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Articles 1 - 6 of 6
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On The Spatial Modelling Of Mixed And Constrained Geospatial Data, Hassan Talebi
On The Spatial Modelling Of Mixed And Constrained Geospatial Data, Hassan Talebi
Theses: Doctorates and Masters
Spatial uncertainty modelling and prediction of a set of regionalized dependent variables from various sample spaces (e.g. continuous and categorical) is a common challenge for geoscience modellers and many geoscience applications such as evaluation of mineral resources, characterization of oil reservoirs or hydrology of groundwater. To consider the complex statistical and spatial relationships, categorical data such as rock types, soil types, alteration units, and continental crustal blocks should be modelled jointly with other continuous attributes (e.g. porosity, permeability, seismic velocity, mineral and geochemical compositions or pollutant concentration). These multivariate geospatial data normally have complex statistical and spatial relationships which should …
An Investigation Into The Use Of Neural Networks For The Prediction Of The Stock Exchange Of Thailand, Suchira Chaigusin
An Investigation Into The Use Of Neural Networks For The Prediction Of The Stock Exchange Of Thailand, Suchira Chaigusin
Theses: Doctorates and Masters
Stock markets are affected by many interrelated factors such as economics and politics at both national and international levels. Predicting stock indices and determining the set of relevant factors for making accurate predictions are complicated tasks. Neural networks are one of the popular approaches used for research on stock market forecast. This study developed neural networks to predict the movement direction of the next trading day of the Stock Exchange of Thailand (SET) index. The SET has yet to be studied extensively and research focused on the SET will contribute to understanding its unique characteristics and will lead to identifying …
Enhancing The Teaching And Learning Of Computational Estimation In Year 6, Paula Mildenhall
Enhancing The Teaching And Learning Of Computational Estimation In Year 6, Paula Mildenhall
Theses: Doctorates and Masters
There have been repeated calls for computational estimation to have a more prominent position in mathematics teaching and learning but there is still little evidence that quality time is being spent on this topic. Estimating numerical quantities is a useful skill for people to be able to use in their everyday lives in order to meet their personal needs. It is also accepted that number sense is an important component of mathematics learning (McIntosh, Reys, Reys, Bana, & Farrell, 1997; Paterson, 2004) and that computational estimation is an important part of number sense (Edwards, 1984; Markovits & Sowder, 1988; Schoen, …
A Comparison Of Advanced Time Series Models For Environmental Dependent Stock Recruitment Of The Western Rock Lobster, Saarah A. Farag
A Comparison Of Advanced Time Series Models For Environmental Dependent Stock Recruitment Of The Western Rock Lobster, Saarah A. Farag
Theses: Doctorates and Masters
Time series models have been applied in many areas including economics, stuck recruitment and the environment. Most environmental time series involve highly correlated dependent variables, which makes it difficult to apply conventional regression analysis, Traditionally, regression analysis has been applied to the environmental dependent stock and recruitment relationships for crustacean species in Western Australian fisheries. Alternative models, such as transfer function models and state space models have the potential to provide unproved forecasts for these types of data sets. This dissertation will explore the application of regression models, transfer function models, and state space models to modelling the puerulus stage …
On The Relationship Between A Graph And The Cycle Graph Of Its Complement, Christian P. Lopez
On The Relationship Between A Graph And The Cycle Graph Of Its Complement, Christian P. Lopez
Theses: Doctorates and Masters
From an arbitrary graph G, another graph called the cycle graph of G and denoted by C(G) can be derived. The cycle graph C(G) of G has as its vertices the chordless cycles of G and two vertices in C(G) are adjacent if and only if the corresponding chordless cycles have at least one edge in common.
Modelling Time Series Using Time Varying Coefficient Autoregressive Models : With Application To Several Data Sets, Retno Maharesi
Modelling Time Series Using Time Varying Coefficient Autoregressive Models : With Application To Several Data Sets, Retno Maharesi
Theses: Doctorates and Masters
In this thesis the state space approach and the Kalman recursions are used for modelling univariate time series data. The models that are examined in this thesis are time varying Coefficient Autoregressive models, which can be represented in state space form. The coefficients are assumed to change according to a stationary process, a non-stationary process or a random process. In order to be able to estimate these changing unknown coefficients, they will be treated as state variables and the equation describing the changes of the state variables will be given by the state equation. The model can then be expressed …