Estimation of the population mean using two extremes in order statistics

For most non-parametric statistical inference, the sampling theory of order statistics has been playing a fundamental role because of that properties of the range and the average of the smallest and largest order statistics are useful for estimate the population parameters of both large and small samples; The applications of the method using order statistics in a given sample to estimate the parametric values appear quite often in the literature. For a certain data set, such as stock market data, the method we are considering may have an advantage in estimating the mean due to the fact that the stock data have a fairly large amount of observations during a given period, even a day; In addition to estimating the mean, it is of interest to compute (1-alpha) 100% confidence limits as well. Using the two extremes, X(1) and X(n), we wish to construct a confidence interval for the population mean mu.

Name thesis:degree_name

Master of Science (MS)

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Mathematical Sciences

Grantor dc:publisher

University of Nevada, Las Vegas

Year

2003

Author dc:creator

• Minev, Vladimir Emil

Contributors dc:contributor

• Hokwon Cho

Statement dc:rights

• IN COPYRIGHT. For more information about this rights statement, please visit http://rightsstatements.org/vocab/InC/1.0/

Language dc:language

English

Identifier

https://oasis.library.unlv.edu/rtds/1496

OAI identifier oai:identifier

oai:oasis.library.unlv.edu:rtds-2495