Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 3 of 3
Full-Text Articles in Entire DC Network
Mechanism Design For Land Acquisition., Soumendu Sarkar Dr.
Mechanism Design For Land Acquisition., Soumendu Sarkar Dr.
Doctoral Theses
Conversion of land use from agriculture to industry is a typical feature of economic development in many densely populated countries. Large scale construction often requires industry or the government to acquire vast areas of land that are inhabited and often cultivated, by hundreds and even thousands of people. For some landowners, possession signifies power and status in society, while for others, it is the only means for earning a livelihood.Adamopoulos and Restuccia (2014) use data from World Census of Agriculture to show that average farm size in the poorest 20% of countries is 1.6 hectares, while that in the richest …
Inference On Time-To-Event Distribution From Retrospective Data With Imperfect Recall., Sedigheh Salehabadi Dr.
Inference On Time-To-Event Distribution From Retrospective Data With Imperfect Recall., Sedigheh Salehabadi Dr.
Doctoral Theses
Time-to-event data arises from measurements of time till the occurrence of an event of interest. Such data are common in the fields of biology, epidemiology, pub- lic health, medical research, economics and industry. The event of interest can be the death of a human being (Klein and Moeschberger, 2003), failure of a machine (Zhiguo et al., 2007), onset of menarche in adolescent and young adult females (Bergsten-Brucefors, 1976; Chumlea et al., 2003; Mirzaei, Sengupta and Das, 2015), onset (or relapse) of a disease (Klein and Moeschberger, 2003), dental develop- ment (Demirjian, Goldstien and Tanner, 1973; Eveleth and Tanner, 1990), breast …
Some Distribution-Free Two-Sample Tests Applicable To High Dimension, Low Sample Size Data., Munmun Biswas Dr.
Some Distribution-Free Two-Sample Tests Applicable To High Dimension, Low Sample Size Data., Munmun Biswas Dr.
Doctoral Theses
The advancement of data acquisition technologies and computing resources have greatly facilitated the analysis of massive data sets in various fields of sciences. Researchers from different disciplines rigorously investigate these data sets to extract useful information for new scientific discoveries. Many of these data sets contain large number of features but small number of observations. For instance, in the fields of chemometrics (see e.g., Schoonover et al. (2003)), medical image analysis (see e.g., Yushkevich et al. (2001)) and microarray gene expression data analysis (see e.g., Eisen and Brown (1999), Alter et al. (2000)), we often deal with data of dimensions …