Haziq Jamil

Universiti Brunei Darussalam · Mathematics

Additive regression models with interactions have been considered extensively in the literature, using estimation methods such as splines or Gaussian process regression. At least two difficulties have hampered their application: (i) estimating the models can be difficult due to potentially many tuning (or smoothing) parameters, and (ii) model selec...

The aim of this research was the analysis of the effect of a dam height raise on the water quality of a tropical reservoir used for drinking water purposes in South East Asia. Analyses of iron, manganese, pH and ammonia were performed over a 5-year period from daily water sampling at the reservoir. In addition, high-frequency monitoring data of nit...

The objective of this study is to examine the sociodemographic factors contributing to the readmission to a drug rehabilitation center among drug addicts in Brunei Darussalam.This retrospective study used de-identified data obtained from the Al-Islah Rehabilitation Center for the period 1 January 2010 to 31 December 2017. Univariate and multiple lo...

Hypothesis testing is an essential tool among researchers and practitioners alike, with its use being being widely taught in many a programme at university level. However, past studies have shown that students hold misconceptions about important statistical concepts. This present study aims to reconfirm past efforts in this area, specifically in a...

Institutional mathematics education has long been traditional in its ways of being teacher-centric, a tradition which perhaps dates back to the Ancient Greece. Much like the society in those days, where there was a wary public feeling about the rigidness of the mathematical instruction in Pythagoras’ school, mathematics educators find themselves in...

Institutional mathematics education has long been traditional in its ways of being teacher-centric, a tradition which perhaps dates back to the Ancient Greece. Much like the society in those days, where there was a wary public feeling about the rigidness of the mathematical instruction in Pythagoras’ school, mathematics educators find themselves in...

Methods for the treatment of item non-response in attitudinal scales and in large-scale assessments under the pairwise likelihood (PL) estimation framework and under a missing at random (MAR) mechanism are proposed. Under a full information likelihood estimation framework and MAR, ignorability of the missing data mechanism does not lead to biased e...

Various global health initiatives are currently advocating the elimination of schistosomiasis within the next decade. Schistosomiasis is a highly debilitating tropical infectious disease with severe burden of morbidity and thus operational research accurately evaluating diagnostics that quantify the epidemic status for guiding effective strategies...

The Bayesian approach to modelling differs from the frequentist approach primarily in the supplementation of additional information about the parameters to the data. If we specify a “good” prior, in the sense that the prior nudges the likelihood in the right direction, then the estimates will also be good. This is what we aim to do in the case of v...

We introduce a methodology with the aim of providing a unifying framework for estimating a variety of regression methods and models, including multilevel, varying coefficient, longitudinal models, and models with functional covariates and responses. As we show, a natural space for the regression functions pertaining to such models is the reproducin...

This is an overview of the R package iprior, which implements a unified methodology for fitting parametric and nonparametric regression models, including additive models, multilevel models, and models with one or more functional covariates. Based on the principle of maximum entropy, an I-prior is an objective Gaussian process prior for the regressi...

Regression analysis is undoubtedly an important tool to understand the relationship between one or more explanatory and independent variables of interest. In this thesis, we explore a novel methodology for fitting a wide range of parametric and nonparametric regression models, called the I-prior methodology (Bergsma, 2018). We assume that the regre...