Muslims' participation in Ethiopian Civil Society: findings from field research in Addis Ababa

This thesis is an investigation into the Ethiopian Civil Society, with a focus on Muslims’participation and activities. This research is the result of a series of interviews carried on in AddisAbaba during my staying there thank to a scholarship from Pavia University.Chapter One is a general introduction of the study, presenting the object, the methodology anduse of sources as well as the state of the current research of the topics covered by this research.Chapter Two is a framework chapter about Islām in Ethiopia offering an historical perspective aswell as focusing on its characteristics and current developments. Chapter Three deals withEthiopian Civil Society characteristics and with its legal framework. Chapter Four constitutes thecore of this research: in it, I collected the findings of my research describing the presence ofMuslims into Ethiopian Civil Society. I analyzed the activities and characteristics of the differentorganizations and associations that I met in Addis Ababa, their self-representation concerningtheir being related with Islām and their opinions on Muslims’ marginalization and lack of nonpoliticizationin Ethiopia. A set of conclusions constitutes the last section of the thesis.

Fitting spatial models in the R package: hglm

We present a new version of the hglm package for fittinghierarchical generalized linear models (HGLM) with spatially correlated random effects. A CAR family for conditional autoregressive random effects was implemented. Eigen decomposition of the matrix describing the spatial structure (e.g. the neighborhood matrix) was used to transform the CAR random effectsinto an independent, but heteroscedastic, gaussian random effect. A linear predictor is fitted for the random effect variance to estimate the parameters in the CAR model.This gives a computationally efficient algorithm for moderately sized problems (e.g. n<5000).

Fitting conditional and simultaneous autoregressive spatial models in hglm

We present a new version (> 2.0) of the hglm package for fitting hierarchical generalized linear models (HGLMs) with spatially correlated random effects. CAR() and SAR() families for conditional and simultaneous autoregressive random effects were implemented. Eigen decomposition of the matrix describing the spatial structure (e.g., the neighborhood matrix) was used to transform the CAR/SAR random effects into an independent, but eteroscedastic, Gaussian random effect. A linear predictor is fitted for the random effect variance to estimate the parameters in the CAR and SAR models. This gives a computationally efficient algorithm for moderately sized problems.