rigorous mathematical results and proofs. Moreover, numerical simulations and application to real data sets can improve the quality of papers, and should be included where appropriate. Statistics does not publish papers which represent mere application of existing procedures to case studies, and papers are required to contain methodological or theoretical innovation. Topics of interest include, for example, nonparametric statistics, time series, analysis of topological or functional data. Furthermore the journal also welcomes submissions in the field of theoretical econometrics and its links to mathematical statistics.
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