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The Use Of Overlapping Vs. Non-Overlapping Moving Block Bootstrapping To Estimate The Variance Of A Statistic Of Dependent Data
Title
The Use Of Overlapping Vs. Non-Overlapping Moving Block Bootstrapping To Estimate The Variance Of A Statistic Of Dependent Data.
Creator
Davis, Benjamin F., Radulovic, Dragan, Florida Atlantic University
Abstract/Description
Determining the variance of a statistic (such as the sample median) can be difficult. Various methods of Bootstrapping (re-sampling with replacement) were used to estimate variance of one or more statistics based on a single sample. This estimator was compared to the empirical estimators based on repeated simulations of various sample sizes from a given distribution. Of particular interest was which of the methods of Bootstrapping were most effective with a dependent data set. Different...
Show moreDetermining the variance of a statistic (such as the sample median) can be difficult. Various methods of Bootstrapping (re-sampling with replacement) were used to estimate variance of one or more statistics based on a single sample. This estimator was compared to the empirical estimators based on repeated simulations of various sample sizes from a given distribution. Of particular interest was which of the methods of Bootstrapping were most effective with a dependent data set. Different degrees of dependency were used for the simulations with dependent data.
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Date Issued
2008
PURL
http://purl.flvc.org/fau/fd/FA00000738
Subject Headings
Bootstrap (Statistics), Social sciences--Statistical methods, Mathematical statistics, Sampling (Statistics), Estimation theory, Nonparametric statistics
Format
Document (PDF)
Influences of climate variability and change on precipitation characteristics and extremes
Title
Influences of climate variability and change on precipitation characteristics and extremes.
Creator
Goly, Aneesh, College of Engineering and Computer Science, Department of Civil, Environmental and Geomatics Engineering
Abstract/Description
This study focuses on two main broad areas of active research on climate: climate variability and climate change and their implications on regional precipitation characteristics. All the analysis is carried out for a climate change-sensitive region, the state of Florida, USA. The focus of the climate variability analysis is to evaluate the influence of individual and coupled phases (cool and warm) of Atlantic multidecadal oscillation (AMO) and El Niäno southern oscillation (ENSO) on regional...
Show moreThis study focuses on two main broad areas of active research on climate: climate variability and climate change and their implications on regional precipitation characteristics. All the analysis is carried out for a climate change-sensitive region, the state of Florida, USA. The focus of the climate variability analysis is to evaluate the influence of individual and coupled phases (cool and warm) of Atlantic multidecadal oscillation (AMO) and El Niäno southern oscillation (ENSO) on regional precipitation characteristics. The two oscillations in cool and warm phases modulate each other which have implications on flood control and water supply in the region. Extreme precipitation indices, temporal distribution of rainfall within extreme storm events, dry and wet spell transitions and antecedent conditions preceding extremes are evaluated. Kernel density estimates using Gaussian kernel for distribution-free comparative analysis and bootstrap sampling-based confidence intervals are used to compare warm and cool phases of different lengths. Depth-duration-frequency (DDF) curves are also developed using generalized extreme value (GEV) distributions characterizing the extremes. ... This study also introduces new approaches to optimally select the predictor variables which help in modeling regional precipitation and further provides a mechanism to select an optimum spatial resolution to downscale the precipitation projections. New methods for correcting the biases in monthly downscaled precipitation projections are proposed, developed and evaluated in this study. The methods include bias corrections in an optimization framework using various objective functions, hybrid methods based on universal function approximation and new variants.
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Date Issued
2013
PURL
http://purl.flvc.org/fcla/dt/3362383
Subject Headings
Climatic changes, Environmental aspects, Global temperature changes, Environmental aspects, Precipitation (Meteorology), Measurement, Bootstrap (Statistics)
Format
Document (PDF)