Author Type

Graduate Student

Date of Award

2002

Document Type

Thesis

Publication Status

Version of Record

Submission Date

October 2026

Thesis/Dissertation Advisor [Chair]

Qian, Lianfen

Abstract

In this thesis, we analyze wind speeds collected by South Florida Water Management District at stations L001, L005, L006 and LZ40 in Lake Okeechobee from January 1995 to December 2000. There are many missing values and out-liers in this data. To impute the missing values, three different methods are used: Nearby window average imputation, Jones imputation using Kalman filter, and EM algorithm imputation. To detect outliers and remove impacts, we use ARIMA models of time series. Innovational and additive outliers are considered. It turns out that EM algorithm imputation is the best method for our wind speed data set. After imputing missing values, detecting outliers and removing the impacts, we obtain the best models for all four stations. They are all in the form of seasonal ARIMA(2, 0, 0) x (1, 0, 0)24 for the hourly wind speed data.

Extent

72 p.

Comments

Charles E. Schmidt College of Science|Thesis (M.S.)--Florida Atlantic University, 2002.|FAU Electronic Theses and Dissertations Collection|Charles E. Schmidt College of Science

Identifier

FADT12883

Format

pdf

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