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You searched for subject:(order statistics property). Showing records 1 – 3 of 3 total matches.

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NSYSU

1. Su, Nan-cheng. An Investigation of Distribution Functions.

Degree: PhD, Applied Mathematics, 2008, NSYSU

The study of properties of probability distributions has always been a persistent theme of statistics and of applied probability. This thesis deals with an investigation of distribution functions under the following two topics: (i) characterization of distributions based on record values and order statistics, (ii) properties of the skew-t distribution. Within the extensive characterization literature there are several results involving properties of record values and order statistics. Although there have been many well known results already developed, it is still of great interest to find new characterization of distributions based on record values and order statistics. In the first part, we provide the conditional distribution of any record value given the maximum order statistics and study characterizations of distributions based on record values and the maximum order statistics. We also give some characterizations of the mean value function within the class of order statistics point processes, by using certain relations between the conditional moments of the jump times or current lives. These results can be applied to characterize the uniform distribution using the sequence of order statistics, and the exponential distribution using the sequence of record values, respectively. Azzalini (1985, 1986) introduced the skew-normal distribution which includes the normal distribution and has some properties like the normal and yet is skew. This class of distributions is useful in studying robustness and for modeling skewness. Since then, skew-symmetric distributions have been proposed by many authors. In the second part, the so-called generalized skew-t distribution is defined and studied. Examples of distributions in this class, generated by the ratio of two independent skew-symmetric distributions, are given. We also investigate properties of the skew-symmetric distribution. Advisors/Committee Members: Jyh-Cherng Su (chair), Wen-Jang Huang (committee member), Mei-Hui Guo (chair), Ray-Bing Chen (chair), Fu-Chuen Chang (chair), Mong-Na Lo Huang (chair).

Subjects/Keywords: skew-normal distribution; nonhomogeneous Poisson process; conditional expectation; skew-Cauchy distribution; skew-t distribution.; skew-symmetric distribution; order statistics; characterization; conditional distribution; record values; order statistics property

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APA (6th Edition):

Su, N. (2008). An Investigation of Distribution Functions. (Doctoral Dissertation). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0624108-184139

Chicago Manual of Style (16th Edition):

Su, Nan-cheng. “An Investigation of Distribution Functions.” 2008. Doctoral Dissertation, NSYSU. Accessed January 25, 2020. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0624108-184139.

MLA Handbook (7th Edition):

Su, Nan-cheng. “An Investigation of Distribution Functions.” 2008. Web. 25 Jan 2020.

Vancouver:

Su N. An Investigation of Distribution Functions. [Internet] [Doctoral dissertation]. NSYSU; 2008. [cited 2020 Jan 25]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0624108-184139.

Council of Science Editors:

Su N. An Investigation of Distribution Functions. [Doctoral Dissertation]. NSYSU; 2008. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0624108-184139


NSYSU

2. Kuo, Tzu-Fang. Characterizations Based on Conditional Expectations of Order Statistics.

Degree: Master, Applied Mathematics, 2000, NSYSU

It is known that record values and order statistics are closely related. When record values and order statistics are viewed as point processes, the two processes both share the order statistics property. The results of Beg and Balasubramanian(1990), Wu and Ouyang(1996), and Huang and Su(1999) about record values and order statistics motivated us to investigate more general results of characterization for order statistics point processes by using conditional expectations based on order statistics. On the other hand, in the class of point processes, there are a lot of characterizations of homogeneous Poisson processes based on the memoryless property of exponential distribution. The result of Asadi(1999) about characterization of the Gumble bivariate exponential or the bivariate geometric distribution inspired us be interested in investigating some similar results about non-independent bivarite homogeneous Poisson processes. Advisors/Committee Members: Yung-Zi Su (chair), Wen-Jang Huang (committee member), Jyh-Cherng Su (chair).

Subjects/Keywords: non-independent bivarite homogeneous Poisson proce; Characterization; Bivariate geometric distribution; Gumble bivariate exponential distribution; order statistics property; order statistics

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Kuo, T. (2000). Characterizations Based on Conditional Expectations of Order Statistics. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0704100-010736

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Kuo, Tzu-Fang. “Characterizations Based on Conditional Expectations of Order Statistics.” 2000. Thesis, NSYSU. Accessed January 25, 2020. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0704100-010736.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Kuo, Tzu-Fang. “Characterizations Based on Conditional Expectations of Order Statistics.” 2000. Web. 25 Jan 2020.

Vancouver:

Kuo T. Characterizations Based on Conditional Expectations of Order Statistics. [Internet] [Thesis]. NSYSU; 2000. [cited 2020 Jan 25]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0704100-010736.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Kuo T. Characterizations Based on Conditional Expectations of Order Statistics. [Thesis]. NSYSU; 2000. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0704100-010736

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

3. Paulson, Noah H. Structure-property linkages for polycrystalline materials using materials knowledge systems.

Degree: PhD, Mechanical Engineering, 2017, Georgia Tech

Computational tools that are capable of rapidly exploring candidate microstructures and their associated properties are required to accelerate the rate of development and deployment of novel materials. In this work, a suite of computationally efficient protocols, based on the materials knowledge system (MKS) framework, are developed to evaluate the properties and performance of polycrystalline microstructures. In the MKS approach, physics-capturing coefficients (calibrated with microstructures and their responses obtained via experiments or simulations) store the microstructure-sensitive response of the material system of interest. Once calibrated, the linkages may be employed to predict the local responses (through localization) or effective properties (through homogenization) of new microstructures at low computational expense. Specifically, protocols are developed to predict bulk properties (elastic stiffness and yield strength), local cyclic plastic strains and resistance to fatigue crack formation and early growth (in the high cycle fatigue and transition fatigue regimes). These protocols are demonstrated on a diverse set of α-titanium microstructures, which exhibit heterogeneous microstructure features, in addition to anisotropy on multiple length-scales. Advisors/Committee Members: Kalidindi, Surya R. (advisor), McDowell, David L. (committee member), Shih, Donald S. (committee member), Neu, Richard W. (committee member), Garmestani, Hamid (committee member).

Subjects/Keywords: Microstructure; Structure-property relationship; Polycrystalline; Titanium alloys; High cycle fatigue; Transition fatigue; Yield strength; Elastic modulus; Data science; Materials informatics; High-throughput; 2-point correlations; Computational model; Crystal plasticity; Reduced-order model; Extreme value statistics

Statistics Metrics must be employed in the construction of reduced-order homogenization… …compared against the property predicted by the reduced-order S-P linkage for each MVE in the… …target microstructure statistics for microstructures A through G… …viii 3.4 Error in the property prediction versus number of PCs included in the S-P linkage… …target microstructure statistics from the original seven microstructure classes… 

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Paulson, N. H. (2017). Structure-property linkages for polycrystalline materials using materials knowledge systems. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/60113

Chicago Manual of Style (16th Edition):

Paulson, Noah H. “Structure-property linkages for polycrystalline materials using materials knowledge systems.” 2017. Doctoral Dissertation, Georgia Tech. Accessed January 25, 2020. http://hdl.handle.net/1853/60113.

MLA Handbook (7th Edition):

Paulson, Noah H. “Structure-property linkages for polycrystalline materials using materials knowledge systems.” 2017. Web. 25 Jan 2020.

Vancouver:

Paulson NH. Structure-property linkages for polycrystalline materials using materials knowledge systems. [Internet] [Doctoral dissertation]. Georgia Tech; 2017. [cited 2020 Jan 25]. Available from: http://hdl.handle.net/1853/60113.

Council of Science Editors:

Paulson NH. Structure-property linkages for polycrystalline materials using materials knowledge systems. [Doctoral Dissertation]. Georgia Tech; 2017. Available from: http://hdl.handle.net/1853/60113

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