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Nonparametric Estimation of the Conditional Distribution Characteristic Quantity for Functional Data Under Long Memory Conditions

Author: ZhaoYunYun
Tutor: LingNengXiang
School: Hefei University of Technology
Course: Applied Mathematics
Keywords: Long memory time series Functional Data Median Conditions Conditions quantile Conditions plural Convergence in probability
CLC: O212.1
Type: Master's thesis
Year: 2010
Downloads: 70
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Abstract


Functional Data theoretical and applied research began in the growth curve analysis , taxonomy , biomechanics , medicine and other fields, and developed in the last 10 years , especially in recent years in economics, pattern recognition, and other fields have a wide range of applications due to related disciplines are present in a large number of function type data, so in theory there are new problems to be solved. Functional Data nonparametric statistical inference especially regression model studies because of its infinite-dimensional data structures and models to the traditional the theory of statistical inference challenges , the need to explore the unknown parameters in the model for the unknown function operator new estimation method and its large sample properties . The first thesis on the basis of existing literature , in-depth study based on long memory function type condition estimation of the amount and distribution of related properties . First, the data structure based on functional characteristics of the conditional distribution of the estimated amount of the relevant amount , including function -type data condition median estimate of Functional Data estimates and conditions plural condition of Functional Data quantile estimates ; Then, limit the use of probability theory knowledge to study the asymptotic properties of estimators . In addition, on the basis of this study , the paper concludes with a further proposed research related issues.

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CLC: > Mathematical sciences and chemical > Mathematics > Probability Theory and Mathematical Statistics > Mathematical Statistics > General mathematical statistics
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