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3426

STATS 720

: Stochastic Processes
2024 Semester One (1243)
Stochastic models and their applications. Discrete and continuous-time jump Markov processes. A selection of topics from point processes, renewal theory, Markov decision processes, stochastic networks, inference for stochastic processes, simulation of stochastic processes, and computational methods using R.
Subject: Statistics
Prerequisite: STATS 320 or 325
3427

STATS 720

: Stochastic Processes
2023 Semester One (1233)
Continuous-time jump Markov processes. A selection of topics from: point processes, renewal theory, martingales, Brownian motion, Gaussian processes and inference for stochastic processes.
Subject: Statistics
Prerequisite: STATS 320 or 325
3428

STATS 720

: Stochastic Processes
2022 Semester One (1223)
Continuous-time jump Markov processes. A selection of topics from: point processes, renewal theory, martingales, Brownian motion, Gaussian processes and inference for stochastic processes.
Subject: Statistics
Prerequisite: STATS 320 or 325
3429

STATS 720

: Stochastic Processes
2021 Semester One (1213)
Continuous-time jump Markov processes. A selection of topics from: point processes, renewal theory, martingales, Brownian motion, Gaussian processes and inference for stochastic processes.
Subject: Statistics
Prerequisite: STATS 320 or 325
3430

STATS 720

: Stochastic Processes
2020 Semester One (1203)
Continuous-time jump Markov processes. A selection of topics from: point processes, renewal theory, martingales, Brownian motion, Gaussian processes and inference for stochastic processes.
Subject: Statistics
Prerequisite: STATS 320 or 325
3431

STATS 721

: Foundations of Stochastic Processes
2025 Semester Two (1255)
Fundamentals of stochastic processes. Topics include: generating functions, branching processes, Markov chains, and random walks.
Subject: Statistics
Prerequisite: 15 points from STATS 125, 210, 225, 320 with at least a B+ and 15 points from MATHS 208, 250, 253
Restriction: STATS 325
3432

STATS 721

: Foundations of Stochastic Processes
2024 Semester Two (1245)
Fundamentals of stochastic processes. Topics include: generating functions, branching processes, Markov chains, and random walks.
Subject: Statistics
Prerequisite: 15 points from STATS 125, 210, 225, 320 with at least a B+ and 15 points from MATHS 208, 250, 253
Restriction: STATS 325
3433

STATS 721

: Foundations of Stochastic Processes
2023 Semester Two (1235)
Fundamentals of stochastic processes. Topics include: generating functions, branching processes, Markov chains, and random walks.
Subject: Statistics
Restriction: STATS 325
3434

STATS 721

: Foundations of Stochastic Processes
2022 Semester Two (1225)
Fundamentals of stochastic processes. Topics include: generating functions, branching processes, Markov chains, and random walks.
Subject: Statistics
Restriction: STATS 325
3435

STATS 721

: Foundations of Stochastic Processes
2021 Semester Two (1215)
Fundamentals of stochastic processes. Topics include: generating functions, branching processes, Markov chains, and random walks.
Subject: Statistics
Restriction: STATS 325
3436

STATS 721

: Foundations of Stochastic Processes
2020 Semester Two (1205)
Fundamentals of stochastic processes. Topics include: generating functions, branching processes, Markov chains, and random walks.
Subject: Statistics
Restriction: STATS 325
3437

STATS 722

: Foundations of Financial Mathematics
2020 Semester Two (1205)
Fundamentals of financial mathematics. Topics include: mean-variance portfolio theory; options, arbitrage and put-call relationships; introduction of binomial and Black-Scholes option pricing models; compound interest, annuities, capital redemption policies, valuation of securities, sinking funds; varying rates of interest, taxation; duration and immunisation; introduction to life annuities and life insurance mathematics.
Subject: Statistics
Prerequisite: 15 points at Stage II in Statistics or BIOSCI 209, and 15 points at Stage II in Mathematics
Restriction: STATS 370
3438

STATS 723

: Stochastic Methods in Finance
2022 Semester One (1223)
Contingent claims theory in discrete and continuous time. Risk-neutral option pricing, Cox-Ross-Rubinstein and Black-Scholes models, stochastic calculus, hedging and risk management.
Subject: Statistics
Prerequisite: STATS 125 and 370, or 15 points from STATS 210, 225, 325
3439

STATS 723

: Stochastic Methods in Finance
2021 Semester One (1213)
Contingent claims theory in discrete and continuous time. Risk-neutral option pricing, Cox-Ross-Rubinstein and Black-Scholes models, stochastic calculus, hedging and risk management.
Subject: Statistics
Prerequisite: STATS 125 and 370, or 15 points from STATS 210, 225, 325
3440

STATS 723

: Stochastic Methods in Finance
2020 Semester One (1203)
Contingent claims theory in discrete and continuous time. Risk-neutral option pricing, Cox-Ross-Rubinstein and Black-Scholes models, stochastic calculus, hedging and risk management.
Subject: Statistics
Prerequisite: STATS 125 and 370, or 15 points from STATS 210, 225, 325
3441

STATS 726

: Time Series
2025 Semester Two (1255)
Stationary processes, modelling and estimation in the time domain, forecasting and spectral analysis.
Subject: Statistics
Prerequisite: STATS 210, and 15 points from STATS 326, 786
3442

STATS 726

: Time Series
2024 Semester Two (1245)
Stationary processes, modelling and estimation in the time domain, forecasting and spectral analysis.
Subject: Statistics
Prerequisite: STATS 210, and 15 points from STATS 326, 786
3443

STATS 726

: Time Series
2023 Semester Two (1235)
Stationary processes, modelling and estimation in the time domain, forecasting and spectral analysis.
Subject: Statistics
Prerequisite: STATS 210, and 320 or 325
3444

STATS 726

: Time Series
2022 Semester Two (1225)
Stationary processes, modelling and estimation in the time domain, forecasting and spectral analysis.
Subject: Statistics
Prerequisite: STATS 210, and 320 or 325
3445

STATS 726

: Time Series
2021 Semester Two (1215)
Stationary processes, modelling and estimation in the time domain, forecasting and spectral analysis.
Subject: Statistics
Prerequisite: STATS 210, and 320 or 325
3446

STATS 726

: Time Series
2020 Semester Two (1205)
Stationary processes, modelling and estimation in the time domain, forecasting and spectral analysis.
Subject: Statistics
No pre-requisites or restrictions
3447

STATS 727

: Foundations of Applied Time Series Analysis
2021 Semester One (1213)
Fundamentals of applied time series analysis. Topics include: components, decompositions, smoothing and filtering, modelling and forecasting. Examples and techniques from a variety of application areas are presented.
Subject: Statistics
Prerequisite: 15 points from BIOSCI 209, ECON 221, STATS 201, 207, 208, 707
Restriction: STATS 326
3448

STATS 727

: Foundations of Applied Time Series Analysis
2020 Semester One (1203)
Fundamentals of applied time series analysis. Topics include: components, decompositions, smoothing and filtering, modelling and forecasting. Examples and techniques from a variety of application areas are presented.
Subject: Statistics
Prerequisite: 15 points from BIOSCI 209, ECON 221, STATS 201, 207, 208
Restriction: STATS 326
3449

STATS 730

: Statistical Inference
2025 Semester Two (1255)
Fundamental topics in estimation and statistical inference. Advanced topics in modelling including regression with dependent data, survival analysis, methods to handle missing data. Advanced topics in current statistical practice researched by students. Students will undertake and present individual research projects on assigned topics, consisting in a literature search and a computational application to a data analysis task.
Subject: Statistics
Prerequisite: STATS 310 or 732
3450

STATS 730

: Statistical Inference
2024 Semester Two (1245)
Fundamentals of likelihood-based inference, including sufficiency, conditioning, likelihood principle, statistical paradoxes. Theory and practice of maximum likelihood. Examples covered may include survival analysis, GLM's, nonlinear models, random effects and empirical Bayes models, and quasi-likelihood.
Subject: Statistics
Prerequisite: STATS 310 or 732