A Bayesian hierarchical model for categorical longitudinal data from a social survey of immigrants

The paper investigates a Bayesian hierarchical model for the analysis of categorical longitudinal data from a large social survey of immigrants to Australia. Data for each subject are observed on three separate occasions, or waves, of the survey. One of the features of the data set is that observations for some variables are missing for at least one wave. A model for the employment status of immigrants is developed by introducing, at the first stage of a hierarchical model, a multinomial model for the response and then subsequent terms are introduced to explain wave and subject effects. To estimate the model, we use the Gibbs sampler, which allows missing data for both the response and the explanatory variables to be imputed at each iteration of the algorithm, given some appropriate prior distributions. After accounting for significant covariate effects in the model, results show that the relative probability of remaining unemployed diminished with time following arrival in Australia.

Advances in Dynamic Modeling and Computation for Count Data

A class of multi-process models is developed for collections of time indexed count data. Autocorrelation in counts is achieved with dynamic models for the natural parameter of the binomial distribution. In addition to modeling binomial time series, the framework includes dynamic models for multinomial and Poisson time series. Markov chain Monte Carlo (MCMC) and Po ́lya-Gamma data augmentation (Polson et al., 2013) are critical for fitting multi-process models of counts. To facilitate computation when the counts are high, a Gaussian approximation to the P ́olya- Gamma random variable is developed.

Three applied analyses are presented to explore the utility and versatility of the framework. The first analysis develops a model for complex dynamic behavior of themes in collections of text documents. Documents are modeled as a “bag of words”, and the multinomial distribution is used to characterize uncertainty in the vocabulary terms appearing in each document. State-space models for the natural parameters of the multinomial distribution induce autocorrelation in themes and their proportional representation in the corpus over time.

The second analysis develops a dynamic mixed membership model for Poisson counts. The model is applied to a collection of time series which record neuron level firing patterns in rhesus monkeys. The monkey is exposed to two sounds simultaneously, and Gaussian processes are used to smoothly model the time-varying rate at which the neuron’s firing pattern fluctuates between features associated with each sound in isolation.

The third analysis presents a switching dynamic generalized linear model for the time-varying home run totals of professional baseball players. The model endows each player with an age specific latent natural ability class and a performance enhancing drug (PED) use indicator. As players age, they randomly transition through a sequence of ability classes in a manner consistent with traditional aging patterns. When the performance of the player significantly deviates from the expected aging pattern, he is identified as a player whose performance is consistent with PED use.

All three models provide a mechanism for sharing information across related series locally in time. The models are fit with variations on the P ́olya-Gamma Gibbs sampler, MCMC convergence diagnostics are developed, and reproducible inference is emphasized throughout the dissertation.

Sparse hierarchical Bayesian models for detecting relevant antigenic sites in virus evolution

Understanding how virus strains offer protection against closely related emerging strains is vital for creating effective vaccines. For many viruses, including Foot-and-Mouth Disease Virus (FMDV) and the Influenza virus where multiple serotypes often co-circulate, in vitro testing of large numbers of vaccines can be infeasible. Therefore the development of an in silico predictor of cross-protection between strains is important to help optimise vaccine choice. Vaccines will offer cross-protection against closely related strains, but not against those that are antigenically distinct. To be able to predict cross-protection we must understand the antigenic variability within a virus serotype, distinct lineages of a virus, and identify the antigenic residues and evolutionary changes that cause the variability. In this thesis we present a family of sparse hierarchical Bayesian models for detecting relevant antigenic sites in virus evolution (SABRE), as well as an extended version of the method, the extended SABRE (eSABRE) method, which better takes into account the data collection process. The SABRE methods are a family of sparse Bayesian hierarchical models that use spike and slab priors to identify sites in the viral protein which are important for the neutralisation of the virus. In this thesis we demonstrate how the SABRE methods can be used to identify antigenic residues within different serotypes and show how the SABRE method outperforms established methods, mixed-effects models based on forward variable selection or l1 regularisation, on both synthetic and viral datasets. In addition we also test a number of different versions of the SABRE method, compare conjugate and semi-conjugate prior specifications and an alternative to the spike and slab prior; the binary mask model. We also propose novel proposal mechanisms for the Markov chain Monte Carlo (MCMC) simulations, which improve mixing and convergence over that of the established component-wise Gibbs sampler. The SABRE method is then applied to datasets from FMDV and the Influenza virus in order to identify a number of known antigenic residue and to provide hypotheses of other potentially antigenic residues. We also demonstrate how the SABRE methods can be used to create accurate predictions of the important evolutionary changes of the FMDV serotypes. In this thesis we provide an extended version of the SABRE method, the eSABRE method, based on a latent variable model. The eSABRE method takes further into account the structure of the datasets for FMDV and the Influenza virus through the latent variable model and gives an improvement in the modelling of the error. We show how the eSABRE method outperforms the SABRE methods in simulation studies and propose a new information criterion for selecting the random effects factors that should be included in the eSABRE method; block integrated Widely Applicable Information Criterion (biWAIC). We demonstrate how biWAIC performs equally to two other methods for selecting the random effects factors and combine it with the eSABRE method to apply it to two large Influenza datasets. Inference in these large datasets is computationally infeasible with the SABRE methods, but as a result of the improved structure of the likelihood, we are able to show how the eSABRE method offers a computational improvement, leading it to be used on these datasets. The results of the eSABRE method show that we can use the method in a fully automatic manner to identify a large number of antigenic residues on a variety of the antigenic sites of two Influenza serotypes, as well as making predictions of a number of nearby sites that may also be antigenic and are worthy of further experiment investigation.

A Python package for Bayesian estimation using Markov Chain Monte Carlo

Markov chain Monte Carlo (MCMC) estimation provides a solution to the complex integration problems that are faced in the Bayesian analysis of statistical problems. The implementation of MCMC algorithms is, however, code intensive and time consuming. We have developed a Python package, which is called PyMCMC, that aids in the construction of MCMC samplers and helps to substantially reduce the likelihood of coding error, as well as aid in the minimisation of repetitive code. PyMCMC contains classes for Gibbs, Metropolis Hastings, independent Metropolis Hastings, random walk Metropolis Hastings, orientational bias Monte Carlo and slice samplers as well as specific modules for common models such as a module for Bayesian regression analysis. PyMCMC is straightforward to optimise, taking advantage of the Python libraries Numpy and Scipy, as well as being readily extensible with C or Fortran.

Phase Equilibria in the System $Al_{2}O_{3}-CaO-CoO$ and Gibbs Energy of Formation of $Ca_{3}CoAl_{4}O_{10}$

The floating-zone method with different growth ambiences has been used to selectively obtain hexagonal or orthorhombic DyMnO3 single crystals. The crystals were characterized by x-ray powder diffraction of ground specimens and a structure refinement as well as electron diffraction. We report magnetic susceptibility, magnetization and specific heat studies of this multiferroic compound in both the hexagonal and the orthorhombic structure. The hexagonal DyMnO3 shows magnetic ordering of Mn3+ (S = 2) spins on a triangular Mn lattice at T-N(Mn) = 57 K characterized by a cusp in the specific heat. This transition is not apparent in the magnetic susceptibility due to the frustration on the Mn triangular lattice and the dominating paramagnetic susceptibility of the Dy3+ (S = 9/2) spins. At T-N(Dy) = 3 K, a partial antiferromagnetic order of Dy moments has been observed. In comparison, the magnetic data for orthorhombic DyMnO3 display three transitions. The data broadly agree with results from earlier neutron diffraction experiments, which allows for the following assignment: a transition from an incommensurate antiferromagnetic ordering of Mn3+ spins at T-N(Mn) = 39 K, a lock-in transition at Tlock-in = 16 K and a second antiferromagnetic transition at T-N(Dy) = 5 K due to the ordering of Dy moments. Both the hexagonal and the orthorhombic crystals show magnetic anisotropy and complex magnetic properties due to 4f-4f and 4f-3d couplings.

Gibbs Energy of Formation of Cobalt Divanadium Tetroxide

The Gibbs energy of formation of V2O3-saturated spinel CoV2O4 has been measured in the temperature range 900–1700 K using a solid state galvanic cell, which can be represented as Pt, Co + CoV2O4 + V2O3/(CaO) ZrO2/Co + CoO, Pt. The standard free energy of formation of cobalt vanadite from component oxides can be represented as CoO (rs) + V2O3 (cor) → CoV2O4 (sp), ΔG° = −30,125 − 5.06T (± 150) J mole−1. Cation mixing on crystallographically nonequivalent sites of the spinel is responsible for the decrease in free energy with increasing temperature. A correlation between “second law” entropies of formation of cubic 2–3 spinels from component oxides with rock salt and corundum structures and cation distribution is presented. Based on the information obtained in this study and trends in the stability of aluminate and chromite spinels, it can be deduced that copper vanadite is unstable.

Gibbs energies of formation of rare earth oxysulfides

The standard Gibbs energy change accompanying the conversion of rare earth oxides to oxysulfides by reaction of rare earth oxides with diatomic sulfur gas has been measured in the temperature range 870 to 1300 K using the solid state cell: Pt/Cu+Cu2S/R2O2S+R2O3‖(CaO)ZrO2‖Ni+NiO, Pt where R=La, Nd, Sm, Gd, Tb, and Dy. The partial pressure of diatomic sulfur over a mixture of rare earth oxide (R2O3) and oxysulfide (R2O2S) is fixed by the dissociation of Cu2S to Cu in a closed system. The buffer mixture of Cu+Cu2S is physically separated from the rare earth oxide and oxysulfide to avoid complications arising from interaction between them. The corresponding equilibrium oxygen partial pressure is measured with an oxide solid electrolyte cell. Gibbs energy change for the conversion of oxide to the corresponding oxysulfide increases monotonically with atomic number of the rare earth element. Second law enthalpy of formation also shows a similar trend. Based on this empirical trend Gibbs energies of formation of oxysulfides of Pr, Eu, Ho, and Er are estimated as a function of temperature.

Enterprise education: Revisiting Whitehead to satisfy Gibbs

Purpose – This paper seeks to demonstrate that a truly learner-centred enterprise education programme can be developed within a traditional business school environment. Design/methodology/approach – This paper unites the broad teaching philosophy of Alfred Whitehead with that of Allan Gibbs’s enterprise specific teaching philosophies to consider the fitness of the recently developed hic et nunc enterprise framework. This is largely achieved by testing the framework for constructive alignment. Findings – It is argued that the hic et nunc framework is consistent with the philosophies of both Whitehead and Gibb. Further, the framework illustrates a process through which enterprise education programmes can be developed independently of any pressures to conform to more traditional pedagogy. Practical implications – Through careful consideration of the process of constructive alignment, an analytical approach to developing and/or refining an enterprise education program exists. Importantly, it represents an approach that is explicitly learner-centred, and therefore free from the constraints of the environment within which the programme is delivered. Originality/value – This paper brings to life the wonderful ideas of the great philosopher, Alfred Whitehead, combining them with the contemporary ideas of Allan Gibb. In doing so, the complementary nature of their thoughts helps to illustrate the minimal requirements of a learner-centred approach to enterprise education

Gibbs Energy of Formation of MnO: Measurement and Assessment

Based on the measurements of Alcock and Zador, Grundy et al. estimated an uncertainty of the order of +/- 5 kJ mol(-1) for the standard Gibbs energy of formation of MnO in a recent assessment. Since the evaluation of thermodynamic data for the higher oxides Mn3O4, Mn2O3, and MnO2 depends on values for MnO, a redetermination of its Gibbs energy of formation was undertaken in the temperature range from 875 to 1300 K using a solid-state electrochemical cell incorporating yttria-doped thoria (YDT) as the solid electrolyte and Fe + Fe1-delta O as the reference electrode. The cell can be presented as Pt, Mn + MnO/YDT/Fe + Fe1+delta O, Pt Since the metals Fe and Mn undergo phase transitions in the temperature range of measurement, the reversible emf of the cell is represented by the three linear segments. Combining the emf with the oxygen potential for the reference electrode, the standard Gibbs energy of formation of MnO from alpha-Mn and gaseous diatomic oxygen in the temperature range from 875 to 980 K is obtained as: Delta G(f)(o)/Jmol(-1)(+/- 250) = -385624 + 73.071T From 980 to 1300 K the Gibbs energy of formation of MnO from beta-Mn and oxygen gas is given by: Delta G(f)(o)/Jmol(-1)(+/- 250) = -387850 + 75.36T The new data are in excellent agreement with the earlier measurements of Alcock and Zador. Grundy et al. incorrectly analyzed the data of Alcock and Zador showing relatively large difference (+/- 5 kJ mol(-1)) in Gibbs energies of MnO from their two cells with Fe + Fe1-delta O and Ni + NiO as reference electrodes. Thermodynamic data for MnO is reassessed in the light of the new measurements. A table of refined thermodynamic data for MnO from 298.15 to 2000 K is presented.

Use of metastable equilibria for determination of Gibbs energy of solids

Attempts are made to measure activities of both components of a binary alloy (A�B) at 650 K using a solid-state galvanic cell incorporating a new composite solid electrolyte. Since the ionic conductivity of the composite solid electrolyte is three orders of magnitude higher than that of pure CaF2, the cell can be operated at lower temperatures. The alloy phase is equilibrated in separate experiments with flourides of each component and fluorine potential is measured. The mixture of the alloy (A�B) and the fluoride of the more reactive component (BF2) is stable, while (A�B) + AF2 mixture is metastable, Factors governing the possible use of metastable equilibria have been elucidated in this study. In the Co�Ni system, where the difference in Gibbs energies of formation of the fluorides is 21.4 kJ/mol, emf of the cell with metastable phases at the electrode is constant for periods ranging from 90 to 160 ks depending on alloy composition. Subsequently, the emf decreases because of the onset of the displacement reaction. In the Ni�Mn system, measurement of the activity of Ni using metastable equilibria is not fully successful at 650 K because of the large driving force for the displacement reaction (208.8 kJ/mol). Critical factors in the application of metastable equilibria are the driving force for displacement reaction and diffusion coefficients in both the alloy and fluoride solid solution.

Standard Gibbs' energies of formation of BaCuO2, Y2Cu2O5 and Y2BaCuO5

The Gibbs' energies of formation of BaCuO2, Y2Cu2O5 and Y2BaCuO5 from component oxides have been measured using solid state galvanic cells incorporating CaF2 as the solid electrolyte under pure oxygen at a pressure of 1.01 x 10(5) Pa Because the superconducting compound YBa2Cu3O7-delta coexists with any two of the phases CuO, BaCuO2 and Y2BaCuO5, the data on BaCuO2 and Y2BaCuO5 obtained in this study provide the basis for the evaluation of the Gibbs' energy of formation of the 1-2-3 compound at high temperatures.

Phase Relations in the System Cu-Gd-O and Gibbs Energy of Formation of CuGd204

The phase relations in the system Cu-Gd-O have been determined at 1273 K by X-ray diffrac- tion, optical microscopy, and electron microprobe analysis of samples equilibrated in quartz ampules and in pure oxygen. Only one ternary compound, CuGd2O4, was found to be stable. The Gibbs free energy of formation of this compound has been measured using the solid-state cell Pt, Cu2O + CuGd2O4 + Gd2O3 // (Y2O3) ZrO2 // CuO + Cu2O, Pt in the temperature range of 900 to 1350 K. For the formation of CuGd2O4 from its binary component oxides, CuO (s) + Gd2O3 (s) → CuGd2O4 (s) ΔG° = 8230 - 11.2T (±50) J mol-1 Since the formation is endothermic, CuGd2O4 becomes thermodynamically unstable with respect to CuO and Gd2O3 below 735 K. When the oxygen partial pressure over CuGd2O4 is lowered, it decomposes according to the reaction 4CuGd2O4 (s) → 4Gd2O3 (s) + 2Cu2O (s) + O2 (g) for which the equilibrium oxygen potential is given by Δμo 2 = −227,970 + 143.2T (±500) J mol−1 An oxygen potential diagram for the system Cu-Gd-O at 1273 K is presented.

Phase relations in the systems Cu–O–R2O3(R = Tm, Lu) and Gibbs energies of formation of Cu2R2O5 compounds

The phase relations in the systems Cu–O–R2O3(R = Tm, Lu) have been determined at 1273 K by X-ray diffraction, optical microscopy and electron probe microanalysis of samples equilibrated in evacuated quartz ampules and in pure oxygen. Only ternary compounds of the type Cu2R2O5 were found to be stable. The standard Gibbs energies of formation of the compounds have been measured using solid-state galvanic cells of the type, Pt|Cu2O + Cu2R2O5+ R2O3‖(Y2O3)ZrO2‖CuO + Cu2O‖Pt in the temperature range 950–1325 K. The standard Gibbs energy changes associated with the formation of Cu2R2O5 compounds from their binary component oxides are: 2CuO(s)+ Tm2O3(s)→Cu2Tm2O5(s), ΔG°=(10400 – 14.0 T/K)± 100 J mol–1, 2CuO(s)+ Lu2O3(s)→Cu2Lu2O5(s), ΔG°=(10210 – 14.4 T/K)± 100 J mol–1 Since the formation is endothermic, the compounds become thermodynamically unstable with respect to component oxides at low temperatures, Cu2Tm2O5 below 743 K and Cu2Lu2O5 below 709 K. When the chemical potential of oxygen over the Cu2R2O5 compounds is lowered, they decompose according to the reaction, 2Cu2R2O5(s)→2R2O3(s)+ 2Cu2O(s)+ O2(g) The equilibrium oxygen potential corresponding to this reaction is obtained from the emf. Oxygen potential diagrams for the Cu–O–R2O3 systems at 1273 K are presented.