Browsing by Author "Mutwiri, Robert M."

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    Application Of Multiple Circular-Linear Regression Models To Animal Movement Data With Covariates
    (2016-04) Mutwiri, Robert M.
    In a many biological and physical sciences studies, a set of techniques have been developed to analyse the relationship between the circular and linear data derived from the geographical positioning system (GPS) telemetry to describe animal movement. Yet, many of the models used by ecologists do not provide a link between the circular and linear variables. This chapter demonstrates the application of the circular-linear regression in describing such a relationship. We describe numerical methods of obtaining maximum likelihood model parameter estimates. We discuss the technical limitations of the model through simulation and application to real elephant movement data with covariates collected from Kruger national park, South Africa. These results provide a new statistical paradigm for understanding the need to landscape features in elephant and similar animal models and evolutionary forces driving unpredictable.
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    Approaches for Testing Uniformity Hypothesis in Angular Data of Mega-Herbivores
    (2016-03) Mutwiri, Robert M.; Mwambi, Henry; Slotow, Rob
    Circularstatistics is an area not used verymuch by ecologists to describe animal movement patterns.Nevertheless,the connection betweenthe evaluation of temporalrecurring events and theanalysis of directional data haveconverged in several papers, and showcircularstatistics to be an outstandingtoolforunderstanding animal movementbetter. Theaim of thischapter is to evaluate the applications of circularstatisticaltests to check uniformityhypothesis in animal movement and its potential interpretationwithin the general framework of movementecology. Four methods of circularstatistics: Rayleigh’s,Watson’s,Rao’s spacing and Kuiper’s test based on the mean resultantlengthare applied to examine theuniformityhypothesis of GPS derived telemetry data of elephant movementcollected fromKrugerNationalPark(KNP) South Africa.Overall,circularstatisticaluniformitytests methods represent a usefultoolfor evaluation of directionalityelephant movement with applications including(i) assessment of animal foragingstrategies; (ii)determination of orientation in response to landscape features and (iii)determination of therelativestrengths of landscape features present binacomplex environment.
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    Spatial Analysis and Mapping of Infant Mortality in Kenya On The Basis Of Demographic and Health Survey Data
    (University of Nairobi, 2010) Mutwiri, Robert M.
    This study set out to examine and map the spatial variation of infant mortality in Kenya. We used data from Demographic and Health Survey (DHS) database to explore spatial variation. Generalized linear mixed inodel(GLMM) with Enumeration Areas (EA) specific random effects was used to assess the effects of geographical heterogeneity and other covariates. The model based Geostatistical methods were used to quantify the spatial variations of the observations using the variograms and fitted the exponential and matern parametric models to the sample variograms. Then utilizing the fitted variogram function, Trans-gaussian kriging was performed infant mortality rates based on both models and produced smooth maps. Generalized linear mixed model (GLMM) showed significant geographical heterogeneity in infant mortality. However, moran's I statistic showed spatial autocorrelation unaccounted for by GLMM. Modeling the correlation between people as a decreasing function of the spatial distance between them, Geostatistical models gave information no only on the magnitude but also on the scale of spatial variation. The socioeconomic status and infant mortality varied significantly across districts in Kenya. EA indicators better explained spatial variation of mortality when measured across a continuous space rather than within administrative areas. The resulting map broadly agreed with the the previous studies on the variation of risk in the country, and further showed marked variation even at local level. High risk areas were in Nyanza regions, while low risk areas are in Central of the country. The maps provided an initial description of the geographic variation of IMR in Kenya, and might help in the choice and design of interventions, which is crucial for reducing the child mortality by two thirds by 2015.
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    Spatial Modelling and Mapping of Socio-Demographic Determinants of Infant Mortality in Kenya
    (2016-03) Mutwiri, Robert M.
    This paper addresses the problem of monitoring the infant and child mortality from point referenced data. Indicators of the determinants of child survival based on Mosley and Chen framework are derived and used to model the spatial distribution of infant mortality. Spatial generalised linear model which assumes a Bernoulli distribution to model the indicator determinants of child survival. A smooth map of the predicted values at both sampled and the un sampled is produced. We find evidence of spatial autocorrelation in the data and the smooth map indicates the hot spot of infant mortality where more resources are needed to attain the millennium development goal four.
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    Statistical Distributions and Modelling of GPS-Telemetry Elephant Movement Data including the Effect of Covariates
    (University of KwaZulu Natal, South Africa, 2015-04) Mutwiri, Robert M.
    In this thesis, I investigate the application of various statistical methods towards analysing GPS tracking data collected using GPS collars placed on large mammals in Kruger National Park, South Africa. Animal movement tracking is a rapidly advancing area of ecological research and large amount of data is being collected, with short sampling intervals between successive locations. A statistical challenge is to determine appropriate methods that capture most properties of the data is lacking despite the obvious importance of such information to understanding animal movement. The aim of this study was to investigate appropriate alter- native models and compare them with the existing approaches in the literature for analysing GPS tracking data and establish appropriate statistical approaches for interpreting large scale mega-herbivore movements patterns. The focus was on which methods are the most appropriate for the linear metrics (step length and movement speed) and circular metrics (turn angles) for these animals and the comparison of the movement patterns across herds with covariate. A four parameter family of stable distributions was found to better describe the animal movement linear metrics as it captured both skewness and heavy tail properties of the data. The stable model performed favourably better than normal, Student's t and skewed Student's t models in an ARMA-GARCH modelling set-up. The ex- ibility of the stable distribution was further demonstrated in a regression model and compared with the heavy tailed t regression model. We also explore the ap- plication circular linear regression model in analysing animal turn angle data with covariate. A regression model assuming Von Mises distributed turn angles was shown to t the data well and further areas of model development highlighted. A couple of methods for testing the uniformity hypothesis of turn angles are pre- sented. Finally, we model the linear metrics assuming the error terms are stable distributed and the turn angles assuming the error terms are von Mises distributed are recommended for analysing animal movement data with covariate.