英文标题：
《Latent class analyisis for reliable measure of inflation expectation in
  the indian public》
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作者：
Sunil Kumar
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最新提交年份：
2016
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英文摘要：
  The main aim of this paper is to inspect the properties of survey based on households inflation expectations, conducted by Reserve Bank of India. It is theorized that the respondents answers are exaggerated by extreme response bias. Latent class analysis has been hailed as a promising technique for studying measurement errors in surveys, because the model produces estimates of the error rates associated with a given question of the questionnaire. I have identified a model with optimum performance and hence categorize the objective as well as reliable classifiers or otherwise.
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中文摘要：
本文的主要目的是检验印度储备银行基于家庭通胀预期进行的调查的性质。从理论上讲，受访者的回答被极端的反应偏见夸大了。潜在类别分析被认为是研究调查中测量误差的一种很有前途的技术，因为该模型可以估计与给定问卷问题相关的误差率。我已经确定了一个具有最佳性能的模型，因此将目标和可靠的分类器或其他分类。
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分类信息：

一级分类：Statistics        统计学
二级分类：Applications        应用程序
分类描述：Biology, Education, Epidemiology, Engineering, Environmental Sciences, Medical, Physical Sciences, Quality Control, Social Sciences
生物学，教育学，流行病学，工程学，环境科学，医学，物理科学，质量控制，社会科学
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一级分类：Quantitative Finance        数量金融学
二级分类：General Finance        一般财务
分类描述：Development of general quantitative methodologies with applications in finance
通用定量方法的发展及其在金融中的应用
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一级分类：Quantitative Finance        数量金融学
二级分类：Statistical Finance        统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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