Modelling temporal rainfall patterns in Kenya based on temperature trends/ (Record no. 85760)

MARC details
000 -LEADER
fixed length control field 02366nam a22002057a 4500
003 - CONTROL NUMBER IDENTIFIER
control field KE-MeUCS
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20180118123353.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 171208b xxu||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number
022 ## - INTERNATIONAL STANDARD SERIAL NUMBER
Source
040 ## - CATALOGING SOURCE
Transcribing agency KE-MeUCS
Modifying agency KE-MeUCS
050 ## - LIBRARY OF CONGRESS CALL NUMBER
Classification number QC926.2.G5 2014
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Murage, Peter Githinji
245 ## - TITLE STATEMENT
Title Modelling temporal rainfall patterns in Kenya based on temperature trends/
Statement of responsibility, etc Peter Githinji Murage,
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc Meru:
Name of publisher, distributor, etc Peter Githinji Murage,
Date of publication, distribution, etc 2014.
300 ## - PHYSICAL DESCRIPTION
Extent xiv,133p.
500 ## - GENERAL NOTE
General note A Research Project submitted in partial fulfillment for the award of masters of science degree in applied statistics in the school of pure and applied sciences of Meru University of Science and Technology
520 ## - SUMMARY, ETC.
Summary, etc Rainfall and temperature series and their corresponding extreme events impact heavily on the performance of a county's economy especially in a developing county like Kenya, which relies on rained agriculture. Such extremes when not analyzed and solved, have led to lots of uncertainties amongst stakeholders.These processes were analyzed to study the evolution of their mean variability.In particular, this study sort to model the Temporal Rainfall Patterns in different Zones in Kenya Considering Temperature Trends as indicators of the rainfall variations. In achieving this objective,two broad statistical approaches were used, one based on inference on the entire series to predict the mean amount of rainfall using the maximum and minimum temperatures and the other on modeling the extreme event processes.Data from different counties in Kenya regarding rainfall and temperature was obtained.The study then came up with zones dependent on rainfall using cluster analysis,fitted Poisson, Quasi-Poisson and Negative-Binomial models. Using the AIC criterion, the best model that could be used to explain the variability of rainfall patters in these Zones as maximum and minimum temperatures changed were identified. Finally,GPD model using POT methods were used to study the distribution of the extreme seasons in the Zones.It was realized in the end that the Negative Binomial glm model was the best fit for the seven identified zones while POT coupled with mean residual life (mean excess function) fitted the GPD model to the extreme seasons and accordingly, discussions on the same have been provided.
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Library of Congress Classification
Koha item type Thesis
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Shelving location Date acquired Source of acquisition Cataloger Total Checkouts Full call number Barcode Date last seen Price effective from Koha item type
    Library of Congress Classification     Meru University Meru University Short Loan 08/12/2017       QC926.2.G5 2014 17-29618 14/11/2018 08/12/2017 Thesis

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